radarsys Commit - r178:6920059c9c16 · Jicamarca Repository

Task #716: ABS Views, plot beams patterns with OverJRO and overJroShow scripts...

Fiorella Quino -

r178:6920059c9c16

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apps/abs/templates/abs_downpattern_img.html created 644 +25 0

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	1	{% load static %}
	2	{% load bootstrap3 %}
	3	{% load main_tags %}
	4
	5	{% block content %}
	6	<style>
	7	</style>
	8
	9	<div id="PictureOverJRODown" style="float: right">
	10	<img id="imgMainDown" src="{% url 'url_plot_down_beam' beam.abs_conf.id beam.id %}" alt="Error in Parameters" style="width:360px;height:270px;">
	11	<img id="imgLoaderDown" src="{% static 'images/loading_loading.gif' %}" alt="Error in Parameters" width="50" height="50" align="left">
	12
	13	</div>
	14
	15	<script>
	16
	17	$('#imgMainDown').hide();
	18	$('#imgLoaderDown').show();
	19	$('#imgMainDown').load(function(){
	20	$('#imgLoaderDown').hide();
	21	$('#imgMainDown').show();
	22	});
	23	//window.onload = function () { alert("It's loaded!") }
	24	</script>
	25	{% endblock %}

apps/abs/templates/abs_uppattern_img.html created 644 +25 0

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	1	{% load static %}
	2	{% load bootstrap3 %}
	3	{% load main_tags %}
	4
	5	{% block content %}
	6	<style>
	7	</style>
	8
	9	<div id="PictureOverJROUp" style="float: right">
	10	<img id="imgMain" src="{% url 'url_plot_up_beam' beam.abs_conf.id beam.id %}" alt="Error in Parameters" style="width:360px;height:270px;">
	11	<img id="imgLoader" src="{% static 'images/loading_loading.gif' %}" alt="Error in Parameters" width="50" height="50">
	12
	13	</div>
	14
	15	<script>
	16
	17	$('#imgMain').hide();
	18	$('#imgLoader').show();
	19	$('#imgMain').load(function(){
	20	$('#imgLoader').hide();
	21	$('#imgMain').show();
	22	});
	23
	24	</script>
	25	{% endblock %}

apps/abs/utils/Astro_Coords.py created 644 +1419 0

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		1	"""
		2	The module ASTRO_COORDS.py gathers classes and functions for coordinates transformation. Additiona-
		3	lly a class EquatorialCorrections and celestial bodies are defined. The first of these is to correct
		4	any error in the location of the body and the second to know the location of certain celestial bo-
		5	dies in the sky.
		6
		7	MODULES CALLED:
		8	OS, NUMPY, NUMERIC, SCIPY, TIME_CONVERSIONS
		9
		10	MODIFICATION HISTORY:
		11	Created by Ing. Freddy Galindo (frederickgalindo@gmail.com). ROJ Sep 20, 2009.
		12	"""
		13
		14	import numpy
		15	#import Numeric
		16	import scipy.interpolate
		17	import os
		18	import sys
		19	import TimeTools
		20	import Misc_Routines
		21
		22	class EquatorialCorrections():
		23	def __init__(self):
		24	"""
		25	EquatorialCorrections class creates an object to call methods to correct the loca-
		26	tion of the celestial bodies.
		27
		28	Modification History
		29	--------------------
		30	Converted to Object-oriented Programming by Freddy Galindo, ROJ, 27 September 2009.
		31	"""
		32
		33	pass
		34
		35	def co_nutate(self,jd,ra,dec):
		36	"""
		37	co_nutate calculates changes in RA and Dec due to nutation of the Earth's rotation
		38	Additionally it returns the obliquity of the ecliptic (eps), nutation in the longi-
		39	tude of the ecliptic (d_psi) and nutation in the pbliquity of the ecliptic (d_eps).
		40
		41	Parameters
		42	----------
		43	jd = Julian Date (Scalar or array).
		44	RA = A scalar o array giving the Right Ascention of interest.
		45	Dec = A scalar o array giving the Right Ascention of interest.
		46
		47	Return
		48	------
		49	d_ra = Correction to ra due to nutation.
		50	d_dec = Correction to dec due to nutation.
		51
		52	Examples
		53	--------
		54	>> Julian = 2462088.7
		55	>> Ra = 41.547213
		56	>> Dec = 49.348483
		57	>> [d_ra,d_dec,eps,d_psi,d_eps] = co_nutate(julian,Ra,Dec)
		58	>> print d_ra, d_dec, eps, d_psi, d_eps
		59	[ 15.84276651] [ 6.21641029] [ 0.4090404] [ 14.85990198] [ 2.70408658]
		60
		61	Modification history
		62	--------------------
		63	Written by Chris O'Dell, 2002.
		64	Converted to Python by Freddy R. Galindo, ROJ, 26 September 2009.
		65	"""
		66
		67	jd = numpy.atleast_1d(jd)
		68	ra = numpy.atleast_1d(ra)
		69	dec = numpy.atleast_1d(dec)
		70
		71	# Useful transformation constants
		72	d2as = numpy.pi/(180.*3600.)
		73
		74	# Julian centuries from J2000 of jd
		75	T = (jd - 2451545.0)/36525.0
		76
		77	# Must calculate obliquity of ecliptic
		78	[d_psi, d_eps] = self.nutate(jd)
		79	d_psi = numpy.atleast_1d(d_psi)
		80	d_eps = numpy.atleast_1d(d_eps)
		81
		82	eps0 = (23.43929113600.) - (46.8150T) - (0.00059T2) + (0.001813T**3)
		83	# True obliquity of the ecliptic in radians
		84	eps = (eps0 + d_eps)/3600.*Misc_Routines.CoFactors.d2r
		85
		86	# Useful numbers
		87	ce = numpy.cos(eps)
		88	se = numpy.sin(eps)
		89
		90	# Convert Ra-Dec to equatorial rectangular coordinates
		91	x = numpy.cos(raMisc_Routines.CoFactors.d2r)numpy.cos(dec*Misc_Routines.CoFactors.d2r)
		92	y = numpy.sin(raMisc_Routines.CoFactors.d2r)numpy.cos(dec*Misc_Routines.CoFactors.d2r)
		93	z = numpy.sin(dec*Misc_Routines.CoFactors.d2r)
		94
		95	# Apply corrections to each rectangular coordinate
		96	x2 = x - (yce + zse)d_psiMisc_Routines.CoFactors.s2r
		97	y2 = y + (xced_psi - zd_eps)Misc_Routines.CoFactors.s2r
		98	z2 = z + (xsed_psi + yd_eps)Misc_Routines.CoFactors.s2r
		99
		100	# Convert bask to equatorial spherical coordinates
		101	r = numpy.sqrt(x22. + y22. + z2**2.)
		102	xyproj =numpy.sqrt(x22. + y22.)
		103
		104	ra2 = x2*0.0
		105	dec2 = x2*0.0
		106
		107	xyproj = numpy.atleast_1d(xyproj)
		108	z = numpy.atleast_1d(z)
		109	r = numpy.atleast_1d(r)
		110	x2 = numpy.atleast_1d(x2)
		111	y2 = numpy.atleast_1d(y2)
		112	z2 = numpy.atleast_1d(z2)
		113	ra2 = numpy.atleast_1d(ra2)
		114	dec2 = numpy.atleast_1d(dec2)
		115
		116	w1 = numpy.where((xyproj==0) & (z!=0))
		117	w2 = numpy.where(xyproj!=0)
		118
		119	# Calculate Ra and Dec in radians (later convert to degrees)
		120	if w1[0].size>0:
		121	# Places where xyproj=0 (point at NCP or SCP)
		122	dec2[w1] = numpy.arcsin(z2[w1]/r[w1])
		123	ra2[w1] = 0
		124
		125	if w2[0].size>0:
		126	# Places other than NCP or SCP
		127	ra2[w2] = numpy.arctan2(y2[w2],x2[w2])
		128	dec2[w2] = numpy.arcsin(z2[w2]/r[w2])
		129
		130	# Converting to degree
		131	ra2 = ra2/Misc_Routines.CoFactors.d2r
		132	dec2 = dec2/Misc_Routines.CoFactors.d2r
		133
		134	w = numpy.where(ra2<0.)
		135	if w[0].size>0:
		136	ra2[w] = ra2[w] + 360.
		137
		138	# Return changes in Ra and Dec in arcseconds
		139	d_ra = (ra2 -ra)*3600.
		140	d_dec = (dec2 - dec)*3600.
		141
		142	return d_ra, d_dec, eps, d_psi, d_eps
		143
		144	def nutate(self,jd):
		145	"""
		146	nutate returns the nutation in longitude and obliquity for a given Julian date.
		147
		148	Parameters
		149	----------
		150	jd = Julian ephemeris date, scalar or vector.
		151
		152	Return
		153	------
		154	nut_long = The nutation in longitude.
		155	nut_obliq = The nutation in latitude.
		156
		157	Example
		158	-------
		159	>> julian = 2446895.5
		160	>> [nut_long,nut_obliq] = nutate(julian)
		161	>> print nut_long, nut_obliq
		162	-3.78793107711 9.44252069864
		163
		164	>> julians = 2415020.5 + numpy.arange(50)
		165	>> [nut_long,nut_obliq] = nutate(julians)
		166
		167	Modification History
		168	--------------------
		169	Written by W.Landsman (Goddard/HSTX), June 1996.
		170	Converted to Python by Freddy R. Galindo, ROJ, 26 September 2009.
		171	"""
		172
		173	jd = numpy.atleast_1d(jd)
		174
		175	# Form time in Julian centuries from 1900
		176	t = (jd - 2451545.0)/36525.0
		177
		178	# Mean elongation of the moon
		179	coeff1 = numpy.array([1/189474.0,-0.0019142,445267.111480,297.85036])
		180	d = numpy.poly1d(coeff1)
		181	d = d(t)*Misc_Routines.CoFactors.d2r
		182	d = self.cirrange(d,rad=1)
		183
		184	# Sun's mean elongation
		185	coeff2 = numpy.array([-1./3e5,-0.0001603,35999.050340,357.52772])
		186	m = numpy.poly1d(coeff2)
		187	m = m(t)*Misc_Routines.CoFactors.d2r
		188	m = self.cirrange(m,rad=1)
		189
		190	# Moon's mean elongation
		191	coeff3 = numpy.array([1.0/5.625e4,0.0086972,477198.867398,134.96298])
		192	mprime = numpy.poly1d(coeff3)
		193	mprime = mprime(t)*Misc_Routines.CoFactors.d2r
		194	mprime = self.cirrange(mprime,rad=1)
		195
		196	# Moon's argument of latitude
		197	coeff4 = numpy.array([-1.0/3.27270e5,-0.0036825,483202.017538,93.27191])
		198	f = numpy.poly1d(coeff4)
		199	f = f(t)*Misc_Routines.CoFactors.d2r
		200	f = self.cirrange(f,rad=1)
		201
		202	# Longitude fo the ascending node of the Moon's mean orbit on the ecliptic, measu-
		203	# red from the mean equinox of the date.
		204	coeff5 = numpy.array([1.0/4.5e5,0.0020708,-1934.136261,125.04452])
		205	omega = numpy.poly1d(coeff5)
		206	omega = omega(t)*Misc_Routines.CoFactors.d2r
		207	omega = self.cirrange(omega,rad=1)
		208
		209	d_lng = numpy.array([0,-2,0,0,0,0,-2,0,0,-2,-2,-2,0,2,0,2,0,0,-2,0,2,0,0,-2,0,-2,0,0,\
		210	2,-2,0,-2,0,0,2,2,0,-2,0,2,2,-2,-2,2,2,0,-2,-2,0,-2,-2,0,-1,-2,1,0,0,-1,0,\
		211	0,2,0,2])
		212
		213	m_lng = numpy.array([0,0,0,0,1,0,1,0,0,-1])
		214	m_lng = numpy.append(m_lng,numpy.zeros(17))
		215	m_lng = numpy.append(m_lng,numpy.array([2,0,2,1,0,-1,0,0,0,1,1,-1,0,0,0,0,0,0,-1,-1,0,0,\
		216	0,1,0,0,1,0,0,0,-1,1,-1,-1,0,-1]))
		217
		218	mp_lng = numpy.array([0,0,0,0,0,1,0,0,1,0,1,0,-1,0,1,-1,-1,1,2,-2,0,2,2,1,0,0, -1, 0,\
		219	-1,0,0,1,0,2,-1,1,0,1,0,0,1,2,1,-2,0,1,0,0,2,2,0,1,1,0,0,1,-2,1,1,1,-1,3,0])
		220
		221	f_lng = numpy.array([0,2,2,0,0,0,2,2,2,2,0,2,2,0,0,2,0,2,0,2,2,2,0,2,2,2,2,0,0,2,0,0,\
		222	0,-2,2,2,2,0,2,2,0,2,2,0,0,0,2,0,2,0,2,-2,0,0,0,2,2,0,0,2,2,2,2])
		223
		224	om_lng = numpy.array([1,2,2,2,0,0,2,1,2,2,0,1,2,0,1,2,1,1,0,1,2,2,0,2,0,0,1,0,1,2,1, \
		225	1,1,0,1,2,2,0,2,1,0,2,1,1,1,0,1,1,1,1,1,0,0,0,0,0,2,0,0,2,2,2,2])
		226
		227	sin_lng = numpy.array([-171996,-13187,-2274,2062,1426,712,-517,-386,-301, 217, -158, \
		228	129,123,63,63,-59,-58,-51,48,46,-38,-31,29,29,26,-22,21,17,16,-16,-15,-13,\
		229	-12,11,-10,-8,7,-7,-7,-7,6,6,6,-6,-6,5,-5,-5,-5,4,4,4,-4,-4,-4,3,-3,-3,-3,\
		230	-3,-3,-3,-3])
		231
		232	sdelt = numpy.array([-174.2,-1.6,-0.2,0.2,-3.4,0.1,1.2,-0.4,0,-0.5,0, 0.1, 0, 0, 0.1,\
		233	0,-0.1])
		234	sdelt = numpy.append(sdelt,numpy.zeros(10))
		235	sdelt = numpy.append(sdelt,numpy.array([-0.1, 0, 0.1]))
		236	sdelt = numpy.append(sdelt,numpy.zeros(33))
		237
		238	cos_lng = numpy.array([92025,5736,977,-895,54,-7,224,200,129,-95,0,-70,-53,0,-33,26, \
		239	32,27,0,-24,16,13,0,-12,0,0,-10,0,-8,7,9,7,6,0,5,3,-3,0,3,3,0,-3,-3,3,3,0,\
		240	3,3,3])
		241	cos_lng = numpy.append(cos_lng,numpy.zeros(14))
		242
		243	cdelt = numpy.array([8.9,-3.1,-0.5,0.5,-0.1,0.0,-0.6,0.0,-0.1,0.3])
		244	cdelt = numpy.append(cdelt,numpy.zeros(53))
		245
		246	# Sum the periodic terms.
		247	n = numpy.size(jd)
		248	nut_long = numpy.zeros(n)
		249	nut_obliq = numpy.zeros(n)
		250
		251	d_lng = d_lng.reshape(numpy.size(d_lng),1)
		252	d = d.reshape(numpy.size(d),1)
		253	matrix_d_lng = numpy.dot(d_lng,d.transpose())
		254
		255	m_lng = m_lng.reshape(numpy.size(m_lng),1)
		256	m = m.reshape(numpy.size(m),1)
		257	matrix_m_lng = numpy.dot(m_lng,m.transpose())
		258
		259	mp_lng = mp_lng.reshape(numpy.size(mp_lng),1)
		260	mprime = mprime.reshape(numpy.size(mprime),1)
		261	matrix_mp_lng = numpy.dot(mp_lng,mprime.transpose())
		262
		263	f_lng = f_lng.reshape(numpy.size(f_lng),1)
		264	f = f.reshape(numpy.size(f),1)
		265	matrix_f_lng = numpy.dot(f_lng,f.transpose())
		266
		267	om_lng = om_lng.reshape(numpy.size(om_lng),1)
		268	omega = omega.reshape(numpy.size(omega),1)
		269	matrix_om_lng = numpy.dot(om_lng,omega.transpose())
		270
		271	arg = matrix_d_lng + matrix_m_lng + matrix_mp_lng + matrix_f_lng + matrix_om_lng
		272
		273	sarg = numpy.sin(arg)
		274	carg = numpy.cos(arg)
		275
		276	for ii in numpy.arange(n):
		277	nut_long[ii] = 0.0001numpy.sum((sdeltt[ii] + sin_lng)*sarg[:,ii])
		278	nut_obliq[ii] = 0.0001numpy.sum((cdeltt[ii] + cos_lng)*carg[:,ii])
		279
		280	if numpy.size(jd)==1:
		281	nut_long = nut_long[0]
		282	nut_obliq = nut_obliq[0]
		283
		284	return nut_long, nut_obliq
		285
		286	def co_aberration(self,jd,ra,dec):
		287	"""
		288	co_aberration calculates changes to Ra and Dec due to "the effect of aberration".
		289
		290	Parameters
		291	----------
		292	jd = Julian Date (Scalar or vector).
		293	ra = A scalar o vector giving the Right Ascention of interest.
		294	dec = A scalar o vector giving the Declination of interest.
		295
		296	Return
		297	------
		298	d_ra = The correction to right ascension due to aberration (must be added to ra to
		299	get the correct value).
		300	d_dec = The correction to declination due to aberration (must be added to the dec
		301	to get the correct value).
		302	eps = True obliquity of the ecliptic (in radians).
		303
		304	Examples
		305	--------
		306	>> Julian = 2462088.7
		307	>> Ra = 41.547213
		308	>> Dec = 49.348483
		309	>> [d_ra,d_dec,eps] = co_aberration(julian,Ra,Dec)
		310	>> print d_ra, d_dec, eps
		311	[ 30.04441796] [ 6.69837858] [ 0.40904059]
		312
		313	Modification history
		314	--------------------
		315	Written by Chris O'Dell , Univ. of Wisconsin, June 2002.
		316	Converted to Python by Freddy R. Galindo, ROJ, 27 September 2009.
		317	"""
		318
		319	# Julian centuries from J2000 of jd.
		320	T = (jd - 2451545.0)/36525.0
		321
		322	# Getting obliquity of ecliptic
		323	njd = numpy.size(jd)
		324	jd = numpy.atleast_1d(jd)
		325	ra = numpy.atleast_1d(ra)
		326	dec = numpy.atleast_1d(dec)
		327
		328	d_psi = numpy.zeros(njd)
		329	d_epsilon = d_psi
		330	for ii in numpy.arange(njd):
		331	[dp,de] = self.nutate(jd[ii])
		332	d_psi[ii] = dp
		333	d_epsilon[ii] = de
		334
		335	coeff = 23 + 26/60. + 21.488/3600.
		336	eps0 = coeff3600. - 46.8150T - 0.00059T2. + 0.001813T**3.
		337	# True obliquity of the ecliptic in radians
		338	eps = (eps0 + d_epsilon)/3600*Misc_Routines.CoFactors.d2r
		339
		340	celestialbodies = CelestialBodies()
		341	[sunra,sundec,sunlon,sunobliq] = celestialbodies.sunpos(jd)
		342
		343	# Earth's orbital eccentricity
		344	e = 0.016708634 - 0.000042037T - 0.0000001267T**2.
		345
		346	# longitude of perihelion, in degrees
		347	pi = 102.93735 + 1.71946T + 0.00046T**2
		348
		349	# Constant of aberration, in arcseconds
		350	k = 20.49552
		351
		352	cd = numpy.cos(decMisc_Routines.CoFactors.d2r) ; sd = numpy.sin(decMisc_Routines.CoFactors.d2r)
		353	ce = numpy.cos(eps) ; te = numpy.tan(eps)
		354	cp = numpy.cos(piMisc_Routines.CoFactors.d2r) ; sp = numpy.sin(piMisc_Routines.CoFactors.d2r)
		355	cs = numpy.cos(sunlonMisc_Routines.CoFactors.d2r) ; ss = numpy.sin(sunlonMisc_Routines.CoFactors.d2r)
		356	ca = numpy.cos(raMisc_Routines.CoFactors.d2r) ; sa = numpy.sin(raMisc_Routines.CoFactors.d2r)
		357
		358	term1 = (cacsce + sa*ss)/cd
		359	term2 = (cacpce + sa*sp)/cd
		360	term3 = (csce(tecd - sasd) + casdss)
		361	term4 = (cpce(tecd - sasd) + casdsp)
		362
		363	d_ra = -kterm1 + ek*term2
		364	d_dec = -kterm3 + ek*term4
		365
		366	return d_ra, d_dec, eps
		367
		368	def precess(self,ra,dec,equinox1=None,equinox2=None,FK4=0,rad=0):
		369	"""
		370	precess coordinates from EQUINOX1 to EQUINOX2
		371
		372	Parameters
		373	-----------
		374	ra = A scalar o vector giving the Right Ascention of interest.
		375	dec = A scalar o vector giving the Declination of interest.
		376	equinox1 = Original equinox of coordinates, numeric scalar. If omitted, the __Pre-
		377	cess will query for equinox1 and equinox2.
		378	equinox2 = Original equinox of coordinates.
		379	FK4 = If this keyword is set and non-zero, the FK4 (B1950) system will be used
		380	otherwise FK5 (J2000) will be used instead.
		381	rad = If this keyword is set and non-zero, then the input and output RAD and DEC
		382	vectors are in radian rather than degree.
		383
		384	Return
		385	------
		386	ra = Right ascension after precession (scalar or vector) in degrees, unless the rad
		387	keyword is set.
		388	dec = Declination after precession (scalar or vector) in degrees, unless the rad
		389	keyword is set.
		390
		391	Examples
		392	--------
		393	>> Ra = 329.88772
		394	>> Dec = -56.992515
		395	>> [p_ra,p_dec] = precess(Ra,Dec,1950,1975,FK4=1)
		396	>> print p_ra, p_dec
		397	[ 330.31442971] [-56.87186154]
		398
		399	Modification history
		400	--------------------
		401	Written by Wayne Landsman, STI Corporation, August 1986.
		402	Converted to Python by Freddy R. Galindo, ROJ, 27 September 2009.
		403	"""
		404
		405	npts = numpy.size(ra)
		406	ra = numpy.atleast_1d(ra)
		407	dec = numpy.atleast_1d(dec)
		408
		409	if rad==0:
		410	ra_rad = ra*Misc_Routines.CoFactors.d2r
		411	dec_rad = dec*Misc_Routines.CoFactors.d2r
		412	else:
		413	ra_rad = ra
		414	dec_rad = dec
		415
		416	x = numpy.zeros((npts,3))
		417	x[:,0] = numpy.cos(dec_rad)*numpy.cos(ra_rad)
		418	x[:,1] = numpy.cos(dec_rad)*numpy.sin(ra_rad)
		419	x[:,2] = numpy.sin(dec_rad)
		420
		421	# Use premat function to get precession matrix from equinox1 to equinox2
		422	r = self.premat(equinox1,equinox2,FK4)
		423
		424	x2 = numpy.dot(r,x.transpose())
		425
		426	ra_rad = numpy.arctan2(x2[1,:],x2[0,:])
		427	dec_rad = numpy.arcsin(x2[2,:])
		428
		429	if rad==0:
		430	ra = ra_rad/Misc_Routines.CoFactors.d2r
		431	ra = ra + (ra<0)*360.
		432	dec = dec_rad/Misc_Routines.CoFactors.d2r
		433	else:
		434	ra = ra_rad
		435	ra = ra + (ra<0)numpy.pi2.
		436	dec = dec_rad
		437
		438	return ra, dec
		439
		440	def premat(self,equinox1,equinox2,FK4=0):
		441	"""
		442	premat returns the precession matrix needed to go from EQUINOX1 to EQUINOX2.
		443
		444	Parameters
		445	----------
		446	equinox1 = Original equinox of coordinates, numeric scalar.
		447	equinox2 = Equinox of precessed coordinates.
		448	FK4 = If this keyword is set and non-zero, the FK4 (B1950) system precession angles
		449	are used to compute the precession matrix. The default is to use FK5 (J2000) pre-
		450	cession angles.
		451
		452	Return
		453	------
		454	r = Precession matrix, used to precess equatorial rectangular coordinates.
		455
		456	Examples
		457	--------
		458	>> matrix = premat(1950.0,1975.0,FK4=1)
		459	>> print matrix
		460	[[ 9.99981438e-01 -5.58774959e-03 -2.42908517e-03]
		461	[ 5.58774959e-03 9.99984388e-01 -6.78691471e-06]
		462	[ 2.42908517e-03 -6.78633095e-06 9.99997050e-01]]
		463
		464	Modification history
		465	--------------------
		466	Written by Wayne Landsman, HSTX Corporation, June 1994.
		467	Converted to Python by Freddy R. Galindo, ROJ, 27 September 2009.
		468	"""
		469
		470	t = 0.001*(equinox2 - equinox1)
		471
		472	if FK4==0:
		473	st=0.001*(equinox1 - 2000.)
		474	# Computing 3 rotation angles.
		475	A=Misc_Routines.CoFactors.s2rt(23062.181+st(139.656+0.0139st)+t(30.188-0.344st+17.998*t))
		476	B=Misc_Routines.CoFactors.s2rtt(79.280+0.410st+0.205*t)+A
		477	C=Misc_Routines.CoFactors.s2rt(20043.109-st(85.33+0.217st)+ t(-42.665-0.217st-41.833*t))
		478	else:
		479	st=0.001*(equinox1 - 1900)
		480	# Computing 3 rotation angles
		481	A=Misc_Routines.CoFactors.s2rt(23042.53+st(139.75+0.06st)+t(30.23-0.27st+18.0*t))
		482	B=Misc_Routines.CoFactors.s2rtt(79.27+0.66st+0.32*t)+A
		483	C=Misc_Routines.CoFactors.s2rt(20046.85-st(85.33+0.37st)+t(-42.67-0.37st-41.8*t))
		484
		485	sina = numpy.sin(A); sinb = numpy.sin(B); sinc = numpy.sin(C)
		486	cosa = numpy.cos(A); cosb = numpy.cos(B); cosc = numpy.cos(C)
		487
		488	r = numpy.zeros((3,3))
		489	r[:,0] = numpy.array([cosacosbcosc-sinasinb,sinacosb+cosasinbcosc,cosa*sinc])
		490	r[:,1] = numpy.array([-cosasinb-sinacosbcosc,cosacosb-sinasinbcosc,-sina*sinc])
		491	r[:,2] = numpy.array([-cosbsinc,-sinbsinc,cosc])
		492
		493	return r
		494
		495	def cirrange(self,angle,rad=0):
		496	"""
		497	cirrange forces an angle into the range 0<= angle < 360.
		498
		499	Parameters
		500	----------
		501	angle = The angle to modify, in degrees. Can be scalar or vector.
		502	rad = Set to 1 if the angle is specified in radians rather than degrees. It is for-
		503	ced into the range 0 <= angle < 2 PI
		504
		505	Return
		506	------
		507	angle = The angle after the modification.
		508
		509	Example
		510	-------
		511	>> angle = cirrange(numpy.array([420,400,361]))
		512	>> print angle
		513	>> [60, 40, 1]
		514
		515	Modification History
		516	--------------------
		517	Written by Michael R. Greason, Hughes STX, 10 February 1994.
		518	Converted to Python by Freddy R. Galindo, ROJ, 26 September 2009.
		519	"""
		520
		521	angle = numpy.atleast_1d(angle)
		522
		523	if rad==1:
		524	cnst = numpy.pi*2.
		525	elif rad==0:
		526	cnst = 360.
		527
		528	# Deal with the lower limit.
		529	angle = angle % cnst
		530
		531	# Deal with negative values, if way
		532	neg = numpy.where(angle<0.0)
		533	if neg[0].size>0: angle[neg] = angle[neg] + cnst
		534
		535	return angle
		536
		537
		538	class CelestialBodies(EquatorialCorrections):
		539	def __init__(self):
		540	"""
		541	CelestialBodies class creates a object to call methods of celestial bodies location.
		542
		543	Modification History
		544	--------------------
		545	Converted to Object-oriented Programming by Freddy Galindo, ROJ, 27 September 2009.
		546	"""
		547
		548	EquatorialCorrections.__init__(self)
		549
		550	def sunpos(self,jd,rad=0):
		551	"""
		552	sunpos method computes the RA and Dec of the Sun at a given date.
		553
		554	Parameters
		555	----------
		556	jd = The julian date of the day (and time), scalar or vector.
		557	rad = If this keyword is set and non-zero, then the input and output RAD and DEC
		558	vectors are in radian rather than degree.
		559
		560	Return
		561	------
		562	ra = The right ascension of the sun at that date in degrees.
		563	dec = The declination of the sun at that date in degrees.
		564	elong = Ecliptic longitude of the sun at that date in degrees.
		565	obliquity = The declination of the sun at that date in degrees.
		566
		567	Examples
		568	--------
		569	>> jd = 2466880
		570	>> [ra,dec,elong,obliquity] = sunpos(jd)
		571	>> print ra, dec, elong, obliquity
		572	[ 275.53499556] [-23.33840558] [ 275.08917968] [ 23.43596165]
		573
		574	>> [ra,dec,elong,obliquity] = sunpos(jd,rad=1)
		575	>> print ra, dec, elong, obliquity
		576	[ 4.80899288] [-0.40733202] [ 4.80121192] [ 0.40903469]
		577
		578	>> jd = 2450449.5 + numpy.arange(365)
		579	>> [ra,dec,elong,obliquity] = sunpos(jd)
		580
		581	Modification history
		582	--------------------
		583	Written by Micheal R. Greason, STX Corporation, 28 October 1988.
		584	Converted to Python by Freddy R. Galindo, ROJ, 27 September 2009.
		585	"""
		586
		587	jd = numpy.atleast_1d(jd)
		588
		589	# Form time in Julian centuries from 1900.
		590	t = (jd -2415020.0)/36525.0
		591
		592	# Form sun's mean longitude
		593	l = (279.696678+((36000.768925t) % 360.0))3600.0
		594
		595	# Allow for ellipticity of the orbit (equation of centre) using the Earth's mean
		596	# anomoly ME
		597	me = 358.475844 + ((35999.049750*t) % 360.0)
		598	ellcor = (6910.1 - 17.2t)numpy.sin(meMisc_Routines.CoFactors.d2r) + 72.3numpy.sin(2.0meMisc_Routines.CoFactors.d2r)
		599	l = l + ellcor
		600
		601	# Allow for the Venus perturbations using the mean anomaly of Venus MV
		602	mv = 212.603219 + ((58517.803875*t) % 360.0)
		603	vencorr = 4.8numpy.cos((299.1017 + mv - me)Misc_Routines.CoFactors.d2r) + \
		604	5.5numpy.cos((148.3133 + 2.0mv - 2.0me )Misc_Routines.CoFactors.d2r) + \
		605	2.5numpy.cos((315.9433 + 2.0mv - 3.0me )Misc_Routines.CoFactors.d2r) + \
		606	1.6numpy.cos((345.2533 + 3.0mv - 4.0me )Misc_Routines.CoFactors.d2r) + \
		607	1.0numpy.cos((318.15 + 3.0mv - 5.0me )Misc_Routines.CoFactors.d2r)
		608	l = l + vencorr
		609
		610	# Allow for the Mars perturbations using the mean anomaly of Mars MM
		611	mm = 319.529425 + ((19139.858500*t) % 360.0)
		612	marscorr = 2.0numpy.cos((343.8883 - 2.0mm + 2.0me)Misc_Routines.CoFactors.d2r ) + \
		613	1.8numpy.cos((200.4017 - 2.0mm + me)*Misc_Routines.CoFactors.d2r)
		614	l = l + marscorr
		615
		616	# Allow for the Jupiter perturbations using the mean anomaly of Jupiter MJ
		617	mj = 225.328328 + ((3034.6920239*t) % 360.0)
		618	jupcorr = 7.2numpy.cos((179.5317 - mj + me )Misc_Routines.CoFactors.d2r) + \
		619	2.6numpy.cos((263.2167 - mj)Misc_Routines.CoFactors.d2r) + \
		620	2.7numpy.cos((87.1450 - 2.0mj + 2.0me)Misc_Routines.CoFactors.d2r) + \
		621	1.6numpy.cos((109.4933 - 2.0mj + me)*Misc_Routines.CoFactors.d2r)
		622	l = l + jupcorr
		623
		624	# Allow for Moons perturbations using mean elongation of the Moon from the Sun D
		625	d = 350.7376814 + ((445267.11422*t) % 360.0)
		626	mooncorr = 6.5numpy.sin(dMisc_Routines.CoFactors.d2r)
		627	l = l + mooncorr
		628
		629	# Allow for long period terms
		630	longterm = + 6.4numpy.sin((231.19 + 20.20t)*Misc_Routines.CoFactors.d2r)
		631	l = l + longterm
		632	l = (l + 2592000.0) % 1296000.0
		633	longmed = l/3600.0
		634
		635	# Allow for Aberration
		636	l = l - 20.5
		637
		638	# Allow for Nutation using the longitude of the Moons mean node OMEGA
		639	omega = 259.183275 - ((1934.142008*t) % 360.0)
		640	l = l - 17.2numpy.sin(omegaMisc_Routines.CoFactors.d2r)
		641
		642	# Form the True Obliquity
		643	oblt = 23.452294 - 0.0130125t + (9.2numpy.cos(omega*Misc_Routines.CoFactors.d2r))/3600.0
		644
		645	# Form Right Ascension and Declination
		646	l = l/3600.0
		647	ra = numpy.arctan2((numpy.sin(lMisc_Routines.CoFactors.d2r)numpy.cos(obltMisc_Routines.CoFactors.d2r)),numpy.cos(lMisc_Routines.CoFactors.d2r))
		648
		649	neg = numpy.where(ra < 0.0)
		650	if neg[0].size > 0: ra[neg] = ra[neg] + 2.0*numpy.pi
		651
		652	dec = numpy.arcsin(numpy.sin(lMisc_Routines.CoFactors.d2r)numpy.sin(oblt*Misc_Routines.CoFactors.d2r))
		653
		654	if rad==1:
		655	oblt = oblt*Misc_Routines.CoFactors.d2r
		656	longmed = longmed*Misc_Routines.CoFactors.d2r
		657	else:
		658	ra = ra/Misc_Routines.CoFactors.d2r
		659	dec = dec/Misc_Routines.CoFactors.d2r
		660
		661	return ra, dec, longmed, oblt
		662
		663	def moonpos(self,jd,rad=0):
		664	"""
		665	moonpos method computes the RA and Dec of the Moon at specified Julian date(s).
		666
		667	Parameters
		668	----------
		669	jd = The julian date of the day (and time), scalar or vector.
		670	rad = If this keyword is set and non-zero, then the input and output RAD and DEC
		671	vectors are in radian rather than degree.
		672
		673	Return
		674	------
		675	ra = The right ascension of the sun at that date in degrees.
		676	dec = The declination of the sun at that date in degrees.
		677	dist = The Earth-moon distance in kilometers (between the center of the Earth and
		678	the center of the moon).
		679	geolon = Apparent longitude of the moon in degrees, referred to the ecliptic of the
		680	specified date(s).
		681	geolat = Apparent latitude the moon in degrees, referred to the ecliptic of the
		682	specified date(s).
		683
		684	Examples
		685	--------
		686	>> jd = 2448724.5
		687	>> [ra,dec,dist,geolon,geolat] = sunpos(jd)
		688	>> print ra, dec, dist, geolon, geolat
		689	[ 134.68846855] [ 13.76836663] [ 368409.68481613] [ 133.16726428] [-3.22912642]
		690
		691	>> [ra,dec,dist,geolon, geolat] = sunpos(jd,rad=1)
		692	>> print ra, dec, dist, geolon, geolat
		693	[ 2.35075724] [ 0.24030333] [ 368409.68481613] [ 2.32420722] [-0.05635889]
		694
		695	>> jd = 2450449.5 + numpy.arange(365)
		696	>> [ra,dec,dist,geolon, geolat] = sunpos(jd)
		697
		698	Modification history
		699	--------------------
		700	Written by Micheal R. Greason, STX Corporation, 31 October 1988.
		701	Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009.
		702	"""
		703
		704	jd = numpy.atleast_1d(jd)
		705
		706	# Form time in Julian centuries from 1900.
		707	t = (jd - 2451545.0)/36525.0
		708
		709	d_lng = numpy.array([0,2,2,0,0,0,2,2,2,2,0,1,0,2,0,0,4,0,4,2,2,1,1,2,2,4,2,0,2,2,1,2,\
		710	0,0,2,2,2,4,0,3,2,4,0,2,2,2,4,0,4,1,2,0,1,3,4,2,0,1,2,2])
		711
		712	m_lng = numpy.array([0,0,0,0,1,0,0,-1,0,-1,1,0,1,0,0,0,0,0,0,1,1,0,1,-1,0,0,0,1,0,-1,\
		713	0,-2,1,2,-2,0,0,-1,0,0,1,-1,2,2,1,-1,0,0,-1,0,1,0,1,0,0,-1,2,1,0,0])
		714
		715	mp_lng = numpy.array([1,-1,0,2,0,0,-2,-1,1,0,-1,0,1,0,1,1,-1,3,-2,-1,0,-1,0,1,2,0,-3,\
		716	-2,-1,-2,1,0,2,0,-1,1,0,-1,2,-1,1,-2,-1,-1,-2,0,1,4,0,-2,0,2,1,-2,-3,2,1,-1,3,-1])
		717
		718	f_lng = numpy.array([0,0,0,0,0,2,0,0,0,0,0,0,0,-2,2,-2,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,\
		719	0,0,0,0,-2,2,0,2,0,0,0,0,0,0,-2,0,0,0,0,-2,-2,0,0,0,0,0,0,0,-2])
		720
		721	sin_lng = numpy.array([6288774,1274027,658314,213618,-185116,-114332,58793,57066,\
		722	53322,45758,-40923,-34720,-30383,15327,-12528,10980,10675,10034,8548,-7888,\
		723	-6766,-5163,4987,4036,3994,3861,3665,-2689,-2602,2390,-2348,2236,-2120,-2069,\
		724	2048,-1773,-1595,1215,-1110,-892,-810,759,-713,-700,691,596,549,537,520,-487,\
		725	-399,-381,351,-340,330,327,-323,299,294,0.0])
		726
		727	cos_lng = numpy.array([-20905355,-3699111,-2955968,-569925,48888,-3149,246158,-152138,\
		728	-170733,-204586,-129620,108743,104755,10321,0,79661,-34782,-23210,-21636,24208,\
		729	30824,-8379,-16675,-12831,-10445,-11650,14403,-7003,0,10056,6322, -9884,5751,0,\
		730	-4950,4130,0,-3958,0,3258,2616,-1897,-2117,2354,0,0,-1423,-1117,-1571,-1739,0, \
		731	-4421,0,0,0,0,1165,0,0,8752.0])
		732
		733	d_lat = numpy.array([0,0,0,2,2,2,2,0,2,0,2,2,2,2,2,2,2,0,4,0,0,0,1,0,0,0,1,0,4,4,0,4,\
		734	2,2,2,2,0,2,2,2,2,4,2,2,0,2,1,1,0,2,1,2,0,4,4,1,4,1,4,2])
		735
		736	m_lat = numpy.array([0,0,0,0,0,0,0,0,0,0,-1,0,0,1,-1,-1,-1,1,0,1,0,1,0,1,1,1,0,0,0,0,\
		737	0,0,0,0,-1,0,0,0,0,1,1,0,-1,-2,0,1,1,1,1,1,0,-1,1,0,-1,0,0,0,-1,-2])
		738
		739	mp_lat = numpy.array([0,1,1,0,-1,-1,0,2,1,2,0,-2,1,0,-1,0,-1,-1,-1,0,0,-1,0,1,1,0,0,\
		740	3,0,-1,1,-2,0,2,1,-2,3,2,-3,-1,0,0,1,0,1,1,0,0,-2,-1,1,-2,2,-2,-1,1,1,-1,0,0])
		741
		742	f_lat = numpy.array([1,1,-1,-1,1,-1,1,1,-1,-1,-1,-1,1,-1,1,1,-1,-1,-1,1,3,1,1,1,-1,\
		743	-1,-1,1,-1,1,-3,1,-3,-1,-1,1,-1,1,-1,1,1,1,1,-1,3,-1,-1,1,-1,-1,1,-1,1,-1,-1, \
		744	-1,-1,-1,-1,1])
		745
		746	sin_lat = numpy.array([5128122,280602,277693,173237,55413,46271, 32573, 17198, 9266, \
		747	8822,8216,4324,4200,-3359,2463,2211,2065,-1870,1828,-1794, -1749, -1565, -1491, \
		748	-1475,-1410,-1344,-1335,1107,1021,833,777,671,607,596,491,-451,439,422,421,-366,\
		749	-351,331,315,302,-283,-229,223,223,-220,-220,-185,181,-177,176, 166, -164, 132, \
		750	-119,115,107.0])
		751
		752	# Mean longitude of the moon refered to mean equinox of the date.
		753	coeff0 = numpy.array([-1./6.5194e7,1./538841.,-0.0015786,481267.88123421,218.3164477])
		754	lprimed = numpy.poly1d(coeff0)
		755	lprimed = lprimed(t)
		756	lprimed = self.cirrange(lprimed,rad=0)
		757	lprime = lprimed*Misc_Routines.CoFactors.d2r
		758
		759	# Mean elongation of the moon
		760	coeff1 = numpy.array([-1./1.13065e8,1./545868.,-0.0018819,445267.1114034,297.8501921])
		761	d = numpy.poly1d(coeff1)
		762	d = d(t)*Misc_Routines.CoFactors.d2r
		763	d = self.cirrange(d,rad=1)
		764
		765	# Sun's mean anomaly
		766	coeff2 = numpy.array([1.0/2.449e7,-0.0001536,35999.0502909,357.5291092])
		767	M = numpy.poly1d(coeff2)
		768	M = M(t)*Misc_Routines.CoFactors.d2r
		769	M = self.cirrange(M,rad=1)
		770
		771	# Moon's mean anomaly
		772	coeff3 = numpy.array([-1.0/1.4712e7,1.0/6.9699e4,0.0087414,477198.8675055,134.9633964])
		773	Mprime = numpy.poly1d(coeff3)
		774	Mprime = Mprime(t)*Misc_Routines.CoFactors.d2r
		775	Mprime = self.cirrange(Mprime,rad=1)
		776
		777	# Moon's argument of latitude
		778	coeff4 = numpy.array([1.0/8.6331e8,-1.0/3.526e7,-0.0036539,483202.0175233,93.2720950])
		779	F = numpy.poly1d(coeff4)
		780	F = F(t)*Misc_Routines.CoFactors.d2r
		781	F = self.cirrange(F,rad=1)
		782
		783	# Eccentricity of Earth's orbit around the sun
		784	e = 1 - 0.002516t - 7.4e-6(t**2.)
		785	e2 = e**2.
		786
		787	ecorr1 = numpy.where((numpy.abs(m_lng))==1)
		788	ecorr2 = numpy.where((numpy.abs(m_lat))==1)
		789	ecorr3 = numpy.where((numpy.abs(m_lng))==2)
		790	ecorr4 = numpy.where((numpy.abs(m_lat))==2)
		791
		792	# Additional arguments.
		793	A1 = (119.75 + 131.849t)Misc_Routines.CoFactors.d2r
		794	A2 = (53.09 + 479264.290t)Misc_Routines.CoFactors.d2r
		795	A3 = (313.45 + 481266.484t)Misc_Routines.CoFactors.d2r
		796	suml_add = 3958.numpy.sin(A1) + 1962.numpy.sin(lprime - F) + 318*numpy.sin(A2)
		797	sumb_add = -2235.numpy.sin(lprime) + 382.numpy.sin(A3) + 175.*numpy.sin(A1-F) + \
		798	175.numpy.sin(A1 + F) + 127.numpy.sin(lprime - Mprime) - 115.*numpy.sin(lprime + Mprime)
		799
		800	# Sum the periodic terms
		801	geolon = numpy.zeros(jd.size)
		802	geolat = numpy.zeros(jd.size)
		803	dist = numpy.zeros(jd.size)
		804
		805	for i in numpy.arange(jd.size):
		806	sinlng = sin_lng
		807	coslng = cos_lng
		808	sinlat = sin_lat
		809
		810	sinlng[ecorr1] = e[i]*sinlng[ecorr1]
		811	coslng[ecorr1] = e[i]*coslng[ecorr1]
		812	sinlat[ecorr2] = e[i]*sinlat[ecorr2]
		813	sinlng[ecorr3] = e2[i]*sinlng[ecorr3]
		814	coslng[ecorr3] = e2[i]*coslng[ecorr3]
		815	sinlat[ecorr4] = e2[i]*sinlat[ecorr4]
		816
		817	arg = d_lngd[i] + m_lngM[i] + mp_lngMprime[i] + f_lngF[i]
		818	geolon[i] = lprimed[i] + (numpy.sum(sinlng*numpy.sin(arg)) + suml_add[i] )/1.e6
		819	dist[i] = 385000.56 + numpy.sum(coslng*numpy.cos(arg))/1.e3
		820	arg = d_latd[i] + m_latM[i] + mp_latMprime[i] + f_latF[i]
		821	geolat[i] = (numpy.sum(sinlat*numpy.sin(arg)) + sumb_add[i])/1.e6
		822
		823	[nlon, elon] = self.nutate(jd)
		824	geolon = geolon + nlon/3.6e3
		825	geolon = self.cirrange(geolon,rad=0)
		826	lamb = geolon*Misc_Routines.CoFactors.d2r
		827	beta = geolat*Misc_Routines.CoFactors.d2r
		828
		829	# Find mean obliquity and convert lamb, beta to RA, Dec
		830	c = numpy.array([2.45,5.79,27.87,7.12,-39.05,-249.67,-51.38,1999.25,-1.55,-4680.93, \
		831	21.448])
		832	junk = numpy.poly1d(c);
		833	epsilon = 23. + (26./60.) + (junk(t/1.e2)/3600.)
		834	# True obliquity in radians
		835	eps = (epsilon + elon/3600. )*Misc_Routines.CoFactors.d2r
		836
		837	ra = numpy.arctan2(numpy.sin(lamb)numpy.cos(eps)-numpy.tan(beta)numpy.sin(eps),numpy.cos(lamb))
		838	ra = self.cirrange(ra,rad=1)
		839
		840	dec = numpy.arcsin(numpy.sin(beta)numpy.cos(eps) + numpy.cos(beta)numpy.sin(eps)*numpy.sin(lamb))
		841
		842	if rad==1:
		843	geolon = lamb
		844	geolat = beta
		845	else:
		846	ra = ra/Misc_Routines.CoFactors.d2r
		847	dec = dec/Misc_Routines.CoFactors.d2r
		848
		849	return ra, dec, dist, geolon, geolat
		850
		851	def hydrapos(self):
		852	"""
		853	hydrapos method returns RA and Dec provided by Bill Coles (Oct 2003).
		854
		855	Parameters
		856	----------
		857	None
		858
		859	Return
		860	------
		861	ra = The right ascension of the sun at that date in degrees.
		862	dec = The declination of the sun at that date in degrees.
		863	Examples
		864	--------
		865	>> [ra,dec] = hydrapos()
		866	>> print ra, dec
		867	139.45 -12.0833333333
		868
		869	Modification history
		870	--------------------
		871	Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009.
		872	"""
		873
		874	ra = (9. + 17.8/60.)*15.
		875	dec = -(12. + 5./60.)
		876
		877	return ra, dec
		878
		879
		880	def skynoise_jro(self,dec_cut=-11.95,filename='skynoise_jro.dat',filepath=None):
		881	"""
		882	hydrapos returns RA and Dec provided by Bill Coles (Oct 2003).
		883
		884	Parameters
		885	----------
		886	dec_cut = A scalar giving the declination to get a cut of the skynoise over Jica-
		887	marca. The default value is -11.95.
		888	filename = A string to specify name the skynoise file. The default value is skynoi-
		889	se_jro.dat
		890
		891	Return
		892	------
		893	maxra = The maximum right ascension to the declination used to get a cut.
		894	ra = The right ascension.
		895	Examples
		896	--------
		897	>> [maxra,ra] = skynoise_jro()
		898	>> print maxra, ra
		899	139.45 -12.0833333333
		900
		901	Modification history
		902	--------------------
		903	Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009.
		904	"""
		905
		906	if filepath==None:filepath = './resource'
		907
		908	f = open(os.path.join(filepath,filename),'rb')
		909
		910	# Reading SkyNoise Power (lineal scale)
		911	ha_sky = numpy.fromfile(f,numpy.dtype([('var','<f4')]),480*20)
		912	ha_sky = ha_sky['var'].reshape(20,480).transpose()
		913
		914	dec_sky = numpy.fromfile(f,numpy.dtype([('var','<f4')]),480*20)
		915	dec_sky = dec_sky['var'].reshape((20,480)).transpose()
		916
		917	tmp_sky = numpy.fromfile(f,numpy.dtype([('var','<f4')]),480*20)
		918	tmp_sky = tmp_sky['var'].reshape((20,480)).transpose()
		919
		920	f.close()
		921
		922	nha = 480
		923	tmp_cut = numpy.zeros(nha)
		924	for iha in numpy.arange(nha):
		925	tck = scipy.interpolate.splrep(dec_sky[iha,:],tmp_sky[iha,:],s=0)
		926	tmp_cut[iha] = scipy.interpolate.splev(dec_cut,tck,der=0)
		927
		928	ptr = numpy.nanargmax(tmp_cut)
		929
		930	maxra = ha_sky[ptr,0]
		931	ra = ha_sky[:,0]
		932
		933	return maxra, ra
		934
		935	def skyNoise(self,jd,ut=-5.0,longitude=-76.87,filename='galaxy.txt',filepath=None):
		936	"""
		937	hydrapos returns RA and Dec provided by Bill Coles (Oct 2003).
		938
		939	Parameters
		940	----------
		941	jd = The julian date of the day (and time), scalar or vector.
		942
		943	dec_cut = A scalar giving the declination to get a cut of the skynoise over Jica-
		944	marca. The default value is -11.95.
		945	filename = A string to specify name the skynoise file. The default value is skynoi-
		946	se_jro.dat
		947
		948	Return
		949	------
		950	maxra = The maximum right ascension to the declination used to get a cut.
		951	ra = The right ascension.
		952
		953	Examples
		954	--------
		955	>> [maxra,ra] = skynoise_jro()
		956	>> print maxra, ra
		957	139.45 -12.0833333333
		958
		959	Modification history
		960	--------------------
		961	Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009.
		962	"""
		963
		964	# Defining date to compute SkyNoise.
		965	[year, month, dom, hour, mis, secs] = TimeTools.Julian(jd).change2time()
		966	is_dom = (month==9) & (dom==21)
		967	if is_dom:
		968	tmp = jd
		969	jd = TimeTools.Time(year,9,22).change2julian()
		970	dom = 22
		971
		972	# Reading SkyNoise
		973	if filepath==None:filepath='./resource'
		974	f = open(os.path.join(filepath,filename))
		975
		976	lines = f.read()
		977	f.close()
		978
		979	nlines = 99
		980	lines = lines.split('\n')
		981	data = numpy.zeros((2,nlines))*numpy.float32(0.)
		982	for ii in numpy.arange(nlines):
		983	line = numpy.array([lines[ii][0:6],lines[ii][6:]])
		984	data[:,ii] = numpy.float32(line)
		985
		986	# Getting SkyNoise to the date desired.
		987	otime = data[0,:]*60.0
		988	opowr = data[1,:]
		989
		990	hour = numpy.array([0,23]);
		991	mins = numpy.array([0,59]);
		992	secs = numpy.array([0,59]);
		993	LTrange = TimeTools.Time(year,month,dom,hour,mins,secs).change2julday()
		994	LTtime = LTrange[0] + numpy.arange(1440)*((LTrange[1] - LTrange[0])/(1440.-1))
		995	lst = TimeTools.Julian(LTtime + (-3600.*ut/86400.)).change2lst()
		996
		997	ipowr = lst*0.0
		998	# Interpolating using scipy (inside max and min "x")
		999	otime = otime/3600.
		1000	val = numpy.where((lst>numpy.min(otime)) & (lst<numpy.max(otime))); val = val[0]
		1001	tck = scipy.interpolate.interp1d(otime,opowr)
		1002	ipowr[val] = tck(lst[val])
		1003
		1004	# Extrapolating above maximum time data (23.75).
		1005	uval = numpy.where(lst>numpy.max(otime))
		1006	if uval[0].size>0:
		1007	ii = numpy.min(uval[0])
		1008	m = (ipowr[ii-1] - ipowr[ii-2])/(lst[ii-1] - lst[ii-2])
		1009	b = ipowr[ii-1] - m*lst[ii-1]
		1010	ipowr[uval] = m*lst[uval] + b
		1011
		1012	if is_dom:
		1013	lst = numpy.roll(lst,4)
		1014	ipowr = numpy.roll(ipowr,4)
		1015
		1016	new_lst = numpy.int32(lst*3600.)
		1017	new_pow = ipowr
		1018
		1019	return ipowr, LTtime, lst
		1020
		1021
		1022	class AltAz(EquatorialCorrections):
		1023	def __init__(self,alt,az,jd,lat=-11.95,lon=-76.8667,WS=0,altitude=500,nutate_=0,precess_=0,\
		1024	aberration_=0,B1950=0):
		1025	"""
		1026	The AltAz class creates an object which represents the target position in horizontal
		1027	coordinates (alt-az) and allows to convert (using the methods) from this coordinate
		1028	system to others (e.g. Equatorial).
		1029
		1030	Parameters
		1031	----------
		1032	alt = Altitude in degrees. Scalar or vector.
		1033	az = Azimuth angle in degrees (measured EAST from NORTH, but see keyword WS). Sca-
		1034	lar or vector.
		1035	jd = Julian date. Scalar or vector.
		1036	lat = North geodetic latitude of location in degrees. The default value is -11.95.
		1037	lon = East longitude of location in degrees. The default value is -76.8667.
		1038	WS = Set this to 1 to get the azimuth measured westward from south.
		1039	altitude = The altitude of the observing location, in meters. The default 500.
		1040	nutate_ = Set this to 1 to force nutation, 0 for no nutation.
		1041	precess_ = Set this to 1 to force precession, 0 for no precession.
		1042	aberration_ = Set this to 1 to force aberration correction, 0 for no correction.
		1043	B1950 = Set this if your RA and DEC are specified in B1950, FK4 coordinates (ins-
		1044	tead of J2000, FK5)
		1045
		1046	Modification History
		1047	--------------------
		1048	Converted to Object-oriented Programming by Freddy Galindo, ROJ, 26 September 2009.
		1049	"""
		1050
		1051	EquatorialCorrections.__init__(self)
		1052
		1053	self.alt = numpy.atleast_1d(alt)
		1054	self.az = numpy.atleast_1d(az)
		1055	self.jd = numpy.atleast_1d(jd)
		1056	self.lat = lat
		1057	self.lon = lon
		1058	self.WS = WS
		1059	self.altitude = altitude
		1060
		1061	self.nutate_ = nutate_
		1062	self.aberration_ = aberration_
		1063	self.precess_ = precess_
		1064	self.B1950 = B1950
		1065
		1066	def change2equatorial(self):
		1067	"""
		1068	change2equatorial method converts horizon (Alt-Az) coordinates to equatorial coordi-
		1069	nates (ra-dec).
		1070
		1071	Return
		1072	------
		1073	ra = Right ascension of object (J2000) in degrees (FK5). Scalar or vector.
		1074	dec = Declination of object (J2000), in degrees (FK5). Scalar or vector.
		1075	ha = Hour angle in degrees.
		1076
		1077	Example
		1078	-------
		1079	>> alt = 88.5401
		1080	>> az = -128.990
		1081	>> jd = 2452640.5
		1082	>> ObjAltAz = AltAz(alt,az,jd)
		1083	>> [ra, dec, ha] = ObjAltAz.change2equatorial()
		1084	>> print ra, dec, ha
		1085	[ 22.20280632] [-12.86610025] [ 1.1638927]
		1086
		1087	Modification History
		1088	--------------------
		1089	Written Chris O'Dell Univ. of Wisconsin-Madison, May 2002.
		1090	Converted to Python by Freddy R. Galindo, ROJ, 26 September 2009.
		1091	"""
		1092
		1093	az = self.az
		1094	alt = self.alt
		1095	if self.WS>0:az = az -180.
		1096	ra_tmp = numpy.zeros(numpy.size(self.jd)) + 45.
		1097	dec_tmp = numpy.zeros(numpy.size(self.jd)) + 45.
		1098	[dra1,ddec1,eps,d_psi,d_eps] = self.co_nutate(self.jd,ra_tmp, dec_tmp)
		1099
		1100	# Getting local mean sidereal time (lmst)
		1101	lmst = TimeTools.Julian(self.jd[0]).change2lst()
		1102	lmst = lmst*Misc_Routines.CoFactors.h2d
		1103	# Getting local apparent sidereal time (last)
		1104	last = lmst + d_psi*numpy.cos(eps)/3600.
		1105
		1106	# Now do the spherical trig to get APPARENT hour angle and declination (Degrees).
		1107	[ha, dec] = self.change2HaDec()
		1108
		1109	# Finding Right Ascension (in degrees, from 0 to 360.)
		1110	ra = (last - ha + 360.) % 360.
		1111
		1112	# Calculate NUTATION and ABERRATION Correction to Ra-Dec
		1113	[dra1, ddec1,eps,d_psi,d_eps] = self.co_nutate(self.jd,ra,dec)
		1114	[dra2,ddec2,eps] = self.co_aberration(self.jd,ra,dec)
		1115
		1116	# Make Nutation and Aberration correction (if wanted)
		1117	ra = ra - (dra1self.nutate_ + dra2self.aberration_)/3600.
		1118	dec = dec - (ddec1self.nutate_ + ddec2self.aberration_)/3600.
		1119
		1120	# Computing current equinox
		1121	j_now = (self.jd - 2451545.)/365.25 + 2000
		1122
		1123	# Precess coordinates to current date
		1124	if self.precess_==1:
		1125	njd = numpy.size(self.jd)
		1126	for ii in numpy.arange(njd):
		1127	ra_i = ra[ii]
		1128	dec_i = dec[ii]
		1129	now = j_now[ii]
		1130
		1131	if self.B1950==1:
		1132	[ra_i,dec_i] = self.precess(ra_i,dec_i,now,1950.,FK4=1)
		1133	elif self.B1950==0:
		1134	[ra_i,dec_i] = self.precess(ra_i,dec_i,now,2000.,FK4=0)
		1135
		1136	ra[ii] = ra_i
		1137	dec[ii] = dec_i
		1138
		1139	return ra, dec, ha
		1140
		1141	def change2HaDec(self):
		1142	"""
		1143	change2HaDec method converts from horizon (Alt-Az) coordinates to hour angle and de-
		1144	clination.
		1145
		1146	Return
		1147	------
		1148	ha = The local apparent hour angle, in degrees. The hour angle is the time that ri-
		1149	ght ascension of 0 hours crosses the local meridian. It is unambiguisoly defined.
		1150	dec = The local apparent declination, in degrees.
		1151
		1152	Example
		1153	-------
		1154	>> alt = 88.5401
		1155	>> az = -128.990
		1156	>> jd = 2452640.5
		1157	>> ObjAltAz = AltAz(alt,az,jd)
		1158	>> [ha, dec] = ObjAltAz.change2HaDec()
		1159	>> print ha, dec
		1160	[ 1.1638927] [-12.86610025]
		1161
		1162	Modification History
		1163	--------------------
		1164	Written Chris O'Dell Univ. of Wisconsin-Madison, May 2002.
		1165	Converted to Python by Freddy R. Galindo, ROJ, 26 September 2009.
		1166	"""
		1167
		1168	alt_r = numpy.atleast_1d(self.alt*Misc_Routines.CoFactors.d2r)
		1169	az_r = numpy.atleast_1d(self.az*Misc_Routines.CoFactors.d2r)
		1170	lat_r = numpy.atleast_1d(self.lat*Misc_Routines.CoFactors.d2r)
		1171
		1172	# Find local hour angle (in degrees, from 0 to 360.)
		1173	y_ha = -1numpy.sin(az_r)numpy.cos(alt_r)
		1174	x_ha = -1numpy.cos(az_r)numpy.sin(lat_r)numpy.cos(alt_r) + numpy.sin(alt_r)numpy.cos(lat_r)
		1175
		1176	ha = numpy.arctan2(y_ha,x_ha)
		1177	ha = ha/Misc_Routines.CoFactors.d2r
		1178
		1179	w = numpy.where(ha<0.)
		1180	if w[0].size>0:ha[w] = ha[w] + 360.
		1181	ha = ha % 360.
		1182
		1183	# Find declination (positive if north of celestial equatorial, negative if south)
		1184	sindec = numpy.sin(lat_r)numpy.sin(alt_r) + numpy.cos(lat_r)numpy.cos(alt_r)*numpy.cos(az_r)
		1185	dec = numpy.arcsin(sindec)/Misc_Routines.CoFactors.d2r
		1186
		1187	return ha, dec
		1188
		1189
		1190	class Equatorial(EquatorialCorrections):
		1191	def __init__(self,ra,dec,jd,lat=-11.95,lon=-76.8667,WS=0,altitude=500,nutate_=0,precess_=0,\
		1192	aberration_=0,B1950=0):
		1193	"""
		1194	The Equatorial class creates an object which represents the target position in equa-
		1195	torial coordinates (ha-dec) and allows to convert (using the class methods) from
		1196	this coordinate system to others (e.g. AltAz).
		1197
		1198	Parameters
		1199	----------
		1200	ra = Right ascension of object (J2000) in degrees (FK5). Scalar or vector.
		1201	dec = Declination of object (J2000), in degrees (FK5). Scalar or vector.
		1202	jd = Julian date. Scalar or vector.
		1203	lat = North geodetic latitude of location in degrees. The default value is -11.95.
		1204	lon = East longitude of location in degrees. The default value is -76.8667.
		1205	WS = Set this to 1 to get the azimuth measured westward from south.
		1206	altitude = The altitude of the observing location, in meters. The default 500.
		1207	nutate = Set this to 1 to force nutation, 0 for no nutation.
		1208	precess = Set this to 1 to force precession, 0 for no precession.
		1209	aberration = Set this to 1 to force aberration correction, 0 for no correction.
		1210	B1950 = Set this if your RA and DEC are specified in B1950, FK4 coordinates (ins-
		1211	tead of J2000, FK5)
		1212
		1213	Modification History
		1214	--------------------
		1215	Converted to Object-oriented Programming by Freddy Galindo, ROJ, 29 September 2009.
		1216	"""
		1217
		1218	EquatorialCorrections.__init__(self)
		1219
		1220	self.ra = numpy.atleast_1d(ra)
		1221	self.dec = numpy.atleast_1d(dec)
		1222	self.jd = numpy.atleast_1d(jd)
		1223	self.lat = lat
		1224	self.lon = lon
		1225	self.WS = WS
		1226	self.altitude = altitude
		1227
		1228	self.nutate_ = nutate_
		1229	self.aberration_ = aberration_
		1230	self.precess_ = precess_
		1231	self.B1950 = B1950
		1232
		1233	def change2AltAz(self):
		1234	"""
		1235	change2AltAz method converts from equatorial coordinates (ha-dec) to horizon coordi-
		1236	nates (alt-az).
		1237
		1238	Return
		1239	------
		1240	alt = Altitude in degrees. Scalar or vector.
		1241	az = Azimuth angle in degrees (measured EAST from NORTH, but see keyword WS). Sca-
		1242	lar or vector.
		1243	ha = Hour angle in degrees.
		1244
		1245	Example
		1246	-------
		1247	>> ra = 43.370609
		1248	>> dec = -28.0000
		1249	>> jd = 2452640.5
		1250	>> ObjEq = Equatorial(ra,dec,jd)
		1251	>> [alt, az, ha] = ObjEq.change2AltAz()
		1252	>> print alt, az, ha
		1253	[ 65.3546497] [ 133.58753124] [ 339.99609002]
		1254
		1255	Modification History
		1256	--------------------
		1257	Written Chris O'Dell Univ. of Wisconsin-Madison. May 2002
		1258	Converted to Python by Freddy R. Galindo, ROJ, 29 September 2009.
		1259	"""
		1260
		1261	ra = self.ra
		1262	dec = self.dec
		1263
		1264	# Computing current equinox
		1265	j_now = (self.jd - 2451545.)/365.25 + 2000
		1266
		1267	# Precess coordinates to current date
		1268	if self.precess_==1:
		1269	njd = numpy.size(self.jd)
		1270	for ii in numpy.arange(njd):
		1271	ra_i = ra[ii]
		1272	dec_i = dec[ii]
		1273	now = j_now[ii]
		1274
		1275	if self.B1950==1:
		1276	[ra_i,dec_i] = self.precess(ra_i,dec_i,now,1950.,FK4=1)
		1277	elif self.B1950==0:
		1278	[ra_i,dec_i] = self.precess(ra_i,dec_i,now,2000.,FK4=0)
		1279
		1280	ra[ii] = ra_i
		1281	dec[ii] = dec_i
		1282
		1283	# Calculate NUTATION and ABERRATION Correction to Ra-Dec
		1284	[dra1, ddec1,eps,d_psi,d_eps] = self.co_nutate(self.jd,ra,dec)
		1285	[dra2,ddec2,eps] = self.co_aberration(self.jd,ra,dec)
		1286
		1287	# Make Nutation and Aberration correction (if wanted)
		1288	ra = ra + (dra1self.nutate_ + dra2self.aberration_)/3600.
		1289	dec = dec + (ddec1self.nutate_ + ddec2self.aberration_)/3600.
		1290
		1291	# Getting local mean sidereal time (lmst)
		1292	lmst = TimeTools.Julian(self.jd).change2lst()
		1293
		1294	lmst = lmst*Misc_Routines.CoFactors.h2d
		1295	# Getting local apparent sidereal time (last)
		1296	last = lmst + d_psi*numpy.cos(eps)/3600.
		1297
		1298	# Finding Hour Angle (in degrees, from 0 to 360.)
		1299	ha = last - ra
		1300	w = numpy.where(ha<0.)
		1301	if w[0].size>0:ha[w] = ha[w] + 360.
		1302	ha = ha % 360.
		1303
		1304	# Now do the spherical trig to get APPARENT hour angle and declination (Degrees).
		1305	[alt, az] = self.HaDec2AltAz(ha,dec)
		1306
		1307	return alt, az, ha
		1308
		1309	def HaDec2AltAz(self,ha,dec):
		1310	"""
		1311	HaDec2AltAz convert hour angle and declination (ha-dec) to horizon coords (alt-az).
		1312
		1313	Parameters
		1314	----------
		1315	ha = The local apparent hour angle, in DEGREES, scalar or vector.
		1316	dec = The local apparent declination, in DEGREES, scalar or vector.
		1317
		1318	Return
		1319	------
		1320	alt = Altitude in degrees. Scalar or vector.
		1321	az = Azimuth angle in degrees (measured EAST from NORTH, but see keyword WS). Sca-
		1322	lar or vector.
		1323
		1324	Modification History
		1325	--------------------
		1326	Written Chris O'Dell Univ. of Wisconsin-Madison, May 2002.
		1327	Converted to Python by Freddy R. Galindo, ROJ, 26 September 2009.
		1328	"""
		1329
		1330	sh = numpy.sin(haMisc_Routines.CoFactors.d2r) ; ch = numpy.cos(haMisc_Routines.CoFactors.d2r)
		1331	sd = numpy.sin(decMisc_Routines.CoFactors.d2r) ; cd = numpy.cos(decMisc_Routines.CoFactors.d2r)
		1332	sl = numpy.sin(self.latMisc_Routines.CoFactors.d2r) ; cl = numpy.cos(self.latMisc_Routines.CoFactors.d2r)
		1333
		1334	x = -1chcdsl + sdcl
		1335	y = -1shcd
		1336	z = chcdcl + sd*sl
		1337	r = numpy.sqrt(x2. + y2.)
		1338
		1339	az = numpy.arctan2(y,x)/Misc_Routines.CoFactors.d2r
		1340	alt = numpy.arctan2(z,r)/Misc_Routines.CoFactors.d2r
		1341
		1342	# correct for negative az.
		1343	w = numpy.where(az<0.)
		1344	if w[0].size>0:az[w] = az[w] + 360.
		1345
		1346	# Convert az to West from South, if desired
		1347	if self.WS==1: az = (az + 180.) % 360.
		1348
		1349	return alt, az
		1350
		1351
		1352	class Geodetic():
		1353	def __init__(self,lat=-11.95,alt=0):
		1354	"""
		1355	The Geodetic class creates an object which represents the real position on earth of
		1356	a target (Geodetic Coordinates: lat-alt) and allows to convert (using the class me-
		1357	thods) from this coordinate system to others (e.g. geocentric).
		1358
		1359	Parameters
		1360	----------
		1361	lat = Geodetic latitude of location in degrees. The default value is -11.95.
		1362
		1363	alt = Geodetic altitude (km). The default value is 0.
		1364
		1365	Modification History
		1366	--------------------
		1367	Converted to Object-oriented Programming by Freddy R. Galindo, ROJ, 02 October 2009.
		1368	"""
		1369
		1370	self.lat = numpy.atleast_1d(lat)
		1371	self.alt = numpy.atleast_1d(alt)
		1372
		1373	self.a = 6378.16
		1374	self.ab2 = 1.0067397
		1375	self.ep2 = 0.0067397
		1376
		1377	def change2geocentric(self):
		1378	"""
		1379	change2geocentric method converts from Geodetic to Geocentric coordinates. The re-
		1380	ference geoid is that adopted by the IAU in 1964.
		1381
		1382	Return
		1383	------
		1384	gclat = Geocentric latitude (in degrees), scalar or vector.
		1385	gcalt = Geocentric radial distance (km), scalar or vector.
		1386
		1387	Example
		1388	-------
		1389	>> ObjGeoid = Geodetic(lat=-11.95,alt=0)
		1390	>> [gclat, gcalt] = ObjGeoid.change2geocentric()
		1391	>> print gclat, gcalt
		1392	[-11.87227742] [ 6377.25048195]
		1393
		1394	Modification History
		1395	--------------------
		1396	Converted to Python by Freddy R. Galindo, ROJ, 02 October 2009.
		1397	"""
		1398
		1399	gdl = self.lat*Misc_Routines.CoFactors.d2r
		1400	slat = numpy.sin(gdl)
		1401	clat = numpy.cos(gdl)
		1402	slat2 = slat**2.
		1403	clat2 = (self.ab2clat)*2.
		1404
		1405	sbet = slat/numpy.sqrt(slat2 + clat2)
		1406	sbet2 = (sbet**2.) # < 1
		1407	noval = numpy.where(sbet2>1)
		1408	if noval[0].size>0:sbet2[noval] = 1
		1409	cbet = numpy.sqrt(1. - sbet2)
		1410
		1411	rgeoid = self.a/numpy.sqrt(1. + self.ep2*sbet2)
		1412
		1413	x = rgeoidcbet + self.altclat
		1414	y = rgeoidsbet + self.altslat
		1415
		1416	gcalt = numpy.sqrt(x2. + y2.)
		1417	gclat = numpy.arctan2(y,x)/Misc_Routines.CoFactors.d2r
		1418
		1419	return gclat, gcalt

apps/abs/utils/Files.py created 644 +18 0

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	1	'''
	2	Created on Jun 19, 2013
	3
	4	@author: Jose Antonio Sal y Rosas Celi
	5	@contact: jose.salyrosas@jro.igp.gob.pe
	6	'''
	7
	8	from datetime import datetime
	9
	10	class Files(object):
	11
	12	def setFilename(self):
	13	return datetime.today().strftime("%Y%m%d%H%M%S%f")
	14
	15	def save(self, filename, contentFile):
	16	f = open(filename, 'a+')
	17	f.write(contentFile)
	18	f.close()

apps/abs/utils/Graphics_Miscens.py created 644 +51 0

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	1	"""
	2	The GRAPHICS_MISC.py module gathers classes and/or functions useful for generation of plots.
	3
	4	MODULES CALLED:
	5	NUMPY, OS
	6
	7	MODIFICATION HISTORY:
	8	Created by Ing. Freddy Galindo (frederickgalindo@gmail.com). ROJ, 13 August 2009.
	9	"""
	10
	11	import os
	12	import numpy
	13	import sys
	14
	15
	16	class ColorTable:
	17	def __init__(self,table=1,filepath=None):
	18	self.table = table
	19	#set to path for data folder, file: col_koki.dat
	20	if filepath==None:
	21	filepath= './data/'
	22	self.filepath = filepath
	23
	24	def readTable(self):
	25	if self.table>0:
	26	if self.table==1:
	27	f = open(os.path.join(self.filepath,'col_koki.dat'),'rb')
	28
	29	#f = open('./col_koki.dat','rb')
	30
	31	# Reading SkyNoise Power (lineal scale)
	32	blue = numpy.fromfile(f,numpy.dtype([('var','b')]),256)
	33	blue = numpy.int32(blue['var'])
	34	val = numpy.where(blue<0)
	35	if val[0].size:blue[val] = blue[val] + numpy.int32(256)
	36
	37	green = numpy.fromfile(f,numpy.dtype([('var','b')]),256)
	38	green = numpy.int32(green['var'])
	39	val = numpy.where(green<0)
	40	if val[0].size:green[val] = green[val] + numpy.int32(256)
	41
	42	red = numpy.fromfile(f,numpy.dtype([('var','b')]),256)
	43	red = numpy.int32(red['var'])
	44	val = numpy.where(red<0)
	45	if val[0].size:red[val] = red[val] + numpy.int32(256)
	46
	47	f.close()
	48
	49	colortable = numpy.array([red/255.,green/255.,blue/255.])
	50
	51	return colortable

apps/abs/utils/Graphics_OverJro.py created 644 +563 0

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		1	"""
		2	The module GRAPHICS_OVERJRO.py gathers classes or/and functions to create graphics from OVER-JRO
		3	project (e.g. antenna patterns, skynoise, ...).
		4
		5	MODULES CALLED:
		6	TIME, NUMPY, MATPLOTLIB, TIMETOOLS
		7
		8	MODIFICATION HISTORY:
		9	Created by Ing. Freddy Galindo (frederickgalindo@gmail.com). ROJ Oct 18, 2009.
		10	"""
		11
		12	import time
		13	import numpy
		14	import sys
		15	import os
		16
		17	# set HOME environment variable to a directory the httpd server can write to
		18	#os.environ[ 'HOME' ] = '/usr/local/www/htdocs/overJro/tempReports'
		19	#os.environ[ 'HOME' ] = '/home/dsuarez/Pictures'
		20	#os.environ[ 'HOME' ] = '/tmp/'
		21	import matplotlib
		22	#if ide==1:
		23	# matplotlib.use('Qt4Agg')
		24	#elif ide==2:
		25	# matplotlib.use("Agg")
		26	#else:
		27	# matplotlib.use('TKAgg')
		28	#matplotlib.use("Agg")
		29	#matplotlib.interactive(1)
		30	import matplotlib.pyplot
		31	#import Numeric
		32	#import scipy
		33	import scipy.interpolate
		34
		35	import Astro_Coords
		36	import TimeTools
		37	import Graphics_Miscens
		38
		39	import Misc_Routines
		40
		41	class AntPatternPlot:
		42	def __init__(self):
		43	"""
		44	AntPatternPlot creates an object to call methods to plot the antenna pattern.
		45
		46	Modification History
		47	--------------------
		48	Created by Freddy Galindo, ROJ, 06 October 2009.
		49	"""
		50	self.figure = None
		51	pass
		52
		53	def contPattern(self,iplot=0,gpath='',filename='',mesg='',amp=None ,x=None ,y=None ,getCut=None,title=''):
		54	"""
		55	contPattern plots a contour map of the antenna pattern.
		56
		57	Parameters
		58	----------
		59	iplot = A integer to specify if the plot is the first, second, ... The default va-
		60	lue is 0.
		61
		62	Examples
		63	--------
		64	>> Over_Jro.JroPattern(pattern=2).contPattern()
		65
		66	Modification history
		67	--------------------
		68	Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009.
		69	"""
		70
		71	if getCut == 1:
		72	return
		73
		74	xmax = numpy.max(x)
		75	xmin = numpy.min(x)
		76	ymax = numpy.max(y)
		77	ymin = numpy.min(y)
		78
		79	levels = numpy.array([1e-3,1e-2,1e-1,0.5,1.0])
		80	tmp = numpy.round(10*numpy.log10(levels),decimals=1)
		81	labels = range(5)
		82	for i in numpy.arange(5):labels[i] = str(numpy.int(tmp[i]))
		83
		84	if iplot==0:
		85	xsize = 8.0
		86	if matplotlib.get_backend()=='QT4Agg':xsize = 6.0
		87	ysize = 8.0
		88	self.figure = matplotlib.pyplot.figure(num=2,figsize=(xsize,ysize))
		89	matplotlib.pyplot.clf()
		90
		91	colors = ((0,0,1.),(0,170/255.,0),(127/255.,1.,0),(1.,109/255.,0),(128/255.,0,0))
		92	CS = matplotlib.pyplot.contour(x,y,amp.transpose(),levels,colors=colors)
		93	fmt = {}
		94	for l,s in zip(CS.levels,labels):fmt[l] = s
		95
		96	matplotlib.pyplot.annotate('Ng',xy=(-0.05,1.04),xytext=(0.01,0.962),xycoords='axes fraction',arrowprops=dict(facecolor='black', width=1.,shrink=0.2),fontsize=15.)
		97	matplotlib.pyplot.annotate(mesg,xy=(0,0),xytext=(0.01,0.01),xycoords='figure fraction')
		98	matplotlib.pyplot.clabel(CS,CS.levels,inline=True,fmt=fmt,fontsize=10)
		99	matplotlib.pyplot.xlim(xmin,xmax)
		100	matplotlib.pyplot.ylim(ymin,ymax)
		101	matplotlib.pyplot.title("Total Pattern" + title)
		102	matplotlib.pyplot.xlabel("West to South")
		103	matplotlib.pyplot.ylabel("West to North")
		104	matplotlib.pyplot.grid(True)
		105	print "SAVE_FIG"
		106	print gpath
		107	print filename
		108	save_fig = os.path.join(gpath,filename)
		109	matplotlib.pyplot.savefig(save_fig,format='png')
		110
		111	def plotRaDec(self,gpath=None,filename=None,jd=2452640.5,ra_obs=None,xg=None,yg=None,x=None,y=None):
		112	"""
		113	plotRaDec draws right ascension and declination lines on a JRO plane. This function
		114	must call after conPattern.
		115
		116	Parameters
		117	----------
		118	jd = A scalar giving the Julian date.
		119	ra_obs = Scalar giving the right ascension of the observatory.
		120	xg = A 3-element array to specify ..
		121	yg = A 3-element array to specify ..
		122
		123	Examples
		124	--------
		125	>> Over_Jro.JroPattern(pattern=2).contPattern()
		126	>> Over_Jro.JroPattern(pattern=2).plotRaDec(jd=jd,ra_obs=ra_obs,xg=xg,yg=yg)
		127
		128	Modification history
		129	--------------------
		130	Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009.
		131	"""
		132
		133	# Finding RA of observatory for a specific date
		134	if ra_obs==None:ra_obs = numpy.array([23.37060849])
		135	if xg==None:xg = numpy.array([0.62918474,-0.77725579,0.])
		136	if yg==None:yg = numpy.array([0.77700346,0.62898048,0.02547905])
		137
		138	# Getting HA and DEC axes
		139	mindec = -28; maxdec = 4; incdec = 2.
		140	ndec = numpy.int((maxdec - mindec)/incdec) + 1
		141
		142	minha = -20; maxha = 20; incha = 2.
		143	nha = numpy.int((maxha - minha)/incha) + 1
		144
		145	mcosx = numpy.zeros((nha,ndec))
		146	mcosy = numpy.zeros((nha,ndec))
		147
		148	ha_axes = numpy.reshape(numpy.arange(nha)*incha + minha,(nha,1))
		149	ones_dec = numpy.reshape(numpy.zeros(ndec) + 1,(ndec,1))
		150	ha_axes = numpy.dot(ha_axes,ones_dec.transpose())
		151	ha_axes2 = numpy.array(ra_obs - ha_axes)
		152
		153	dec_axes = numpy.reshape(numpy.arange(ndec)*incdec + mindec,(ndec,1))
		154	ones_ra = numpy.reshape(numpy.zeros(nha) + 1,(nha,1))
		155	dec_axes = numpy.dot(ones_ra,dec_axes.transpose())
		156	dec_axes2 = numpy.array(dec_axes)
		157
		158	ObjHor = Astro_Coords.Equatorial(ha_axes2,dec_axes2,jd)
		159	[alt,az,ha] = ObjHor.change2AltAz()
		160
		161	z = numpy.transpose(alt)*Misc_Routines.CoFactors.d2r ; z = z.flatten()
		162	az = numpy.transpose(az)*Misc_Routines.CoFactors.d2r ; az = az.flatten()
		163
		164	vect = numpy.array([numpy.cos(z)numpy.sin(az),numpy.cos(z)numpy.cos(az),numpy.sin(z)])
		165
		166	xg = numpy.atleast_2d(xg)
		167	dcosx = numpy.array(numpy.dot(xg,vect))
		168	yg = numpy.atleast_2d(yg)
		169	dcosy = numpy.array(numpy.dot(yg,vect))
		170
		171	mcosx = dcosx.reshape(ndec,nha)
		172	mcosy = dcosy.reshape(ndec,nha)
		173
		174	# Defining NAN for points outof limits.
		175	xmax = numpy.max(x)
		176	xmin = numpy.min(x)
		177	ymax = numpy.max(y)
		178	ymin = numpy.min(y)
		179
		180	factor = 1.3
		181	noval = numpy.where((mcosx>(xmaxfactor)) \| (mcosx<(xminfactor)))
		182	if noval[0].size>0:mcosx[noval] = numpy.nan
		183	noval = numpy.where((mcosy>(ymaxfactor)) \| (mcosy<(yminfactor)))
		184	if noval[0].size>0:mcosy[noval] = numpy.nan
		185
		186	# Plotting HA and declination grid.
		187	iha0 = numpy.int((0 - minha)/incha)
		188	idec0 = numpy.int((-14 - mindec)/incdec)
		189
		190	colorgrid = (1.,109/255.,0)
		191	matplotlib.pyplot.plot(mcosx.transpose(),mcosy.transpose(),color=colorgrid,linestyle='--')
		192	for idec in numpy.arange(ndec):
		193	if idec != idec0:
		194	valx = (mcosx[idec,iha0]<=xmax) & (mcosx[idec,iha0]>=xmin)
		195	valy = (mcosy[idec,iha0]<=ymax) & (mcosy[idec,iha0]>=ymin)
		196	if valx & valy:
		197	text = str(numpy.int(mindec + incdec*idec))+'$^o$'
		198	matplotlib.pyplot.text(mcosx[idec,iha0],mcosy[idec,iha0],text)
		199
		200	matplotlib.pyplot.plot(mcosx,mcosy,color=colorgrid,linestyle='--')
		201	for iha in numpy.arange(nha):
		202	if iha != iha0:
		203	valx = (mcosx[idec0,iha]<=xmax) & (mcosx[idec0,iha]>=xmin)
		204	valy = (mcosy[idec0,iha]<=ymax) & (mcosy[idec0,iha]>=ymin)
		205	if valx & valy:
		206	text = str(4numpy.int(minha + inchaiha))+"'"
		207	matplotlib.pyplot.text(mcosx[idec0,iha],mcosy[idec0,iha],text)
		208
		209	matplotlib.pyplot.xlim(xmin,xmax)
		210	matplotlib.pyplot.ylim(ymin,ymax)
		211
		212	save_fig = os.path.join(gpath,filename)
		213	matplotlib.pyplot.savefig(save_fig,format='png')
		214
		215
		216	class BFieldPlot:
		217	def __init__(self):
		218	"""
		219	BFieldPlot creates an object for drawing magnetic Field lines over Jicamarca.
		220
		221	Modification History
		222	--------------------
		223	Created by Freddy Galindo, ROJ, 07 October 2009.
		224	"""
		225
		226	self.alpha_location = 1
		227	# pass
		228
		229	def plotBField(self,gpath,filename,dcos,alpha, nlon, nlat, dcosxrange, dcosyrange, heights, alpha_i):
		230	"""
		231	plotBField draws the magnetic field in a directional cosines plot.
		232
		233	Parameters
		234	----------
		235	dcos = An 4-dimensional array giving the directional cosines of the magnetic field
		236	over the desired place.
		237	alpha = An 3-dimensional array giving the angle of the magnetic field over the desi-
		238	red place.
		239	nlon = An integer to specify the number of elements per longitude.
		240	nlat = An integer to specify the number of elements per latitude.
		241	dcosxrange = A 2-element array giving the range of the directional cosines in the
		242	"x" axis.
		243	dcosyrange = A 2-element array giving the range of the directional cosines in the
		244	"y" axis.
		245	heights = An array giving the heights (km) where the magnetic field will be modeled By default the magnetic field will be computed at 100, 500 and 1000km.
		246	alpha_i = Angle to interpolate the magnetic field.
		247	Modification History
		248	--------------------
		249	Converted to Python by Freddy R. Galindo, ROJ, 07 October 2009.
		250	"""
		251
		252	handles = []
		253	objects = []
		254	colors = ['k','m','c','b','g','r','y']
		255	marker = ['-+','-*','-D','-x','-s','->','-o','-^']
		256
		257	alpha_location = numpy.zeros((nlon,2,heights.size))
		258
		259	for ih in numpy.arange(heights.size):
		260	alpha_location[:,0,ih] = dcos[:,0,ih,0]
		261	for ilon in numpy.arange(nlon):
		262	myx = (alpha[ilon,:,ih])[::-1]
		263	myy = (dcos[ilon,:,ih,0])[::-1]
		264	tck = scipy.interpolate.splrep(myx,myy,s=0)
		265	mydcosx = scipy.interpolate.splev(alpha_i,tck,der=0)
		266
		267	myx = (alpha[ilon,:,ih])[::-1]
		268	myy = (dcos[ilon,:,ih,1])[::-1]
		269	tck = scipy.interpolate.splrep(myx,myy,s=0)
		270	mydcosy = scipy.interpolate.splev(alpha_i,tck,der=0)
		271	alpha_location[ilon,:,ih] = numpy.array([mydcosx, mydcosy])
		272
		273
		274	ObjFig, = matplotlib.pyplot.plot(alpha_location[:,0,ih],alpha_location[:,1,ih], \
		275	marker[ih % 8],color=colors[numpy.int(ih/8)],ms=4.5,lw=0.5)
		276	handles.append(ObjFig)
		277	objects.append(numpy.str(heights[ih]) + ' km')
		278
		279	matplotlib.pyplot.xlim(dcosxrange[0],dcosxrange[1])
		280	matplotlib.pyplot.ylim(dcosyrange[0],dcosyrange[1])
		281
		282	try:
		283	ObjlegB = matplotlib.pyplot.legend(handles,objects,loc="lower right", numpoints=1, handlelength=0.3, \
		284	handletextpad=0.02, borderpad=0.3, labelspacing=0.1)
		285	except:
		286	ObjlegB = matplotlib.pyplot.legend(handles,objects,loc=[0.01,0.75], numpoints=1, handlelength=0, \
		287	pad=0.015, handletextsep=0.02,labelsep=0.01)
		288
		289	matplotlib.pyplot.setp(ObjlegB.get_texts(),fontsize='small')
		290	matplotlib.pyplot.gca().add_artist(ObjlegB)
		291
		292	save_fig = os.path.join(gpath,filename)
		293	matplotlib.pyplot.savefig(save_fig,format='png')
		294	self.alpha_location = alpha_location
		295
		296
		297	class CelestialObjectsPlot:
		298	def __init__(self,jd,dec,tod,maxha_min,show_object=None):
		299
		300	self.jd = jd
		301	self.dec = dec
		302	self.tod = tod
		303	self.maxha_min = maxha_min
		304
		305	if show_object==None:show_object=numpy.zeros(4)+2
		306	self.show_object = show_object
		307
		308	self.dcosx_sun = 1
		309	self.dcosy_sun = 1
		310	self.ha_sun = 1
		311	self.time_sun = 1
		312
		313	self.dcosx_moon = 1
		314	self.dcosy_moon = 1
		315	self.ha_moon = 1
		316	self.time_moon = 1
		317
		318	self.dcosx_hydra = 1
		319	self.dcosy_hydra = 1
		320	self.ha_hydra = 1
		321	self.time_hydra = 1
		322
		323	self.dcosx_galaxy = 1
		324	self.dcosy_galaxy = 1
		325	self.ha_galaxy = 1
		326	self.time_galaxy = 1
		327
		328	def drawObject(self,glat,glon,xg,yg,dcosxrange,dcosyrange,gpath='',filename=''):
		329
		330	jd = self.jd
		331	main_dec = self.dec
		332	tod = self.tod
		333	maxha_min = self.maxha_min
		334
		335	mesg = "Drawing celestial objects over Observatory"
		336	# print mesg
		337	# if textid!=None:textid.append(mesg)
		338
		339	maxlev = 24; minlev = 0; maxcol = 39; mincol = 10
		340	handles = []
		341	objects = ['$Sun$','$Moon$','$Hydra$','$Galaxy$']
		342	marker = ['--^','--s','--*','--o']
		343
		344	# Getting RGB table to plot celestial object over Jicamarca
		345	colortable = Graphics_Miscens.ColorTable(table=1).readTable()
		346
		347	for io in (numpy.arange(4)+1):
		348	if self.show_object[io]!=0:
		349	ObjBodies = Astro_Coords.CelestialBodies()
		350	if io==1:
		351	[ra,dec,sunlon,sunobliq] = ObjBodies.sunpos(jd)
		352	elif io==2:
		353	[ra,dec,dist,moonlon,moonlat] = ObjBodies.moonpos(jd)
		354	elif io==3:
		355	[ra,dec] = ObjBodies.hydrapos()
		356	elif io==4:
		357	[maxra,ra] = ObjBodies.skynoise_jro(dec_cut=main_dec)
		358	ra = maxra*15.
		359	dec = main_dec
		360
		361	ObjEq = Astro_Coords.Equatorial(ra,dec,jd,lat=glat,lon=glon)
		362	[alt, az, ha] = ObjEq.change2AltAz()
		363	vect = numpy.array([az,alt]).transpose()
		364	vect = Misc_Routines.Vector(vect,direction=0).Polar2Rect()
		365
		366	dcosx = numpy.array(numpy.dot(vect,xg))
		367	dcosy = numpy.array(numpy.dot(vect,yg))
		368	wrap = numpy.where(ha>=180.)
		369	if wrap[0].size>0:ha[wrap] = ha[wrap] - 360.
		370
		371	val = numpy.where((numpy.abs(ha))<=(maxha_min*0.25))
		372	if val[0].size>2:
		373	tod_1 = tod*1.
		374	shift_1 = numpy.where(tod>12.)
		375	tod_1[shift_1] = tod_1[shift_1] - 24.
		376	tod_2 = tod*1.
		377	shift_2 = numpy.where(tod<12.)
		378	tod_2[shift_2] = tod_2[shift_2] + 24.
		379
		380	diff0 = numpy.nanmax(tod[val]) - numpy.nanmin(tod[val])
		381	diff1 = numpy.nanmax(tod_1[val]) - numpy.nanmin(tod_1[val])
		382	diff2 = numpy.nanmax(tod_2[val]) - numpy.nanmin(tod_2[val])
		383
		384	if ((diff0<=diff1) & (diff0<=diff2)):
		385	tod_0 = tod
		386	elif ((diff1<diff0) & (diff1<diff2)):
		387	tod_0 = tod_1
		388	else:
		389	tod_0 = tod_2
		390
		391	if io==1:
		392	self.dcosx_sun = dcosx[val]
		393	self.dcosy_sun = dcosy[val]
		394	self.ha_sun = ha[val]
		395	self.time_sun = numpy.median(tod_0[val])
		396	elif io==2:
		397	self.dcosx_moon = dcosx[val]
		398	self.dcosy_moon = dcosy[val]
		399	self.ha_moon = ha[val]
		400	self.time_moon = numpy.median(tod_0[val])
		401	elif io==3:
		402	self.dcosx_hydra = dcosx[val]
		403	self.dcosy_hydra = dcosy[val]
		404	self.ha_hydra = ha[val]
		405	self.time_hydra = numpy.mean(tod_0[val])
		406	elif io==4:
		407	self.dcosx_galaxy = dcosx[val]
		408	self.dcosy_galaxy = dcosy[val]
		409	self.ha_galaxy = ha[val]
		410	self.time_galaxy = numpy.mean(tod_0[val])
		411
		412	index = numpy.mean(tod_0[val]) - minlev
		413	index = (index*(maxcol - mincol)/(maxlev - minlev)) + mincol
		414	index = numpy.int(index)
		415	figobjects, = matplotlib.pyplot.plot(dcosx[val],dcosy[val],marker[io-1],\
		416	lw=1,ms=7,mew=0,color=tuple(colortable[:,index]))
		417	handles.append(figobjects)
		418
		419	xmax = numpy.max(dcosxrange[1])
		420	xmin = numpy.min(dcosxrange[0])
		421	ymax = numpy.max(dcosyrange[1])
		422	ymin = numpy.min(dcosyrange[0])
		423	matplotlib.pyplot.xlim(xmin,xmax)
		424	matplotlib.pyplot.ylim(ymin,ymax)
		425
		426	val = numpy.where(self.show_object[1:]>0)
		427	objects = numpy.array(objects)
		428	objects = list(objects[val])
		429	try:
		430	ObjlegC = matplotlib.pyplot.legend(handles,objects,loc="lower left", numpoints=1, handlelength=0.3, \
		431	borderpad=0.3, handletextpad=0.02,labelspacing=0.1)
		432	except:
		433	ObjlegC = matplotlib.pyplot.legend(handles,objects,loc=[0.01,0.75], numpoints=1, handlelength=0, \
		434	pad=0.015, handletextsep=0.02,labelsep=0.01)
		435
		436	matplotlib.pyplot.setp(ObjlegC.get_texts(),fontsize='small')
		437	ObjlegC.isaxes = False
		438	save_fig = os.path.join(gpath,filename)
		439	matplotlib.pyplot.savefig(save_fig,format='png')
		440
		441
		442	class PatternCutPlot:
		443	def __init__(self,nsubplots):
		444	self.nsubplots = nsubplots
		445
		446	self.fig = None
		447
		448	self.__plot_width = 8
		449
		450	if self.nsubplots == 5:
		451	self.__plot_height = 11
		452
		453	if self.nsubplots == 4:
		454	self.__plot_height = 9
		455
		456	if self.nsubplots == 3:
		457	self.__plot_height = 7
		458
		459	if self.nsubplots == 2:
		460	self.__plot_height = 5
		461
		462	if self.nsubplots == 1:
		463	self.__plot_height = 3
		464
		465	self.fig = matplotlib.pyplot.figure(num = 4,figsize = (self.__plot_width, self.__plot_height))
		466
		467	if self.nsubplots < 5:
		468	self.__height_inch = 1.1 #altura de los subplots (pulgadas)
		469	top_inch = 1.5/2.7 #espacio entre el primer subplot y el limite superior del plot
		470	self.__vspace_plot_inch = 1.0#1.5/2 # espacio vertical entre subplots
		471	self.__left = 0.1
		472	else:
		473	self.__height_inch = 1.1 #altura de los subplots (pulgadas)
		474	top_inch = 1.5/2.7 #espacio entre el primer subplot y el limite superior del plot
		475	self.__vspace_plot_inch = 1.0 # espacio vertical entre subplots
		476	self.__left = 0.1
		477
		478	self.__bottom_inch = self.__plot_height - (self.__height_inch + top_inch)
		479	self.__height = self.__height_inch/self.__plot_height
		480
		481	self.__width = 0.8
		482
		483
		484	def drawCut(self,io,patterns,npatterns,ha,otitle,subtitle,ptitle):
		485
		486	t_cuts = ['B','Sun','Moon','Hydra','Galaxy']
		487	self.__bottom = self.__bottom_inch/self.__plot_height
		488
		489
		490	subp = self.fig.add_axes([self.__left,self.__bottom,self.__width,self.__height])
		491
		492	on_axis_angle = -4.65562
		493	for icut in numpy.arange(npatterns):
		494	# Getting Antenna cut.
		495	pattern = patterns[icut]
		496	power = numpy.abs(pattern/numpy.nanmax(pattern))
		497	max_power_db = numpy.round(10.*numpy.log10(numpy.nanmax(pattern)),2)
		498
		499	bval = numpy.where(power[:,0]==numpy.nanmax(power))
		500	beta = -0.25*(ha[bval[0]] + on_axis_angle)
		501	# print 'Angle (deg): '+"%f"%(beta)
		502
		503	subp.plot(ha,power)
		504
		505
		506	xmax = numpy.max(numpy.nanmin(ha))
		507	xmin = numpy.min(numpy.nanmax(ha))
		508	ymax = numpy.max(1)
		509	ymin = numpy.min(0)
		510
		511
		512	subp.set_xlim(xmin, xmax)
		513
		514	subp.set_ylim(ymin, ymax)
		515
		516	subp.set_title(otitle + ' ' + ptitle,size="medium")
		517
		518	subp.text(0.5, 1.26,subtitle[0],
		519	horizontalalignment='center',
		520	verticalalignment='center',
		521	transform = subp.transAxes)
		522
		523	xlabels = subp.get_xticks()
		524
		525	subp.set_xticklabels(xlabels,size="small")
		526
		527	ylabels = subp.get_yticks()
		528
		529	subp.set_yticklabels(ylabels,size="small")
		530
		531	subp.set_xlabel('Hour angle (min) (+ve to West)',size="small")
		532
		533	subp.set_ylabel("Power [Max: " + str(max_power_db) + ' dB]',size="small")
		534
		535	subp.grid()
		536
		537
		538	self.__bottom_inch = self.__bottom_inch - (self.__height_inch + self.__vspace_plot_inch)
		539
		540
		541	class SkyNoisePlot:
		542	def __init__(self,date,powr,time,time_lst):
		543	"""
		544	SkyNoisePlot class creates an object which represents the SkyNoise Object to genera-
		545	te a SkyNoise map.
		546
		547	Parameters
		548	----------
		549	date = A List of 3 elements to define the desired date ([year, month, day]).
		550	powr = An array giving the SkyNoise power for the desired time.
		551	time = An array giving the number of seconds since 1970 to the desired time.
		552	time_lst = Set this input to an array to define the Local Sidereal Time of the desi-
		553	red time.
		554
		555	Modification History
		556	--------------------
		557	Created by Freddy Galindo, ROJ, 18 October 2009.
		558	"""
		559
		560	self.date = date
		561	self.powr = powr
		562	self.time = time
		563	self.time_lst = time_lst

apps/abs/utils/JroAntSetup.py created 644 +1035 0

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		1	'''
		2	The module JroAntSetup contains the pre-defined parameters for beam modelling of the Jicamarca ante-
		3	nna. Any new configuration must be added in this module (if the user decides that) using a specific
		4	ID (pattern value) or it would be read from a file using pattern=None.
		5
		6	MODULES CALLED:
		7	OS, NUMPY
		8
		9	MODIFICATION HISTORY:
		10	Created by Ing. Freddy Galindo (frederickgalindo@gmail.com). ROJ Sep 20, 2009.
		11	'''
		12
		13	import os
		14	import numpy
		15
		16	def ReturnSetup(path=None,filename=None,pattern=0):
		17	"""
		18	ReturnSetup is a pre-defined list of Jicamarca antenna configurations which returns a dic-
		19	tionary giving the configuration parameters (e.g. transmitted phases). To choose one, the
		20	user must define the input "pattern" (See valid values below).
		21
		22	Parameters:
		23	-----------
		24
		25	pattern = A integer (>=0) to specify the setup to choose. The default value is zero. If the
		26	antenna configuration is user-defined pattern must be None.
		27
		28	path = Set this input a string to specifiy the folder path where the user-defined configu-
		29	ration file is placed. If this value is not defined ReturnSetup will return None.
		30
		31	file = Set this input a string to specifiy the name of the user-defined configuration file
		32	(*.txt). if this value is not defined ReturnSEtup will return None.
		33
		34	Examples:
		35	---------
		36
		37	Choosing a pre-defined antenna configuration
		38	setup = ReturnSetup(pattern=1)
		39
		40	Reading a user-defined antenna configuration
		41	setup = ReturnSetup(path="/users/users/Progs/Patterns/",file="ExpSep232009.txt")
		42	"""
		43
		44
		45	if pattern == 0:
		46	title = "for module (rx)"
		47
		48	ues = numpy.array([1.,2.,2.,1.])
		49	phase = numpy.zeros([8,8])
		50	phase[0:4,:] = 4
		51	phase[4:8,:] = 5
		52
		53	gaintx = numpy.zeros([8,8])
		54	gaintx[0,0] = 1
		55
		56	gainrx = numpy.zeros([8,8])
		57	gainrx[0,0] = 1
		58
		59	justrx = 1
		60
		61	elif pattern==1:
		62	# Configuration 1/16 on-axis (rx)
		63	title = " for 1/16 on-axis (rx)"
		64
		65	ues = numpy.array([1.,2.,2.,1.])
		66	phase = numpy.zeros([8,8])
		67	phase[0:4,:] = 4
		68	phase[4:8,:] = 5
		69
		70	gaintx = numpy.zeros([8,8])
		71	gaintx[0:2,0:2] = 1
		72
		73	gainrx = numpy.zeros([8,8])
		74	gainrx[0:2,0:2] = 1
		75
		76	justrx = 1
		77
		78	elif pattern == 2:
		79	# Configuration for On-Axis
		80	title = " for 1/4 on-axis (rx)"
		81
		82	ues = numpy.array([1.,2.,2.,1.])
		83	phase = numpy.zeros([8,8])
		84	phase[0:4,:] = 4
		85	phase[4:8,:] = 5
		86
		87	gaintx = numpy.zeros([8,8])
		88	gaintx[0:4,0:4] = 1
		89
		90	gainrx = numpy.zeros([8,8])
		91	gainrx[0:4,0:4] = 1
		92
		93	justrx = 1
		94
		95	elif pattern == 3:
		96	# Configuration for On-Axis
		97	title = " for all on-axis (rx)"
		98
		99	ues = numpy.array([1.,2.,2.,1.])
		100	phase = numpy.zeros([8,8])
		101	phase[0:4,:] = 4
		102	phase[4:8,:] = 5
		103
		104	gaintx = numpy.zeros([8,8])
		105	gaintx[:,:] = 1
		106
		107	gainrx = numpy.zeros([8,8])
		108	gainrx[:,:] = 1
		109
		110	justrx = 0
		111
		112	elif pattern == 4:
		113	# Configuration for oblique ISR On-Axis
		114	title = " for Oblique ISR On-axis"
		115
		116	ues = numpy.array([1.,2.,2.,1.])
		117	phase = numpy.zeros([8,8])
		118	phase[0:4,:] = 4
		119	phase[4:8,:] = 5
		120
		121	gaintx = numpy.zeros([8,8])
		122	gaintx[:,:] = 1
		123
		124	gainrx = numpy.zeros([8,8])
		125	gainrx[:,:] = 1
		126
		127	justrx = 0
		128
		129	elif pattern == 5:
		130	# Configuration for oblique ISR "4.5"
		131	title = " for Oblique ISR '4.5'"
		132
		133	ues = numpy.array([1.,2.,2.,1.])
		134	phase = numpy.array([[4,4,5,5,2,2,3,3],
		135	[4,5,5,2,2,3,3,4],
		136	[5,5,2,2,3,3,4,4],
		137	[5,2,2,3,3,4,4,5],
		138	[3,3,4,4,5,5,2,2],
		139	[3,4,4,5,5,2,2,3],
		140	[4,4,5,5,2,2,3,3],
		141	[4,5,5,2,2,3,3,4]],dtype=float)
		142
		143	gaintx = numpy.zeros([8,8])
		144	gaintx[:,:] = 1
		145
		146	gainrx = numpy.zeros([8,8])
		147	gainrx[:,:] = 1
		148
		149	justrx = 0
		150
		151	elif pattern == 6:
		152	# Configuration for oblique ISR "6.0S"
		153	title = " for Oblique ISR '6.0S'"
		154
		155	ues = numpy.array([1.,2.,2.,1.])
		156	phase = numpy.array([[4,5,2,3,4,5,2,3],
		157	[5,2,3,4,5,2,3,4],
		158	[2,3,4,5,2,3,4,5],
		159	[3,4,5,2,3,4,5,2],
		160	[5,2,3,4,5,2,3,4],
		161	[2,3,4,5,2,3,4,5],
		162	[3,4,5,2,3,4,5,2],
		163	[4,5,2,3,4,5,2,3]],dtype=float)
		164
		165	gaintx = numpy.zeros([8,8])
		166	gaintx[:,:] = 1
		167
		168	gainrx = numpy.zeros([8,8])
		169	gainrx[:,:] = 1
		170
		171	justrx = 0
		172
		173	elif pattern == 7:
		174	# Configuration for oblique ISR "3.0N"
		175	title = " for Oblique ISR '3.0N'"
		176
		177	ues = numpy.array([1.,2.,2.,1.])
		178	phase = numpy.array([[4,3,2,5,4,3,2,5],
		179	[3,2,5,4,3,2,5,4],
		180	[2,5,4,3,2,5,4,3],
		181	[5,4,3,2,5,4,3,2],
		182	[5,4,3,2,5,4,3,2],
		183	[4,3,2,5,4,3,2,5],
		184	[3,2,5,4,3,2,5,4],
		185	[2,5,4,3,2,5,4,3]],dtype=float)
		186
		187	gaintx = numpy.zeros([8,8])
		188	gaintx[:,:] = 1
		189
		190	gainrx = numpy.zeros([8,8])
		191	gainrx[:,:] = 1
		192
		193	justrx = 0
		194
		195	elif pattern == 8:
		196	# Configuration for North Fritts"
		197	title = " for North (Fritts)"
		198
		199	ues = numpy.array([2.513, 1.0, 3.0, 0.413])
		200	phase = numpy.array([[4.29, 3.55, 2.82, 2.08, 4.20, 3.47, 2.73, 2.00],
		201	[2.94, 2.20, 5.44, 4.70, 4.32, 3.59, 2.85, 2.12],
		202	[5.56, 4.82, 4.09, 3.35, 4.44, 3.71, 2.97, 2.24],
		203	[4.20, 3.47, 2.73, 2.00, 4.56, 3.82, 3.09, 2.35],
		204	[4.20, 3.47, 2.73, 2.00, 4.56, 3.82, 3.09, 2.35],
		205	[4.32, 3.59, 2.85, 2.12, 2.94, 2.20, 5.44, 4.70],
		206	[4.44, 3.71, 2.97, 2.24, 5.56, 4.82, 4.09, 3.35],
		207	[4.56, 3.82, 3.09, 2.35, 4.20, 3.47, 2.73, 2.00]],dtype=float)
		208
		209	gaintx = numpy.zeros([8,8])
		210	gaintx[0:4,0:4] = 1
		211	gaintx[4:8,4:8] = 1
		212
		213	gainrx = numpy.zeros([8,8])
		214	gainrx[0:4,0:4] = 1
		215	gainrx[4:8,4:8] = 1
		216
		217	justrx = 0
		218
		219	elif pattern == 9:
		220	# Configuration for West Fritts"
		221	title = " for West (Fritts)"
		222
		223	ues = numpy.array([2.513, 1.0, 3.0, 0.413])
		224	phase = numpy.array([[4.29, 3.55, 2.82, 2.08, 4.20, 3.47, 2.73, 2.00],
		225	[2.94, 2.20, 5.44, 4.70, 4.32, 3.59, 2.85, 2.12],
		226	[5.56, 4.82, 4.09, 3.35, 4.44, 3.71, 2.97, 2.24],
		227	[4.20, 3.47, 2.73, 2.00, 4.56, 3.82, 3.09, 2.35],
		228	[4.20, 3.47, 2.73, 2.00, 4.56, 3.82, 3.09, 2.35],
		229	[4.32, 3.59, 2.85, 2.12, 2.94, 2.20, 5.44, 4.70],
		230	[4.44, 3.71, 2.97, 2.24, 5.56, 4.82, 4.09, 3.35],
		231	[4.56, 3.82, 3.09, 2.35, 4.20, 3.47, 2.73, 2.00]],dtype=float)
		232
		233	gaintx = numpy.zeros([8,8])
		234	gaintx[4:8,0:4] = 1
		235	gaintx[4:8,0:4] = 1
		236
		237	gainrx = numpy.zeros([8,8])
		238	gainrx[4:8,0:4] = 1
		239	gainrx[4:8,0:4] = 1
		240
		241	justrx = 0
		242
		243	elif pattern == 10:
		244	# Configuration for South Fritts"
		245	title = " for South (Fritts)"
		246
		247	ues = numpy.array([0.413, 2.0, 1.0, 1.513])
		248	phase = numpy.array([[2.0 , 2.73, 3.47, 4.2 , 2.08, 2.82, 3.55, 4.29],
		249	[2.12, 2.85, 3.59, 4.32, 4.7 , 5.44, 2.20, 2.94],
		250	[2.24, 2.97, 3.71, 4.44, 3.35, 4.09, 4.82, 5.56],
		251	[2.35, 3.09, 3.82, 4.56, 2.0 , 2.73, 3.47, 4.20],
		252	[2.08, 2.82, 3.55, 4.29, 2.0 , 2.73, 3.47, 4.20],
		253	[4.70, 5.44, 2.20, 2.94, 2.12, 2.85, 3.59, 4.32],
		254	[3.35, 4.09, 4.82, 5.56, 2.24, 2.97, 3.71, 4.44],
		255	[2.00, 2.73, 3.47, 4.20, 2.35, 3.09, 3.82, 4.56]],dtype=float)
		256
		257	gaintx = numpy.zeros([8,8])
		258	gaintx[0:4,0:4] = 1
		259	gaintx[4:8,4:8] = 1
		260
		261	gainrx = numpy.zeros([8,8])
		262	gainrx[0:4,0:4] = 1
		263	gainrx[4:8,4:8] = 1
		264
		265	justrx = 0
		266
		267	elif pattern == 11:
		268	# Configuration for East Fritts"
		269	title = " for East (Fritts)"
		270
		271	ues = numpy.array([0.413, 2.0, 1.0, 1.513])
		272	phase = numpy.array([[2.0 , 2.73, 3.47, 4.2 , 2.08, 2.82, 3.55, 4.29],
		273	[2.12, 2.85, 3.59, 4.32, 4.7 , 5.44, 2.20, 2.94],
		274	[2.24, 2.97, 3.71, 4.44, 3.35, 4.09, 4.82, 5.56],
		275	[2.35, 3.09, 3.82, 4.56, 2.0 , 2.73, 3.47, 4.20],
		276	[2.08, 2.82, 3.55, 4.29, 2.0 , 2.73, 3.47, 4.20],
		277	[4.70, 5.44, 2.20, 2.94, 2.12, 2.85, 3.59, 4.32],
		278	[3.35, 4.09, 4.82, 5.56, 2.24, 2.97, 3.71, 4.44],
		279	[2.00, 2.73, 3.47, 4.20, 2.35, 3.09, 3.82, 4.56]],dtype=float)
		280
		281	gaintx = numpy.zeros([8,8])
		282	gaintx[4:8,0:4] = 1
		283	gaintx[4:8,0:4] = 1
		284
		285	gainrx = numpy.zeros([8,8])
		286	gainrx[4:8,0:4] = 1
		287	gainrx[4:8,0:4] = 1
		288
		289	justrx = 0
		290
		291	elif pattern == 12:
		292	# Configuration for DEWD position (2009)
		293	title = " for DEWD position (2009) East Beam"
		294
		295	ues = numpy.array([0.,0.,0.75,0.75])
		296	phase = numpy.array([[2,3,3,3,3,4,4,4],
		297	[5,2,2,2,2,3,3,3],
		298	[3,4,4,4,4,5,5,5],
		299	[2,3,3,3,3,4,4,4],
		300	[4,5,5,5,5,2,2,2],
		301	[3,4,4,4,4,5,5,5],
		302	[5,2,2,2,2,3,3,3],
		303	[4,5,5,5,5,2,2,2]],dtype=float)
		304
		305	gaintx = numpy.zeros([8,8])
		306	gaintx[:,:] = 1
		307
		308	gainrx = numpy.zeros([8,8])
		309	gainrx[:,0:4] = 1
		310
		311	justrx = 0
		312
		313	elif pattern == 13:
		314	# Configuration for DEWD position (2009)
		315	title = " for DEWD position (2009) West Beam"
		316
		317	ues = numpy.array([1.0,0.5,1.5,2.0])
		318	phase = numpy.array([[5,4,2,5,3,2,4,3],
		319	[2,5,3,2,4,3,5,4],
		320	[2,5,3,2,4,3,5,4],
		321	[3,2,4,3,5,4,2,5],
		322	[3,2,4,3,5,4,2,5],
		323	[4,3,5,4,2,5,3,2],
		324	[4,3,5,4,2,5,3,2],
		325	[5,4,2,5,3,2,4,3]],dtype=float)
		326
		327	gaintx = numpy.zeros([8,8])
		328	gaintx[:,:] = 1
		329
		330	gainrx = numpy.zeros([8,8])
		331	gainrx[4:8,:] = 1
		332
		333	justrx = 0
		334
		335	elif pattern == 14:
		336	# Configuration for DVD position (2009)
		337	title = " for DVD position (2009)"
		338
		339	ues = numpy.array([1.0,2.0,2.0,1.25])
		340	phase = numpy.array([[2,2,5,5,4,4,3,3],
		341	[2,5,5,4,4,3,3,2],
		342	[5,5,4,4,3,3,2,2],
		343	[5,4,4,3,3,2,2,5],
		344	[5,5,4,4,3,3,2,2],
		345	[5,4,4,3,3,2,2,5],
		346	[4,4,3,3,2,2,5,5],
		347	[4,3,3,2,2,5,5,4]],dtype=float)
		348
		349	gaintx = numpy.zeros([8,8])
		350	gaintx[:,:] = 1
		351
		352	gainrx = numpy.zeros([8,8])
		353	gainrx[0:4,0:4] = 1
		354
		355	justrx = 0
		356
		357	elif pattern == 15:
		358	# Configuration for Julia CP2
		359	title = " for Julia CP2 Ew"
		360
		361	ues = numpy.array([0.0,1.0,1.0,0.0])
		362	phase = numpy.array([[2,2,5,4,3,3,2,5],
		363	[2,5,4,4,3,2,5,5],
		364	[5,4,3,3,2,5,4,4],
		365	[4,4,3,2,5,5,4,3],
		366	[4,4,3,2,5,5,4,3],
		367	[4,3,2,2,5,4,3,3],
		368	[3,2,5,5,4,3,2,2],
		369	[2,2,5,4,3,3,2,5]],dtype=float)
		370
		371	gaintx = numpy.zeros([8,8])
		372	gaintx[0:4,4:8] = 1
		373	gaintx[4:8,0:4] = 1
		374
		375	gainrx = numpy.zeros([8,8])
		376	gainrx[0,0] = 1
		377
		378	justrx = 0
		379
		380	elif pattern == 16:
		381	# Configuration for Julia CP2
		382	title = " for Julia CP2 NS"
		383
		384	ues = numpy.array([1.0,2.0,2.0,1.0])
		385	phase = numpy.array([[4,4,3,2,5,5,4,3],
		386	[4,3,2,2,5,4,3,3],
		387	[3,2,5,5,4,3,2,2],
		388	[2,2,5,4,3,3,2,5],
		389	[2,2,5,4,3,3,2,5],
		390	[2,5,4,4,3,2,5,5],
		391	[5,4,3,3,2,5,4,4],
		392	[4,4,3,2,5,5,4,3]],dtype=float)
		393
		394	gaintx = numpy.zeros([8,8])
		395	gaintx[0:4,0:4] = 1
		396	gaintx[4:8,4:8] = 1
		397
		398	gainrx = numpy.zeros([8,8])
		399	gainrx[0:4,0:4] = 1
		400
		401	justrx = 0
		402
		403	elif pattern == 17:
		404	# Configuration for Julia CP3
		405	title = " for Julia CP3 NS"
		406
		407	ues = numpy.array([1.0,1.0,1.0,1.0])
		408	phase = numpy.array([[4,4,3,2,5,5,4,3],
		409	[4,3,2,2,5,4,3,3],
		410	[3,2,5,5,4,3,2,2],
		411	[2,2,5,4,3,3,2,5],
		412	[2,2,5,4,3,3,2,5],
		413	[2,5,4,4,3,2,5,5],
		414	[5,4,3,3,2,5,4,4],
		415	[4,4,3,2,5,5,4,3]],dtype=float)
		416
		417	gaintx = numpy.zeros([8,8])
		418	gaintx[0:4,0:4] = 1
		419	gaintx[4:8,4:8] = 1
		420
		421	gainrx = numpy.zeros([8,8])
		422	gainrx[0:4,0:4] = 1
		423
		424	justrx = 0
		425
		426	elif pattern == 18:
		427	# Configuration for Julia V
		428	title = " for Julia V"
		429
		430	ues = (2/3.)*numpy.array([1.5,3.0+0.75,3.0,1.5-0.75])
		431	phase = numpy.array([[4,4,3,3,2,2,5,5],
		432	[4,3,3,2,2,5,5,4],
		433	[3,3,2,2,5,5,4,4],
		434	[3,2,2,5,5,4,4,3],
		435	[3,3,2,2,5,5,4,4],
		436	[3,2,2,5,5,4,4,3],
		437	[2,2,5,5,4,4,3,3],
		438	[2,5,5,4,4,3,3,2]],dtype=float)
		439
		440	gaintx = numpy.zeros([8,8])
		441	gaintx[0:4,0:4] = 1
		442	gaintx[4:8,4:8] = 1
		443
		444	gainrx = numpy.zeros([8,8])
		445	gainrx[0:4,0:4] = 1
		446
		447	justrx = 0
		448
		449	elif pattern == 19:
		450	# Configuration for Julia V
		451	title = " for Julia EW 2006-2007 (W)"
		452
		453	ues = numpy.array([1.0+0.66,2.0+0.66,2.0,1.0])
		454	phase = numpy.array([[4,3,2,5,4,3,2,5],
		455	[4,3,2,5,4,3,2,5],
		456	[4,3,2,5,4,3,2,5],
		457	[4,3,2,5,4,3,2,5],
		458	[5,4,3,2,5,4,3,2],
		459	[5,4,3,2,5,4,3,2],
		460	[5,4,3,2,5,4,3,2],
		461	[5,4,3,2,5,4,3,2]],dtype=float)
		462
		463	gaintx = numpy.zeros([8,8])
		464	gaintx[:,:] = 1
		465
		466	gainrx = numpy.zeros([8,8])
		467	gainrx[:,:] = 1
		468
		469	justrx = 0
		470
		471	elif pattern == 20:
		472	# Configuration for Julia V
		473	title = " for Julia EW 2006-2007 (E)"
		474
		475	ues = numpy.array([1.0,1.0,1.0,1.0])
		476	phase = numpy.array([[4,4,4,4,5,5,5,5],
		477	[3,3,3,3,4,4,4,4],
		478	[5,5,5,5,2,2,2,2],
		479	[4,4,4,4,5,5,5,5],
		480	[2,2,2,2,3,3,3,3],
		481	[5,5,5,5,2,2,2,2],
		482	[3,3,3,3,4,4,4,4],
		483	[2,2,2,2,3,3,3,3]],dtype=float)
		484
		485	gaintx = numpy.zeros([8,8])
		486	gaintx[:,:] = 1
		487
		488	gainrx = numpy.zeros([8,8])
		489	gainrx[0:4,0:4] = 1
		490	gainrx[4:8,4:8] = 1
		491
		492	justrx = 0
		493
		494	elif pattern == 21:
		495	# Configuration for EW Imaging 1996
		496	title = " for EW Imaging 1996"
		497
		498	ues = numpy.array([1.0,2.0,2.0,1.0])
		499	phase = numpy.array([[4,4,3,2,5,5,4,3],
		500	[4,3,2,2,5,4,3,3],
		501	[3,2,5,5,4,3,2,2],
		502	[2,2,5,4,3,3,2,5],
		503	[2,2,5,4,3,3,2,5],
		504	[2,5,4,4,3,2,5,5],
		505	[5,4,3,3,2,5,4,4],
		506	[4,4,3,2,5,5,4,3]],dtype=float)
		507
		508	gaintx = numpy.zeros([8,8])
		509	gaintx[0:4,0:4] = 1
		510	gaintx[4:8,4:8] = 1
		511
		512	gainrx = numpy.zeros([8,8])
		513	gainrx[0,0] = 1
		514
		515	justrx = 0
		516
		517	elif pattern == 22:
		518	# Configuration for EW Imaging 2003
		519	title = " for EW Imaging 2003"
		520
		521	ues = numpy.array([1.0,1.0,1.0,1.0])
		522	phase = numpy.array([[4,4,3,2,0,0,0,0],
		523	[2,3,2,2,0,0,0,0],
		524	[5,0,2,5,0,0,0,0],
		525	[2,4,3,4,0,0,0,0],
		526	[0,0,0,0,3,3,2,5],
		527	[0,0,0,0,2,2,5,5],
		528	[0,0,0,0,4,3,5,4],
		529	[0,0,0,0,5,3,2,3]],dtype=float)
		530
		531	gaintx = numpy.zeros([8,8])
		532	gaintx[0:4,0:4] = 1
		533	gaintx[4:8,4:8] = 1
		534
		535	gainrx = numpy.zeros([8,8])
		536	gainrx[0,0] = 1
		537
		538	justrx = 0
		539
		540	elif pattern == 23:
		541	# Configuration for EW Imaging 2003
		542	title = " for EW Imaging 2006-2008"
		543
		544	ues = numpy.array([1.0,1.0,1.0,2.0])
		545	phase = numpy.array([[4,4,3,2,0,0,0,0],
		546	[2,3,2,2,0,0,0,0],
		547	[5,0,2,5,0,0,0,0],
		548	[2,4,3,4,0,0,0,0],
		549	[0,0,0,0,3,3,2,5],
		550	[0,0,0,0,2,2,5,5],
		551	[0,0,0,0,4,3,5,4],
		552	[0,0,0,0,5,3,2,3]],dtype=float)
		553
		554	gaintx = numpy.zeros([8,8])
		555	gaintx[0:4,0:4] = 1
		556	gaintx[4:8,4:8] = 1
		557
		558	gainrx = numpy.zeros([8,8])
		559	gainrx[0,0] = 1
		560
		561	justrx = 0
		562
		563	elif pattern == 50:
		564	# Configuration for vertical drift 1996
		565	title = " for Vertical drift 1996"
		566
		567	ues = (2/3.)*numpy.array([0.,1.5,1.5,0.])
		568	phase = numpy.array([[4,4,3,2,5,5,4,3],
		569	[4,3,2,2,5,4,3,3],
		570	[3,2,5,5,4,3,2,2],
		571	[2,2,5,4,3,3,2,5],
		572	[2,2,5,4,3,3,2,5],
		573	[2,5,4,4,3,2,5,5],
		574	[5,4,3,3,2,5,4,4],
		575	[4,4,3,2,5,5,4,3]],dtype=float)
		576
		577	gaintx = numpy.zeros([8,8])
		578	gaintx[:,:] = 1
		579
		580	gainrx = numpy.zeros([8,8])
		581	gainrx[:,:] = 1
		582
		583	justrx = 0
		584
		585	elif pattern == 51:
		586	# Configuration for vertical drift 1996
		587	title = " for East-West Drifts 1996 (W beam)"
		588
		589	ues = numpy.array([0.0,1.0,2.0,1.0])
		590	phase = numpy.array([[4,3,5,4,2,5,3,2],
		591	[4,3,5,4,2,5,3,2],
		592	[4,3,5,4,2,5,3,2],
		593	[4,3,5,4,2,5,3,2],
		594	[5,4,2,5,3,2,4,3],
		595	[5,4,2,5,3,2,4,3],
		596	[5,4,2,5,3,2,4,3],
		597	[5,4,2,5,3,2,4,3]],dtype=float)
		598
		599	gaintx = numpy.zeros([8,8])
		600	gaintx[:,:] = 1
		601
		602	gainrx = numpy.zeros([8,8])
		603	gainrx[4:8,:] = 1
		604
		605	justrx = 0
		606
		607	elif pattern == 52:
		608	# Configuration for vertical drift 1996
		609	title = " for East-West Drifts 1996 (E Beam)"
		610
		611	ues = numpy.array([1.0,1.0,0.0,0.0])
		612	phase = numpy.array([[4,4,4,4,5,5,5,5],
		613	[3,3,3,3,4,4,4,4],
		614	[5,5,5,5,2,2,2,2],
		615	[4,4,4,4,5,5,5,5],
		616	[2,2,2,2,3,3,3,3],
		617	[5,5,5,5,2,2,2,2],
		618	[3,3,3,3,4,4,4,4],
		619	[2,2,2,2,3,3,3,3]],dtype=float)
		620
		621	gaintx = numpy.zeros([8,8])
		622	gaintx[:,:] = 1
		623
		624	gainrx = numpy.zeros([8,8])
		625	gainrx[:,0:4] = 1
		626
		627	justrx = 0
		628
		629	elif pattern == 53:
		630	# Configuration for vertical drift 1996
		631	title = " for DVD position 3 (2006-2008)"
		632
		633	ues = numpy.array([1.,2,2,1])
		634	phase = numpy.array([[4,4,3,3,2,2,5,5],
		635	[4,3,3,2,2,5,5,4],
		636	[3,3,2,2,5,5,4,4],
		637	[3,2,2,5,5,4,4,3],
		638	[3,3,2,2,5,5,4,4],
		639	[3,2,2,5,5,4,4,3],
		640	[2,2,5,5,4,4,3,3],
		641	[2,5,5,4,4,3,3,2]],dtype=float)
		642
		643	gaintx = numpy.zeros([8,8])
		644	gaintx[:,:] = 1
		645
		646	gainrx = numpy.zeros([8,8])
		647	gainrx[0:4,4:8] = 1
		648
		649	justrx = 0
		650
		651	elif pattern == 54:
		652	# Configuration for vertical drift 1996
		653	title = " for DEWD (Mar 2005)"
		654
		655	ues = numpy.array([0.,1.,1/3.,1])
		656	phase = numpy.array([[4,3,2,5,3,3,3,3],
		657	[4,3,2,5,2,2,2,2],
		658	[4,3,2,4,5,5,5,5],
		659	[4,3,2,4,4,4,3,3],
		660	[5,4,3,2,2,2,2,2],
		661	[5,4,3,2,5,5,5,5],
		662	[5,4,3,5,4,4,4,4],
		663	[5,4,3,5,3,3,2,2]],dtype=float)
		664
		665	gaintx = numpy.zeros([8,8])
		666	gaintx[:,:] = 1
		667
		668	gainrx = numpy.zeros([8,8])
		669	gainrx[:,0:4] = 1
		670
		671	justrx = 0
		672
		673	elif pattern == 55:
		674	# Configuration for vertical drift 1996
		675	title = " for DEWD (Mar 2005)"
		676
		677	ues = numpy.array([0.,1.,1/3.,1])
		678	phase = numpy.array([[4,3,2,5,3,3,3,3],
		679	[4,3,2,5,2,2,2,2],
		680	[4,3,2,4,5,5,5,5],
		681	[4,3,2,4,4,4,3,3],
		682	[5,4,3,2,2,2,2,2],
		683	[5,4,3,2,5,5,5,5],
		684	[5,4,3,5,4,4,4,4],
		685	[5,4,3,5,3,3,2,2]],dtype=float)
		686
		687	gaintx = numpy.zeros([8,8])
		688	gaintx[:,:] = 1
		689
		690	gainrx = numpy.zeros([8,8])
		691	gainrx[0:4:,4:8] = 1
		692
		693	justrx = 0
		694
		695	elif pattern ==56:
		696	# Configuration using antenna compression
		697	title = " for antenna compression AA*"
		698
		699	ues = numpy.array([0.0,0.0,0.0,0.0])
		700	phase = numpy.array([[4,4,4,2,4,4,2,4],
		701	[4,4,4,2,4,4,2,4],
		702	[2,2,2,4,2,2,4,2],
		703	[4,4,4,2,4,4,2,4],
		704	[2,2,2,4,2,2,4,2],
		705	[2,2,2,4,2,2,4,2],
		706	[4,4,4,2,4,4,2,4],
		707	[2,2,2,4,2,2,4,2]],dtype=float)
		708
		709	gaintx = numpy.zeros([8,8])
		710	gaintx[:,:] = 1
		711
		712	gainrx = numpy.zeros([8,8])
		713	gainrx[0:4,0:4] = 1
		714
		715	justrx = 0
		716
		717	elif pattern ==57:
		718	# Configuration using antenna compression
		719	title = " for antenna compression AB*"
		720
		721	ues = numpy.array([0.0,0.0,0.0,0.0])
		722	phase = numpy.array([[4,4,2,4,2,2,4,2],
		723	[4,4,2,4,2,2,4,2],
		724	[2,2,4,2,4,4,2,4],
		725	[4,4,2,4,2,2,4,2],
		726	[2,2,4,2,4,4,2,4],
		727	[2,2,4,2,4,4,2,4],
		728	[4,4,2,4,2,2,4,2],
		729	[2,2,4,2,4,4,2,4]],dtype=float)
		730
		731	gaintx = numpy.zeros([8,8])
		732	gaintx[:,:] = 1
		733
		734	gainrx = numpy.zeros([8,8])
		735	gainrx[0:4,0:4] = 1
		736
		737	justrx = 0
		738
		739	elif pattern ==58:
		740	# Configuration using in Oblique ISR 4.5
		741	title = " for Oblique ISR 4.5"
		742
		743	ues = numpy.array([1.0,2.0,2.0,1.0])
		744	phase = numpy.array([[4,4,5,5,2,2,3,3],
		745	[4,5,5,2,2,3,3,4],
		746	[5,5,2,2,3,3,4,4],
		747	[5,2,2,3,3,4,4,5],
		748	[3,3,4,4,5,5,2,2],
		749	[3,4,4,5,5,2,2,3],
		750	[4,4,5,5,2,2,3,3],
		751	[4,5,5,2,2,3,3,4]],dtype=float)
		752
		753	gaintx = numpy.zeros([8,8])
		754	gaintx[:,:] = 1
		755
		756	gainrx = numpy.zeros([8,8])
		757	gainrx[:,:] = 1
		758
		759	justrx = 1
		760
		761	elif pattern == 60:
		762	title=" for Differential phase 2000"
		763	ues = (2/3.)*numpy.array([0.,1.5-0.5,1.5,0.+0.5])
		764
		765	phase = numpy.array([[4,4,3,2,5,5,4,3],
		766	[4,3,2,2,5,4,3,3],
		767	[3,2,5,5,4,3,2,2],
		768	[2,2,5,4,3,3,2,5],
		769	[2,2,5,4,3,3,2,5],
		770	[2,5,4,4,3,2,5,5],
		771	[5,4,3,3,2,5,4,4],
		772	[4,4,3,2,5,5,4,3]],dtype=float)
		773
		774	gaintx = numpy.zeros([8,8])
		775	gaintx[:,:] = 1
		776
		777	gainrx = numpy.zeros([8,8])
		778	gainrx[0:4,0:4] = 1
		779
		780	justrx = 0
		781
		782	elif pattern == 61:
		783	#for East-West 2003 W
		784	title=" for East-West 2003"
		785
		786	ues = numpy.array([1.+0.66,2.+0.66,2.,1.])
		787
		788	phase = numpy.array([[4,3,2,5,4,3,2,5],
		789	[4,3,2,5,4,3,2,5],
		790	[4,3,2,5,4,3,2,5],
		791	[4,3,2,5,4,3,2,5],
		792	[5,4,3,2,5,4,3,2],
		793	[5,4,3,2,5,4,3,2],
		794	[5,4,3,2,5,4,3,2],
		795	[5,4,3,2,5,4,3,2]],dtype=float)
		796
		797	gaintx = numpy.zeros([8,8])
		798	gaintx[:,:] = 1
		799
		800	gainrx = numpy.zeros([8,8])
		801	gainrx[4:8,:] = 1
		802
		803	justrx = 0
		804
		805	elif pattern == 62:
		806	#for East-West 2003 E
		807	title=" for East-West 2003"
		808
		809	ues = numpy.array([1.,1.,0.+1.0,0.+1.0])
		810
		811	phase = numpy.array([[4,4,4,4,5,5,5,5],
		812	[3,3,3,3,4,4,4,4],
		813	[5,5,5,5,2,2,2,2],
		814	[4,4,4,4,5,5,5,5],
		815	[2,2,2,2,3,3,3,3],
		816	[5,5,5,5,2,2,2,2],
		817	[3,3,3,3,4,4,4,4],
		818	[2,2,2,2,3,3,3,3]],dtype=float)
		819
		820	gaintx = numpy.zeros([8,8])
		821	gaintx[:,:] = 1
		822
		823	gainrx = numpy.zeros([8,8])
		824	gainrx[:,0:4] = 1
		825
		826	justrx = 0
		827
		828	elif pattern == 63:
		829
		830	title=" for Differential phase 2004 High Alt."
		831
		832	ues = (2/3.)*numpy.array([0.,1.5-1.0,1.5,0.+1.0])
		833
		834	phase = numpy.array([[4,4,3,2,5,5,4,3],
		835	[4,3,2,2,5,4,3,3],
		836	[3,2,5,5,4,3,2,2],
		837	[2,2,5,4,3,3,2,5],
		838	[2,2,5,4,3,3,2,5],
		839	[2,5,4,4,3,2,5,5],
		840	[5,4,3,3,2,5,4,4],
		841	[4,4,3,2,5,5,4,3]],dtype=float)
		842
		843	gaintx = numpy.zeros([8,8])
		844	gaintx[:,:] = 1
		845
		846	gainrx = numpy.zeros([8,8])
		847	gainrx[:,:] = 1
		848
		849	justrx = 0
		850
		851	elif pattern == 64:
		852
		853	title=" for Differential Phase Perp to B 2005-2006"
		854
		855	ues = (2/3.)*numpy.array([1.5,3.0+0.75,3.0,1.5-0.75])
		856
		857	phase = numpy.array([[4,4,3,3,2,2,5,5],
		858	[4,3,3,2,2,5,5,4],
		859	[3,3,2,2,5,5,4,4],
		860	[3,2,2,5,5,4,4,3],
		861	[3,3,2,2,5,5,4,4],
		862	[3,2,2,5,5,4,4,3],
		863	[2,2,5,5,4,4,3,3],
		864	[2,5,5,4,4,3,3,2]],dtype=float)
		865
		866	gaintx = numpy.zeros([8,8])
		867	gaintx[:,:] = 1
		868
		869	gainrx = numpy.zeros([8,8])
		870	gainrx[0:4,4:8] = 1
		871
		872	justrx = 0
		873
		874	elif pattern == 65:
		875	#for JULIA EW 2003 W
		876	title=" for JULIA EW 2003"
		877
		878	ues = numpy.array([1+0.66,2+0.66,2.,1.])
		879
		880	phase = numpy.array([[4,3,2,5,4,3,2,5],
		881	[4,3,2,5,4,3,2,5],
		882	[4,3,2,5,4,3,2,5],
		883	[4,3,2,5,4,3,2,5],
		884	[5,4,3,2,5,4,3,2],
		885	[5,4,3,2,5,4,3,2],
		886	[5,4,3,2,5,4,3,2],
		887	[5,4,3,2,5,4,3,2]],dtype=float)
		888
		889	gaintx = numpy.zeros([8,8])
		890	gaintx[:,:] = 1
		891
		892	gainrx = numpy.zeros([8,8])
		893	gainrx[4:8,:] = 1
		894
		895	justrx = 0
		896
		897	elif pattern == 66:
		898	#for JULIA EW 2003 E
		899	title=" for JULIA EW 2003"
		900
		901	ues = numpy.array([1.,1.,0.,0.])
		902
		903	phase = numpy.array([[4,4,4,4,5,5,5,5],
		904	[3,3,3,3,4,4,4,4],
		905	[5,5,5,5,2,2,2,2],
		906	[4,4,4,4,5,5,5,5],
		907	[2,2,2,2,3,3,3,3],
		908	[5,5,5,5,2,2,2,2],
		909	[3,3,3,3,4,4,4,4],
		910	[2,2,2,2,3,3,3,3]],dtype=float)
		911
		912	gaintx = numpy.zeros([8,8])
		913	gaintx[:,:] = 1
		914
		915	gainrx = numpy.zeros([8,8])
		916	gainrx[:,0:4] = 1
		917
		918	justrx = 0
		919
		920	elif pattern == 67:
		921
		922	title=" for Vertical (Yellow Cables)"
		923
		924	ues = numpy.array([0.25, 0.25, 0.25, 0.25])
		925
		926	phase = numpy.array([[3.41, 3.41, 3.41, 3.41, 3.41, 3.41, 3.41, 3.41],
		927	[2.78, 2.78, 2.78, 2.78, 2.78, 2.78, 2.78, 2.78],
		928	[2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15],
		929	[5.52, 5.52, 5.52, 5.52, 5.52, 5.52, 5.52, 5.52],
		930	[4.89, 4.89, 4.89, 4.89, 4.89, 4.89, 4.89, 4.89],
		931	[4.26, 4.26, 4.26, 4.26, 4.26, 4.26, 4.26, 4.26],
		932	[3.63, 3.63, 3.63, 3.63, 3.63, 3.63, 3.63, 3.63],
		933	[3.00, 3.00, 3.00, 3.00, 3.00, 3.00, 3.00, 3.00]],dtype=float)
		934
		935	gaintx = numpy.zeros([8,8])
		936	gaintx[:,:] = 1
		937
		938	gainrx = numpy.zeros([8,8])
		939	gainrx[:,:] = 1
		940
		941	justrx = 0
		942
		943	elif pattern == 100:
		944
		945	title=" for High Altitude Drift"
		946
		947	ues = numpy.array([ 2.0,0.8,1.0,2.2])
		948
		949	phase = numpy.array([[5,5,4,4, 4,4,3,3],
		950	[5,4,4,4, 4,3,3,3],
		951	[4,4,4,4, 3,3,3,3],
		952	[4,4,4,3, 3,3,3,2],
		953	[3,3,2,2, 2,2,5,5],
		954	[3,2,2,2, 2,5,5,5],
		955	[2,2,2,2, 5,5,5,5],
		956	[2,2,2,5, 5,5,5,4]],dtype=float)
		957
		958	gaintx = numpy.zeros([8,8])
		959	gaintx[:,:] = 1
		960
		961	gainrx = numpy.zeros([8,8])
		962	gainrx[:,:] = 1
		963
		964	justrx = 0
		965
		966
		967	elif pattern==None:
		968
		969	inputs = numpy.array(["title","ues_tx","phase_tx","gain_tx","gain_rx","just_rx"])
		970
		971	# Reading user-defined configuration.
		972	if path==None:path = os.getcwd() + os.sep + "patterns" + os.sep
		973	if filename==None:filename = "jropattern.txt"
		974
		975	ff = open(os.path.join(path,filename),'r')
		976
		977	while 1:
		978	# Checking EOF.
		979	init = ff.tell()
		980	if not ff.readline():break
		981	else:ff.seek(init)
		982
		983	line = ff.readline().lstrip()
		984	if line.__len__()!=0:
		985	if line[0]!='#':
		986	keys = line.split("=")
		987	key = keys[0].lstrip().rstrip().lower()
		988	vv = numpy.where(inputs==key)
		989	if vv[0][0]==0:
		990	title = keys[1].lstrip().rstrip()
		991	elif vv[0][0]==1:
		992	ues = (keys[1].lstrip().rstrip())
		993	ues = numpy.float32(ues[1:-1].split(","))
		994	elif vv[0][0]==2:
		995	phase = numpy.zeros([8,8])
		996	tx = (keys[1].lstrip().rstrip())
		997	tx = numpy.float32(tx[2:-3].split(","))
		998	phase[0,:] = tx
		999	for ii in numpy.arange(7):
		1000	tx = ff.readline().lstrip().rstrip()
		1001	tx = numpy.float32(tx[1:-3+(ii==6)].split(","))
		1002	phase[ii+1,:] = tx
		1003	elif vv[0][0]==3:
		1004	gaintx = numpy.zeros([8,8])
		1005	gg = (keys[1].lstrip().rstrip())
		1006	gg = numpy.float32(gg[2:-3].split(","))
		1007	gaintx[0,:] = gg
		1008	for ii in numpy.arange(7):
		1009	gg = ff.readline().lstrip().rstrip()
		1010	gg = numpy.float32(gg[1:-3+(ii==6)].split(","))
		1011	gaintx[ii+1,:] = gg
		1012	elif vv[0][0]==4:
		1013	gainrx = numpy.zeros([8,8])
		1014	gg = (keys[1].lstrip().rstrip())
		1015	gg = numpy.float32(gg[2:-3].split(","))
		1016	gainrx[0,:] = gg
		1017	for ii in numpy.arange(7):
		1018	gg = ff.readline().lstrip().rstrip()
		1019	gg = numpy.float32(gg[1:-3+(ii==6)].split(","))
		1020	gainrx[ii+1,:] = gg
		1021	elif vv[0][0]==5:
		1022	justrx = numpy.float(keys[1].lstrip().rstrip())
		1023
		1024	ff.close()
		1025
		1026
		1027
		1028	setup = {"ues":ues, "phase":phase, "gaintx":gaintx, "gainrx":gainrx, "justrx":justrx, \
		1029	"title":title}
		1030
		1031	return setup
		1032
		1033
		1034
		1035	No newline at end of file

apps/abs/utils/Misc_Routines.py created 644 +81 0

@@ -0,0 +1,81
	1	"""
	2	The module MISC_ROUTINES gathers classes and functions which are useful for daily processing. As an
	3	example we have conversion factor or universal constants.
	4
	5	MODULES CALLED:
	6	NUMPY, SYS
	7
	8	MODIFICATION HISTORY:
	9	Created by Ing. Freddy Galindo (frederickgalindo@gmail.com). ROJ, 21 October 2009.
	10	"""
	11
	12	import numpy
	13	import sys
	14
	15	class CoFactors():
	16	"""
	17	CoFactor class used to call pre-defined conversion factor (e.g. degree to radian). The cu-
	18	The current available factor are:
	19
	20	d2r = degree to radian.
	21	s2r = seconds to radian?, degree to arcsecond.?
	22	h2r = hour to radian.
	23	h2d = hour to degree
	24	"""
	25
	26	d2r = numpy.pi/180.
	27	s2r = numpy.pi/(180.*3600.)
	28	h2r = numpy.pi/12.
	29	h2d = 15.
	30
	31	class Redirect:
	32	def __init__(self,stdout):
	33	self.stdout = stdout
	34
	35	def write(self,message):
	36	self.stdout.insertPlainText(message)
	37
	38	class WidgetPrint:
	39	"""
	40	WidgetPrint class allows to define the standard output.
	41	"""
	42	def __init__(self,textid=None):
	43	self.__stdout = sys.stdout
	44	self.textid = textid
	45	self.wPrint()
	46
	47	def wPrint(self):
	48	if self.textid == None: sys.stdout = self.__stdout
	49	if self.textid != None: sys.stdout = Redirect(self.textid)
	50	print ("")
	51
	52	class Vector:
	53	"""
	54	direction = 0 Polar to rectangular; direction=1 rectangular to polar
	55	"""
	56	def __init__(self,vect,direction=0):
	57	nsize = numpy.size(vect)
	58	if nsize <= 3:
	59	vect = vect.reshape(1,nsize)
	60
	61	self.vect = vect
	62	self.dirc = direction
	63
	64
	65
	66	def Polar2Rect(self):
	67	if self.dirc == 0:
	68	jvect = self.vect*numpy.pi/180.
	69	mmx = numpy.cos(jvect[:,1])*numpy.sin(jvect[:,0])
	70	mmy = numpy.cos(jvect[:,1])*numpy.cos(jvect[:,0])
	71	mmz = numpy.sin(jvect[:,1])
	72	mm = numpy.array([mmx,mmy,mmz]).transpose()
	73
	74	elif self.dirc == 1:
	75	mm = [numpy.arctan2(self.vect[:,0],self.vect[:,1]),numpy.arcsin(self.vect[:,2])]
	76	mm = numpy.array(mm)*180./numpy.pi
	77
	78	return mm
	79
	80
	81

apps/abs/utils/OverJRO.py created 644 +97 0

@@ -0,0 +1,97
	1	'''
	2	Created on May 8, 2013
	3
	4	@author: Jose Antonio Sal y Rosas Celi
	5	@contact: jose.salyrosas@jro.igp.gob.pe
	6	'''
	7
	8	import os
	9	from Files import Files
	10
	11	class OverJRO(Files):
	12
	13	__scriptName = "OverJRO.py"
	14
	15	def __init__(self):
	16	pass
	17
	18	def setParameters(self, path, exp_name, phase_tx, gain_tx, gain_rx, ues_tx, just_rx):
	19	self.path = path
	20	self.exp_name = exp_name
	21	self.phase_tx = phase_tx
	22	self.gain_tx = gain_tx
	23	self.gain_rx = gain_rx
	24	self.ues_tx = ues_tx
	25	self.just_rx = just_rx
	26
	27	def saveFile(self, contentFile):
	28	filename = self.setFilename()
	29	finalpath = os.path.join(self.path, self.setFileExtension(filename))
	30	print "HAHAH"
	31	finalpath = "apps/abs/static/data/"+finalpath
	32	self.save(finalpath, contentFile)
	33	return finalpath
	34
	35	def setTextContent(self):
	36	title = "title ='%s'" % self.exp_name
	37	ues_tx = "ues_tx = %s" % self.ues_tx
	38	phase_tx = "phase_tx = %s" % (self.convertValue(self.phase_tx))
	39	gain_tx = "gain_tx = %s" % (self.convertValue(self.gain_tx))
	40	gain_rx = "gain_rx = %s" % (self.convertValue(self.gain_rx))
	41	just_rx = "just_rx = %d" % self.just_rx
	42	content = " %s\r\n\n %s\r\n\n %s\r\n %s\r\n %s\r\n %s\r\n" % (title, ues_tx, phase_tx, gain_tx, gain_rx, just_rx)
	43	return content
	44
	45	def setFileExtension(self, filename):
	46	txtFile = filename + ".txt"
	47
	48	return txtFile
	49
	50	def convertValue(self, strAntenna):
	51	value = ""
	52	strAntenna = strAntenna.replace("],[","]+[")
	53	lsAntenna = strAntenna.split("+")
	54	for i,element in enumerate(lsAntenna):
	55	if i == 0:
	56	value += "%s,$\n" % element
	57	elif i == 7:
	58	value += " %s\n" % element
	59	else:
	60	value += " %s,$\n" % element
	61
	62	return value
	63
	64
	65	if __name__ == '__main__':
	66	path = "/home/fquino/workspace/radarsys/webapp/apps/abs/static/data"
	67	exp_name = "MST-ISR 2009 (NS-Up)"
	68	phase_tx = "[[0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5]," \
	69	"[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0]," \
	70	"[0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5]," \
	71	"[0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5]," \
	72	"[1.0,1.0,1.0,1.0,1.5,1.5,1.5,1.5]," \
	73	"[0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5]," \
	74	"[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0]," \
	75	"[0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5]]"
	76	gain_tx = "[[1,1,1,1,1,1,1,1]," \
	77	"[1,1,1,1,1,1,1,1]," \
	78	"[1,1,1,1,1,1,1,1]," \
	79	"[1,1,1,1,1,1,1,1]," \
	80	"[1,1,1,1,1,1,1,1]," \
	81	"[1,1,1,1,1,1,1,1]," \
	82	"[1,1,1,1,1,1,1,1]," \
	83	"[1,1,1,1,1,1,1,1]]"
	84	gain_rx = "[[1,1,1,1,0,0,0,0]," \
	85	"[1,1,1,1,0,0,0,0]," \
	86	"[1,1,1,1,0,0,0,0]," \
	87	"[1,1,1,1,0,0,0,0]," \
	88	"[0,0,0,0,1,1,1,1]," \
	89	"[0,0,0,0,1,1,1,1]," \
	90	"[0,0,0,0,1,1,1,1]," \
	91	"[0,0,0,0,1,1,1,1]]"
	92	ues_tx = "[0.533333,0.00000,1.06667,0.00000]"
	93	just_rx = 0
	94	data = OverJRO()
	95	data.setParameters(path, exp_name, phase_tx, gain_tx, gain_rx, ues_tx, just_rx)
	96	contentFile = data.setTextContent()
	97	data.saveFile(contentFile)

apps/abs/utils/TimeTools.py created 644 +427 0

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	1	"""
	2	The TIME_CONVERSIONS.py module gathers classes and functions for time system transformations
	3	(e.g. between seconds from 1970 to datetime format).
	4
	5	MODULES CALLED:
	6	NUMPY, TIME, DATETIME, CALENDAR
	7
	8	MODIFICATION HISTORY:
	9	Created by Ing. Freddy Galindo (frederickgalindo@gmail.com). ROJ Aug 13, 2009.
	10	"""
	11
	12	import numpy
	13	import time
	14	#import datetime as dt
	15	import calendar
	16
	17	class Time:
	18	"""
	19	time(year,month,dom,hour,min,secs)
	20
	21	An object represents a date and time of certain event..
	22
	23	Parameters
	24	----------
	25	YEAR = Number of the desired year. Year must be valid values from the civil calendar.
	26	Years B.C.E must be represented as negative integers. Years in the common era are repre-
	27	sented as positive integers. In particular, note that there is no year 0 in the civil
	28	calendar. 1 B.C.E. (-1) is followed by 1 C.E. (1).
	29
	30	MONTH = Number of desired month (1=Jan, ..., 12=December).
	31
	32	DOM = Number of day of the month.
	33
	34	HOUR = Number of the hour of the day. By default hour=0
	35
	36	MINS = Number of the minute of the hour. By default min=0
	37
	38	SECS = Number of the second of the minute. By default secs=0.
	39
	40	Examples
	41	--------
	42	time_info = time(2008,9,30,12,30,00)
	43
	44	time_info = time(2008,9,30)
	45	"""
	46
	47	def __init__(self,year=None,month=None,dom=None,hour=0,mins=0,secs=0):
	48	# If one the first three inputs are not defined, it takes the current date.
	49	date = time.localtime()
	50	if year==None:year=date[0]
	51	if month==None:month=date[1]
	52	if dom==None:dom=date[2]
	53
	54	# Converting to arrays
	55	year = numpy.array([year]); month = numpy.array([month]); dom = numpy.array([dom])
	56	hour = numpy.array([hour]); mins = numpy.array([mins]); secs = numpy.array([secs])
	57
	58	# Defining time information object.
	59	self.year = numpy.atleast_1d(year)
	60	self.month = numpy.atleast_1d(month)
	61	self.dom = numpy.atleast_1d(dom)
	62	self.hour = numpy.atleast_1d(hour)
	63	self.mins = numpy.atleast_1d(mins)
	64	self.secs = numpy.atleast_1d(secs)
	65
	66	def change2julday(self):
	67	"""
	68	Converts a datetime to Julian days.
	69	"""
	70
	71	# Defining constants
	72	greg = 2299171 # incorrect Julian day for Oct, 25, 1582.
	73	min_calendar = -4716
	74	max_calendar = 5000000
	75
	76	min_year = numpy.nanmin(self.year)
	77	max_year = numpy.nanmax(self.year)
	78	if (min_year<min_calendar) or (max_year>max_calendar):
	79	print ("Value of Julian date is out of allowed range")
	80	return -1
	81
	82	noyear = numpy.sum(self.year==0)
	83	if noyear>0:
	84	print ("There is no year zero in the civil calendar")
	85	return -1
	86
	87	# Knowing if the year is less than 0.
	88	bc = self.year<0
	89
	90	# Knowing if the month is less than March.
	91	inJanFeb = self.month<=2
	92
	93	jy = self.year + bc - inJanFeb
	94	jm = self.month + (1 + 12*inJanFeb)
	95
	96	# Computing Julian days.
	97	jul= numpy.floor(365.25jy) + numpy.floor(30.6001jm) + (self.dom+1720995.0)
	98
	99	# Test whether to change to Gregorian Calendar
	100	if numpy.min(jul) >= greg:
	101	ja = numpy.int32(0.01*jy)
	102	jul = jul + 2 - ja + numpy.int32(0.25*ja)
	103	else:
	104	gregchange = numpy.where(jul >= greg)
	105	if gregchange[0].size>0:
	106	ja = numpy.int32(0.01 + jy[gregchange])
	107	jy[gregchange] = jy[gregchange] + 2 - ja + numpy.int32(0.25*ja)
	108
	109	# Determining machine-specific parameters affecting floating-point.
	110	eps = 0.0 # Replace this line for a function to get precision.
	111	eps = abs(jul)*0.0 > eps
	112
	113	jul = jul + (self.hour/24. -0.5) + (self.mins/1440.) + (self.secs/86400.) + eps
	114
	115	return jul[0]
	116
	117	def change2secs(self):
	118	"""
	119	Converts datetime to number of seconds respect to 1970.
	120	"""
	121
	122	year = self.year
	123	if year.size>1: year = year[0]
	124
	125	month = self.month
	126	if month.size>1: month = month[0]
	127
	128	dom = self.dom
	129	if dom.size>1: dom = dom[0]
	130
	131	# Resizing hour, mins and secs if it was necessary.
	132	hour = self.hour
	133	if hour.size>1:hour = hour[0]
	134	if hour.size==1:hour = numpy.resize(hour,year.size)
	135
	136	mins = self.mins
	137	if mins.size>1:mins = mins[0]
	138	if mins.size==1:mins = numpy.resize(mins,year.size)
	139
	140	secs = self.secs
	141	if secs.size>1:secs = secs[0]
	142	if secs.size==1:secs = numpy.resize(secs,year.size)
	143
	144	# Using time.mktime to compute seconds respect to 1970.
	145	secs1970 = numpy.zeros(year.size)
	146	for ii in numpy.arange(year.size):
	147	secs1970[ii] = time.mktime((int(year[ii]),int(month[ii]),int(dom[ii]),\
	148	int(hour[ii]),int(mins[ii]),int(secs[ii]),0,0,0))
	149
	150	secs1970 = numpy.int32(secs1970 - time.timezone)
	151
	152	return secs1970
	153
	154	def change2strdate(self,mode=1):
	155	"""
	156	change2strdate method converts a date and time of certain event to date string. The
	157	string format is like localtime (e.g. Fri Oct 9 15:00:19 2009).
	158
	159	Parameters
	160	----------
	161	None.
	162
	163	Return
	164	------
	165
	166	Modification History
	167	--------------------
	168	Created by Freddy R. Galindo, ROJ, 09 October 2009.
	169
	170	"""
	171
	172	secs = numpy.atleast_1d(self.change2secs())
	173	strdate = []
	174	for ii in numpy.arange(numpy.size(secs)):
	175	secs_tmp = time.localtime(secs[ii] + time.timezone)
	176	if mode==1:
	177	strdate.append(time.strftime("%d-%b-%Y (%j) %H:%M:%S",secs_tmp))
	178	elif mode==2:
	179	strdate.append(time.strftime("%d-%b-%Y (%j)",secs_tmp))
	180
	181	strdate = numpy.array(strdate)
	182
	183	return strdate
	184
	185
	186	class Secs:
	187	"""
	188	secs(secs):
	189
	190	An object represents the number of seconds respect to 1970.
	191
	192	Parameters
	193	----------
	194
	195	SECS = A scalar or array giving the number of seconds respect to 1970.
	196
	197	Example:
	198	--------
	199	secs_info = secs(1251241373)
	200
	201	secs_info = secs([1251241373,1251241383,1251241393])
	202	"""
	203	def __init__(self,secs):
	204	self.secs = secs
	205
	206	def change2julday(self):
	207	"""
	208	Convert seconds from 1970 to Julian days.
	209	"""
	210
	211	secs_1970 = time(1970,1,1,0,0,0).change2julday()
	212
	213	julian = self.secs/86400.0 + secs_1970
	214
	215	return julian
	216
	217	def change2time(self):
	218	"""
	219	Converts seconds from 1970 to datetime.
	220	"""
	221
	222	secs1970 = numpy.atleast_1d(self.secs)
	223
	224	datetime = numpy.zeros((9,secs1970.size))
	225	for ii in numpy.arange(secs1970.size):
	226	tuple = time.gmtime(secs1970[ii])
	227	datetime[0,ii] = tuple[0]
	228	datetime[1,ii] = tuple[1]
	229	datetime[2,ii] = tuple[2]
	230	datetime[3,ii] = tuple[3]
	231	datetime[4,ii] = tuple[4]
	232	datetime[5,ii] = tuple[5]
	233	datetime[6,ii] = tuple[6]
	234	datetime[7,ii] = tuple[7]
	235	datetime[8,ii] = tuple[8]
	236
	237	datetime = numpy.int32(datetime)
	238
	239	return datetime
	240
	241
	242	class Julian:
	243	"""
	244	julian(julian):
	245
	246	An object represents julian days.
	247
	248	Parameters
	249	----------
	250
	251	JULIAN = A scalar or array giving the julina days.
	252
	253	Example:
	254	--------
	255	julian_info = julian(2454740)
	256
	257	julian_info = julian([2454740,2454760,2454780])
	258	"""
	259	def __init__(self,julian):
	260	self.julian = numpy.atleast_1d(julian)
	261
	262	def change2time(self):
	263	"""
	264	change2time method converts from julian day to calendar date and time.
	265
	266	Return
	267	------
	268	year = An array giving the year of the desired julian day.
	269	month = An array giving the month of the desired julian day.
	270	dom = An array giving the day of the desired julian day.
	271	hour = An array giving the hour of the desired julian day.
	272	mins = An array giving the minute of the desired julian day.
	273	secs = An array giving the second of the desired julian day.
	274
	275	Examples
	276	--------
	277	>> jd = 2455119.0
	278	>> [yy,mo,dd,hh,mi,ss] = TimeTools.julian(jd).change2time()
	279	>> print ([yy,mo,dd,hh,mi,ss])
	280	[2009] [10] [ 14.] [ 12.] [ 0.] [ 0.]
	281
	282	Modification history
	283	--------------------
	284	Translated from "Numerical Recipies in C", by William H. Press, Brian P. Flannery,
	285	Saul A. Teukolsky, and William T. Vetterling. Cambridge University Press, 1988.
	286	Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009.
	287	"""
	288
	289	min_julian = -1095
	290	max_julian = 1827933925
	291	if (numpy.min(self.julian) < min_julian) or (numpy.max(self.julian) > max_julian):
	292	print ('Value of Julian date is out of allowed range.')
	293	return None
	294
	295	# Beginning of Gregorian calendar
	296	igreg = 2299161
	297	julLong = numpy.floor(self.julian + 0.5)
	298	minJul = numpy.min(julLong)
	299
	300	if (minJul >= igreg):
	301	# All are Gregorian
	302	jalpha = numpy.int32(((julLong - 1867216) - 0.25)/36524.25)
	303	ja = julLong + 1 + jalpha - numpy.int32(0.25*jalpha)
	304	else:
	305	ja = julLong
	306	gregChange = numpy.where(julLong >= igreg)
	307	if gregChange[0].size>0:
	308	jalpha = numpy.int32(((julLong[gregChange]-1867216) - 0.25)/36524.25)
	309	ja[gregChange] = julLong[gregChange]+1+jalpha-numpy.int32(0.25*jalpha)
	310
	311	# clear memory.
	312	jalpha = -1
	313
	314	jb = ja + 1524
	315	jc = numpy.int32(6680. + ((jb-2439870)-122.1)/365.25)
	316	jd = numpy.int32(365.jc + (0.25jc))
	317	je = numpy.int32((jb - jd)/30.6001)
	318
	319	dom = jb - jd - numpy.int32(30.6001*je)
	320	month = je - 1
	321	month = ((month - 1) % 12) + 1
	322	month = numpy.atleast_1d(month)
	323	year = jc - 4715
	324	year = year - (month > 2)*1
	325	year = year - (year <= 0)*1
	326	year = numpy.atleast_1d(year)
	327
	328	# Getting hours, minutes, seconds
	329	fraction = self.julian + 0.5 - julLong
	330	eps_0 = dom*0.0 + 1.0e-12
	331	eps_1 = 1.0e-12*numpy.abs(julLong)
	332	eps = (eps_0>eps_1)eps_0 + (eps_0<=eps_1)eps_1
	333
	334	hour_0 = dom*0 + 23
	335	hour_2 = dom*0 + 0
	336	hour_1 = numpy.floor(fraction*24.0 + eps)
	337	hour = ((hour_1>hour_0)23) + ((hour_1<=hour_0)hour_1)
	338	hour = ((hour_1<hour_2)0) + ((hour_1>=hour_2)hour_1)
	339
	340	fraction = fraction - (hour/24.0)
	341	mins_0 = dom*0 + 59
	342	mins_2 = dom*0 + 0
	343	mins_1 = numpy.floor(fraction*1440.0 + eps)
	344	mins = ((mins_1>mins_0)59) + ((mins_1<=mins_0)mins_1)
	345	mins = ((mins_1<mins_2)0) + ((mins_1>=mins_2)mins_1)
	346
	347	secs_2 = dom*0 + 0
	348	secs_1 = (fraction - mins/1440.0)*86400.0
	349	secs = ((secs_1<secs_2)0) + ((secs_1>=secs_2)secs_1)
	350
	351	return year,month,dom,hour,mins,secs
	352
	353	def change2secs(self):
	354	"""
	355	Converts from Julian days to seconds from 1970.
	356	"""
	357
	358	jul_1970 = Time(1970,1,1,0,0,0).change2julday()
	359
	360	secs = numpy.int32((self.julian - jul_1970)*86400)
	361
	362	return secs
	363
	364	def change2lst(self,longitude=-76.8667):
	365	"""
	366	CT2LST converts from local civil time to local mean sideral time
	367
	368	longitude = The longitude in degrees (east of Greenwich) of the place for which
	369	the local sideral time is desired, scalar. The Greenwich mean sideral time (GMST)
	370	can be found by setting longitude=0.
	371	"""
	372
	373	# Useful constants, see Meus, p. 84
	374	c = numpy.array([280.46061837, 360.98564736629, 0.000387933, 38710000.0])
	375	jd2000 = 2451545.0
	376	t0 = self.julian - jd2000
	377	t = t0/36525.
	378
	379	# Computing GST in seconds
	380	theta = c[0] + (c[1]t0) + (t2)(c[2]-t/c[3])
	381
	382	# Computing LST in hours
	383	lst = (theta + longitude)/15.0
	384	neg = numpy.where(lst < 0.0)
	385	if neg[0].size>0:lst[neg] = 24.0 + (lst[neg] % 24)
	386	lst = lst % 24.0
	387
	388	return lst
	389
	390
	391	class date2doy:
	392	def __init__(self,year,month,day):
	393	self.year = year
	394	self.month = month
	395	self.day = day
	396
	397	def change2doy(self):
	398	if calendar.isleap(self.year) == True:
	399	tfactor = 1
	400	else:
	401	tfactor = 2
	402
	403	day = self.day
	404	month = self.month
	405
	406	doy = numpy.floor((275month)/9.0) - (tfactornumpy.floor((month+9)/12.0)) + day - 30
	407
	408	return numpy.int32(doy)
	409
	410
	411	class Doy2Date:
	412	def __init__(self,year,doy):
	413	self.year = year
	414	self.doy = doy
	415
	416	def change2date(self):
	417	months = numpy.arange(12) + 1
	418
	419	first_dem = date2doy(self.year,months,1)
	420	first_dem = first_dem.change2doy()
	421
	422	imm = numpy.where((self.doy - first_dem) > 0)
	423
	424	month = imm[0].size
	425	dom = self.doy -first_dem[month - 1] + 1
	426
	427	return month, dom

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apps/abs/utils/contributors.txt created 644 +1 0

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				1	Edwin Christian Yllanes Cucho

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apps/abs/utils/gaussfit.py created 644 +34 0

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	1	from numpy import *
	2	from scipy import optimize
	3
	4	def gaussian(height, center_x, center_y, width_x, width_y):
	5	"""Returns a gaussian function with the given parameters"""
	6	width_x = float(width_x)
	7	width_y = float(width_y)
	8	return lambda x,y: height*exp(
	9	-(((center_x-x)/width_x)2+((center_y-y)/width_y)2)/2)
	10
	11	def moments(data):
	12	"""Returns (height, x, y, width_x, width_y)
	13	the gaussian parameters of a 2D distribution by calculating its
	14	moments """
	15	total = data.sum()
	16	X, Y = indices(data.shape)
	17	x = (X*data).sum()/total
	18	y = (Y*data).sum()/total
	19	col = data[:, int(y)]
	20	width_x = sqrt(abs((arange(col.size)-y)*2col).sum()/col.sum())
	21	row = data[int(x), :]
	22	width_y = sqrt(abs((arange(row.size)-x)*2row).sum()/row.sum())
	23	height = data.max()
	24	return height, x, y, width_x, width_y
	25
	26	def fitgaussian(data):
	27	"""Returns (height, x, y, width_x, width_y)
	28	the gaussian parameters of a 2D distribution found by a fit"""
	29	params = moments(data)
	30	errorfunction = lambda p: ravel(gaussian(p)(indices(data.shape)) -
	31	data)
	32	p, success = optimize.leastsq(errorfunction, params)
	33	return p
	34

apps/abs/utils/manage.py created 644 +10 0

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	1	#!/usr/bin/env python
	2	import os
	3	import sys
	4
	5	if __name__ == "__main__":
	6	os.environ.setdefault("DJANGO_SETTINGS_MODULE", "radarsys.settings")
	7
	8	from django.core.management import execute_from_command_line
	9
	10	execute_from_command_line(sys.argv)

apps/abs/utils/overJroShow.py created 644 +1632 0

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		1	#!/usr/bin/python
		2
		3
		4	import sys, os, os.path
		5	import traceback
		6	import cgi, Cookie
		7	import time, datetime
		8	import types
		9	import numpy
		10	import numpy.fft
		11	import scipy.linalg
		12	import scipy.special
		13	#import Numeric
		14
		15	import Misc_Routines
		16	import TimeTools
		17	import JroAntSetup
		18	import Graphics_OverJro
		19	import Astro_Coords
		20
		21	class JroPattern():
		22	def __init__(self,pattern=0,path=None,filename=None,nptsx=101,nptsy=101,maxphi=5,fftopt=0, \
		23	getcut=0,dcosx=None,dcosy=None,eomwl=6,airwl=4):
		24	"""
		25	JroPattern class creates an object to represent the useful parameters for beam mode-
		26	lling of the Jicamarca VHF radar.
		27
		28	Parameters
		29	----------
		30	pattern = An integer (See JroAntSetup to know the available values) to load a prede-
		31	fined configuration. The default value is 0. To use a user-defined configuration
		32	pattern must be None.
		33	path = A string giving the directory that contains the user-configuration file. PATH
		34	will work if pattern is None.
		35	filename = A string giving the name of the user-configuration file. FILENAME will
		36	work if pattern is None.
		37	nptsx = A scalar to specify the number of points used to define the angular resolu-
		38	tion in the "x" axis. The default value is 101.
		39	nptsy = A scalar to specify the number of points used to define the angular resolu-
		40	tion in the "x" axis. The default value is 101.
		41	maxphi = A scalar giving the maximum (absolute) angle (in degree) to model the ante-
		42	nna pattern. The default value is 5 degrees.
		43	fftopt = Set this input to 1 to model the beam using FFT. To model using antenna
		44	theory set to 0 (default value).
		45	getcut = Set to 1 to show an antenna cut instead of a contour plot of itself (set to
		46	0). The defautl value is 0.
		47	dcosx = An array giving the directional cosines for the x-axis. DCOSX will work if
		48	getcut is actived.
		49	dcosy = An array giving the directional cosines for the y-axis. DCOSY will work if
		50	getcut is actived.
		51	eomwl = A scalar giving the radar wavelength. The default value is 6m (50 MHZ).
		52	airwl = Set this input to float (or intger) to specify the wavelength (in meters) of
		53	the transmitted EOM wave in the air. The default value is 4m.
		54
		55	Modification History
		56	--------------------
		57	Converted to Object-oriented Programming by Freddy Galindo, ROJ, 20 September 2009.
		58	"""
		59
		60
		61
		62	# Getting antenna configuration.
		63	setup = JroAntSetup.ReturnSetup(path=path,filename=filename,pattern=pattern)
		64
		65	ues = setup["ues"]
		66	phase = setup["phase"]
		67	gaintx = setup["gaintx"]
		68	gainrx = setup["gainrx"]
		69	justrx = setup["justrx"]
		70
		71	# Defining attributes for JroPattern class.
		72	# Antenna configuration
		73	self.uestx = ues
		74	self.phasetx = phase
		75	self.gaintx = gaintx
		76	self.uesrx = ues
		77	self.phaserx = phase
		78	self.gainrx = gainrx
		79	self.justrx = justrx
		80
		81	# Pattern resolution & method to model
		82	self.maxphi = maxphi
		83	self.nptsx = nptsx
		84	self.nptsy = nptsy
		85	self.fftopt = fftopt
		86
		87	# To get a cut of the pattern.
		88	self.getcut = getcut
		89
		90	maxdcos = numpy.sin(maxphi*Misc_Routines.CoFactors.d2r)
		91	if dcosx==None:dcosx = ((numpy.arange(nptsx,dtype=float)/(nptsx-1))-0.5)2maxdcos
		92	if dcosy==None:dcosy = ((numpy.arange(nptsy,dtype=float)/(nptsy-1))-0.5)2maxdcos
		93	self.dcosx = dcosx
		94	self.dcosy = dcosy
		95	self.nx = dcosx.size
		96	self.ny = dcosy.size*(getcut==0) + (getcut==1)
		97
		98	self.eomwl = eomwl
		99	self.airwl = airwl
		100
		101	self.kk = 2.*numpy.pi/eomwl
		102
		103	self.pattern = None
		104	self.meanpos = None
		105	self.norpattern = None
		106	self.maxpattern = None
		107
		108	self.title = setup["title"]
		109
		110	self.getPattern()
		111
		112	def getPattern(self):
		113	"""
		114	getpattern method returns the modelled total antenna pattern and its mean position.
		115
		116	Return
		117	------
		118	pattern = An array giving the Modelled antenna pattern.
		119	mean_pos = A 2-elements array giving the mean position of the main beam.
		120
		121	Examples
		122	--------
		123	>> [pattern, mean_pos] = JroPattern(pattern=2).getPattern()
		124	>> print meanpos
		125	[ 8.08728085e-14 -4.78193873e-14]
		126
		127	Modification history
		128	--------------------
		129	Developed by Jorge L. Chau.
		130	Converted to Python by Freddy R. Galindo, ROJ, 20 September 2009.
		131	"""
		132
		133	if (self.fftopt>0) and (self.getcut>0):
		134	#print "Conflict bewteen fftopt and getcut"
		135	#print "To get a cut of the antenna pattern uses ffopt=0"
		136	return None, None
		137
		138	if (self.fftopt==0):
		139	# Getting antenna pattern using the array method
		140	self.pattern = self.__usingArray(rx=1)
		141	if (self.justrx==0):self.pattern = self.pattern*self.__usingArray(rx=0)
		142
		143	elif (self.fftopt>0):
		144	# Getting antenna pattern using FFT method
		145	self.pattern = self.__usingFFT(rx=1)
		146	if (self.justrx==0):self.pattern = self.pattern*self.__usingFFT(rx=0)
		147
		148	self.maxpattern = numpy.nanmax(self.pattern)
		149	self.norpattern = self.pattern/self.maxpattern
		150	if self.getcut==0:self.__getBeamPars()
		151
		152	def __usingArray(self,rx):
		153	"""
		154	__usingArray method returns the Jicamarca antenna pattern computed using array model
		155
		156	pattern = dipolepattern x modulepattern
		157
		158	Parameters
		159	----------
		160	rx = Set to 1 to use the Rx information. Otherwise set to 0 for Tx.
		161
		162	Return
		163	------
		164	pattern = An array giving the modelled antenna pattern using the array model.
		165
		166	Modification history
		167	--------------------
		168	Developed by Jorge L. Chau.
		169	Converted to Python by Freddy R. Galindo, ROJ, 20 September 2009.
		170	"""
		171
		172	if rx==1:
		173	ues = self.uesrx
		174	phase = self.phaserx
		175	gain = self.gainrx
		176	elif rx==0:
		177	ues = self.uestx
		178	phase = self.phasetx
		179	gain = self.gaintx
		180
		181	ues = ues*360./self.airwl
		182	phase = phase*360./self.airwl
		183
		184	for ii in range(4):
		185	if ii==0:dim = numpy.array([4,0,8,4]) # WEST
		186	elif ii==1:dim = numpy.array([0,0,4,4]) # NORTH
		187	elif ii==2:dim = numpy.array([0,4,4,8]) # EAST
		188	elif ii==3:dim = numpy.array([4,4,8,8]) # SOUTH
		189	xi = dim[0]; xf = dim[2]; yi = dim[1]; yf = dim[3]
		190	phase[xi:xf,yi:yf] = phase[xi:xf,yi:yf] + ues[ii]
		191
		192	phase = -phase
		193
		194	ar = self.eomwl*numpy.array([[0.5,6., 24.5],[0.5,6.,24.5]])
		195	nr = numpy.array([[12.,4.,2.],[12.,4.,2.]])
		196	lr = 0.25self.eomwlnumpy.array([[0,0.,0],[0.,0,0]])
		197
		198	# Computing module and dipole patterns.
		199	pattern = (numpy.abs(self.__dipPattern(ar,nr,lr)self.__modPattern(phase,gain)))*2
		200
		201	return pattern
		202
		203	def __usingFFT(self,rx):
		204	"""
		205	__usingFFT method returns the Jicamarca antenna pattern computed using The Fast Fou-
		206	rier Transform.
		207
		208	pattern = iFFT(FFT(gainEXP(jphase)))
		209
		210	Parameters
		211	----------
		212	rx = Set to 1 to use the Rx information. Otherwise set to 0 for Tx.
		213
		214	Return
		215	------
		216	pattern = An array giving the modelled antenna pattern using the array model.
		217
		218	Modification history
		219	--------------------
		220	Developed by Jorge L. Chau.
		221	Converted to Python by Freddy R. Galindo, ROJ, 20 September 2009.
		222	"""
		223
		224	if rx==1:
		225	ues = self.uesrx
		226	phase = self.phaserx
		227	gain = self.gainrx
		228	elif rx==0:
		229	ues = self.uestx
		230	phase = self.phasetx
		231	gain = self.gaintx
		232
		233	ues = ues*360./self.airwl
		234	phase = phase*360./self.airwl
		235
		236	for ii in range(4):
		237	if ii==0:dim = numpy.array([4,0,8,4]) # WEST
		238	elif ii==1:dim = numpy.array([0,0,4,4]) # NORTH
		239	elif ii==2:dim = numpy.array([0,4,4,8]) # EAST
		240	elif ii==3:dim = numpy.array([4,4,8,8]) # SOUTH
		241	xi = dim[0]; xf = dim[2]; yi = dim[1]; yf = dim[3]
		242	phase[xi:xf,yi:yf] = phase[xi:xf,yi:yf] + ues[ii]
		243
		244	phase = -phase
		245
		246	delta_x = self.eomwl/2.
		247	delta_y = self.eomwl/2.
		248
		249	nxfft = 2048
		250	nyfft = 2048
		251	dcosx = (numpy.arange(nxfft) - (0.5nxfft))/(nxfftdelta_x)*self.eomwl
		252	dcosy = (numpy.arange(nyfft) - (0.5nyfft))/(nyfftdelta_y)*self.eomwl
		253
		254	fft_gain = numpy.zeros((nxfft,nyfft))
		255	fft_phase = numpy.zeros((nxfft,nyfft))
		256
		257	nx = 8
		258	ny = 8
		259	ndx =12
		260	ndy =12
		261	for iy in numpy.arange(ny):
		262	for ix in numpy.arange(nx):
		263	ix1 = nxfft/2-self.nx/2ndx+ixndx
		264	if ix<(nx/2):ix1 = ix1 - 1
		265	if ix>=(nx/2):ix1 = ix1 + 1
		266
		267	iy1 = nyfft/2-ny/2ndx+iyndy
		268	if iy<(ny/2):iy1 = iy1 - 1
		269	if iy>=(ny/2):iy1 = iy1 + 1
		270
		271	fft_gain[ix1:ix1+ndx-1,iy1:iy1+ndy-1] = gain[ix,ny-1-iy]
		272	fft_phase[ix1:ix1+ndx-1,iy1:iy1+ndy-1] = phase[ix,ny-1-iy]
		273
		274
		275	fft_phase = fft_phase*Misc_Routines.CoFactors.d2r
		276
		277	pattern = numpy.abs(numpy.fft.fft2(fft_gainnumpy.exp(numpy.complex(0,1)fft_phase)))**2
		278	pattern = numpy.fft.fftshift(pattern)
		279
		280	xvals = numpy.where((dcosx>=(numpy.min(self.dcosx))) & (dcosx<=(numpy.max(self.dcosx))))
		281	yvals = numpy.where((dcosy>=(numpy.min(self.dcosy))) & (dcosy<=(numpy.max(self.dcosy))))
		282
		283	pattern = pattern[xvals[0][0]:xvals[0][-1],yvals[0][0]:yvals[0][-1]]
		284
		285	return pattern
		286
		287	def __readAttenuation(self):
		288	"""
		289	_readAttenuation reads the attenuations' file and returns an array giving these va-
		290	lues (dB). The ext file must be in the directory "resource".
		291
		292	Return
		293	------
		294	attenuation = An array giving attenuation values read from the text file.
		295
		296	Modification history
		297	--------------------
		298	Developed by Jorge L. Chau.
		299	Converted to Python by Freddy R. Galindo, ROJ, 20 September 2009.
		300	"""
		301
		302	attenuation = None
		303	# foldr = sys.path[-1] + os.sep + "resource" + os.sep
		304	base_path = os.path.dirname(os.path.abspath(__file__))
		305	#foldr = './resource'
		306	#filen = "attenuation.txt"
		307	attenuationFile = os.path.join(base_path,"resource","attenuation.txt")
		308	#ff = open(os.path.join(foldr,filen),'r')
		309	ff = open(attenuationFile,'r')
		310	exec(ff.read())
		311	ff.close()
		312
		313	return attenuation
		314
		315	def __dipPattern(self,ar,nr,lr):
		316	"""
		317	_dipPattern function computes the dipole's pattern to the Jicamarca radar. The next
		318	equation defines the pattern as a function of the mainlobe direction:
		319
		320	sincx = SIN(k/2n0x(a0xSIN(phi)COS(alpha)))/SIN(k/2(a0xSIN(phi)*COS(alpha)))
		321	sincy = SIN(k/2n0y(a0ySIN(phi)SIN(alpha)))/SIN(k/2(a0ySIN(phi)*SIN(alpha)))
		322	A0(phi,alpha) = sincx*sincy
		323	Parameters
		324	----------
		325	ar = ?
		326	nr = ?
		327	lr = ?
		328
		329	Return
		330	------
		331	dipole = An array giving antenna pattern from the dipole point of view..
		332
		333	Modification history
		334	--------------------
		335	Developed by Jorge L. Chau.
		336	Converted to Python by Freddy R. Galindo, ROJ, 20 September 2009.
		337	"""
		338
		339	dipole = numpy.zeros((self.nx,self.ny),dtype=complex)
		340	for iy in range(self.ny):
		341	for ix in range(self.nx):
		342	yindex = iy(self.getcut==0) + ix(self.getcut==1)
		343
		344	argx = ar[0,0]*self.dcosx[ix] - lr[0,0]
		345	junkx = numpy.sin(0.5self.kknr[0,0]argx)/numpy.sin(0.5self.kk*argx)
		346	if argx == 0.0: junkx = nr[0,0]
		347
		348	argy = ar[1,0]*self.dcosy[yindex] - lr[1,0]
		349	junky = numpy.sin(0.5self.kknr[1,0]argy)/numpy.sin(0.5self.kk*argy)
		350	if argy == 0.0: junky = nr[1,0]
		351
		352	dipole[ix,iy] = junkx*junky
		353
		354	return dipole
		355
		356	def __modPattern(self,phase,gain):
		357	"""
		358	ModPattern computes the module's pattern to the Jicamarca radar. The next equation
		359	defines the pattern as a function mainlobe direction:
		360
		361	phasex = pos(x)SIN(phi)COS(alpha)
		362	phasey = pos(y)SIN(phi)SIN(alpha)
		363
		364	A1(phi,alpha) = TOTAL(gainEXP(COMPLEX(0,k(phasex+phasey)+phase)))
		365
		366	Parameters
		367	----------
		368	phase = Bidimensional array (8x8) giving the phase (in meters) of each module.
		369	gain = Bidimensional array (8x8) giving to define modules will be active (ones)
		370	and which will not (zeros).
		371
		372	Return
		373	------
		374	module = An array giving antenna pattern from the module point of view..
		375
		376	Modification history
		377	--------------------
		378	Developed by Jorge L. Chau.
		379	Converted to Python by Freddy R. Galindo, ROJ, 20 September 2009.
		380	"""
		381
		382	pos = self.eomwl*self.__readAttenuation()
		383	posx = pos[0,:,:]
		384	posy = pos[1,:,:]
		385
		386	phase = phase*Misc_Routines.CoFactors.d2r
		387	module = numpy.zeros((self.nx,self.ny),dtype=complex)
		388	for iy in range(self.ny):
		389	for ix in range(self.nx):
		390	yindex = iy(self.getcut==0) + ix(self.getcut==1)
		391	phasex = posx*self.dcosx[ix]
		392	phasey = posy*self.dcosy[yindex]
		393	tmp = gainnumpy.exp(numpy.complex(0,1.)(self.kk*(phasex+phasey)+phase))
		394	module[ix,iy] = tmp.sum()
		395
		396	return module
		397
		398	def __getBeamPars(self):
		399	"""
		400	_getBeamPars computes the main-beam parameters of the antenna.
		401
		402	Modification history
		403	--------------------
		404	Developed by Jorge L. Chau.
		405	Converted to Python by Freddy R. Galindo, ROJ, 20 September 2009.
		406	"""
		407
		408	dx = self.dcosx[1] - self.dcosx[0]
		409	dy = self.dcosy[1] - self.dcosy[0]
		410
		411	amp = self.norpattern
		412
		413	xx = numpy.resize(self.dcosx,(self.nx,self.nx)).transpose()
		414	yy = numpy.resize(self.dcosy,(self.ny,self.ny))
		415
		416	mm0 = amp[numpy.where(amp > 0.5)]
		417	xx0 = xx[numpy.where(amp > 0.5)]
		418	yy0 = yy[numpy.where(amp > 0.5)]
		419
		420	xc = numpy.sum(mm0*xx0)/numpy.sum(mm0)
		421	yc = numpy.sum(mm0*yy0)/numpy.sum(mm0)
		422	rc = numpy.sqrt(mm0.sizedxdy/numpy.pi)
		423
		424	nnx = numpy.where(numpy.abs(self.dcosx - xc) < rc)
		425	nny = numpy.where(numpy.abs(self.dcosy - yc) < rc)
		426
		427	mm1 = amp[numpy.min(nnx):numpy.max(nnx)+1,numpy.min(nny):numpy.max(nny)+1]
		428	xx1 = self.dcosx[numpy.min(nnx):numpy.max(nnx)+1]
		429	yy1 = self.dcosy[numpy.min(nny):numpy.max(nny)+1]
		430
		431	# fitting data into the main beam.
		432	import gaussfit
		433	params = gaussfit.fitgaussian(mm1)
		434
		435	# Tranforming from indexes to axis' values
		436	xcenter = xx1[0] + (((xx1[xx1.size-1] - xx1[0])/(xx1.size -1))*(params[1]))
		437	ycenter = yy1[0] + (((yy1[yy1.size-1] - yy1[0])/(yy1.size -1))*(params[2]))
		438	xwidth = ((xx1[xx1.size-1] - xx1[0])/(xx1.size-1))(params[3])(1/Misc_Routines.CoFactors.d2r)
		439	ywidth = ((yy1[yy1.size-1] - yy1[0])/(yy1.size-1))(params[4])(1/Misc_Routines.CoFactors.d2r)
		440	meanwx = (xwidth*ywidth)
		441	meanpos = numpy.array([xcenter,ycenter])
		442
		443	#print 'Position: %f %f' %(xcenter,ycenter)
		444	#print 'Widths: %f %f' %(xwidth, ywidth)
		445	#print 'BWHP: %f' %(2numpy.sqrt(2meanwx)*numpy.sqrt(-numpy.log(0.5)))
		446
		447	self.meanpos = meanpos
		448
		449
		450	class BField():
		451	def __init__(self,year=None,doy=None,site=1,heights=None,alpha_i=90):
		452	"""
		453	BField class creates an object to get the Magnetic field for a specific date and
		454	height(s).
		455
		456	Parameters
		457	----------
		458	year = A scalar giving the desired year. If the value is None (default value) then
		459	the current year will be used.
		460	doy = A scalar giving the desired day of the year. If the value is None (default va-
		461	lue) then the current doy will be used.
		462	site = An integer to choose the geographic coordinates of the place where the magne-
		463	tic field will be computed. The default value is over Jicamarca (site=1)
		464	heights = An array giving the heights (km) where the magnetic field will be modeled By default the magnetic field will be computed at 100, 500 and 1000km.
		465	alpha_i = Angle to interpolate the magnetic field.
		466
		467	Modification History
		468	--------------------
		469	Converted to Object-oriented Programming by Freddy Galindo, ROJ, 07 October 2009.
		470	"""
		471
		472	tmp = time.localtime()
		473	if year==None: year = tmp[0]
		474	if doy==None: doy = tmp[7]
		475	self.year = year
		476	self.doy = doy
		477	self.site = site
		478	if heights==None:heights = numpy.array([100,500,1000])
		479	self.heights = heights
		480	self.alpha_i = alpha_i
		481
		482	def getBField(self,maglimits=numpy.array([-7,-7,7,7])):
		483	"""
		484	getBField models the magnetic field for a different heights in a specific date.
		485
		486	Parameters
		487	----------
		488	maglimits = An 4-elements array giving ..... The default value is [-7,-7,7,7].
		489
		490	Return
		491	------
		492	dcos = An 4-dimensional array giving the directional cosines of the magnetic field
		493	over the desired place.
		494	alpha = An 3-dimensional array giving the angle of the magnetic field over the desi-
		495	red place.
		496
		497	Modification History
		498	--------------------
		499	Converted to Python by Freddy R. Galindo, ROJ, 07 October 2009.
		500	"""
		501
		502	x_ant = numpy.array([1,0,0])
		503	y_ant = numpy.array([0,1,0])
		504	z_ant = numpy.array([0,0,1])
		505
		506	if self.site==0:
		507	title_site = "Magnetic equator"
		508	coord_site = numpy.array([-76+52./60.,-11+57/60.,0.5])
		509	elif self.site==1:
		510	title_site = 'Jicamarca'
		511	coord_site = [-76-52./60.,-11-57/60.,0.5]
		512	theta = (45+5.35)*numpy.pi/180. # (50.35 and 1.46 from Fleish Thesis)
		513	delta = -1.46*numpy.pi/180
		514
		515	x_ant1 = numpy.roll(self.rotvector(self.rotvector(x_ant,1,delta),3,theta),1)
		516	y_ant1 = numpy.roll(self.rotvector(self.rotvector(y_ant,1,delta),3,theta),1)
		517	z_ant1 = numpy.roll(self.rotvector(self.rotvector(z_ant,1,delta),3,theta),1)
		518
		519	ang0 = -1coord_site[0]numpy.pi/180.
		520	ang1 = coord_site[1]*numpy.pi/180.
		521	x_ant = self.rotvector(self.rotvector(x_ant1,2,ang1),3,ang0)
		522	y_ant = self.rotvector(self.rotvector(y_ant1,2,ang1),3,ang0)
		523	z_ant = self.rotvector(self.rotvector(z_ant1,2,ang1),3,ang0)
		524	else:
		525	# print "No defined Site. Skip..."
		526	return None
		527
		528	nhei = self.heights.size
		529	pt_intercep = numpy.zeros((nhei,2))
		530	nfields = 1
		531
		532	grid_res = 0.5
		533	nlon = numpy.int(maglimits[2] - maglimits[0])/grid_res + 1
		534	nlat = numpy.int(maglimits[3] - maglimits[1])/grid_res + 1
		535
		536	location = numpy.zeros((nlon,nlat,2))
		537	mlon = numpy.atleast_2d(numpy.arange(nlon)*grid_res + maglimits[0])
		538	mrep = numpy.atleast_2d(numpy.zeros(nlat) + 1)
		539	location0 = numpy.dot(mlon.transpose(),mrep)
		540
		541	mlat = numpy.atleast_2d(numpy.arange(nlat)*grid_res + maglimits[1])
		542	mrep = numpy.atleast_2d(numpy.zeros(nlon) + 1)
		543	location1 = numpy.dot(mrep.transpose(),mlat)
		544
		545	location[:,:,0] = location0
		546	location[:,:,1] = location1
		547
		548	alpha = numpy.zeros((nlon,nlat,nhei))
		549	rr = numpy.zeros((nlon,nlat,nhei,3))
		550	dcos = numpy.zeros((nlon,nlat,nhei,2))
		551
		552	global first_time
		553
		554	first_time = None
		555	for ilon in numpy.arange(nlon):
		556	for ilat in numpy.arange(nlat):
		557	outs = self.__bdotk(self.heights,
		558	self.year + self.doy/366.,
		559	coord_site[1],
		560	coord_site[0],
		561	coord_site[2],
		562	coord_site[1]+location[ilon,ilat,1],
		563	location[ilon,ilat,0]*720./180.)
		564
		565	alpha[ilon, ilat,:] = outs[1]
		566	rr[ilon, ilat,:,:] = outs[3]
		567
		568	mrep = numpy.atleast_2d((numpy.zeros(nhei)+1)).transpose()
		569	tmp = outs[3]*numpy.dot(mrep,numpy.atleast_2d(x_ant))
		570	tmp = tmp.sum(axis=1)
		571	dcos[ilon,ilat,:,0] = tmp/numpy.sqrt((outs[3]**2).sum(axis=1))
		572
		573	mrep = numpy.atleast_2d((numpy.zeros(nhei)+1)).transpose()
		574	tmp = outs[3]*numpy.dot(mrep,numpy.atleast_2d(y_ant))
		575	tmp = tmp.sum(axis=1)
		576	dcos[ilon,ilat,:,1] = tmp/numpy.sqrt((outs[3]**2).sum(axis=1))
		577
		578	return dcos, alpha, nlon, nlat
		579
		580
		581	def __bdotk(self,heights,tm,gdlat=-11.95,gdlon=-76.8667,gdalt=0.0,decd=-12.88, ham=-4.61666667):
		582
		583	global first_time
		584	# Mean Earth radius in Km WGS 84
		585	a_igrf = 6371.2
		586
		587	bk = numpy.zeros(heights.size)
		588	alpha = numpy.zeros(heights.size)
		589	bfm = numpy.zeros(heights.size)
		590	rr = numpy.zeros((heights.size,3))
		591	rgc = numpy.zeros((heights.size,3))
		592
		593	ObjGeodetic = Astro_Coords.Geodetic(gdlat,gdalt)
		594	[gclat,gcalt] = ObjGeodetic.change2geocentric()
		595
		596	gclat = gclat*numpy.pi/180.
		597	gclon = gdlon*numpy.pi/180.
		598
		599	# Antenna position from center of Earth
		600	ca_vector = [numpy.cos(gclat)numpy.cos(gclon),numpy.cos(gclat)numpy.sin(gclon),numpy.sin(gclat)]
		601	ca_vector = gcalt*numpy.array(ca_vector)
		602
		603	dec = decd*numpy.pi/180.
		604
		605	# K vector respect to the center of earth.
		606	klon = gclon + ham*numpy.pi/720.
		607	k_vector = [numpy.cos(dec)numpy.cos(klon),numpy.cos(dec)numpy.sin(klon),numpy.sin(dec)]
		608	k_vector = numpy.array(k_vector)
		609
		610	for ih in numpy.arange(heights.size):
		611	# Vector from Earth's center to volume of interest
		612	rr[ih,:] = k_vector*heights[ih]
		613	cv_vector = numpy.squeeze(ca_vector) + rr[ih,:]
		614
		615	cv_gcalt = numpy.sqrt(numpy.sum(cv_vector**2.))
		616	cvxy = numpy.sqrt(numpy.sum(cv_vector[0:2]**2.))
		617
		618	radial = cv_vector/cv_gcalt
		619	east = numpy.array([-1*cv_vector[1],cv_vector[0],0])/cvxy
		620	comp1 = east[1]radial[2] - radial[1]east[2]
		621	comp2 = east[2]radial[0] - radial[2]east[0]
		622	comp3 = east[0]radial[1] - radial[0]east[1]
		623	north = -1*numpy.array([comp1, comp2, comp3])
		624
		625	rr_k = cv_vector - numpy.squeeze(ca_vector)
		626	u_rr = rr_k/numpy.sqrt(numpy.sum(rr_k**2.))
		627
		628	cv_gclat = numpy.arctan2(cv_vector[2],cvxy)
		629	cv_gclon = numpy.arctan2(cv_vector[1],cv_vector[0])
		630
		631	bhei = cv_gcalt-a_igrf
		632	blat = cv_gclat*180./numpy.pi
		633	blon = cv_gclon*180./numpy.pi
		634	bfield = self.__igrfkudeki(bhei,tm,blat,blon)
		635
		636	B = (bfield[0]north + bfield[1]east - bfield[2]radial)1.0e-5
		637
		638	bfm[ih] = numpy.sqrt(numpy.sum(B**2.)) #module
		639	bk[ih] = numpy.sum(u_rr*B)
		640	alpha[ih] = numpy.arccos(bk[ih]/bfm[ih])*180/numpy.pi
		641	rgc[ih,:] = numpy.array([cv_gclon, cv_gclat, cv_gcalt])
		642
		643	return bk, alpha, bfm, rr, rgc
		644
		645
		646	def __igrfkudeki(self,heights,time,latitude,longitude,ae=6371.2):
		647	"""
		648	__igrfkudeki calculates the International Geomagnetic Reference Field for given in-
		649	put conditions based on IGRF2005 coefficients.
		650
		651	Parameters
		652	----------
		653	heights = Scalar or vector giving the height above the Earth of the point in ques-
		654	tion in kilometers.
		655	time = Scalar or vector giving the decimal year of time in question (e.g. 1991.2).
		656	latitude = Latitude of point in question in decimal degrees. Scalar or vector.
		657	longitude = Longitude of point in question in decimal degrees. Scalar or vector.
		658	ae =
		659	first_time =
		660
		661	Return
		662	------
		663	bn =
		664	be =
		665	bd =
		666	bmod =
		667	balpha =
		668	first_time =
		669
		670	Modification History
		671	--------------------
		672	Converted to Python by Freddy R. Galindo, ROJ, 03 October 2009.
		673	"""
		674
		675	global first_time
		676	global gs, hs, nvec, mvec, maxcoef
		677
		678	heights = numpy.atleast_1d(heights)
		679	time = numpy.atleast_1d(time)
		680	latitude = numpy.atleast_1d(latitude)
		681	longitude = numpy.atleast_1d(longitude)
		682
		683	if numpy.max(latitude)==90:
		684	# print "Field calculations are not supported at geographic poles"
		685	pass
		686
		687	# output arrays
		688	bn = numpy.zeros(heights.size)
		689	be = numpy.zeros(heights.size)
		690	bd = numpy.zeros(heights.size)
		691
		692	if first_time==None:first_time=0
		693
		694	time0 = time[0]
		695	if time!=first_time:
		696	#print "Getting coefficients for", time0
		697	[periods,g,h ] = self.__readIGRFcoeff()
		698	top_year = numpy.max(periods)
		699	nperiod = (top_year - 1900)/5 + 1
		700
		701	maxcoef = 10
		702	if time0>=2000:maxcoef = 12
		703
		704
		705	# Normalization array for Schmidt fucntions
		706	multer = numpy.zeros((2+maxcoef,1+maxcoef)) + 1
		707	for cn in (numpy.arange(maxcoef)+1):
		708	for rm in (numpy.arange(cn)+1):
		709	tmp = numpy.arange(2*rm) + cn - rm + 1.
		710	multer[rm+1,cn] = ((-1.)*rm)numpy.sqrt(2./tmp.prod())
		711
		712	schmidt = multer[1:,1:].transpose()
		713
		714	# n and m arrays
		715	nvec = numpy.atleast_2d(numpy.arange(maxcoef)+2)
		716	mvec = numpy.atleast_2d(numpy.arange(maxcoef+1)).transpose()
		717
		718	# Time adjusted igrf g and h with Schmidt normalization
		719	# IGRF coefficient arrays: g0(n,m), n=1, maxcoeff,m=0, maxcoeff, ...
		720	if time0<top_year:
		721	dtime = (time0 - 1900) % 5
		722	ntime = (time0 - 1900 - dtime)/5
		723	else:
		724	# Estimating coefficients for times > top_year
		725	dtime = (time0 - top_year) + 5
		726	ntime = g[:,0,0].size - 2
		727
		728	g0 = g[ntime,1:maxcoef+1,:maxcoef+1]
		729	h0 = h[ntime,1:maxcoef+1,:maxcoef+1]
		730	gdot = g[ntime+1,1:maxcoef+1,:maxcoef+1]-g[ntime,1:maxcoef+1,:maxcoef+1]
		731	hdot = h[ntime+1,1:maxcoef+1,:maxcoef+1]-h[ntime,1:maxcoef+1,:maxcoef+1]
		732	gs = (g0 + dtime(gdot/5.))schmidt[:maxcoef,0:maxcoef+1]
		733	hs = (h0 + dtime(hdot/5.))schmidt[:maxcoef,0:maxcoef+1]
		734
		735	first_time = time0
		736
		737	for ii in numpy.arange(heights.size):
		738	# Height dependence array rad = (ae/(ae+height))**(n+3)
		739	rad = numpy.atleast_2d((ae/(ae + heights[ii]))**(nvec+1))
		740
		741	# Sin and Cos of m times longitude phi arrays
		742	mphi = mveclongitude[ii]numpy.pi/180.
		743	cosmphi = numpy.atleast_2d(numpy.cos(mphi))
		744	sinmphi = numpy.atleast_2d(numpy.sin(mphi))
		745
		746	# Cos of colatitude theta
		747	c = numpy.cos((90 - latitude[ii])*numpy.pi/180.)
		748
		749	# Legendre functions p(n,m\|c)
		750	[p,dp]= scipy.special.lpmn(maxcoef+1,maxcoef+1,c)
		751	p = p[:,:-1].transpose()
		752	s = numpy.sqrt((1. - c)*(1 + c))
		753
		754	# Generate derivative array dpdtheta = -s*dpdc
		755	dpdtheta = c*p/s
		756	for m in numpy.arange(maxcoef+2): dpdtheta[:,m] = m*dpdtheta[:,m]
		757	dpdtheta = dpdtheta + numpy.roll(p,-1,axis=1)
		758
		759	# Extracting arrays required for field calculations
		760	p = p[1:maxcoef+1,:maxcoef+1]
		761	dpdtheta = dpdtheta[1:maxcoef+1,:maxcoef+1]
		762
		763	# Weigh p and dpdtheta with gs and hs coefficients.
		764	gp = gs*p
		765	hp = hs*p
		766	gdpdtheta = gs*dpdtheta
		767	hdpdtheta = hs*dpdtheta
		768	# Calcultate field components
		769	matrix0 = numpy.dot(gdpdtheta,cosmphi)
		770	matrix1 = numpy.dot(hdpdtheta,sinmphi)
		771	bn[ii] = numpy.dot(rad,(matrix0 + matrix1))
		772	matrix0 = numpy.dot(hp,(mvec*cosmphi))
		773	matrix1 = numpy.dot(gp,(mvec*sinmphi))
		774	be[ii] = numpy.dot((-1*rad),((matrix0 - matrix1)/s))
		775	matrix0 = numpy.dot(gp,cosmphi)
		776	matrix1 = numpy.dot(hp,sinmphi)
		777	bd[ii] = numpy.dot((-1nvecrad),(matrix0 + matrix1))
		778
		779	bmod = numpy.sqrt(bn2. + be2. + bd**2.)
		780	btheta = numpy.arctan(bd/numpy.sqrt(be2. + bn2.))*180/numpy.pi
		781	balpha = numpy.arctan(be/bn)*180./numpy.pi
		782
		783	#bn : north
		784	#be : east
		785	#bn : radial
		786	#bmod : module
		787
		788
		789	return bn, be, bd, bmod, btheta, balpha
		790
		791	def str2num(self, datum):
		792	try:
		793	return int(datum)
		794	except:
		795	try:
		796	return float(datum)
		797	except:
		798	return datum
		799
		800	def __readIGRFfile(self, filename):
		801	list_years=[]
		802	for i in range(1,24):
		803	list_years.append(1895.0 + i*5)
		804
		805	epochs=list_years
		806	epochs.append(epochs[-1]+5)
		807	nepochs = numpy.shape(epochs)
		808
		809	gg = numpy.zeros((13,14,nepochs[0]),dtype=float)
		810	hh = numpy.zeros((13,14,nepochs[0]),dtype=float)
		811
		812	coeffs_file=open(filename)
		813	lines=coeffs_file.readlines()
		814
		815	coeffs_file.close()
		816
		817	for line in lines:
		818	items = line.split()
		819	g_h = items[0]
		820	n = self.str2num(items[1])
		821	m = self.str2num(items[2])
		822
		823	coeffs = items[3:]
		824
		825	for i in range(len(coeffs)-1):
		826	coeffs[i] = self.str2num(coeffs[i])
		827
		828	#coeffs = numpy.array(coeffs)
		829	ncoeffs = numpy.shape(coeffs)[0]
		830
		831	if g_h == 'g':
		832	# print n," g ",m
		833	gg[n-1,m,:]=coeffs
		834	elif g_h=='h':
		835	# print n," h ",m
		836	hh[n-1,m,:]=coeffs
		837	# else :
		838	# continue
		839
		840	# Ultimo Reordenamiento para almacenar .
		841	gg[:,:,nepochs[0]-1] = gg[:,:,nepochs[0]-2] + 5*gg[:,:,nepochs[0]-1]
		842	hh[:,:,nepochs[0]-1] = hh[:,:,nepochs[0]-2] + 5*hh[:,:,nepochs[0]-1]
		843
		844	# return numpy.array([gg,hh])
		845	periods = numpy.array(epochs)
		846	g = gg
		847	h = hh
		848	return periods, g, h
		849
		850
		851	def __readIGRFcoeff(self,filename="igrf10coeffs.dat"):
		852	"""
		853	__readIGRFcoeff reads the coefficients from a binary file which is located in the
		854	folder "resource."
		855
		856	Parameter
		857	---------
		858	filename = A string to specify the name of the file which contains thec coeffs. The
		859	default value is "igrf10coeffs.dat"
		860
		861	Return
		862	------
		863	periods = A lineal array giving...
		864	g1 =
		865	h1 =
		866
		867	Modification History
		868	--------------------
		869	Converted to Python by Freddy R. Galindo, ROJ, 03 October 2009.
		870	"""
		871
		872	# # igrfile = sys.path[-1] + os.sep + "resource" + os.sep + filename
		873	# igrfile = os.path.join('./resource',filename)
		874	# f = open(igrfile,'rb')
		875	# #f = open(os.getcwd() + os.sep + "resource" + os.sep + filename,'rb')
		876	#
		877	# # Reading SkyNoise Power (lineal scale)
		878	# periods = numpy.fromfile(f,numpy.dtype([('var','<f4')]),23)
		879	# periods = periods['var']
		880	#
		881	# g = numpy.fromfile(f,numpy.dtype([('var','<f8')]),231414)
		882	# g = g['var'].reshape((14,14,23)).transpose()
		883	#
		884	# h = numpy.fromfile(f,numpy.dtype([('var','<f8')]),231414)
		885	# h = h['var'].reshape((14,14,23)).transpose()
		886	#
		887	# f.close()
		888	base_path = os.path.dirname(os.path.abspath(__file__))
		889	filename = os.path.join(base_path,"resource","igrf11coeffs.txt")
		890
		891	period_v, g_v, h_v = self.__readIGRFfile(filename)
		892	g2 = numpy.zeros((14,14,24))
		893	h2 = numpy.zeros((14,14,24))
		894	g2[1:14,:,:] = g_v
		895	h2[1:14,:,:] = h_v
		896
		897	g = numpy.transpose(g2, (2,0,1))
		898	h = numpy.transpose(h2, (2,0,1))
		899	periods = period_v.copy()
		900
		901	return periods, g, h
		902
		903	def rotvector(self,vector,axis=1,ang=0):
		904	"""
		905	rotvector function returns the new vector generated rotating the rectagular coords.
		906
		907	Parameters
		908	----------
		909	vector = A lineal 3-elements array (x,y,z).
		910	axis = A integer to specify the axis used to rotate the coord systems. The default
		911	value is 1.
		912	axis = 1 -> Around "x"
		913	axis = 2 -> Around "y"
		914	axis = 3 -> Around "z"
		915	ang = Angle of rotation (in radians). The default value is zero.
		916
		917	Return
		918	------
		919	rotvector = A lineal array of 3 elements giving the new coordinates.
		920
		921	Modification History
		922	--------------------
		923	Converted to Python by Freddy R. Galindo, ROJ, 01 October 2009.
		924	"""
		925
		926	if axis==1:
		927	t = [[1,0,0],[0,numpy.cos(ang),numpy.sin(ang)],[0,-numpy.sin(ang),numpy.cos(ang)]]
		928	elif axis==2:
		929	t = [[numpy.cos(ang),0,-numpy.sin(ang)],[0,1,0],[numpy.sin(ang),0,numpy.cos(ang)]]
		930	elif axis==3:
		931	t = [[numpy.cos(ang),numpy.sin(ang),0],[-numpy.sin(ang),numpy.cos(ang),0],[0,0,1]]
		932
		933	rotvector = numpy.array(numpy.dot(numpy.array(t),numpy.array(vector)))
		934
		935	return rotvector
		936
		937
		938	class overJroShow:
		939
		940	# __serverdocspath = '/usr/local/www/htdocs'
		941	# __tmpDir = 'overJro/tempReports'
		942	# __serverdocspath = '/Users/dsuarez/Pictures'
		943	# __tmpDir = 'overjro'
		944	__serverdocspath = None
		945	__tmpDir = None
		946
		947	def __init__(self):
		948	self.year = None
		949	self.month = None
		950	self.dom = None
		951	self.pattern = None
		952	self.maxphi = None
		953	self.heights = None
		954	self.filename = None
		955	self.showType = None
		956	self.path = None
		957	self.objects = None
		958	self.nptsx = 101
		959	self.nptsy = 101
		960	self.fftopt = 0
		961	self.site = 1
		962	self.dcosx = 1
		963	self.dcosy = 1
		964	self.dcosxrange = None
		965	self.dcosyrange = None
		966	self.maxha_min= 0.
		967	self.show_object = None
		968	self.dcosx_mag = None
		969	self.dcosy_mag = None
		970	self.ha_mag = None
		971	self.time_mag = None
		972	self.main_dec = None
		973	self.ObjC = None
		974	self.ptitle = ''
		975	self.path4plotname = None
		976	self.plotname0 = None
		977	self.plotname1 = None
		978	self.plotname2 = None
		979	self.scriptHeaders = 0
		980	# self.outputHead('Show Plot')
		981	# self.printBody()
		982
		983	def setScriptState(self):
		984	self.madForm = cgi.FieldStorage()
		985
		986	if self.madForm.has_key('serverdocspath'):
		987	self.__serverdocspath = self.madForm.getvalue('serverdocspath')#'/usr/local/www/htdocs'
		988
		989	if self.madForm.has_key('tmpdir'):
		990	self.__tmpDir = self.madForm.getvalue('tmpdir')#'overJro/tempReports'
		991
		992	if self.madForm.has_key('showType'):
		993	self.showType = int(self.madForm.getvalue('showType'))
		994
		995	if self.showType == 0 or self.showType == 1:
		996
		997	# if self.madForm.has_key('year') and \
		998	# self.madForm.has_key('month') and \
		999	# self.madForm.has_key('dom') and \
		1000	# self.madForm.has_key('pattern') and \
		1001	# self.madForm.has_key('maxphi') and \
		1002	# self.madForm.has_key('objects') and \
		1003	# self.madForm.has_key('heights'):
		1004
		1005	if self.madForm.has_key('year') and \
		1006	self.madForm.has_key('month') and \
		1007	self.madForm.has_key('dom') and \
		1008	self.madForm.has_key('maxphi') and \
		1009	self.madForm.has_key('objects') and \
		1010	self.madForm.has_key('heights'):
		1011
		1012	self.year = int(self.madForm.getvalue('year'))
		1013	self.month = int(self.madForm.getvalue('month'))
		1014	self.dom = int(self.madForm.getvalue('dom'))
		1015	self.maxphi = float(self.madForm.getvalue('maxphi'))
		1016
		1017	if self.madForm.has_key('pattern'):
		1018
		1019	tmp_pattern = self.madForm.getvalue('pattern') #pattern es predifinido en listado o definido por el usuario
		1020	self.pattern=[]
		1021	if tmp_pattern[0] == '[':
		1022	tmp_pattern=tmp_pattern[1:]
		1023
		1024	if tmp_pattern[-1] == ']':
		1025	tmp_pattern=tmp_pattern[0:len(tmp_pattern)-1]
		1026
		1027	for s in tmp_pattern.split(','):
		1028	self.pattern.append(float(s))
		1029	elif self.madForm.has_key('filename'):
		1030	if self.madForm.has_key('filename'):
		1031	self.filename = self.madForm.getvalue('filename') # nombre de archivo: patron de radiacion definido por el usuario
		1032
		1033	if self.madForm.has_key('path'):
		1034	self.path = self.madForm.getvalue('path') #path donde se encuentra el archivo: patron de radiacion del usuario
		1035
		1036	else:
		1037	print "Content-Type: text/html\n"
		1038	print '<h3> This cgi plot script was called without the proper arguments.</h3>'
		1039	print '<p> This is a script used to plot Antenna Cuts over Jicamarca Antenna</p>'
		1040	print '<p> Required arguments:</p>'
		1041	print '<p> pattern - chekbox indicating objects over jicamarca antenna</p>'
		1042	print '<p> or'
		1043	print '<p> filename - The pattern defined by users is a file text'
		1044	print '<p> path - folder with pattern files'
		1045	sys.exit(0)
		1046
		1047
		1048	tmp_heights = self.madForm.getvalue('heights')
		1049	self.heights=[]
		1050	if tmp_heights[0] == '[':
		1051	tmp_heights=tmp_heights[1:]
		1052
		1053	if tmp_heights[-1] == ']':
		1054	tmp_heights=tmp_heights[0:len(tmp_heights)-1]
		1055
		1056	for s in tmp_heights.split(','):
		1057	self.heights.append(float(s))
		1058	self.heights = numpy.array(self.heights)
		1059
		1060	tmp_objects = self.madForm.getvalue('objects') #lista con los objetos a graficar en el patron de radiacion
		1061	self.objects=[]
		1062	if tmp_objects[0] == '[':
		1063	tmp_objects=tmp_objects[1:]
		1064
		1065	if tmp_objects[-1] == ']':
		1066	tmp_objects=tmp_objects[0:len(tmp_objects)-1]
		1067
		1068	for s in tmp_objects.split(','):
		1069	self.objects.append(int(s))
		1070
		1071	if self.showType == 1:
		1072	if numpy.sum(self.objects) == 0:
		1073	if self.scriptHeaders == 0:
		1074	print "Content-Type: text/html\n"
		1075	print '<h3> This cgi plot script was called without the proper arguments.</h3>'
		1076	print '<p> This is a script used to plot Antenna Cuts over Jicamarca Antenna</p>'
		1077	print '<p> Required arguments:</p>'
		1078	print '<p> objects - chekbox indicating objects over jicamarca antenna</p>'
		1079	print '<p> Please, options in "Select Object" must be checked'
		1080	sys.exit(0)
		1081
		1082	#considerar para futura implementacion
		1083	if self.madForm.has_key('filename'):
		1084	self.filename = self.madForm.getvalue('filename') # nombre de archivo: patron de radiacion definido por el usuario
		1085
		1086	if self.madForm.has_key('path'):
		1087	self.path = self.madForm.getvalue('path') #path donde se encuentra el archivo: patron de radiacion del usuario
		1088
		1089
		1090	else:
		1091	if self.scriptHeaders == 0:
		1092	print "Content-Type: text/html\n"
		1093
		1094	print '<h3> This cgi plot script was called without the proper arguments.</h3>'
		1095	print '<p> This is a script used to plot Pattern Field and Celestial Objects over Jicamarca Antenna</p>'
		1096	print '<p> Required arguments:</p>'
		1097	print '<p> year - year of event</p>'
		1098	print '<p> month - month of event</p>'
		1099	print '<p> dom - day of month</p>'
		1100	print '<p> pattern - pattern is defined by "Select an Experiment" list box</p>'
		1101	print '<p> maxphi - maxphi is defined by "Max Angle" text box</p>'
		1102	print '<p> objects - objects is a list defined by checkbox in "Select Object"</p>'
		1103	print '<p> heights - heights is defined by "Heights" text box, for default heights=[100,500,1000]</p>'
		1104	print '<p> showType - showType is a hidden element for show plot of Pattern&Object or Antenna Cuts or Sky Noise</p>'
		1105
		1106	sys.exit(0)
		1107
		1108	if self.showType == 2:
		1109	if self.madForm.has_key('year') and \
		1110	self.madForm.has_key('month') and \
		1111	self.madForm.has_key('dom'):
		1112
		1113	self.year = int(self.madForm.getvalue('year'))
		1114	self.month = int(self.madForm.getvalue('month'))
		1115	self.dom = int(self.madForm.getvalue('dom'))
		1116
		1117	else:
		1118	if self.scriptHeaders == 0:
		1119	print "Content-Type: text/html\n"
		1120	print '<h3> This cgi plot script was called without the proper arguments.</h3>'
		1121	print '<p> This is a script used to plot Sky Noise over Jicamarca Antenna</p>'
		1122	print '<p> Required arguments:</p>'
		1123	print '<p> year - year of event</p>'
		1124	print '<p> month - month of event</p>'
		1125	print '<p> dom - day of month</p>'
		1126
		1127	sys.exit(0)
		1128
		1129
		1130	def initParameters1(self):
		1131
		1132	gui=1
		1133	if self.pattern==None:
		1134	if gui==1: self.filename = self.filename.split(',')
		1135
		1136	pattern = numpy.atleast_1d(self.pattern)
		1137	filename = numpy.atleast_1d(self.filename)
		1138
		1139	npatterns = numpy.max(numpy.array([pattern.size,filename.size]))
		1140
		1141	self.pattern = numpy.resize(pattern,npatterns)
		1142	self.filename = numpy.resize(filename,npatterns)
		1143
		1144	self.doy = datetime.datetime(self.year,self.month,self.dom).timetuple().tm_yday
		1145
		1146
		1147	if self.objects==None:
		1148	self.objects=numpy.zeros(5)
		1149	else:
		1150	tmp = numpy.atleast_1d(self.objects)
		1151	self.objects = numpy.zeros(5)
		1152	self.objects[0:tmp.size] = tmp
		1153
		1154	self.show_object = self.objects
		1155
		1156	self.maxha_min = 4self.maxphinumpy.sqrt(2)*1.25
		1157
		1158
		1159	if self.heights==None:
		1160	self.heights = numpy.array([100.,500.,1000.])
		1161
		1162
		1163
		1164	#ROJ geographic coordinates and time zone
		1165	self.glat = -11.95
		1166	self.glon = -76.8667
		1167	self.UT = 5 #timezone
		1168
		1169	self.glat = -11.951481
		1170	self.glon = -76.874383
		1171
		1172
		1173	self.junkjd = TimeTools.Time(self.year,self.month,self.dom).change2julday()
		1174	self.junklst = TimeTools.Julian(self.junkjd).change2lst(longitude=self.glon)
		1175
		1176	# Finding RA of observatory for a specific date
		1177	self.ra_obs = self.junklst*Misc_Routines.CoFactors.h2d
		1178
		1179	def initParameters(self):
		1180
		1181	# Defining plot filenames
		1182	self.path4plotname = os.path.join(self.__serverdocspath,self.__tmpDir)
		1183	print "PATH4"
		1184	print os.path.join(self.__serverdocspath,self.__tmpDir)
		1185	self.plotname0 = 'over_jro_0_%i.png'% (time.time()) #plot pattern & objects
		1186	self.plotname1 = 'over_jro_1_%i.png'% (time.time()) #plot antenna cuts
		1187	self.plotname2 = 'over_jro_2_%i.png'% (time.time()) #plot sky noise
		1188
		1189	# Defining antenna axes respect to geographic coordinates (See Ochs report).
		1190	# alfa = 1.46*Misc_Routines.CoFactors.d2r
		1191	# theta = 51.01*Misc_Routines.CoFactors.d2r
		1192
		1193	alfa = 1.488312*Misc_Routines.CoFactors.d2r
		1194	th = 6.166710 + 45.0
		1195	theta = th*Misc_Routines.CoFactors.d2r
		1196
		1197	sina = numpy.sin(alfa)
		1198	cosa = numpy.cos(alfa)
		1199	MT1 = numpy.array([[1,0,0],[0,cosa,-sina],[0,sina,cosa]])
		1200	sinb = numpy.sin(theta)
		1201	cosb = numpy.cos(theta)
		1202	MT2 = numpy.array([[cosb,sinb,0],[-sinb,cosb,0],[0,0,1]])
		1203	self.MT3 = numpy.array(numpy.dot(MT2, MT1)).transpose()
		1204
		1205	self.xg = numpy.dot(self.MT3.transpose(),numpy.array([1,0,0]))
		1206	self.yg = numpy.dot(self.MT3.transpose(),numpy.array([0,1,0]))
		1207	self.zg = numpy.dot(self.MT3.transpose(),numpy.array([0,0,1]))
		1208
		1209	def plotPattern(self):
		1210	# Plotting Antenna patterns.
		1211	npatterns = numpy.size(self.pattern)
		1212
		1213	if npatterns==1:
		1214	if self.pattern[0] == None: npatterns = self.filename.__len__()
		1215
		1216	date = TimeTools.Time(self.year,self.month,self.dom).change2strdate(mode=2)
		1217
		1218	mesg = 'Over Jicamarca: ' + date[0]
		1219
		1220	title = ''
		1221
		1222	for ii in numpy.arange(npatterns):
		1223	ObjAnt = JroPattern(pattern=self.pattern[ii],
		1224	filename=self.filename[ii],
		1225	path=self.path,
		1226	nptsx=self.nptsx,
		1227	nptsy=self.nptsy,
		1228	maxphi=self.maxphi,
		1229	fftopt=self.fftopt)
		1230
		1231	title += ObjAnt.title
		1232	# Plotting Contour Map
		1233	print "Antes de la creacion"
		1234	self.path4plotname = '/home/fquino/workspace/radarsys/webapp/apps/abs/static/images'
		1235	print self.path4plotname
		1236	print self.plotname0
		1237	dum = Graphics_OverJro.AntPatternPlot()
		1238	dum.contPattern(iplot=ii,
		1239	gpath=self.path4plotname,
		1240	filename=self.plotname0,
		1241	mesg=mesg,
		1242	amp=ObjAnt.norpattern,
		1243	x=ObjAnt.dcosx,
		1244	y=ObjAnt.dcosy,
		1245	getCut=ObjAnt.getcut,
		1246	title=title)
		1247	# title=ObjAnt.title)
		1248	# self.ptitle = ObjAnt.title
		1249	if ii==0:
		1250	self.figure = dum.figure
		1251
		1252	if ii != (npatterns-1):
		1253	title += '+'
		1254
		1255
		1256	vect_ant = numpy.array([ObjAnt.meanpos[0],ObjAnt.meanpos[1],numpy.sqrt(1-numpy.sum(ObjAnt.meanpos**2.))])
		1257
		1258	vect_geo = numpy.dot(scipy.linalg.inv(self.MT3),vect_ant)
		1259
		1260	vect_polar = Misc_Routines.Vector(numpy.array(vect_geo),direction=1).Polar2Rect()
		1261
		1262	[ra,dec,ha] = Astro_Coords.AltAz(vect_polar[1],vect_polar[0],self.junkjd).change2equatorial()
		1263
		1264	print'Main beam position (HA(min), DEC(degrees)): %f %f'%(ha*4.,dec)
		1265
		1266	self.main_dec = dec
		1267
		1268	self.ptitle = title
		1269
		1270	Graphics_OverJro.AntPatternPlot().plotRaDec(gpath=self.path4plotname,filename=self.plotname0,jd=self.junkjd, ra_obs=self.ra_obs, xg=self.xg, yg=self.yg, x=ObjAnt.dcosx, y=ObjAnt.dcosy)
		1271
		1272	self.dcosx = ObjAnt.dcosx
		1273
		1274	self.dcosy = ObjAnt.dcosy
		1275
		1276	self.dcosxrange = [numpy.min(self.dcosx),numpy.max(self.dcosx)]
		1277
		1278	self.dcosyrange = [numpy.min(self.dcosy),numpy.max(self.dcosy)]
		1279
		1280	def plotBfield(self):
		1281
		1282	if self.show_object[0]>0:
		1283	# Getting B field
		1284	ObjB = BField(self.year,self.doy,self.site,self.heights)
		1285
		1286
		1287	[dcos, alpha, nlon, nlat] = ObjB.getBField()
		1288
		1289	# Plotting B field.
		1290	# print "Drawing magnetic field over Observatory"
		1291
		1292	Obj = Graphics_OverJro.BFieldPlot()
		1293
		1294	Obj.plotBField(self.path4plotname,self.plotname0,dcos,alpha,nlon,nlat,self.dcosxrange,self.dcosyrange,ObjB.heights,ObjB.alpha_i)
		1295
		1296	if self.show_object[0]>1:
		1297
		1298	Bhei = 0
		1299
		1300	dcosx = Obj.alpha_location[:,0,Bhei]
		1301
		1302	dcosy = Obj.alpha_location[:,1,Bhei]
		1303
		1304	vect_ant = [dcosx,dcosy,numpy.sqrt(1.-(dcosx2. + dcosy2.))]
		1305
		1306	vect_ant = numpy.array(vect_ant)
		1307
		1308	vect_geo = numpy.dot(scipy.linalg.inv(self.MT3),vect_ant)
		1309
		1310	vect_geo = numpy.array(vect_geo).transpose()
		1311
		1312	vect_polar = Misc_Routines.Vector(vect_geo,direction=1).Polar2Rect()
		1313
		1314	[ra,dec,ha] = Astro_Coords.AltAz(vect_polar[1,:],vect_polar[0,:],self.junkjd).change2equatorial()
		1315
		1316	val = numpy.where(ha>=180)
		1317
		1318	if val[0].size>0:ha[val] = ha[val] -360.
		1319
		1320	val = numpy.where(numpy.abs(ha)<=self.maxphi)
		1321
		1322	if val[0].size>2:
		1323
		1324	self.dcosx_mag = dcosx[val]
		1325
		1326	self.dcosy_mag = dcosy[val]
		1327
		1328	self.ha_mag = ha[val]
		1329
		1330	self.time_mag = 0
		1331
		1332	def plotCelestial(self):
		1333
		1334	ntod = 24.*16.
		1335
		1336	tod = numpy.arange(ntod)/ntod*24.
		1337
		1338	[month,dom] = TimeTools.Doy2Date(self.year,self.doy).change2date()
		1339
		1340	jd = TimeTools.Time(self.year,month,dom,tod+self.UT).change2julday()
		1341
		1342	if numpy.sum(self.show_object[1:]>0)!=0:
		1343
		1344	self.ObjC = Graphics_OverJro.CelestialObjectsPlot(jd,self.main_dec,tod,self.maxha_min,self.show_object)
		1345
		1346	self.ObjC.drawObject(self.glat,
		1347	self.glon,
		1348	self.xg,
		1349	self.yg,
		1350	self.dcosxrange,
		1351	self.dcosyrange,
		1352	self.path4plotname,
		1353	self.plotname0)
		1354
		1355	def plotAntennaCuts(self):
		1356	# print "Drawing antenna cuts"
		1357
		1358	incha = 0.05 # min
		1359	nha = numpy.int32(2*self.maxha_min/incha) + 1.
		1360	newha = numpy.arange(nha)/nha2.self.maxha_min - self.maxha_min
		1361	nha_star = numpy.int32(200./incha)
		1362	star_ha = (numpy.arange(nha_star) - (nha_star/2))*nha_star
		1363
		1364	#Init ObjCut for PatternCutPlot()
		1365	view_objects = numpy.where(self.show_object>0)
		1366	subplots = len(view_objects[0])
		1367	ObjCut = Graphics_OverJro.PatternCutPlot(subplots)
		1368
		1369	for io in (numpy.arange(5)):
		1370	if self.show_object[io]==2:
		1371	if io==0:
		1372	if self.dcosx_mag.size!=0:
		1373	dcosx = self.dcosx_mag
		1374	dcosy = self.dcosy_mag
		1375	dcosz = 1 - numpy.sqrt(dcosx2. + dcosy2.)
		1376
		1377	# Finding rotation of B respec to antenna coords.
		1378	[mm,bb] = scipy.polyfit(dcosx,dcosy,1)
		1379	alfa = 0.0
		1380	theta = -1.*numpy.arctan(mm)
		1381	sina = numpy.sin(alfa); cosa = numpy.cos(alfa)
		1382	MT1 = [[1,0,0],[0,cosa,-sina],[0,sina,cosa]]
		1383	MT1 = numpy.array(MT1)
		1384	sinb = numpy.sin(theta); cosb = numpy.cos(theta)
		1385	MT2 = [[cosb,sinb,0],[-sinb,cosb,0],[0,0,1]]
		1386	MT2 = numpy.array(MT2)
		1387	MT3_mag = numpy.dot(MT2, MT1)
		1388	MT3_mag = numpy.array(MT3_mag).transpose()
		1389	# Getting dcos respec to B coords
		1390	vector = numpy.array([dcosx,dcosy,dcosz])
		1391	nvector = numpy.dot(MT3_mag,vector)
		1392	nvector = numpy.array(nvector).transpose()
		1393
		1394	## print 'Rotation (deg) %f'%(theta/Misc_Routines.CoFactors.d2r)
		1395
		1396	yoffset = numpy.sum(nvector[:,1])/nvector[:,1].size
		1397	# print 'Dcosyoffset %f'%(yoffset)
		1398
		1399	ha = self.ha_mag*4.
		1400	time = self.time_mag
		1401	width_star = 0.1 # half width in minutes
		1402	otitle = 'B Perp. cut'
		1403	# else:
		1404	# print "No B perp. over Observatory"
		1405	#
		1406	#
		1407	elif io==1:
		1408	if self.ObjC.dcosx_sun.size!=0:
		1409	dcosx = self.ObjC.dcosx_sun
		1410	dcosy = self.ObjC.dcosy_sun
		1411	ha = self.ObjC.ha_sun*4.0
		1412	time = self.ObjC.time_sun
		1413	width_star = 2. # half width in minutes
		1414	otitle = 'Sun cut'
		1415	# else:
		1416	# print "Sun is not passing over Observatory"
		1417
		1418	elif io==2:
		1419	if self.ObjC.dcosx_moon.size!=0:
		1420	dcosx = self.ObjC.dcosx_moon
		1421	dcosy = self.ObjC.dcosy_moon
		1422	ha = self.ObjC.ha_moon*4
		1423	time = self.ObjC.time_moon
		1424	m_distance = 404114.6 # distance to the Earth in km
		1425	m_diameter = 1734.4 # diameter in km.
		1426	width_star = numpy.arctan(m_distance/m_diameter)
		1427	width_star = width_star/2./Misc_Routines.CoFactors.d2r*4.
		1428	otitle = 'Moon cut'
		1429	# else:
		1430	# print "Moon is not passing over Observatory"
		1431
		1432	elif io==3:
		1433	if self.ObjC.dcosx_hydra.size!=0:
		1434	dcosx = self.ObjC.dcosx_hydra
		1435	dcosy = self.ObjC.dcosy_hydra
		1436	ha = self.ObjC.ha_hydra*4.
		1437	time = self.ObjC.time_hydra
		1438	width_star = 0.25 # half width in minutes
		1439	otitle = 'Hydra cut'
		1440	# else:
		1441	# print "Hydra is not passing over Observatory"
		1442
		1443	elif io==4:
		1444	if self.ObjC.dcosx_galaxy.size!=0:
		1445	dcosx = self.ObjC.dcosx_galaxy
		1446	dcosy = self.ObjC.dcosy_galaxy
		1447	ha = self.ObjC.ha_galaxy*4.
		1448	time = self.ObjC.time_galaxy
		1449	width_star = 25. # half width in minutes
		1450	otitle = 'Galaxy cut'
		1451	# else:
		1452	# print "Galaxy center is not passing over Jicamarca"
		1453	#
		1454	#
		1455	hour = numpy.int32(time)
		1456	mins = numpy.int32((time - hour)*60.)
		1457	secs = numpy.int32(((time - hour)60. - mins)60.)
		1458
		1459	ObjT = TimeTools.Time(self.year,self.month,self.dom,hour,mins,secs)
		1460	subtitle = ObjT.change2strdate()
		1461
		1462	star_cut = numpy.exp(-(star_ha/width_star)**2./2.)
		1463
		1464	pol = scipy.polyfit(ha,dcosx,3.)
		1465	polx = numpy.poly1d(pol); newdcosx = polx(newha)
		1466	pol = scipy.polyfit(ha,dcosy,3.)
		1467	poly = numpy.poly1d(pol);newdcosy = poly(newha)
		1468
		1469	patterns = []
		1470	for icut in numpy.arange(self.pattern.size):
		1471	# Getting Antenna cut.
		1472	Obj = JroPattern(dcosx=newdcosx,
		1473	dcosy=newdcosy,
		1474	getcut=1,
		1475	pattern=self.pattern[icut],
		1476	path=self.path,
		1477	filename=self.filename[icut])
		1478
		1479	Obj.getPattern()
		1480
		1481	patterns.append(Obj.pattern)
		1482
		1483
		1484	ObjCut.drawCut(io,
		1485	patterns,
		1486	self.pattern.size,
		1487	newha,
		1488	otitle,
		1489	subtitle,
		1490	self.ptitle)
		1491
		1492	ObjCut.saveFig(self.path4plotname,self.plotname1)
		1493
		1494	def plotSkyNoise(self):
		1495	# print 'Creating SkyNoise map over Jicamarca'
		1496	dom = self.dom
		1497	month = self.month
		1498	year = self.year
		1499
		1500	julian = TimeTools.Time(year,month,dom).change2julday()
		1501
		1502	[powr,time, lst] = Astro_Coords.CelestialBodies().skyNoise(julian)
		1503
		1504	Graphics_OverJro.SkyNoisePlot([year,month,dom],powr,time,lst).getPlot(self.path4plotname,self.plotname2)
		1505
		1506
		1507	def outputHead(self,title):
		1508	print "Content-Type: text/html"
		1509	print
		1510	self.scriptHeaders = 1
		1511	print '<html>'
		1512	print '<head>'
		1513	print '\t<title>' + title + '</title>'
		1514	print '<style type="text/css">'
		1515	print 'body'
		1516	print '{'
		1517	print 'background-color:#ffffff;'
		1518	print '}'
		1519	print 'h1'
		1520	print '{'
		1521	print 'color:black;'
		1522	print 'font-size:18px;'
		1523	print 'text-align:center;'
		1524	print '}'
		1525	print 'p'
		1526	print '{'
		1527	print 'font-family:"Arial";'
		1528	print 'font-size:16px;'
		1529	print 'color:black;'
		1530	print '}'
		1531	print '</style>'
		1532	# self.printJavaScript()
		1533	print '</head>'
		1534
		1535	def printJavaScript(self):
		1536	print
		1537
		1538	def printBody(self):
		1539	print '<body>'
		1540	# print '<h1>Test Input Parms</h1>'
		1541	# for key in self.madForm.keys():
		1542	# #print '<p> name=' + str(key)
		1543	# if type(self.madForm.getvalue(key)) == types.ListType:
		1544	# for value in self.madForm.getvalue(key):
		1545	# print '<p> name=' + str(key) + \
		1546	# ' value=' + value + ''
		1547	# else:
		1548	# print '<p> name=' + str(key) + \
		1549	# ' value=' + str(cgi.escape(self.madForm.getvalue(key))) + ''
		1550
		1551	print '<form name="form1" method="post" target="showFrame">'
		1552	print ' <div align="center">'
		1553	print ' <table width=98% border="1" cellpadding="1">'
		1554	print ' <tr>'
		1555	print ' <td colspan="2" align="center">'
		1556	if self.showType == 0:
		1557	print ' <IMG SRC="%s" BORDER="0" >'%(os.path.join(os.sep + self.__tmpDir,self.plotname0))
		1558	if self.showType == 1:
		1559	print ' <IMG SRC="%s" BORDER="0" >'%(os.path.join(os.sep + self.__tmpDir,self.plotname1))
		1560	if self.showType == 2:
		1561	print ' <IMG SRC="%s" BORDER="0" >'%(os.path.join(os.sep + self.__tmpDir,self.plotname2))
		1562	print ' </td>'
		1563	print ' </tr>'
		1564	print ' </table>'
		1565	print ' </div>'
		1566	print '</form>'
		1567
		1568	print '</body>'
		1569	print '</html>'
		1570
		1571	#def execute(self, serverdocspath, tmpdir, currentdate, finalpath, showType=0, maxphi=5.0, objects="[1,1]", heights="[150,500,1000]"):
		1572	def setInputParameters(self, serverpath, currentdate, finalpath, showType=0, maxphi=5.0, objects="[1,1]", heights="[150,500,1000]"):
		1573	self.objects=[]
		1574	self.heights=[]
		1575	#self.__serverdocspath = serverdocspath
		1576	self.__serverdocspath = os.path.split(serverpath)[0]
		1577	#self.__tmpDir = tmpdir
		1578	self.__tmpDir = os.path.split(serverpath)[1]
		1579	self.showType = int(showType)
		1580	self.year = int(currentdate.strftime("%Y")) # Get year of currentdate
		1581	self.month = int(currentdate.strftime("%m")) # Get month of currentdate
		1582	self.dom = int(currentdate.strftime("%d")) # Get day of currentdate
		1583	self.filename = os.path.split(finalpath)[1]
		1584	self.path = os.path.split(finalpath)[0]
		1585	self.maxphi = float(maxphi)
		1586
		1587	tmp_objects = (objects.replace("[","")).replace("]","")
		1588	for s in tmp_objects.split(','):
		1589	self.objects.append(int(s))
		1590
		1591	tmp_heights = (heights.replace("[","")).replace("]","")
		1592	for s in tmp_heights.split(','):
		1593	self.heights.append(float(s))
		1594	self.heights = numpy.array(self.heights)
		1595
		1596	def setupParameters(self):
		1597	self.initParameters()
		1598
		1599	def initParametersCGI(self):
		1600	self.setScriptState()
		1601	self.initParameters()
		1602
		1603	def execute(self):
		1604	if self.showType == 0 or self.showType == 1:
		1605	self.initParameters1()
		1606	self.plotPattern()
		1607
		1608	if numpy.sum(self.show_object>0) != 0:
		1609	self.plotBfield()
		1610	self.plotCelestial()
		1611
		1612	if numpy.sum(self.show_object>1) != 0:
		1613	self.plotAntennaCuts()
		1614
		1615	if self.showType == 2:
		1616	self.plotSkyNoise()
		1617
		1618	def getPlot(self):
		1619	print "GETPLot"
		1620	print os.path.join(self.__serverdocspath,self.__tmpDir,self.plotname0)
		1621	return os.path.join(self.__serverdocspath,self.__tmpDir,self.plotname0)
		1622
		1623
		1624	if __name__ == '__main__':
		1625
		1626	# Script overJroShow.py
		1627	# This script only calls the init function of the class overJroShow()
		1628	# All work is done by the init function
		1629
		1630	newOverJro = overJroShow()
		1631	newOverJro.initParametersCGI()
		1632	newOverJro.execute()

apps/abs/utils/resource/attenuation.txt created 644 +17 0

@@ -0,0 +1,17
	1	attenuation = numpy.array([[[-21.25,-15.25,-9.25,-3.25,03.25,09.25,15.25,21.25],
	2	[-21.25,-15.25,-9.25,-3.25,03.25,09.25,15.25,21.25],
	3	[-21.25,-15.25,-9.25,-3.25,03.25,09.25,15.25,21.25],
	4	[-21.25,-15.25,-9.25,-3.25,03.25,09.25,15.25,21.25],
	5	[-21.25,-15.25,-9.25,-3.25,03.25,09.25,15.25,21.25],
	6	[-21.25,-15.25,-9.25,-3.25,03.25,09.25,15.25,21.25],
	7	[-21.25,-15.25,-9.25,-3.25,03.25,09.25,15.25,21.25],
	8	[-21.25,-15.25,-9.25,-3.25,03.25,09.25,15.25,21.25]],
	9	[[21.25,21.25,21.25,21.25,21.25,21.25,21.25,21.25],
	10	[15.25,15.25,15.25,15.25,15.25,15.25,15.25,15.25],
	11	[09.25,09.25,09.25,09.25,09.25,09.25,09.25,09.25],
	12	[03.25,03.25,03.25,03.25,03.25,03.25,03.25,03.25],
	13	[-03.25,-03.25,-03.25,-03.25,-03.25,-03.25,-03.25,-03.25],
	14	[-09.25,-09.25,-09.25,-09.25,-09.25,-09.25,-09.25,-09.25],
	15	[-15.25,-15.25,-15.25,-15.25,-15.25,-15.25,-15.25,-15.25],
	16	[-21.25,-21.25,-21.25,-21.25,-21.25,-21.25,-21.25,-21.25]]])
	17

apps/abs/utils/resource/galaxy.txt created 644 +99 0

@@ -0,0 +1,99
	1	0000 13.00
	2	0015 13.00
	3	0030 13.00
	4	0045 13.00
	5	0060 13.00
	6	0075 12.50
	7	0090 12.50
	8	0105 12.50
	9	0120 11.50
	10	0135 11.00
	11	0150 10.50
	12	0165 10.00
	13	0180 10.00
	14	0195 10.00
	15	0210 9.00
	16	0225 8.50
	17	0240 8.50
	18	0255 8.50
	19	0270 8.50
	20	0285 8.00
	21	0300 8.00
	22	0315 8.50
	23	0330 9.00
	24	0345 10.00
	25	0360 11.00
	26	0375 12.50
	27	0390 14.50
	28	0405 17.00
	29	0420 18.00
	30	0435 17.00
	31	0450 15.50
	32	0465 15.00
	33	0480 14.00
	34	0495 12.50
	35	0510 11.00
	36	0525 10.00
	37	0540 9.50
	38	0555 9.00
	39	0570 23.00
	40	0585 8.00
	41	0600 10.00
	42	0615 10.50
	43	0630 10.00
	44	0645 9.00
	45	0660 8.50
	46	0675 9.00
	47	0690 10.00
	48	0705 11.00
	49	0720 12.00
	50	0735 12.50
	51	0750 13.50
	52	0765 13.00
	53	0780 13.00
	54	0795 13.00
	55	0810 13.00
	56	0825 12.50
	57	0840 12.00
	58	0855 12.50
	59	0870 13.00
	60	0885 14.00
	61	0900 15.00
	62	0915 17.00
	63	0930 18.00
	64	0945 17.50
	65	0960 16.50
	66	0975 16.50
	67	0990 17.00
	68	0990 17.00
	69	1005 17.00
	70	1020 20.00
	71	1035 26.00
	72	1050 30.00
	73	1065 36.00
	74	1080 47.00
	75	1095 71.00
	76	1102 60.00
	77	1110 77.00
	78	1115 87.00
	79	1120 83.00
	80	1130 60.00
	81	1140 50.00
	82	1155 35.00
	83	1170 28.00
	84	1185 21.00
	85	1200 18.00
	86	1215 16.00
	87	1237 15.50
	88	1260 15.00
	89	1275 15.50
	90	1290 16.00
	91	1305 15.50
	92	1320 15.00
	93	1335 14.50
	94	1350 14.00
	95	1365 13.00
	96	1380 12.00
	97	1395 12.50
	98	1410 13.00
	99	1425 12.50

apps/abs/utils/resource/igrf10coeffs.dat created 644 binary 0 0

NO CONTENT: new file 100644, binary diff hidden

apps/abs/utils/resource/igrf10coeffs.txt created 644 +196 0

@@ -0,0 +1,196
	1	g/h n m 1900.0 1905.0 1910.0 1915.0 1920.0 1925.0 1930.0 1935.0 1940.0 1945.0 1950.0 1955.0 1960.0 1965.0 1970.0 1975.0 1980.0 1985.0 1990.0 1995.0 2000.0 2005.0 SV
	2	g 1 0 -31543 -31464 -31354 -31212 -31060 -30926 -30805 -30715 -30654 -30594 -30554 -30500 -30421 -30334 -30220 -30100 -29992 -29873 -29775 -29692 -29619.4 -29556.8 8.8
	3	g 1 1 -2298 -2298 -2297 -2306 -2317 -2318 -2316 -2306 -2292 -2285 -2250 -2215 -2169 -2119 -2068 -2013 -1956 -1905 -1848 -1784 -1728.2 -1671.8 10.8
	4	h 1 1 5922 5909 5898 5875 5845 5817 5808 5812 5821 5810 5815 5820 5791 5776 5737 5675 5604 5500 5406 5306 5186.1 5080.0 -21.3
	5	g 2 0 -677 -728 -769 -802 -839 -893 -951 -1018 -1106 -1244 -1341 -1440 -1555 -1662 -1781 -1902 -1997 -2072 -2131 -2200 -2267.7 -2340.5 -15.0
	6	g 2 1 2905 2928 2948 2956 2959 2969 2980 2984 2981 2990 2998 3003 3002 2997 3000 3010 3027 3044 3059 3070 3068.4 3047.0 -6.9
	7	h 2 1 -1061 -1086 -1128 -1191 -1259 -1334 -1424 -1520 -1614 -1702 -1810 -1898 -1967 -2016 -2047 -2067 -2129 -2197 -2279 -2366 -2481.6 -2594.9 -23.3
	8	g 2 2 924 1041 1176 1309 1407 1471 1517 1550 1566 1578 1576 1581 1590 1594 1611 1632 1663 1687 1686 1681 1670.9 1656.9 -1.0
	9	h 2 2 1121 1065 1000 917 823 728 644 586 528 477 381 291 206 114 25 -68 -200 -306 -373 -413 -458.0 -516.7 -14.0
	10	g 3 0 1022 1037 1058 1084 1111 1140 1172 1206 1240 1282 1297 1302 1302 1297 1287 1276 1281 1296 1314 1335 1339.6 1335.7 -0.3
	11	g 3 1 -1469 -1494 -1524 -1559 -1600 -1645 -1692 -1740 -1790 -1834 -1889 -1944 -1992 -2038 -2091 -2144 -2180 -2208 -2239 -2267 -2288.0 -2305.3 -3.1
	12	h 3 1 -330 -357 -389 -421 -445 -462 -480 -494 -499 -499 -476 -462 -414 -404 -366 -333 -336 -310 -284 -262 -227.6 -200.4 5.4
	13	g 3 2 1256 1239 1223 1212 1205 1202 1205 1215 1232 1255 1274 1288 1289 1292 1278 1260 1251 1247 1248 1249 1252.1 1246.8 -0.9
	14	h 3 2 3 34 62 84 103 119 133 146 163 186 206 216 224 240 251 262 271 284 293 302 293.4 269.3 -6.5
	15	g 3 3 572 635 705 778 839 881 907 918 916 913 896 882 878 856 838 830 833 829 802 759 714.5 674.4 -6.8
	16	h 3 3 523 480 425 360 293 229 166 101 43 -11 -46 -83 -130 -165 -196 -223 -252 -297 -352 -427 -491.1 -524.5 -2.0
	17	g 4 0 876 880 884 887 889 891 896 903 914 944 954 958 957 957 952 946 938 936 939 940 932.3 919.8 -2.5
	18	g 4 1 628 643 660 678 695 711 727 744 762 776 792 796 800 804 800 791 782 780 780 780 786.8 798.2 2.8
	19	h 4 1 195 203 211 218 220 216 205 188 169 144 136 133 135 148 167 191 212 232 247 262 272.6 281.4 2.0
	20	g 4 2 660 653 644 631 616 601 584 565 550 544 528 510 504 479 461 438 398 361 325 290 250.0 211.5 -7.1
	21	h 4 2 -69 -77 -90 -109 -134 -163 -195 -226 -252 -276 -278 -274 -278 -269 -266 -265 -257 -249 -240 -236 -231.9 -225.8 1.8
	22	g 4 3 -361 -380 -400 -416 -424 -426 -422 -415 -405 -421 -408 -397 -394 -390 -395 -405 -419 -424 -423 -418 -403.0 -379.5 5.9
	23	h 4 3 -210 -201 -189 -173 -153 -130 -109 -90 -72 -55 -37 -23 3 13 26 39 53 69 84 97 119.8 145.7 5.6
	24	g 4 4 134 146 160 178 199 217 234 249 265 304 303 290 269 252 234 216 199 170 141 122 111.3 100.2 -3.2
	25	h 4 4 -75 -65 -55 -51 -57 -70 -90 -114 -141 -178 -210 -230 -255 -269 -279 -288 -297 -297 -299 -306 -303.8 -304.7 0.0
	26	g 5 0 -184 -192 -201 -211 -221 -230 -237 -241 -241 -253 -240 -229 -222 -219 -216 -218 -218 -214 -214 -214 -218.8 -227.6 -2.6
	27	g 5 1 328 328 327 327 326 326 327 329 334 346 349 360 362 358 359 356 357 355 353 352 351.4 354.4 0.4
	28	h 5 1 -210 -193 -172 -148 -122 -96 -72 -51 -33 -12 3 15 16 19 26 31 46 47 46 46 43.8 42.7 0.1
	29	g 5 2 264 259 253 245 236 226 218 211 208 194 211 230 242 254 262 264 261 253 245 235 222.3 208.8 -3.0
	30	h 5 2 53 56 57 58 58 58 60 64 71 95 103 110 125 128 139 148 150 150 154 165 171.9 179.8 1.8
	31	g 5 3 5 -1 -9 -16 -23 -28 -32 -33 -33 -20 -20 -23 -26 -31 -42 -59 -74 -93 -109 -118 -130.4 -136.6 -1.2
	32	h 5 3 -33 -32 -33 -34 -38 -44 -53 -64 -75 -67 -87 -98 -117 -126 -139 -152 -151 -154 -153 -143 -133.1 -123.0 2.0
	33	g 5 4 -86 -93 -102 -111 -119 -125 -131 -136 -141 -142 -147 -152 -156 -157 -160 -159 -162 -164 -165 -166 -168.6 -168.3 0.2
	34	h 5 4 -124 -125 -126 -126 -125 -122 -118 -115 -113 -119 -122 -121 -114 -97 -91 -83 -78 -75 -69 -55 -39.3 -19.5 4.5
	35	g 5 5 -16 -26 -38 -51 -62 -69 -74 -76 -76 -82 -76 -69 -63 -62 -56 -49 -48 -46 -36 -17 -12.9 -14.1 -0.6
	36	h 5 5 3 11 21 32 43 51 58 64 69 82 80 78 81 81 83 88 92 95 97 107 106.3 103.6 -1.0
	37	g 6 0 63 62 62 61 61 61 60 59 57 59 54 47 46 45 43 45 48 53 61 68 72.3 72.9 -0.8
	38	g 6 1 61 60 58 57 55 54 53 53 54 57 57 57 58 61 64 66 66 65 65 67 68.2 69.6 0.2
	39	h 6 1 -9 -7 -5 -2 0 3 4 4 4 6 -1 -9 -10 -11 -12 -13 -15 -16 -16 -17 -17.4 -20.2 -0.4
	40	g 6 2 -11 -11 -11 -10 -10 -9 -9 -8 -7 6 4 3 1 8 15 28 42 51 59 68 74.2 76.6 -0.2
	41	h 6 2 83 86 89 93 96 99 102 104 105 100 99 96 99 100 100 99 93 88 82 72 63.7 54.7 -1.9
	42	g 6 3 -217 -221 -224 -228 -233 -238 -242 -246 -249 -246 -247 -247 -237 -228 -212 -198 -192 -185 -178 -170 -160.9 -151.1 2.1
	43	h 6 3 2 4 5 8 11 14 19 25 33 16 33 48 60 68 72 75 71 69 69 67 65.1 63.7 -0.4
	44	g 6 4 -58 -57 -54 -51 -46 -40 -32 -25 -18 -25 -16 -8 -1 4 2 1 4 4 3 -1 -5.9 -15.0 -2.1
	45	h 6 4 -35 -32 -29 -26 -22 -18 -16 -15 -15 -9 -12 -16 -20 -32 -37 -41 -43 -48 -52 -58 -61.2 -63.4 -0.4
	46	g 6 5 59 57 54 49 44 39 32 25 18 21 12 7 -2 1 3 6 14 16 18 19 16.9 14.7 -0.4
	47	h 6 5 36 32 28 23 18 13 8 4 0 -16 -12 -12 -11 -8 -6 -4 -2 -1 1 1 0.7 0.0 -0.2
	48	g 6 6 -90 -92 -95 -98 -101 -103 -104 -106 -107 -104 -105 -107 -113 -111 -112 -111 -108 -102 -96 -93 -90.4 -86.4 1.3
	49	h 6 6 -69 -67 -65 -62 -57 -52 -46 -40 -33 -39 -30 -24 -17 -7 1 11 17 21 24 36 43.8 50.3 0.9
	50	g 7 0 70 70 71 72 73 73 74 74 74 70 65 65 67 75 72 71 72 74 77 77 79.0 79.8 -0.4
	51	g 7 1 -55 -54 -54 -54 -54 -54 -54 -53 -53 -40 -55 -56 -56 -57 -57 -56 -59 -62 -64 -72 -74.0 -74.4 0.0
	52	h 7 1 -45 -46 -47 -48 -49 -50 -51 -52 -52 -45 -35 -50 -55 -61 -70 -77 -82 -83 -80 -69 -64.6 -61.4 0.8
	53	g 7 2 0 0 1 2 2 3 4 4 4 0 2 2 5 4 1 1 2 3 2 1 0.0 -1.4 -0.2
	54	h 7 2 -13 -14 -14 -14 -14 -14 -15 -17 -18 -18 -17 -24 -28 -27 -27 -26 -27 -27 -26 -25 -24.2 -22.5 0.4
	55	g 7 3 34 33 32 31 29 27 25 23 20 0 1 10 15 13 14 16 21 24 26 28 33.3 38.6 1.1
	56	h 7 3 -10 -11 -12 -12 -13 -14 -14 -14 -14 2 0 -4 -6 -2 -4 -5 -5 -2 0 4 6.2 6.9 0.1
	57	g 7 4 -41 -41 -40 -38 -37 -35 -34 -33 -31 -29 -40 -32 -32 -26 -22 -14 -12 -6 -1 5 9.1 12.3 0.6
	58	h 7 4 -1 0 1 2 4 5 6 7 7 6 10 8 7 6 8 10 16 20 21 24 24.0 25.4 0.2
	59	g 7 5 -21 -20 -19 -18 -16 -14 -12 -11 -9 -10 -7 -11 -7 -6 -2 0 1 4 5 4 6.9 9.4 0.4
	60	h 7 5 28 28 28 28 28 29 29 29 29 28 36 28 23 26 23 22 18 17 17 17 14.8 10.9 -0.9
	61	g 7 6 18 18 18 19 19 19 18 18 17 15 5 9 17 13 13 12 11 10 9 8 7.3 5.5 -0.5
	62	h 7 6 -12 -12 -13 -15 -16 -17 -18 -19 -20 -17 -18 -20 -18 -23 -23 -23 -23 -23 -23 -24 -25.4 -26.4 -0.3
	63	g 7 7 6 6 6 6 6 6 6 6 5 29 19 18 8 1 -2 -5 -2 0 0 -2 -1.2 2.0 0.9
	64	h 7 7 -22 -22 -22 -22 -22 -21 -20 -19 -19 -22 -16 -18 -17 -12 -11 -12 -10 -7 -4 -6 -5.8 -4.8 0.3
	65	g 8 0 11 11 11 11 11 11 11 11 11 13 22 11 15 13 14 14 18 21 23 25 24.4 24.8 -0.2
	66	g 8 1 8 8 8 8 7 7 7 7 7 7 15 9 6 5 6 6 6 6 5 6 6.6 7.7 0.2
	67	h 8 1 8 8 8 8 8 8 8 8 8 12 5 10 11 7 7 6 7 8 10 11 11.9 11.2 -0.2
	68	g 8 2 -4 -4 -4 -4 -3 -3 -3 -3 -3 -8 -4 -6 -4 -4 -2 -1 0 0 -1 -6 -9.2 -11.4 -0.2
	69	h 8 2 -14 -15 -15 -15 -15 -15 -15 -15 -14 -21 -22 -15 -14 -12 -15 -16 -18 -19 -19 -21 -21.5 -21.0 0.2
	70	g 8 3 -9 -9 -9 -9 -9 -9 -9 -9 -10 -5 -1 -14 -11 -14 -13 -12 -11 -11 -10 -9 -7.9 -6.8 0.2
	71	h 8 3 7 7 6 6 6 6 5 5 5 -12 0 5 7 9 6 4 4 5 6 8 8.5 9.7 0.2
	72	g 8 4 1 1 1 2 2 2 2 1 1 9 11 6 2 0 -3 -8 -7 -9 -12 -14 -16.6 -18.0 -0.2
	73	h 8 4 -13 -13 -13 -13 -14 -14 -14 -15 -15 -7 -21 -23 -18 -16 -17 -19 -22 -23 -22 -23 -21.5 -19.8 0.4
	74	g 8 5 2 2 2 3 4 4 5 6 6 7 15 10 10 8 5 4 4 4 3 9 9.1 10.0 0.2
	75	h 8 5 5 5 5 5 5 5 5 5 5 2 -8 3 4 4 6 6 9 11 12 15 15.5 16.1 0.2
	76	g 8 6 -9 -8 -8 -8 -7 -7 -6 -6 -5 -10 -13 -7 -5 -1 0 0 3 4 4 6 7.0 9.4 0.5
	77	h 8 6 16 16 16 16 17 17 18 18 19 18 17 23 23 24 21 18 16 14 12 11 8.9 7.7 -0.3
	78	g 8 7 5 5 5 6 6 7 8 8 9 7 5 6 10 11 11 10 6 4 2 -5 -7.9 -11.4 -0.7
	79	h 8 7 -5 -5 -5 -5 -5 -5 -5 -5 -5 3 -4 -4 1 -3 -6 -10 -13 -15 -16 -16 -14.9 -12.8 0.5
	80	g 8 8 8 8 8 8 8 8 8 7 7 2 -1 9 8 4 3 1 -1 -4 -6 -7 -7.0 -5.0 0.5
	81	h 8 8 -18 -18 -18 -18 -19 -19 -19 -19 -19 -11 -17 -13 -20 -17 -16 -17 -15 -11 -10 -4 -2.1 -0.1 0.4
	82	g 9 0 8 8 8 8 8 8 8 8 8 5 3 4 4 8 8 7 5 5 4 4 5.0 5.6
	83	g 9 1 10 10 10 10 10 10 10 10 10 -21 -7 9 6 10 10 10 10 10 9 9 9.4 9.8
	84	h 9 1 -20 -20 -20 -20 -20 -20 -20 -20 -21 -27 -24 -11 -18 -22 -21 -21 -21 -21 -20 -20 -19.7 -20.1
	85	g 9 2 1 1 1 1 1 1 1 1 1 1 -1 -4 0 2 2 2 1 1 1 3 3.0 3.6
	86	h 9 2 14 14 14 14 14 14 14 15 15 17 19 12 12 15 16 16 16 15 15 15 13.4 12.9
	87	g 9 3 -11 -11 -11 -11 -11 -11 -12 -12 -12 -11 -25 -5 -9 -13 -12 -12 -12 -12 -12 -10 -8.4 -7.0
	88	h 9 3 5 5 5 5 5 5 5 5 5 29 12 7 2 7 6 7 9 9 11 12 12.5 12.7
	89	g 9 4 12 12 12 12 12 12 12 11 11 3 10 2 1 10 10 10 9 9 9 8 6.3 5.0
	90	h 9 4 -3 -3 -3 -3 -3 -3 -3 -3 -3 -9 2 6 0 -4 -4 -4 -5 -6 -7 -6 -6.2 -6.7
	91	g 9 5 1 1 1 1 1 1 1 1 1 16 5 4 4 -1 -1 -1 -3 -3 -4 -8 -8.9 -10.8
	92	h 9 5 -2 -2 -2 -2 -2 -2 -2 -3 -3 4 2 -2 -3 -5 -5 -5 -6 -6 -7 -8 -8.4 -8.1
	93	g 9 6 -2 -2 -2 -2 -2 -2 -2 -2 -2 -3 -5 1 -1 -1 0 -1 -1 -1 -2 -1 -1.5 -1.3
	94	h 9 6 8 8 8 8 9 9 9 9 9 9 8 10 9 10 10 10 9 9 9 8 8.4 8.1
	95	g 9 7 2 2 2 2 2 2 3 3 3 -4 -2 2 -2 5 3 4 7 7 7 10 9.3 8.7
	96	h 9 7 10 10 10 10 10 10 10 11 11 6 8 7 8 10 11 11 10 9 8 5 3.8 2.9
	97	g 9 8 -1 0 0 0 0 0 0 0 1 -3 3 2 3 1 1 1 2 1 1 -2 -4.3 -6.7
	98	h 9 8 -2 -2 -2 -2 -2 -2 -2 -2 -2 1 -11 -6 0 -4 -2 -3 -6 -7 -7 -8 -8.2 -7.9
	99	g 9 9 -1 -1 -1 -1 -1 -1 -2 -2 -2 -4 8 5 -1 -2 -1 -2 -5 -5 -6 -8 -8.2 -9.2
	100	h 9 9 2 2 2 2 2 2 2 2 2 8 -7 5 5 1 1 1 2 2 2 3 4.8 5.9
	101	g 10 0 -3 -3 -3 -3 -3 -3 -3 -3 -3 -3 -8 -3 1 -2 -3 -3 -4 -4 -3 -3 -2.6 -2.2
	102	g 10 1 -4 -4 -4 -4 -4 -4 -4 -4 -4 11 4 -5 -3 -3 -3 -3 -4 -4 -4 -6 -6.0 -6.3
	103	h 10 1 2 2 2 2 2 2 2 2 2 5 13 -4 4 2 1 1 1 1 2 1 1.7 2.4
	104	g 10 2 2 2 2 2 2 2 2 2 2 1 -1 -1 4 2 2 2 2 3 2 2 1.7 1.6
	105	h 10 2 1 1 1 1 1 1 1 1 1 1 -2 0 1 1 1 1 0 0 1 0 0.0 0.2
	106	g 10 3 -5 -5 -5 -5 -5 -5 -5 -5 -5 2 13 2 0 -5 -5 -5 -5 -5 -5 -4 -3.1 -2.5
	107	h 10 3 2 2 2 2 2 2 2 2 2 -20 -10 -8 0 2 3 3 3 3 3 4 4.0 4.4
	108	g 10 4 -2 -2 -2 -2 -2 -2 -2 -2 -2 -5 -4 -3 -1 -2 -1 -2 -2 -2 -2 -1 -0.5 -0.1
	109	h 10 4 6 6 6 6 6 6 6 6 6 -1 2 -2 2 6 4 4 6 6 6 5 4.9 4.7
	110	g 10 5 6 6 6 6 6 6 6 6 6 -1 4 7 4 4 6 5 5 5 4 4 3.7 3.0
	111	h 10 5 -4 -4 -4 -4 -4 -4 -4 -4 -4 -6 -3 -4 -5 -4 -4 -4 -4 -4 -4 -5 -5.9 -6.5
	112	g 10 6 4 4 4 4 4 4 4 4 4 8 12 4 6 4 4 4 3 3 3 2 1.0 0.3
	113	h 10 6 0 0 0 0 0 0 0 0 0 6 6 1 1 0 0 -1 0 0 0 -1 -1.2 -1.0
	114	g 10 7 0 0 0 0 0 0 0 0 0 -1 3 -2 1 0 1 1 1 1 1 2 2.0 2.1
	115	h 10 7 -2 -2 -2 -2 -2 -2 -2 -1 -1 -4 -3 -3 -1 -2 -1 -1 -1 -1 -2 -2 -2.9 -3.4
	116	g 10 8 2 2 2 1 1 1 1 2 2 -3 2 6 -1 2 0 0 2 2 3 5 4.2 3.9
	117	h 10 8 4 4 4 4 4 4 4 4 4 -2 6 7 6 3 3 3 4 4 3 1 0.2 -0.9
	118	g 10 9 2 2 2 2 3 3 3 3 3 5 10 -2 2 2 3 3 3 3 3 1 0.3 -0.1
	119	h 10 9 0 0 0 0 0 0 0 0 0 0 11 -1 0 0 1 1 0 0 -1 -2 -2.2 -2.3
	120	g 10 10 0 0 0 0 0 0 0 0 0 -2 3 0 0 0 -1 -1 0 0 0 0 -1.1 -2.2
	121	h 10 10 -6 -6 -6 -6 -6 -6 -6 -6 -6 -2 8 -3 -7 -6 -4 -5 -6 -6 -6 -7 -7.4 -8.0
	122	g 11 0 2.7 2.9
	123	g 11 1 -1.7 -1.6
	124	h 11 1 0.1 0.3
	125	g 11 2 -1.9 -1.7
	126	h 11 2 1.3 1.4
	127	g 11 3 1.5 1.5
	128	h 11 3 -0.9 -0.7
	129	g 11 4 -0.1 -0.2
	130	h 11 4 -2.6 -2.4
	131	g 11 5 0.1 0.2
	132	h 11 5 0.9 0.9
	133	g 11 6 -0.7 -0.7
	134	h 11 6 -0.7 -0.6
	135	g 11 7 0.7 0.5
	136	h 11 7 -2.8 -2.7
	137	g 11 8 1.7 1.8
	138	h 11 8 -0.9 -1.0
	139	g 11 9 0.1 0.1
	140	h 11 9 -1.2 -1.5
	141	g 11 10 1.2 1.0
	142	h 11 10 -1.9 -2.0
	143	g 11 11 4.0 4.1
	144	h 11 11 -0.9 -1.4
	145	g 12 0 -2.2 -2.2
	146	g 12 1 -0.3 -0.3
	147	h 12 1 -0.4 -0.5
	148	g 12 2 0.2 0.3
	149	h 12 2 0.3 0.3
	150	g 12 3 0.9 0.9
	151	h 12 3 2.5 2.3
	152	g 12 4 -0.2 -0.4
	153	h 12 4 -2.6 -2.7
	154	g 12 5 0.9 1.0
	155	h 12 5 0.7 0.6
	156	g 12 6 -0.5 -0.4
	157	h 12 6 0.3 0.4
	158	g 12 7 0.3 0.5
	159	h 12 7 0.0 0.0
	160	g 12 8 -0.3 -0.3
	161	h 12 8 0.0 0.0
	162	g 12 9 -0.4 -0.4
	163	h 12 9 0.3 0.3
	164	g 12 10 -0.1 0.0
	165	h 12 10 -0.9 -0.8
	166	g 12 11 -0.2 -0.4
	167	h 12 11 -0.4 -0.4
	168	g 12 12 -0.4 0.0
	169	h 12 12 0.8 1.0
	170	g 13 0 -0.2 -0.2
	171	g 13 1 -0.9 -0.9
	172	h 13 1 -0.9 -0.7
	173	g 13 2 0.3 0.3
	174	h 13 2 0.2 0.3
	175	g 13 3 0.1 0.3
	176	h 13 3 1.8 1.7
	177	g 13 4 -0.4 -0.4
	178	h 13 4 -0.4 -0.5
	179	g 13 5 1.3 1.2
	180	h 13 5 -1.0 -1.0
	181	g 13 6 -0.4 -0.4
	182	h 13 6 -0.1 0.0
	183	g 13 7 0.7 0.7
	184	h 13 7 0.7 0.7
	185	g 13 8 -0.4 -0.3
	186	h 13 8 0.3 0.2
	187	g 13 9 0.3 0.4
	188	h 13 9 0.6 0.6
	189	g 13 10 -0.1 -0.1
	190	h 13 10 0.3 0.4
	191	g 13 11 0.4 0.4
	192	h 13 11 -0.2 -0.2
	193	g 13 12 0.0 -0.1
	194	h 13 12 -0.5 -0.5
	195	g 13 13 0.1 -0.3
	196	h 13 13 -0.9 -1.0

apps/abs/utils/resource/igrf11coeffs.txt created 644 +196 0

@@ -0,0 +1,196
	1	g/h n m 1900.0 1905.0 1910.0 1915.0 1920.0 1925.0 1930.0 1935.0 1940.0 1945.0 1950.0 1955.0 1960.0 1965.0 1970.0 1975.0 1980.0 1985.0 1990.0 1995.0 2000.0 2005.0 2010.0 SV
	2	g 1 0 -31543 -31464 -31354 -31212 -31060 -30926 -30805 -30715 -30654 -30594 -30554 -30500 -30421 -30334 -30220 -30100 -29992 -29873 -29775 -29692 -29619.4 -29554.63 -29496.5 11.4
	3	g 1 1 -2298 -2298 -2297 -2306 -2317 -2318 -2316 -2306 -2292 -2285 -2250 -2215 -2169 -2119 -2068 -2013 -1956 -1905 -1848 -1784 -1728.2 -1669.05 -1585.9 16.7
	4	h 1 1 5922 5909 5898 5875 5845 5817 5808 5812 5821 5810 5815 5820 5791 5776 5737 5675 5604 5500 5406 5306 5186.1 5077.99 4945.1 -28.8
	5	g 2 0 -677 -728 -769 -802 -839 -893 -951 -1018 -1106 -1244 -1341 -1440 -1555 -1662 -1781 -1902 -1997 -2072 -2131 -2200 -2267.7 -2337.24 -2396.6 -11.3
	6	g 2 1 2905 2928 2948 2956 2959 2969 2980 2984 2981 2990 2998 3003 3002 2997 3000 3010 3027 3044 3059 3070 3068.4 3047.69 3026.0 -3.9
	7	h 2 1 -1061 -1086 -1128 -1191 -1259 -1334 -1424 -1520 -1614 -1702 -1810 -1898 -1967 -2016 -2047 -2067 -2129 -2197 -2279 -2366 -2481.6 -2594.50 -2707.7 -23.0
	8	g 2 2 924 1041 1176 1309 1407 1471 1517 1550 1566 1578 1576 1581 1590 1594 1611 1632 1663 1687 1686 1681 1670.9 1657.76 1668.6 2.7
	9	h 2 2 1121 1065 1000 917 823 728 644 586 528 477 381 291 206 114 25 -68 -200 -306 -373 -413 -458.0 -515.43 -575.4 -12.9
	10	g 3 0 1022 1037 1058 1084 1111 1140 1172 1206 1240 1282 1297 1302 1302 1297 1287 1276 1281 1296 1314 1335 1339.6 1336.30 1339.7 1.3
	11	g 3 1 -1469 -1494 -1524 -1559 -1600 -1645 -1692 -1740 -1790 -1834 -1889 -1944 -1992 -2038 -2091 -2144 -2180 -2208 -2239 -2267 -2288.0 -2305.83 -2326.3 -3.9
	12	h 3 1 -330 -357 -389 -421 -445 -462 -480 -494 -499 -499 -476 -462 -414 -404 -366 -333 -336 -310 -284 -262 -227.6 -198.86 -160.5 8.6
	13	g 3 2 1256 1239 1223 1212 1205 1202 1205 1215 1232 1255 1274 1288 1289 1292 1278 1260 1251 1247 1248 1249 1252.1 1246.39 1231.7 -2.9
	14	h 3 2 3 34 62 84 103 119 133 146 163 186 206 216 224 240 251 262 271 284 293 302 293.4 269.72 251.7 -2.9
	15	g 3 3 572 635 705 778 839 881 907 918 916 913 896 882 878 856 838 830 833 829 802 759 714.5 672.51 634.2 -8.1
	16	h 3 3 523 480 425 360 293 229 166 101 43 -11 -46 -83 -130 -165 -196 -223 -252 -297 -352 -427 -491.1 -524.72 -536.8 -2.1
	17	g 4 0 876 880 884 887 889 891 896 903 914 944 954 958 957 957 952 946 938 936 939 940 932.3 920.55 912.6 -1.4
	18	g 4 1 628 643 660 678 695 711 727 744 762 776 792 796 800 804 800 791 782 780 780 780 786.8 797.96 809.0 2.0
	19	h 4 1 195 203 211 218 220 216 205 188 169 144 136 133 135 148 167 191 212 232 247 262 272.6 282.07 286.4 0.4
	20	g 4 2 660 653 644 631 616 601 584 565 550 544 528 510 504 479 461 438 398 361 325 290 250.0 210.65 166.6 -8.9
	21	h 4 2 -69 -77 -90 -109 -134 -163 -195 -226 -252 -276 -278 -274 -278 -269 -266 -265 -257 -249 -240 -236 -231.9 -225.23 -211.2 3.2
	22	g 4 3 -361 -380 -400 -416 -424 -426 -422 -415 -405 -421 -408 -397 -394 -390 -395 -405 -419 -424 -423 -418 -403.0 -379.86 -357.1 4.4
	23	h 4 3 -210 -201 -189 -173 -153 -130 -109 -90 -72 -55 -37 -23 3 13 26 39 53 69 84 97 119.8 145.15 164.4 3.6
	24	g 4 4 134 146 160 178 199 217 234 249 265 304 303 290 269 252 234 216 199 170 141 122 111.3 100.00 89.7 -2.3
	25	h 4 4 -75 -65 -55 -51 -57 -70 -90 -114 -141 -178 -210 -230 -255 -269 -279 -288 -297 -297 -299 -306 -303.8 -305.36 -309.2 -0.8
	26	g 5 0 -184 -192 -201 -211 -221 -230 -237 -241 -241 -253 -240 -229 -222 -219 -216 -218 -218 -214 -214 -214 -218.8 -227.00 -231.1 -0.5
	27	g 5 1 328 328 327 327 326 326 327 329 334 346 349 360 362 358 359 356 357 355 353 352 351.4 354.41 357.2 0.5
	28	h 5 1 -210 -193 -172 -148 -122 -96 -72 -51 -33 -12 3 15 16 19 26 31 46 47 46 46 43.8 42.72 44.7 0.5
	29	g 5 2 264 259 253 245 236 226 218 211 208 194 211 230 242 254 262 264 261 253 245 235 222.3 208.95 200.3 -1.5
	30	h 5 2 53 56 57 58 58 58 60 64 71 95 103 110 125 128 139 148 150 150 154 165 171.9 180.25 188.9 1.5
	31	g 5 3 5 -1 -9 -16 -23 -28 -32 -33 -33 -20 -20 -23 -26 -31 -42 -59 -74 -93 -109 -118 -130.4 -136.54 -141.2 -0.7
	32	h 5 3 -33 -32 -33 -34 -38 -44 -53 -64 -75 -67 -87 -98 -117 -126 -139 -152 -151 -154 -153 -143 -133.1 -123.45 -118.1 0.9
	33	g 5 4 -86 -93 -102 -111 -119 -125 -131 -136 -141 -142 -147 -152 -156 -157 -160 -159 -162 -164 -165 -166 -168.6 -168.05 -163.1 1.3
	34	h 5 4 -124 -125 -126 -126 -125 -122 -118 -115 -113 -119 -122 -121 -114 -97 -91 -83 -78 -75 -69 -55 -39.3 -19.57 0.1 3.7
	35	g 5 5 -16 -26 -38 -51 -62 -69 -74 -76 -76 -82 -76 -69 -63 -62 -56 -49 -48 -46 -36 -17 -12.9 -13.55 -7.7 1.4
	36	h 5 5 3 11 21 32 43 51 58 64 69 82 80 78 81 81 83 88 92 95 97 107 106.3 103.85 100.9 -0.6
	37	g 6 0 63 62 62 61 61 61 60 59 57 59 54 47 46 45 43 45 48 53 61 68 72.3 73.60 72.8 -0.3
	38	g 6 1 61 60 58 57 55 54 53 53 54 57 57 57 58 61 64 66 66 65 65 67 68.2 69.56 68.6 -0.3
	39	h 6 1 -9 -7 -5 -2 0 3 4 4 4 6 -1 -9 -10 -11 -12 -13 -15 -16 -16 -17 -17.4 -20.33 -20.8 -0.1
	40	g 6 2 -11 -11 -11 -10 -10 -9 -9 -8 -7 6 4 3 1 8 15 28 42 51 59 68 74.2 76.74 76.0 -0.3
	41	h 6 2 83 86 89 93 96 99 102 104 105 100 99 96 99 100 100 99 93 88 82 72 63.7 54.75 44.2 -2.1
	42	g 6 3 -217 -221 -224 -228 -233 -238 -242 -246 -249 -246 -247 -247 -237 -228 -212 -198 -192 -185 -178 -170 -160.9 -151.34 -141.4 1.9
	43	h 6 3 2 4 5 8 11 14 19 25 33 16 33 48 60 68 72 75 71 69 69 67 65.1 63.63 61.5 -0.4
	44	g 6 4 -58 -57 -54 -51 -46 -40 -32 -25 -18 -25 -16 -8 -1 4 2 1 4 4 3 -1 -5.9 -14.58 -22.9 -1.6
	45	h 6 4 -35 -32 -29 -26 -22 -18 -16 -15 -15 -9 -12 -16 -20 -32 -37 -41 -43 -48 -52 -58 -61.2 -63.53 -66.3 -0.5
	46	g 6 5 59 57 54 49 44 39 32 25 18 21 12 7 -2 1 3 6 14 16 18 19 16.9 14.58 13.1 -0.2
	47	h 6 5 36 32 28 23 18 13 8 4 0 -16 -12 -12 -11 -8 -6 -4 -2 -1 1 1 0.7 0.24 3.1 0.8
	48	g 6 6 -90 -92 -95 -98 -101 -103 -104 -106 -107 -104 -105 -107 -113 -111 -112 -111 -108 -102 -96 -93 -90.4 -86.36 -77.9 1.8
	49	h 6 6 -69 -67 -65 -62 -57 -52 -46 -40 -33 -39 -30 -24 -17 -7 1 11 17 21 24 36 43.8 50.94 54.9 0.5
	50	g 7 0 70 70 71 72 73 73 74 74 74 70 65 65 67 75 72 71 72 74 77 77 79.0 79.88 80.4 0.2
	51	g 7 1 -55 -54 -54 -54 -54 -54 -54 -53 -53 -40 -55 -56 -56 -57 -57 -56 -59 -62 -64 -72 -74.0 -74.46 -75.0 -0.1
	52	h 7 1 -45 -46 -47 -48 -49 -50 -51 -52 -52 -45 -35 -50 -55 -61 -70 -77 -82 -83 -80 -69 -64.6 -61.14 -57.8 0.6
	53	g 7 2 0 0 1 2 2 3 4 4 4 0 2 2 5 4 1 1 2 3 2 1 0.0 -1.65 -4.7 -0.6
	54	h 7 2 -13 -14 -14 -14 -14 -14 -15 -17 -18 -18 -17 -24 -28 -27 -27 -26 -27 -27 -26 -25 -24.2 -22.57 -21.2 0.3
	55	g 7 3 34 33 32 31 29 27 25 23 20 0 1 10 15 13 14 16 21 24 26 28 33.3 38.73 45.3 1.4
	56	h 7 3 -10 -11 -12 -12 -13 -14 -14 -14 -14 2 0 -4 -6 -2 -4 -5 -5 -2 0 4 6.2 6.82 6.6 -0.2
	57	g 7 4 -41 -41 -40 -38 -37 -35 -34 -33 -31 -29 -40 -32 -32 -26 -22 -14 -12 -6 -1 5 9.1 12.30 14.0 0.3
	58	h 7 4 -1 0 1 2 4 5 6 7 7 6 10 8 7 6 8 10 16 20 21 24 24.0 25.35 24.9 -0.1
	59	g 7 5 -21 -20 -19 -18 -16 -14 -12 -11 -9 -10 -7 -11 -7 -6 -2 0 1 4 5 4 6.9 9.37 10.4 0.1
	60	h 7 5 28 28 28 28 28 29 29 29 29 28 36 28 23 26 23 22 18 17 17 17 14.8 10.93 7.0 -0.8
	61	g 7 6 18 18 18 19 19 19 18 18 17 15 5 9 17 13 13 12 11 10 9 8 7.3 5.42 1.6 -0.8
	62	h 7 6 -12 -12 -13 -15 -16 -17 -18 -19 -20 -17 -18 -20 -18 -23 -23 -23 -23 -23 -23 -24 -25.4 -26.32 -27.7 -0.3
	63	g 7 7 6 6 6 6 6 6 6 6 5 29 19 18 8 1 -2 -5 -2 0 0 -2 -1.2 1.94 4.9 0.4
	64	h 7 7 -22 -22 -22 -22 -22 -21 -20 -19 -19 -22 -16 -18 -17 -12 -11 -12 -10 -7 -4 -6 -5.8 -4.64 -3.4 0.2
	65	g 8 0 11 11 11 11 11 11 11 11 11 13 22 11 15 13 14 14 18 21 23 25 24.4 24.80 24.3 -0.1
	66	g 8 1 8 8 8 8 7 7 7 7 7 7 15 9 6 5 6 6 6 6 5 6 6.6 7.62 8.2 0.1
	67	h 8 1 8 8 8 8 8 8 8 8 8 12 5 10 11 7 7 6 7 8 10 11 11.9 11.20 10.9 0.0
	68	g 8 2 -4 -4 -4 -4 -3 -3 -3 -3 -3 -8 -4 -6 -4 -4 -2 -1 0 0 -1 -6 -9.2 -11.73 -14.5 -0.5
	69	h 8 2 -14 -15 -15 -15 -15 -15 -15 -15 -14 -21 -22 -15 -14 -12 -15 -16 -18 -19 -19 -21 -21.5 -20.88 -20.0 0.2
	70	g 8 3 -9 -9 -9 -9 -9 -9 -9 -9 -10 -5 -1 -14 -11 -14 -13 -12 -11 -11 -10 -9 -7.9 -6.88 -5.7 0.3
	71	h 8 3 7 7 6 6 6 6 5 5 5 -12 0 5 7 9 6 4 4 5 6 8 8.5 9.83 11.9 0.5
	72	g 8 4 1 1 1 2 2 2 2 1 1 9 11 6 2 0 -3 -8 -7 -9 -12 -14 -16.6 -18.11 -19.3 -0.3
	73	h 8 4 -13 -13 -13 -13 -14 -14 -14 -15 -15 -7 -21 -23 -18 -16 -17 -19 -22 -23 -22 -23 -21.5 -19.71 -17.4 0.4
	74	g 8 5 2 2 2 3 4 4 5 6 6 7 15 10 10 8 5 4 4 4 3 9 9.1 10.17 11.6 0.3
	75	h 8 5 5 5 5 5 5 5 5 5 5 2 -8 3 4 4 6 6 9 11 12 15 15.5 16.22 16.7 0.1
	76	g 8 6 -9 -8 -8 -8 -7 -7 -6 -6 -5 -10 -13 -7 -5 -1 0 0 3 4 4 6 7.0 9.36 10.9 0.2
	77	h 8 6 16 16 16 16 17 17 18 18 19 18 17 23 23 24 21 18 16 14 12 11 8.9 7.61 7.1 -0.1
	78	g 8 7 5 5 5 6 6 7 8 8 9 7 5 6 10 11 11 10 6 4 2 -5 -7.9 -11.25 -14.1 -0.5
	79	h 8 7 -5 -5 -5 -5 -5 -5 -5 -5 -5 3 -4 -4 1 -3 -6 -10 -13 -15 -16 -16 -14.9 -12.76 -10.8 0.4
	80	g 8 8 8 8 8 8 8 8 8 7 7 2 -1 9 8 4 3 1 -1 -4 -6 -7 -7.0 -4.87 -3.7 0.2
	81	h 8 8 -18 -18 -18 -18 -19 -19 -19 -19 -19 -11 -17 -13 -20 -17 -16 -17 -15 -11 -10 -4 -2.1 -0.06 1.7 0.4
	82	g 9 0 8 8 8 8 8 8 8 8 8 5 3 4 4 8 8 7 5 5 4 4 5.0 5.58 5.4 0.0
	83	g 9 1 10 10 10 10 10 10 10 10 10 -21 -7 9 6 10 10 10 10 10 9 9 9.4 9.76 9.4 0.0
	84	h 9 1 -20 -20 -20 -20 -20 -20 -20 -20 -21 -27 -24 -11 -18 -22 -21 -21 -21 -21 -20 -20 -19.7 -20.11 -20.5 0.0
	85	g 9 2 1 1 1 1 1 1 1 1 1 1 -1 -4 0 2 2 2 1 1 1 3 3.0 3.58 3.4 0.0
	86	h 9 2 14 14 14 14 14 14 14 15 15 17 19 12 12 15 16 16 16 15 15 15 13.4 12.69 11.6 0.0
	87	g 9 3 -11 -11 -11 -11 -11 -11 -12 -12 -12 -11 -25 -5 -9 -13 -12 -12 -12 -12 -12 -10 -8.4 -6.94 -5.3 0.0
	88	h 9 3 5 5 5 5 5 5 5 5 5 29 12 7 2 7 6 7 9 9 11 12 12.5 12.67 12.8 0.0
	89	g 9 4 12 12 12 12 12 12 12 11 11 3 10 2 1 10 10 10 9 9 9 8 6.3 5.01 3.1 0.0
	90	h 9 4 -3 -3 -3 -3 -3 -3 -3 -3 -3 -9 2 6 0 -4 -4 -4 -5 -6 -7 -6 -6.2 -6.72 -7.2 0.0
	91	g 9 5 1 1 1 1 1 1 1 1 1 16 5 4 4 -1 -1 -1 -3 -3 -4 -8 -8.9 -10.76 -12.4 0.0
	92	h 9 5 -2 -2 -2 -2 -2 -2 -2 -3 -3 4 2 -2 -3 -5 -5 -5 -6 -6 -7 -8 -8.4 -8.16 -7.4 0.0
	93	g 9 6 -2 -2 -2 -2 -2 -2 -2 -2 -2 -3 -5 1 -1 -1 0 -1 -1 -1 -2 -1 -1.5 -1.25 -0.8 0.0
	94	h 9 6 8 8 8 8 9 9 9 9 9 9 8 10 9 10 10 10 9 9 9 8 8.4 8.10 8.0 0.0
	95	g 9 7 2 2 2 2 2 2 3 3 3 -4 -2 2 -2 5 3 4 7 7 7 10 9.3 8.76 8.4 0.0
	96	h 9 7 10 10 10 10 10 10 10 11 11 6 8 7 8 10 11 11 10 9 8 5 3.8 2.92 2.2 0.0
	97	g 9 8 -1 0 0 0 0 0 0 0 1 -3 3 2 3 1 1 1 2 1 1 -2 -4.3 -6.66 -8.4 0.0
	98	h 9 8 -2 -2 -2 -2 -2 -2 -2 -2 -2 1 -11 -6 0 -4 -2 -3 -6 -7 -7 -8 -8.2 -7.73 -6.1 0.0
	99	g 9 9 -1 -1 -1 -1 -1 -1 -2 -2 -2 -4 8 5 -1 -2 -1 -2 -5 -5 -6 -8 -8.2 -9.22 -10.1 0.0
	100	h 9 9 2 2 2 2 2 2 2 2 2 8 -7 5 5 1 1 1 2 2 2 3 4.8 6.01 7.0 0.0
	101	g 10 0 -3 -3 -3 -3 -3 -3 -3 -3 -3 -3 -8 -3 1 -2 -3 -3 -4 -4 -3 -3 -2.6 -2.17 -2.0 0.0
	102	g 10 1 -4 -4 -4 -4 -4 -4 -4 -4 -4 11 4 -5 -3 -3 -3 -3 -4 -4 -4 -6 -6.0 -6.12 -6.3 0.0
	103	h 10 1 2 2 2 2 2 2 2 2 2 5 13 -4 4 2 1 1 1 1 2 1 1.7 2.19 2.8 0.0
	104	g 10 2 2 2 2 2 2 2 2 2 2 1 -1 -1 4 2 2 2 2 3 2 2 1.7 1.42 0.9 0.0
	105	h 10 2 1 1 1 1 1 1 1 1 1 1 -2 0 1 1 1 1 0 0 1 0 0.0 0.10 -0.1 0.0
	106	g 10 3 -5 -5 -5 -5 -5 -5 -5 -5 -5 2 13 2 0 -5 -5 -5 -5 -5 -5 -4 -3.1 -2.35 -1.1 0.0
	107	h 10 3 2 2 2 2 2 2 2 2 2 -20 -10 -8 0 2 3 3 3 3 3 4 4.0 4.46 4.7 0.0
	108	g 10 4 -2 -2 -2 -2 -2 -2 -2 -2 -2 -5 -4 -3 -1 -2 -1 -2 -2 -2 -2 -1 -0.5 -0.15 -0.2 0.0
	109	h 10 4 6 6 6 6 6 6 6 6 6 -1 2 -2 2 6 4 4 6 6 6 5 4.9 4.76 4.4 0.0
	110	g 10 5 6 6 6 6 6 6 6 6 6 -1 4 7 4 4 6 5 5 5 4 4 3.7 3.06 2.5 0.0
	111	h 10 5 -4 -4 -4 -4 -4 -4 -4 -4 -4 -6 -3 -4 -5 -4 -4 -4 -4 -4 -4 -5 -5.9 -6.58 -7.2 0.0
	112	g 10 6 4 4 4 4 4 4 4 4 4 8 12 4 6 4 4 4 3 3 3 2 1.0 0.29 -0.3 0.0
	113	h 10 6 0 0 0 0 0 0 0 0 0 6 6 1 1 0 0 -1 0 0 0 -1 -1.2 -1.01 -1.0 0.0
	114	g 10 7 0 0 0 0 0 0 0 0 0 -1 3 -2 1 0 1 1 1 1 1 2 2.0 2.06 2.2 0.0
	115	h 10 7 -2 -2 -2 -2 -2 -2 -2 -1 -1 -4 -3 -3 -1 -2 -1 -1 -1 -1 -2 -2 -2.9 -3.47 -4.0 0.0
	116	g 10 8 2 2 2 1 1 1 1 2 2 -3 2 6 -1 2 0 0 2 2 3 5 4.2 3.77 3.1 0.0
	117	h 10 8 4 4 4 4 4 4 4 4 4 -2 6 7 6 3 3 3 4 4 3 1 0.2 -0.86 -2.0 0.0
	118	g 10 9 2 2 2 2 3 3 3 3 3 5 10 -2 2 2 3 3 3 3 3 1 0.3 -0.21 -1.0 0.0
	119	h 10 9 0 0 0 0 0 0 0 0 0 0 11 -1 0 0 1 1 0 0 -1 -2 -2.2 -2.31 -2.0 0.0
	120	g 10 10 0 0 0 0 0 0 0 0 0 -2 3 0 0 0 -1 -1 0 0 0 0 -1.1 -2.09 -2.8 0.0
	121	h 10 10 -6 -6 -6 -6 -6 -6 -6 -6 -6 -2 8 -3 -7 -6 -4 -5 -6 -6 -6 -7 -7.4 -7.93 -8.3 0.0
	122	g 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2.7 2.95 3.0 0.0
	123	g 11 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1.7 -1.60 -1.5 0.0
	124	h 11 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.1 0.26 0.1 0.0
	125	g 11 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1.9 -1.88 -2.1 0.0
	126	h 11 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.3 1.44 1.7 0.0
	127	g 11 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.5 1.44 1.6 0.0
	128	h 11 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.9 -0.77 -0.6 0.0
	129	g 11 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.1 -0.31 -0.5 0.0
	130	h 11 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -2.6 -2.27 -1.8 0.0
	131	g 11 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.1 0.29 0.5 0.0
	132	h 11 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.9 0.90 0.9 0.0
	133	g 11 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.7 -0.79 -0.8 0.0
	134	h 11 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.7 -0.58 -0.4 0.0
	135	g 11 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.7 0.53 0.4 0.0
	136	h 11 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -2.8 -2.69 -2.5 0.0
	137	g 11 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.7 1.80 1.8 0.0
	138	h 11 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.9 -1.08 -1.3 0.0
	139	g 11 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.1 0.16 0.2 0.0
	140	h 11 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1.2 -1.58 -2.1 0.0
	141	g 11 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.2 0.96 0.8 0.0
	142	h 11 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1.9 -1.90 -1.9 0.0
	143	g 11 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4.0 3.99 3.8 0.0
	144	h 11 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.9 -1.39 -1.8 0.0
	145	g 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -2.2 -2.15 -2.1 0.0
	146	g 12 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.3 -0.29 -0.2 0.0
	147	h 12 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.4 -0.55 -0.8 0.0
	148	g 12 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.2 0.21 0.3 0.0
	149	h 12 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.23 0.3 0.0
	150	g 12 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.9 0.89 1.0 0.0
	151	h 12 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2.5 2.38 2.2 0.0
	152	g 12 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.2 -0.38 -0.7 0.0
	153	h 12 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -2.6 -2.63 -2.5 0.0
	154	g 12 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.9 0.96 0.9 0.0
	155	h 12 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.7 0.61 0.5 0.0
	156	g 12 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.5 -0.30 -0.1 0.0
	157	h 12 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.40 0.6 0.0
	158	g 12 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.46 0.5 0.0
	159	h 12 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.01 0.0 0.0
	160	g 12 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.3 -0.35 -0.4 0.0
	161	h 12 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.02 0.1 0.0
	162	g 12 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.4 -0.36 -0.4 0.0
	163	h 12 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.28 0.3 0.0
	164	g 12 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.1 0.08 0.2 0.0
	165	h 12 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.9 -0.87 -0.9 0.0
	166	g 12 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.2 -0.49 -0.8 0.0
	167	h 12 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.4 -0.34 -0.2 0.0
	168	g 12 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.4 -0.08 0.0 0.0
	169	h 12 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.8 0.88 0.8 0.0
	170	g 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.2 -0.16 -0.2 0.0
	171	g 13 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.9 -0.88 -0.9 0.0
	172	h 13 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.9 -0.76 -0.8 0.0
	173	g 13 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.30 0.3 0.0
	174	h 13 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.2 0.33 0.3 0.0
	175	g 13 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.1 0.28 0.4 0.0
	176	h 13 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.8 1.72 1.7 0.0
	177	g 13 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.4 -0.43 -0.4 0.0
	178	h 13 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.4 -0.54 -0.6 0.0
	179	g 13 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.3 1.18 1.1 0.0
	180	h 13 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1.0 -1.07 -1.2 0.0
	181	g 13 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.4 -0.37 -0.3 0.0
	182	h 13 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.1 -0.04 -0.1 0.0
	183	g 13 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.7 0.75 0.8 0.0
	184	h 13 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.7 0.63 0.5 0.0
	185	g 13 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.4 -0.26 -0.2 0.0
	186	h 13 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.21 0.1 0.0
	187	g 13 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.35 0.4 0.0
	188	h 13 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.6 0.53 0.5 0.0
	189	g 13 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.1 -0.05 0.0 0.0
	190	h 13 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.3 0.38 0.4 0.0
	191	g 13 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.4 0.41 0.4 0.0
	192	h 13 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.2 -0.22 -0.2 0.0
	193	g 13 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 -0.10 -0.3 0.0
	194	h 13 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.5 -0.57 -0.5 0.0
	195	g 13 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.1 -0.18 -0.3 0.0
	196	h 13 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.9 -0.82 -0.8 0.0

apps/abs/utils/resource/skynoise_jro.dat created 644 binary 0 0

NO CONTENT: new file 100644, binary diff hidden

apps/abs/templates/abs_pattern.html +102 -354

             </style>
-            <script>
-            $(document).ready(function() {
-              {% for beam in abs_beams %}
-                $( "#button-{{ forloop.counter }}" ).click(function() {
-                  var antenna_upvalues     = {{beam.antenna_upvalues}};
-                  var antenna_downvalues     = {{beam.antenna_downvalues}};
-                  var table_up = document.getElementById('antenna_up');
-                  var cells_up = table_up.getElementsByTagName('td');
-                  var table_down = document.getElementById('antenna_down');
-                  var cells_down = table_down.getElementsByTagName('td');
-                  //TX Tables
-                  var tx_upvalues   = {{beam.get_tx.up}};
-                  var tx_downvalues = {{beam.get_tx.down}};
-                  var tabletx_up = document.getElementById('tx_up');
-                  var cellstx_up = tabletx_up.getElementsByTagName('td');
-                  var tabletx_down = document.getElementById('tx_down');
-                  var cellstx_down = tabletx_down.getElementsByTagName('td');
-                  //RX Tables
-                  var rx_upvalues   = {{beam.get_rx.up}};
-                  var rx_downvalues = {{beam.get_rx.down}};
-                  var tablerx_up = document.getElementById('rx_up');
-                  var cellsrx_up = tablerx_up.getElementsByTagName('td');
-                  var tablerx_down = document.getElementById('rx_down');
-                  var cellsrx_down = tablerx_down.getElementsByTagName('td');
-                  //alert(cells_down[51].textContent);
-                  //alert(cells_up[51].textContent);
-                  for (var i = 1, len = 17; i < len; i++) {
-                      if ((i > 12) && (i<17)){
-                        cells_up[i].innerHTML   = antenna_upvalues[3][i-13].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[3][i-13].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[3][i-13];
-                        cellstx_down[i].innerHTML = tx_downvalues[3][i-13];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[3][i-13];
-                        cellsrx_down[i].innerHTML = rx_downvalues[3][i-13];
-                      else if ((i > 8) && (i<13)){
-                        cells_up[i].innerHTML   = antenna_upvalues[2][i-9].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[2][i-9].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[2][i-9];
-                        cellstx_down[i].innerHTML = tx_downvalues[2][i-9];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[2][i-9];
-                        cellsrx_down[i].innerHTML = rx_downvalues[2][i-9];
-                      else if ((i > 4) && (i<9)){
-                        cells_up[i].innerHTML   = antenna_upvalues[1][i-5].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[1][i-5].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[1][i-5];
-                        cellstx_down[i].innerHTML = tx_downvalues[1][i-5];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[1][i-5];
-                        cellsrx_down[i].innerHTML = rx_downvalues[1][i-5];
-                      else if (i < 5) {
-                        cells_up[i].innerHTML   = antenna_upvalues[0][i-1].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[0][i-1].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[0][i-1];
-                        cellstx_down[i].innerHTML = tx_downvalues[0][i-1];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[0][i-1];
-                        cellsrx_down[i].innerHTML = rx_downvalues[0][i-1];
-                    for (var i = 18, len = 34; i < len; i++) {
-                      if ((i > 29) && (i<34)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[3][i-26].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[3][i-26].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[3][i-26];
-                        cellstx_down[i].innerHTML = tx_downvalues[3][i-26];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[3][i-26];
-                        cellsrx_down[i].innerHTML = rx_downvalues[3][i-26];
-                      if ((i > 25) && (i<30)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[2][i-22].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[2][i-22].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[2][i-22];
-                        cellstx_down[i].innerHTML = tx_downvalues[2][i-22];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[2][i-22];
-                        cellsrx_down[i].innerHTML = rx_downvalues[2][i-22];
-                      else if ((i > 21) && (i<26)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[1][i-18].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[1][i-18].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[1][i-18];
-                        cellstx_down[i].innerHTML = tx_downvalues[1][i-18];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[1][i-18];
-                        cellsrx_down[i].innerHTML = rx_downvalues[1][i-18];
-                      else if (i < 22) {
-                        cells_up[i].innerHTML = antenna_upvalues[0][i-14].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[0][i-14].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[0][i-14];
-                        cellstx_down[i].innerHTML = tx_downvalues[0][i-14];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[0][i-14];
-                        cellsrx_down[i].innerHTML = rx_downvalues[0][i-14];
-                    for (var i = 35, len = 51; i < len; i++) {
-                      if ((i > 46) && (i<51)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[7][i-47].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[7][i-47].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[7][i-47];
-                        cellstx_down[i].innerHTML = tx_downvalues[7][i-47];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[7][i-47];
-                        cellsrx_down[i].innerHTML = rx_downvalues[7][i-47];
-                      else if ((i > 42) && (i<47)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[6][i-43].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[6][i-43].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[6][i-43];
-                        cellstx_down[i].innerHTML = tx_downvalues[6][i-43];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[6][i-43];
-                        cellsrx_down[i].innerHTML = rx_downvalues[6][i-43];
-                      else if ((i > 38) && (i<43)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[5][i-39].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[5][i-39].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[5][i-39];
-                        cellstx_down[i].innerHTML = tx_downvalues[5][i-39];
-                        cellsrx_up[i].innerHTML = rx_upvalues[5][i-39];
-                        cellsrx_down[i].innerHTML = rx_downvalues[5][i-39];
-                      else if (i < 39) {
-                        cells_up[i].innerHTML   = antenna_upvalues[4][i-35].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[4][i-35].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[4][i-35];
-                        cellstx_down[i].innerHTML = tx_downvalues[4][i-35];
-                        cellsrx_up[i].innerHTML = rx_upvalues[4][i-35];
-                        cellsrx_down[i].innerHTML = rx_downvalues[4][i-35];
-                    for (var i = 52, len = 68; i < len; i++) {
-                      if ((i > 63) && (i<68)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[7][i-60].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[7][i-60].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[7][i-60];
-                        cellstx_down[i].innerHTML = tx_downvalues[7][i-60];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[7][i-60];
-                        cellsrx_down[i].innerHTML = rx_downvalues[7][i-60];
-                      else if ((i > 59) && (i<64)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[6][i-56].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[6][i-56].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[6][i-56];
-                        cellstx_down[i].innerHTML = tx_downvalues[6][i-56];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[6][i-56];
-                        cellsrx_down[i].innerHTML = rx_downvalues[6][i-56];
-                      else if ((i > 55) && (i<60)) {
-                        cells_up[i].innerHTML   = antenna_upvalues[5][i-52].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[5][i-52].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[5][i-52];
-                        cellstx_down[i].innerHTML = tx_downvalues[5][i-52];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[5][i-52];
-                        cellsrx_down[i].innerHTML = rx_downvalues[5][i-52];
-                      else if (i < 56) {
-                        cells_up[i].innerHTML   = antenna_upvalues[4][i-48].toFixed(1);
-                        cells_down[i].innerHTML = antenna_downvalues[4][i-48].toFixed(1);
-                        cellstx_up[i].innerHTML   = tx_upvalues[4][i-48];
-                        cellstx_down[i].innerHTML = tx_downvalues[4][i-48];
-                        cellsrx_up[i].innerHTML   = rx_upvalues[4][i-48];
-                        cellsrx_down[i].innerHTML = rx_downvalues[4][i-48];
-                    var up_ues = document.getElementById('up_ues');
-                    up_ues.innerHTML = "{{beam.get_up_ues}}";
-                    var down_ues = document.getElementById('down_ues');
-                    down_ues.innerHTML = "{{beam.get_down_ues}}";
-                  });
-              {% endfor %}
-            });
-            </script>
             <div id="UP" class="panel-group">
               <div class="panel panel-default">
                           <tr>
                             <td> North Quarter
                               <table class="north_quarter">
-                                <tr>
+                                <tr> <td>{{beam.get_upvalues.0}}</td> <td>{{beam.get_upvalues.1}}</td> <td>{{beam.get_upvalues.2}}</td> <td>{{beam.get_upvalues.3}}</td> </tr>
-                                  <td>{{abs_beams.0.get_upvalues.0}}</td> <td>{{abs_beams.0.get_upvalues.1}}</td> <td>{{abs_beams.0.get_upvalues.2}}</td> <td>{{abs_beams.0.get_upvalues.3}}</td>
+                                <tr> <td>{{beam.get_upvalues.8}}</td> <td>{{beam.get_upvalues.9}}</td> <td>{{beam.get_upvalues.10}}</td> <td>{{beam.get_upvalues.11}}</td> </tr>
-                                </tr>
+                                <tr> <td>{{beam.get_upvalues.16}}</td> <td>{{beam.get_upvalues.17}}</td> <td>{{beam.get_upvalues.18}}</td> <td>{{beam.get_upvalues.19}}</td> </tr>
-                                <tr>
+                                <tr> <td>{{beam.get_upvalues.24}}</td> <td>{{beam.get_upvalues.25}}</td> <td>{{beam.get_upvalues.26}}</td> <td>{{beam.get_upvalues.27}}</td> </tr>
-                                  <td>{{abs_beams.0.get_upvalues.8}}</td> <td>{{abs_beams.0.get_upvalues.9}}</td> <td>{{abs_beams.0.get_upvalues.10}}</td> <td>{{abs_beams.0.get_upvalues.11}}</td>
-                                </tr>
-                                <tr>
-                                  <td>{{abs_beams.0.get_upvalues.16}}</td> <td>{{abs_beams.0.get_upvalues.17}}</td> <td>{{abs_beams.0.get_upvalues.18}}</td> <td>{{abs_beams.0.get_upvalues.19}}</td>
-                                </tr>
-                                <tr>
-                                  <td>{{abs_beams.0.get_upvalues.24}}</td> <td>{{abs_beams.0.get_upvalues.25}}</td> <td>{{abs_beams.0.get_upvalues.26}}</td> <td>{{abs_beams.0.get_upvalues.27}}</td>
-                                </tr>
                               </table>
                             </td>
                             <td> East Quarter
                               <table class="east_quarter">
-                                <tr>
+                                <tr> <td>{{beam.get_upvalues.4}}</td> <td>{{beam.get_upvalues.5}}</td> <td>{{beam.get_upvalues.6}}</td> <td>{{beam.get_upvalues.7}}</td> </tr>
-                                  <td>{{abs_beams.0.get_upvalues.4}}</td> <td>{{abs_beams.0.get_upvalues.5}}</td> <td>{{abs_beams.0.get_upvalues.6}}</td> <td>{{abs_beams.0.get_upvalues.7}}</td>
+                                <tr> <td>{{beam.get_upvalues.12}}</td> <td>{{beam.get_upvalues.13}}</td> <td>{{beam.get_upvalues.14}}</td> <td>{{beam.get_upvalues.15}}</td> </tr>
-                                </tr>
+                                <tr> <td>{{beam.get_upvalues.20}}</td> <td>{{beam.get_upvalues.21}}</td> <td>{{beam.get_upvalues.22}}</td> <td>{{beam.get_upvalues.23}}</td> </tr>
-                                <tr>
+                                <tr> <td>{{beam.get_upvalues.28}}</td> <td>{{beam.get_upvalues.29}}</td> <td>{{beam.get_upvalues.30}}</td> <td>{{beam.get_upvalues.31}}</td> </tr>
-                                  <td>{{abs_beams.0.get_upvalues.12}}</td> <td>{{abs_beams.0.get_upvalues.13}}</td> <td>{{abs_beams.0.get_upvalues.14}}</td> <td>{{abs_beams.0.get_upvalues.15}}</td>
-                                </tr>
-                                <tr>
-                                  <td>{{abs_beams.0.get_upvalues.20}}</td> <td>{{abs_beams.0.get_upvalues.21}}</td> <td>{{abs_beams.0.get_upvalues.22}}</td> <td>{{abs_beams.0.get_upvalues.23}}</td>
-                                </tr>
-                                <tr>
-                                  <td>{{abs_beams.0.get_upvalues.28}}</td> <td>{{abs_beams.0.get_upvalues.29}}</td> <td>{{abs_beams.0.get_upvalues.30}}</td> <td>{{abs_beams.0.get_upvalues.31}}</td>
-                                </tr>
                               </table>
                             </td>
                           </tr>
                           <tr>
                             <td> West Quarter
                               <table class="west_quarter">
-                                <tr>
+                                <tr> <td>{{beam.get_upvalues.32}}</td> <td>{{beam.get_upvalues.33}}</td> <td>{{beam.get_upvalues.34}}</td> <td>{{beam.get_upvalues.35}}</td> </tr>
-                                  <td>{{abs_beams.0.get_upvalues.32}}</td> <td>{{abs_beams.0.get_upvalues.33}}</td> <td>{{abs_beams.0.get_upvalues.34}}</td> <td>{{abs_beams.0.get_upvalues.35}}</td>
+                                <tr> <td>{{beam.get_upvalues.40}}</td> <td>{{beam.get_upvalues.41}}</td> <td>{{beam.get_upvalues.42}}</td> <td>{{beam.get_upvalues.43}}</td> </tr>
-                                </tr>
+                                <tr> <td>{{beam.get_upvalues.48}}</td> <td>{{beam.get_upvalues.49}}</td> <td>{{beam.get_upvalues.50}}</td> <td>{{beam.get_upvalues.51}}</td> </tr>
-                                <tr>
+                                <tr> <td>{{beam.get_upvalues.56}}</td> <td>{{beam.get_upvalues.57}}</td> <td>{{beam.get_upvalues.58}}</td> <td>{{beam.get_upvalues.59}}</td> </tr>
-                                  <td>{{abs_beams.0.get_upvalues.40}}</td> <td>{{abs_beams.0.get_upvalues.41}}</td> <td>{{abs_beams.0.get_upvalues.42}}</td> <td>{{abs_beams.0.get_upvalues.43}}</td>
-                                </tr>
-                                <tr>
-                                  <td>{{abs_beams.0.get_upvalues.48}}</td> <td>{{abs_beams.0.get_upvalues.49}}</td> <td>{{abs_beams.0.get_upvalues.50}}</td> <td>{{abs_beams.0.get_upvalues.51}}</td>
-                                </tr>
-                                <tr>
-                                  <td>{{abs_beams.0.get_upvalues.56}}</td> <td>{{abs_beams.0.get_upvalues.57}}</td> <td>{{abs_beams.0.get_upvalues.58}}</td> <td>{{abs_beams.0.get_upvalues.59}}</td>
-                                </tr>
                               </table>
                             </td>
                             <td> South Quarter
                               <table class="south_quarter">
-                                <tr>
+                                <tr> <td>{{beam.get_upvalues.36}}</td> <td>{{beam.get_upvalues.37}}</td> <td>{{beam.get_upvalues.38}}</td> <td>{{beam.get_upvalues.39}}</td> </tr>
-                                  <td>{{abs_beams.0.get_upvalues.36}}</td> <td>{{abs_beams.0.get_upvalues.37}}</td> <td>{{abs_beams.0.get_upvalues.38}}</td> <td>{{abs_beams.0.get_upvalues.39}}</td>
+                                <tr> <td>{{beam.get_upvalues.44}}</td> <td>{{beam.get_upvalues.45}}</td> <td>{{beam.get_upvalues.46}}</td> <td>{{beam.get_upvalues.47}}</td> </tr>
-                                </tr>
+                                <tr> <td>{{beam.get_upvalues.52}}</td> <td>{{beam.get_upvalues.53}}</td> <td>{{beam.get_upvalues.54}}</td> <td>{{beam.get_upvalues.55}}</td> </tr>
-                                <tr>
+                                <tr> <td>{{beam.get_upvalues.60}}</td> <td>{{beam.get_upvalues.61}}</td> <td>{{beam.get_upvalues.62}}</td> <td>{{beam.get_upvalues.63}}</td> </tr>
-                                  <td>{{abs_beams.0.get_upvalues.44}}</td> <td>{{abs_beams.0.get_upvalues.45}}</td> <td>{{abs_beams.0.get_upvalues.46}}</td> <td>{{abs_beams.0.get_upvalues.47}}</td>
-                                </tr>
-                                <tr>
-                                  <td>{{abs_beams.0.get_upvalues.52}}</td> <td>{{abs_beams.0.get_upvalues.53}}</td> <td>{{abs_beams.0.get_upvalues.54}}</td> <td>{{abs_beams.0.get_upvalues.55}}</td>
-                                </tr>
-                                <tr>
-                                  <td>{{abs_beams.0.get_upvalues.60}}</td> <td>{{abs_beams.0.get_upvalues.61}}</td> <td>{{abs_beams.0.get_upvalues.62}}</td> <td>{{abs_beams.0.get_upvalues.63}}</td>
-                                </tr>
                               </table>
                             </td>
                           </tr>
                             <td> North Quarter
                               <table align="center" class="north_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.0.0}}</td> <td>{{abs_beams.0.get_tx.up.0.1}}</td> <td>{{abs_beams.0.get_tx.up.0.2}}</td> <td>{{abs_beams.0.get_tx.up.0.3}}</td>
+                                  <td>{{beam.get_tx.up.0.0}}</td> <td>{{beam.get_tx.up.0.1}}</td> <td>{{beam.get_tx.up.0.2}}</td> <td>{{beam.get_tx.up.0.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.1.0}}</td> <td>{{abs_beams.0.get_tx.up.1.1}}</td> <td>{{abs_beams.0.get_tx.up.1.2}}</td> <td>{{abs_beams.0.get_tx.up.1.3}}</td>
+                                  <td>{{beam.get_tx.up.1.0}}</td> <td>{{beam.get_tx.up.1.1}}</td> <td>{{beam.get_tx.up.1.2}}</td> <td>{{beam.get_tx.up.1.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.2.0}}</td> <td>{{abs_beams.0.get_tx.up.2.1}}</td> <td>{{abs_beams.0.get_tx.up.2.2}}</td> <td>{{abs_beams.0.get_tx.up.2.3}}</td>
+                                  <td>{{beam.get_tx.up.2.0}}</td> <td>{{beam.get_tx.up.2.1}}</td> <td>{{beam.get_tx.up.2.2}}</td> <td>{{beam.get_tx.up.2.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.3.0}}</td> <td>{{abs_beams.0.get_tx.up.3.1}}</td> <td>{{abs_beams.0.get_tx.up.3.2}}</td> <td>{{abs_beams.0.get_tx.up.3.3}}</td>
+                                  <td>{{beam.get_tx.up.3.0}}</td> <td>{{beam.get_tx.up.3.1}}</td> <td>{{beam.get_tx.up.3.2}}</td> <td>{{beam.get_tx.up.3.3}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> East Quarter
                               <table align="center" class="east_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.0.4}}</td> <td>{{abs_beams.0.get_tx.up.0.5}}</td> <td>{{abs_beams.0.get_tx.up.0.6}}</td> <td>{{abs_beams.0.get_tx.up.0.7}}</td>
+                                  <td>{{beam.get_tx.up.0.4}}</td> <td>{{beam.get_tx.up.0.5}}</td> <td>{{beam.get_tx.up.0.6}}</td> <td>{{beam.get_tx.up.0.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.1.4}}</td> <td>{{abs_beams.0.get_tx.up.1.5}}</td> <td>{{abs_beams.0.get_tx.up.1.6}}</td> <td>{{abs_beams.0.get_tx.up.1.7}}</td>
+                                  <td>{{beam.get_tx.up.1.4}}</td> <td>{{beam.get_tx.up.1.5}}</td> <td>{{beam.get_tx.up.1.6}}</td> <td>{{beam.get_tx.up.1.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.2.4}}</td> <td>{{abs_beams.0.get_tx.up.2.5}}</td> <td>{{abs_beams.0.get_tx.up.2.6}}</td> <td>{{abs_beams.0.get_tx.up.2.7}}</td>
+                                  <td>{{beam.get_tx.up.2.4}}</td> <td>{{beam.get_tx.up.2.5}}</td> <td>{{beam.get_tx.up.2.6}}</td> <td>{{beam.get_tx.up.2.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.3.4}}</td> <td>{{abs_beams.0.get_tx.up.3.5}}</td> <td>{{abs_beams.0.get_tx.up.3.6}}</td> <td>{{abs_beams.0.get_tx.up.3.7}}</td>
+                                  <td>{{beam.get_tx.up.3.4}}</td> <td>{{beam.get_tx.up.3.5}}</td> <td>{{beam.get_tx.up.3.6}}</td> <td>{{beam.get_tx.up.3.7}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> West Quarter
                               <table align="center" class="west_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.4.0}}</td> <td>{{abs_beams.0.get_tx.up.4.1}}</td> <td>{{abs_beams.0.get_tx.up.4.2}}</td> <td>{{abs_beams.0.get_tx.up.4.3}}</td>
+                                  <td>{{beam.get_tx.up.4.0}}</td> <td>{{beam.get_tx.up.4.1}}</td> <td>{{beam.get_tx.up.4.2}}</td> <td>{{beam.get_tx.up.4.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.5.0}}</td> <td>{{abs_beams.0.get_tx.up.5.1}}</td> <td>{{abs_beams.0.get_tx.up.5.2}}</td> <td>{{abs_beams.0.get_tx.up.5.3}}</td>
+                                  <td>{{beam.get_tx.up.5.0}}</td> <td>{{beam.get_tx.up.5.1}}</td> <td>{{beam.get_tx.up.5.2}}</td> <td>{{beam.get_tx.up.5.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.6.0}}</td> <td>{{abs_beams.0.get_tx.up.6.1}}</td> <td>{{abs_beams.0.get_tx.up.6.2}}</td> <td>{{abs_beams.0.get_tx.up.6.3}}</td>
+                                  <td>{{beam.get_tx.up.6.0}}</td> <td>{{beam.get_tx.up.6.1}}</td> <td>{{beam.get_tx.up.6.2}}</td> <td>{{beam.get_tx.up.6.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.7.0}}</td> <td>{{abs_beams.0.get_tx.up.7.1}}</td> <td>{{abs_beams.0.get_tx.up.7.2}}</td> <td>{{abs_beams.0.get_tx.up.7.3}}</td>
+                                  <td>{{beam.get_tx.up.7.0}}</td> <td>{{beam.get_tx.up.7.1}}</td> <td>{{beam.get_tx.up.7.2}}</td> <td>{{beam.get_tx.up.7.3}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> South Quarter
                               <table align="center" class="south_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.4.4}}</td> <td>{{abs_beams.0.get_tx.up.4.5}}</td> <td>{{abs_beams.0.get_tx.up.4.6}}</td> <td>{{abs_beams.0.get_tx.up.4.7}}</td>
+                                  <td>{{beam.get_tx.up.4.4}}</td> <td>{{beam.get_tx.up.4.5}}</td> <td>{{beam.get_tx.up.4.6}}</td> <td>{{beam.get_tx.up.4.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.5.4}}</td> <td>{{abs_beams.0.get_tx.up.5.5}}</td> <td>{{abs_beams.0.get_tx.up.5.6}}</td> <td>{{abs_beams.0.get_tx.up.5.7}}</td>
+                                  <td>{{beam.get_tx.up.5.4}}</td> <td>{{beam.get_tx.up.5.5}}</td> <td>{{beam.get_tx.up.5.6}}</td> <td>{{beam.get_tx.up.5.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.6.4}}</td> <td>{{abs_beams.0.get_tx.up.6.5}}</td> <td>{{abs_beams.0.get_tx.up.6.6}}</td> <td>{{abs_beams.0.get_tx.up.6.7}}</td>
+                                  <td>{{beam.get_tx.up.6.4}}</td> <td>{{beam.get_tx.up.6.5}}</td> <td>{{beam.get_tx.up.6.6}}</td> <td>{{beam.get_tx.up.6.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.up.7.4}}</td> <td>{{abs_beams.0.get_tx.up.7.5}}</td> <td>{{abs_beams.0.get_tx.up.7.6}}</td> <td>{{abs_beams.0.get_tx.up.7.7}}</td>
+                                  <td>{{beam.get_tx.up.7.4}}</td> <td>{{beam.get_tx.up.7.5}}</td> <td>{{beam.get_tx.up.7.6}}</td> <td>{{beam.get_tx.up.7.7}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> North Quarter
                               <table align="center" class="north_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.0.0}}</td> <td>{{abs_beams.0.get_rx.up.0.1}}</td> <td>{{abs_beams.0.get_rx.up.0.2}}</td> <td>{{abs_beams.0.get_rx.up.0.3}}</td>
+                                  <td>{{beam.get_rx.up.0.0}}</td> <td>{{beam.get_rx.up.0.1}}</td> <td>{{beam.get_rx.up.0.2}}</td> <td>{{beam.get_rx.up.0.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.1.0}}</td> <td>{{abs_beams.0.get_rx.up.1.1}}</td> <td>{{abs_beams.0.get_rx.up.1.2}}</td> <td>{{abs_beams.0.get_rx.up.1.3}}</td>
+                                  <td>{{beam.get_rx.up.1.0}}</td> <td>{{beam.get_rx.up.1.1}}</td> <td>{{beam.get_rx.up.1.2}}</td> <td>{{beam.get_rx.up.1.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.2.0}}</td> <td>{{abs_beams.0.get_rx.up.2.1}}</td> <td>{{abs_beams.0.get_rx.up.2.2}}</td> <td>{{abs_beams.0.get_rx.up.2.3}}</td>
+                                  <td>{{beam.get_rx.up.2.0}}</td> <td>{{beam.get_rx.up.2.1}}</td> <td>{{beam.get_rx.up.2.2}}</td> <td>{{beam.get_rx.up.2.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.3.0}}</td> <td>{{abs_beams.0.get_rx.up.3.1}}</td> <td>{{abs_beams.0.get_rx.up.3.2}}</td> <td>{{abs_beams.0.get_rx.up.3.3}}</td>
+                                  <td>{{beam.get_rx.up.3.0}}</td> <td>{{beam.get_rx.up.3.1}}</td> <td>{{beam.get_rx.up.3.2}}</td> <td>{{beam.get_rx.up.3.3}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> East Quarter
                               <table align="center" class="east_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.0.4}}</td> <td>{{abs_beams.0.get_rx.up.0.5}}</td> <td>{{abs_beams.0.get_rx.up.0.6}}</td> <td>{{abs_beams.0.get_rx.up.0.7}}</td>
+                                  <td>{{beam.get_rx.up.0.4}}</td> <td>{{beam.get_rx.up.0.5}}</td> <td>{{beam.get_rx.up.0.6}}</td> <td>{{beam.get_rx.up.0.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.1.4}}</td> <td>{{abs_beams.0.get_rx.up.1.5}}</td> <td>{{abs_beams.0.get_rx.up.1.6}}</td> <td>{{abs_beams.0.get_rx.up.1.7}}</td>
+                                  <td>{{beam.get_rx.up.1.4}}</td> <td>{{beam.get_rx.up.1.5}}</td> <td>{{beam.get_rx.up.1.6}}</td> <td>{{beam.get_rx.up.1.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.2.4}}</td> <td>{{abs_beams.0.get_rx.up.2.5}}</td> <td>{{abs_beams.0.get_rx.up.2.6}}</td> <td>{{abs_beams.0.get_rx.up.2.7}}</td>
+                                  <td>{{beam.get_rx.up.2.4}}</td> <td>{{beam.get_rx.up.2.5}}</td> <td>{{beam.get_rx.up.2.6}}</td> <td>{{beam.get_rx.up.2.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.3.4}}</td> <td>{{abs_beams.0.get_rx.up.3.5}}</td> <td>{{abs_beams.0.get_rx.up.3.6}}</td> <td>{{abs_beams.0.get_rx.up.3.7}}</td>
+                                  <td>{{beam.get_rx.up.3.4}}</td> <td>{{beam.get_rx.up.3.5}}</td> <td>{{beam.get_rx.up.3.6}}</td> <td>{{beam.get_rx.up.3.7}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> West Quarter
                               <table align="center" class="west_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.4.0}}</td> <td>{{abs_beams.0.get_rx.up.4.1}}</td> <td>{{abs_beams.0.get_rx.up.4.2}}</td> <td>{{abs_beams.0.get_rx.up.4.3}}</td>
+                                  <td>{{beam.get_rx.up.4.0}}</td> <td>{{beam.get_rx.up.4.1}}</td> <td>{{beam.get_rx.up.4.2}}</td> <td>{{beam.get_rx.up.4.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.5.0}}</td> <td>{{abs_beams.0.get_rx.up.5.1}}</td> <td>{{abs_beams.0.get_rx.up.5.2}}</td> <td>{{abs_beams.0.get_rx.up.5.3}}</td>
+                                  <td>{{beam.get_rx.up.5.0}}</td> <td>{{beam.get_rx.up.5.1}}</td> <td>{{beam.get_rx.up.5.2}}</td> <td>{{beam.get_rx.up.5.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.6.0}}</td> <td>{{abs_beams.0.get_rx.up.6.1}}</td> <td>{{abs_beams.0.get_rx.up.6.2}}</td> <td>{{abs_beams.0.get_rx.up.6.3}}</td>
+                                  <td>{{beam.get_rx.up.6.0}}</td> <td>{{beam.get_rx.up.6.1}}</td> <td>{{beam.get_rx.up.6.2}}</td> <td>{{beam.get_rx.up.6.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.7.0}}</td> <td>{{abs_beams.0.get_rx.up.7.1}}</td> <td>{{abs_beams.0.get_rx.up.7.2}}</td> <td>{{abs_beams.0.get_rx.up.7.3}}</td>
+                                  <td>{{beam.get_rx.up.7.0}}</td> <td>{{beam.get_rx.up.7.1}}</td> <td>{{beam.get_rx.up.7.2}}</td> <td>{{beam.get_rx.up.7.3}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> South Quarter
                               <table align="center" class="south_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.4.4}}</td> <td>{{abs_beams.0.get_rx.up.4.5}}</td> <td>{{abs_beams.0.get_rx.up.4.6}}</td> <td>{{abs_beams.0.get_rx.up.4.7}}</td>
+                                  <td>{{beam.get_rx.up.4.4}}</td> <td>{{beam.get_rx.up.4.5}}</td> <td>{{beam.get_rx.up.4.6}}</td> <td>{{beam.get_rx.up.4.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.5.4}}</td> <td>{{abs_beams.0.get_rx.up.5.5}}</td> <td>{{abs_beams.0.get_rx.up.5.6}}</td> <td>{{abs_beams.0.get_rx.up.5.7}}</td>
+                                  <td>{{beam.get_rx.up.5.4}}</td> <td>{{beam.get_rx.up.5.5}}</td> <td>{{beam.get_rx.up.5.6}}</td> <td>{{beam.get_rx.up.5.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.6.4}}</td> <td>{{abs_beams.0.get_rx.up.6.5}}</td> <td>{{abs_beams.0.get_rx.up.6.6}}</td> <td>{{abs_beams.0.get_rx.up.6.7}}</td>
+                                  <td>{{beam.get_rx.up.6.4}}</td> <td>{{beam.get_rx.up.6.5}}</td> <td>{{beam.get_rx.up.6.6}}</td> <td>{{beam.get_rx.up.6.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.up.7.4}}</td> <td>{{abs_beams.0.get_rx.up.7.5}}</td> <td>{{abs_beams.0.get_rx.up.7.6}}</td> <td>{{abs_beams.0.get_rx.up.7.7}}</td>
+                                  <td>{{beam.get_rx.up.7.4}}</td> <td>{{beam.get_rx.up.7.5}}</td> <td>{{beam.get_rx.up.7.6}}</td> <td>{{beam.get_rx.up.7.7}}</td>
                                 </tr>
                               </table>
                             </td>
                   </table>
                   {% if not edit %}
-                    {% include "abs_pattern_img.html" %}
+                    {% include "abs_uppattern_img.html" %}
                   {% endif %}
                   <br>
                   <div id="up_ues" style="display: inline-block">
-                    Ues: {{abs_beams.0.get_up_ues}}
+                    Ues: {{beam.get_up_ues}}
                   </div>
                   <div style="margin-left: 70px; display: inline-block">
-                    <input type="checkbox" id="up_onlyrx" {% if abs_beams.0.get_up_onlyrx == True %} checked="True" {% endif %} disabled>
+                    <input type="checkbox" id="up_onlyrx" {% if beam.get_up_onlyrx == True %} checked="True" {% endif %} disabled>
                       Only RX
                     </input>
                   </div>
                           <tr>
                             <td> <b>North Quarter</b>
                               <table class="north_quarter">
-                                <tr>
+                                <tr> <td>{{beam.get_downvalues.0}}</td> <td>{{beam.get_downvalues.1}}</td> <td>{{beam.get_downvalues.2}}</td> <td>{{beam.get_downvalues.3}}</td> </tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
+                                <tr> <td>{{beam.get_downvalues.8}}</td> <td>{{beam.get_downvalues.9}}</td> <td>{{beam.get_downvalues.10}}</td> <td>{{beam.get_downvalues.11}}</td> </tr>
-                                </tr>
+                                <tr> <td>{{beam.get_downvalues.16}}</td> <td>{{beam.get_downvalues.17}}</td> <td>{{beam.get_downvalues.18}}</td> <td>{{beam.get_downvalues.19}}</td> </tr>
-                                <tr>
+                                <tr> <td>{{beam.get_downvalues.24}}</td> <td>{{beam.get_downvalues.25}}</td> <td>{{beam.get_downvalues.26}}</td> <td>{{beam.get_downvalues.27}}</td> </tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
-                                <tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
-                                <tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
                               </table>
                             </td>
                             <td> <b>East Quarter</b>
                               <table class="east_quarter">
-                                <tr>
+                                <tr> <td>{{beam.get_downvalues.4}}</td> <td>{{beam.get_downvalues.5}}</td> <td>{{beam.get_downvalues.6}}</td> <td>{{beam.get_downvalues.7}}</td> </tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
+                                <tr> <td>{{beam.get_downvalues.12}}</td> <td>{{beam.get_downvalues.13}}</td> <td>{{beam.get_downvalues.14}}</td> <td>{{beam.get_downvalues.15}}</td> </tr>
-                                </tr>
+                                <tr> <td>{{beam.get_downvalues.20}}</td> <td>{{beam.get_downvalues.21}}</td> <td>{{beam.get_downvalues.22}}</td> <td>{{beam.get_downvalues.23}}</td> </tr>
-                                <tr>
+                                <tr> <td>{{beam.get_downvalues.28}}</td> <td>{{beam.get_downvalues.29}}</td> <td>{{beam.get_downvalues.30}}</td> <td>{{beam.get_downvalues.31}}</td> </tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
-                                <tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
-                                <tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
                               </table>
                             </td>
                           </tr>
                           <tr>
                             <td> <b>West Quarter</b>
                               <table class="west_quarter">
-                                <tr>
+                                <tr> <td>{{beam.get_downvalues.32}}</td> <td>{{beam.get_downvalues.33}}</td> <td>{{beam.get_downvalues.34}}</td> <td>{{beam.get_downvalues.35}}</td> </tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
+                                <tr> <td>{{beam.get_downvalues.40}}</td> <td>{{beam.get_downvalues.41}}</td> <td>{{beam.get_downvalues.42}}</td> <td>{{beam.get_downvalues.43}}</td> </tr>
-                                </tr>
+                                <tr> <td>{{beam.get_downvalues.48}}</td> <td>{{beam.get_downvalues.49}}</td> <td>{{beam.get_downvalues.50}}</td> <td>{{beam.get_downvalues.51}}</td> </tr>
-                                <tr>
+                                <tr> <td>{{beam.get_downvalues.56}}</td> <td>{{beam.get_downvalues.57}}</td> <td>{{beam.get_downvalues.58}}</td> <td>{{beam.get_downvalues.59}}</td> </tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
-                                <tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
-                                <tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
                               </table>
                             </td>
                             <td> <b>South Quarter</b>
                               <table class="south_quarter">
-                                <tr>
+                                <tr> <td>{{beam.get_downvalues.36}}</td> <td>{{beam.get_downvalues.37}}</td> <td>{{beam.get_downvalues.38}}</td> <td>{{beam.get_downvalues.39}}</td> </tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
+                                <tr> <td>{{beam.get_downvalues.44}}</td> <td>{{beam.get_downvalues.45}}</td> <td>{{beam.get_downvalues.46}}</td> <td>{{beam.get_downvalues.47}}</td> </tr>
-                                </tr>
+                                <tr> <td>{{beam.get_downvalues.52}}</td> <td>{{beam.get_downvalues.53}}</td> <td>{{beam.get_downvalues.54}}</td> <td>{{beam.get_downvalues.55}}</td> </tr>
-                                <tr>
+                                <tr> <td>{{beam.get_downvalues.60}}</td> <td>{{beam.get_downvalues.61}}</td> <td>{{beam.get_downvalues.62}}</td> <td>{{beam.get_downvalues.63}}</td> </tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
-                                <tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
-                                <tr>
-                                  <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                </tr>
                               </table>
                             </td>
                           </tr>
                             <td> <b>North Quarter</b>
                               <table align="center" class="north_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.0.0}}</td> <td>{{abs_beams.0.get_tx.down.0.1}}</td> <td>{{abs_beams.0.get_tx.down.0.2}}</td> <td>{{abs_beams.0.get_tx.down.0.3}}</td>
+                                  <td>{{beam.get_tx.down.0.0}}</td> <td>{{beam.get_tx.down.0.1}}</td> <td>{{beam.get_tx.down.0.2}}</td> <td>{{beam.get_tx.down.0.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.1.0}}</td> <td>{{abs_beams.0.get_tx.down.1.1}}</td> <td>{{abs_beams.0.get_tx.down.1.2}}</td> <td>{{abs_beams.0.get_tx.down.1.3}}</td>
+                                  <td>{{beam.get_tx.down.1.0}}</td> <td>{{beam.get_tx.down.1.1}}</td> <td>{{beam.get_tx.down.1.2}}</td> <td>{{beam.get_tx.down.1.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.2.0}}</td> <td>{{abs_beams.0.get_tx.down.2.1}}</td> <td>{{abs_beams.0.get_tx.down.2.2}}</td> <td>{{abs_beams.0.get_tx.down.2.3}}</td>
+                                  <td>{{beam.get_tx.down.2.0}}</td> <td>{{beam.get_tx.down.2.1}}</td> <td>{{beam.get_tx.down.2.2}}</td> <td>{{beam.get_tx.down.2.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.3.0}}</td> <td>{{abs_beams.0.get_tx.down.3.1}}</td> <td>{{abs_beams.0.get_tx.down.3.2}}</td> <td>{{abs_beams.0.get_tx.down.3.3}}</td>
+                                  <td>{{beam.get_tx.down.3.0}}</td> <td>{{beam.get_tx.down.3.1}}</td> <td>{{beam.get_tx.down.3.2}}</td> <td>{{beam.get_tx.down.3.3}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> <b>East Quarter</b>
                               <table align="center" class="east_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.0.4}}</td> <td>{{abs_beams.0.get_tx.down.0.5}}</td> <td>{{abs_beams.0.get_tx.down.0.6}}</td> <td>{{abs_beams.0.get_tx.down.0.7}}</td>
+                                  <td>{{beam.get_tx.down.0.4}}</td> <td>{{beam.get_tx.down.0.5}}</td> <td>{{beam.get_tx.down.0.6}}</td> <td>{{beam.get_tx.down.0.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.1.4}}</td> <td>{{abs_beams.0.get_tx.down.1.5}}</td> <td>{{abs_beams.0.get_tx.down.1.6}}</td> <td>{{abs_beams.0.get_tx.down.1.7}}</td>
+                                  <td>{{beam.get_tx.down.1.4}}</td> <td>{{beam.get_tx.down.1.5}}</td> <td>{{beam.get_tx.down.1.6}}</td> <td>{{beam.get_tx.down.1.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.2.4}}</td> <td>{{abs_beams.0.get_tx.down.2.5}}</td> <td>{{abs_beams.0.get_tx.down.2.6}}</td> <td>{{abs_beams.0.get_tx.down.2.7}}</td>
+                                  <td>{{beam.get_tx.down.2.4}}</td> <td>{{beam.get_tx.down.2.5}}</td> <td>{{beam.get_tx.down.2.6}}</td> <td>{{beam.get_tx.down.2.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.3.4}}</td> <td>{{abs_beams.0.get_tx.down.3.5}}</td> <td>{{abs_beams.0.get_tx.down.3.6}}</td> <td>{{abs_beams.0.get_tx.down.3.7}}</td>
+                                  <td>{{beam.get_tx.down.3.4}}</td> <td>{{beam.get_tx.down.3.5}}</td> <td>{{beam.get_tx.down.3.6}}</td> <td>{{beam.get_tx.down.3.7}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> <b>West Quarter</b>
                               <table align="center" class="west_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.4.0}}</td> <td>{{abs_beams.0.get_tx.down.4.1}}</td> <td>{{abs_beams.0.get_tx.down.4.2}}</td> <td>{{abs_beams.0.get_tx.down.4.3}}</td>
+                                  <td>{{beam.get_tx.down.4.0}}</td> <td>{{beam.get_tx.down.4.1}}</td> <td>{{beam.get_tx.down.4.2}}</td> <td>{{beam.get_tx.down.4.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.5.0}}</td> <td>{{abs_beams.0.get_tx.down.5.1}}</td> <td>{{abs_beams.0.get_tx.down.5.2}}</td> <td>{{abs_beams.0.get_tx.down.5.3}}</td>
+                                  <td>{{beam.get_tx.down.5.0}}</td> <td>{{beam.get_tx.down.5.1}}</td> <td>{{beam.get_tx.down.5.2}}</td> <td>{{beam.get_tx.down.5.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.6.0}}</td> <td>{{abs_beams.0.get_tx.down.6.1}}</td> <td>{{abs_beams.0.get_tx.down.6.2}}</td> <td>{{abs_beams.0.get_tx.down.6.3}}</td>
+                                  <td>{{beam.get_tx.down.6.0}}</td> <td>{{beam.get_tx.down.6.1}}</td> <td>{{beam.get_tx.down.6.2}}</td> <td>{{beam.get_tx.down.6.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.7.0}}</td> <td>{{abs_beams.0.get_tx.down.7.1}}</td> <td>{{abs_beams.0.get_tx.down.7.2}}</td> <td>{{abs_beams.0.get_tx.down.7.3}}</td>
+                                  <td>{{beam.get_tx.down.7.0}}</td> <td>{{beam.get_tx.down.7.1}}</td> <td>{{beam.get_tx.down.7.2}}</td> <td>{{beam.get_tx.down.7.3}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> <b>South Quarter</b>
                               <table align="center" class="south_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.4.4}}</td> <td>{{abs_beams.0.get_tx.down.4.5}}</td> <td>{{abs_beams.0.get_tx.down.4.6}}</td> <td>{{abs_beams.0.get_tx.down.4.7}}</td>
+                                  <td>{{beam.get_tx.down.4.4}}</td> <td>{{beam.get_tx.down.4.5}}</td> <td>{{beam.get_tx.down.4.6}}</td> <td>{{beam.get_tx.down.4.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.5.4}}</td> <td>{{abs_beams.0.get_tx.down.5.5}}</td> <td>{{abs_beams.0.get_tx.down.5.6}}</td> <td>{{abs_beams.0.get_tx.down.5.7}}</td>
+                                  <td>{{beam.get_tx.down.5.4}}</td> <td>{{beam.get_tx.down.5.5}}</td> <td>{{beam.get_tx.down.5.6}}</td> <td>{{beam.get_tx.down.5.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.6.4}}</td> <td>{{abs_beams.0.get_tx.down.6.5}}</td> <td>{{abs_beams.0.get_tx.down.6.6}}</td> <td>{{abs_beams.0.get_tx.down.6.7}}</td>
+                                  <td>{{beam.get_tx.down.6.4}}</td> <td>{{beam.get_tx.down.6.5}}</td> <td>{{beam.get_tx.down.6.6}}</td> <td>{{beam.get_tx.down.6.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_tx.down.7.4}}</td> <td>{{abs_beams.0.get_tx.down.7.5}}</td> <td>{{abs_beams.0.get_tx.down.7.6}}</td> <td>{{abs_beams.0.get_tx.down.7.7}}</td>
+                                  <td>{{beam.get_tx.down.7.4}}</td> <td>{{beam.get_tx.down.7.5}}</td> <td>{{beam.get_tx.down.7.6}}</td> <td>{{beam.get_tx.down.7.7}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> <b>North Quarter</b>
                               <table align="center" class="north_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.0.0}}</td> <td>{{abs_beams.0.get_rx.down.0.1}}</td> <td>{{abs_beams.0.get_rx.down.0.2}}</td> <td>{{abs_beams.0.get_rx.down.0.3}}</td>
+                                  <td>{{beam.get_rx.down.0.0}}</td> <td>{{beam.get_rx.down.0.1}}</td> <td>{{beam.get_rx.down.0.2}}</td> <td>{{beam.get_rx.down.0.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.1.0}}</td> <td>{{abs_beams.0.get_rx.down.1.1}}</td> <td>{{abs_beams.0.get_rx.down.1.2}}</td> <td>{{abs_beams.0.get_rx.down.1.3}}</td>
+                                  <td>{{beam.get_rx.down.1.0}}</td> <td>{{beam.get_rx.down.1.1}}</td> <td>{{beam.get_rx.down.1.2}}</td> <td>{{beam.get_rx.down.1.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.2.0}}</td> <td>{{abs_beams.0.get_rx.down.2.1}}</td> <td>{{abs_beams.0.get_rx.down.2.2}}</td> <td>{{abs_beams.0.get_rx.down.2.3}}</td>
+                                  <td>{{beam.get_rx.down.2.0}}</td> <td>{{beam.get_rx.down.2.1}}</td> <td>{{beam.get_rx.down.2.2}}</td> <td>{{beam.get_rx.down.2.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.3.0}}</td> <td>{{abs_beams.0.get_rx.down.3.1}}</td> <td>{{abs_beams.0.get_rx.down.3.2}}</td> <td>{{abs_beams.0.get_rx.down.3.3}}</td>
+                                  <td>{{beam.get_rx.down.3.0}}</td> <td>{{beam.get_rx.down.3.1}}</td> <td>{{beam.get_rx.down.3.2}}</td> <td>{{beam.get_rx.down.3.3}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> <b>East Quarter</b>
                               <table align="center" class="east_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.0.4}}</td> <td>{{abs_beams.0.get_rx.down.0.5}}</td> <td>{{abs_beams.0.get_rx.down.0.6}}</td> <td>{{abs_beams.0.get_rx.down.0.7}}</td>
+                                  <td>{{beam.get_rx.down.0.4}}</td> <td>{{beam.get_rx.down.0.5}}</td> <td>{{beam.get_rx.down.0.6}}</td> <td>{{beam.get_rx.down.0.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.1.4}}</td> <td>{{abs_beams.0.get_rx.down.1.5}}</td> <td>{{abs_beams.0.get_rx.down.1.6}}</td> <td>{{abs_beams.0.get_rx.down.1.7}}</td>
+                                  <td>{{beam.get_rx.down.1.4}}</td> <td>{{beam.get_rx.down.1.5}}</td> <td>{{beam.get_rx.down.1.6}}</td> <td>{{beam.get_rx.down.1.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.2.4}}</td> <td>{{abs_beams.0.get_rx.down.2.5}}</td> <td>{{abs_beams.0.get_rx.down.2.6}}</td> <td>{{abs_beams.0.get_rx.down.2.7}}</td>
+                                  <td>{{beam.get_rx.down.2.4}}</td> <td>{{beam.get_rx.down.2.5}}</td> <td>{{beam.get_rx.down.2.6}}</td> <td>{{beam.get_rx.down.2.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.3.4}}</td> <td>{{abs_beams.0.get_rx.down.3.5}}</td> <td>{{abs_beams.0.get_rx.down.3.6}}</td> <td>{{abs_beams.0.get_rx.down.3.7}}</td>
+                                  <td>{{beam.get_rx.down.3.4}}</td> <td>{{beam.get_rx.down.3.5}}</td> <td>{{beam.get_rx.down.3.6}}</td> <td>{{beam.get_rx.down.3.7}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> <b>West Quarter</b>
                               <table align="center" class="west_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.4.0}}</td> <td>{{abs_beams.0.get_rx.down.4.1}}</td> <td>{{abs_beams.0.get_rx.down.4.2}}</td> <td>{{abs_beams.0.get_rx.down.4.3}}</td>
+                                  <td>{{beam.get_rx.down.4.0}}</td> <td>{{beam.get_rx.down.4.1}}</td> <td>{{beam.get_rx.down.4.2}}</td> <td>{{beam.get_rx.down.4.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.5.0}}</td> <td>{{abs_beams.0.get_rx.down.5.1}}</td> <td>{{abs_beams.0.get_rx.down.5.2}}</td> <td>{{abs_beams.0.get_rx.down.5.3}}</td>
+                                  <td>{{beam.get_rx.down.5.0}}</td> <td>{{beam.get_rx.down.5.1}}</td> <td>{{beam.get_rx.down.5.2}}</td> <td>{{beam.get_rx.down.5.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.6.0}}</td> <td>{{abs_beams.0.get_rx.down.6.1}}</td> <td>{{abs_beams.0.get_rx.down.6.2}}</td> <td>{{abs_beams.0.get_rx.down.6.3}}</td>
+                                  <td>{{beam.get_rx.down.6.0}}</td> <td>{{beam.get_rx.down.6.1}}</td> <td>{{beam.get_rx.down.6.2}}</td> <td>{{beam.get_rx.down.6.3}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.7.0}}</td> <td>{{abs_beams.0.get_rx.down.7.1}}</td> <td>{{abs_beams.0.get_rx.down.7.2}}</td> <td>{{abs_beams.0.get_rx.down.7.3}}</td>
+                                  <td>{{beam.get_rx.down.7.0}}</td> <td>{{beam.get_rx.down.7.1}}</td> <td>{{beam.get_rx.down.7.2}}</td> <td>{{beam.get_rx.down.7.3}}</td>
                                 </tr>
                               </table>
                             </td>
                             <td> <b>South Quarter</b>
                               <table class="south_quarter">
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.4.4}}</td> <td>{{abs_beams.0.get_rx.down.4.5}}</td> <td>{{abs_beams.0.get_rx.down.4.6}}</td> <td>{{abs_beams.0.get_rx.down.4.7}}</td>
+                                  <td>{{beam.get_rx.down.4.4}}</td> <td>{{beam.get_rx.down.4.5}}</td> <td>{{beam.get_rx.down.4.6}}</td> <td>{{beam.get_rx.down.4.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.5.4}}</td> <td>{{abs_beams.0.get_rx.down.5.5}}</td> <td>{{abs_beams.0.get_rx.down.5.6}}</td> <td>{{abs_beams.0.get_rx.down.5.7}}</td>
+                                  <td>{{beam.get_rx.down.5.4}}</td> <td>{{beam.get_rx.down.5.5}}</td> <td>{{beam.get_rx.down.5.6}}</td> <td>{{beam.get_rx.down.5.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.6.4}}</td> <td>{{abs_beams.0.get_rx.down.6.5}}</td> <td>{{abs_beams.0.get_rx.down.6.6}}</td> <td>{{abs_beams.0.get_rx.down.6.7}}</td>
+                                  <td>{{beam.get_rx.down.6.4}}</td> <td>{{beam.get_rx.down.6.5}}</td> <td>{{beam.get_rx.down.6.6}}</td> <td>{{beam.get_rx.down.6.7}}</td>
                                 </tr>
                                 <tr>
-                                  <td>{{abs_beams.0.get_rx.down.7.4}}</td> <td>{{abs_beams.0.get_rx.down.7.5}}</td> <td>{{abs_beams.0.get_rx.down.7.6}}</td> <td>{{abs_beams.0.get_rx.down.7.7}}</td>
+                                  <td>{{beam.get_rx.down.7.4}}</td> <td>{{beam.get_rx.down.7.5}}</td> <td>{{beam.get_rx.down.7.6}}</td> <td>{{beam.get_rx.down.7.7}}</td>
                                 </tr>
                               </table>
                             </td>
                   </table>
                   {% if not edit %}
-                    {% include "abs_pattern_img.html" %}
+                    {% include "abs_downpattern_img.html" %}
                   {% endif %}
                   <br>
                   <div id="down_ues" style="display: inline-block">
-                    Ues: {{abs_beams.0.get_down_ues}}
+                    Ues: {{beam.get_down_ues}}
                   </div>
                   <div style="margin-left: 70px; display: inline-block">
-                    <input type="checkbox" id="up_onlyrx" {% if abs_beams.0.get_down_onlyrx == True %} checked="True" {% endif %} disabled>
+                    <input type="checkbox" id="up_onlyrx" {% if beam.get_down_onlyrx == True %} checked="True" {% endif %} disabled>
                       Only RX
                     </input>
                   </div>

apps/abs/templates/abs_patterns.html +24 -17

             </style>
             {% if abs_beams %}
               <div>
                 <h4>Beams:</h4>
                 <div class="container">
-                  <ul class="nav nav-pills">
+                  <div class="btn-group">
+                    {% for abs_beam in abs_beams %}
-                  {% for beam in abs_beams %}
+                      <button id="bt_beam{{ forloop.counter }}" type="button"  class="btn btn-default">{{ forloop.counter }}</button>
-                  <li {% if forloop.counter == 1 %} class="active" {% endif %}>
+                    {% endfor %}
-                    <a  data-toggle="pill" id="button-{{ forloop.counter }}" href="#">{{ forloop.counter }}</a>
+                  </div>
-                  </li>
-                  {% endfor %}
-                  </ul>
                 </div>
-              </div>
+              </div>
               <br>
-              {% include "abs_pattern.html" %}
-              <br>
+              {% if beam %}
+                {% include "abs_pattern.html" %}
+              {% endif %}
             {% else %}
               <div>
               </div>
             {% endif %}
-            {% endblock %}
             <script>
-            function ChangeColor() {
+            {% for abs_beam in abs_beams %}
-                document.getElementById("button_1").style.backgroundColor = "#2c3e50";
+              $("#bt_beam{{ forloop.counter }}").click(function() {
-                document.getElementById("button_1").style.color = "#ecf0f1";
+                document.location = "{% url 'url_plot_abs_pattern' abs_beam.abs_conf.id abs_beam.id %}";
+              });
+            {% endfor %}
+            //function ChangeColor() {
+            //    document.getElementById("button_1").style.backgroundColor = "#2c3e50";
+            //    document.getElementById("button_1").style.color = "#ecf0f1";
+            //}
             </script>
+            {% endblock %}

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