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

This diff has been collapsed as it changes many lines, (1419 lines changed) Show them Hide them
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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

			@@ -0,0 +1,18
		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

			@@ -0,0 +1,51
		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

			@@ -0,0 +1,427
		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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		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
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		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
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		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
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		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
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		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
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		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>
-                                   <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>
-                                 <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>
+                                 <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>
+                                 <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> <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> <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>
                                </table>
                              </td>
                              <td> East Quarter
                                <table class="east_quarter">
-                                 <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>
-                                 <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>
+                                 <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>
+                                 <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> <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> <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>
                                </table>
                              </td>
                            </tr>
                            <tr>
                              <td> West Quarter
                                <table class="west_quarter">
-                                 <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>
-                                 <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>
+                                 <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>
+                                 <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> <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> <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>
                                </table>
                              </td>
                              <td> South Quarter
                                <table class="south_quarter">
-                                 <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>
-                                 <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>
+                                 <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>
+                                 <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> <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> <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>
                                </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>
-                                   <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>
-                                 <tr>
-                                   <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                 </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>
+                                 <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> <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> <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>
                                </table>
                              </td>
                              <td> <b>East Quarter</b>
                                <table class="east_quarter">
-                                 <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>
-                                 <tr>
-                                   <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                 </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>
+                                 <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> <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> <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>
                                </table>
                              </td>
                            </tr>
                            <tr>
                              <td> <b>West Quarter</b>
                                <table class="west_quarter">
-                                 <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>
-                                 <tr>
-                                   <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                 </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>
+                                 <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> <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> <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>
                                </table>
                              </td>
                              <td> <b>South Quarter</b>
                                <table class="south_quarter">
-                                 <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>
-                                 <tr>
-                                   <td>0.0</td> <td>0.0</td> <td>0.0</td> <td>0.0</td>
-                                 </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>
+                                 <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> <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> <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>
                                </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">
-                   {% for beam in abs_beams %}
-                   <li {% if forloop.counter == 1 %} class="active" {% endif %}>
-                     <a  data-toggle="pill" id="button-{{ forloop.counter }}" href="#">{{ forloop.counter }}</a>
-                   </li>
-                   {% endfor %}
-                   </ul>
+                   <div class="btn-group">
+                     {% for abs_beam in abs_beams %}
+                       <button id="bt_beam{{ forloop.counter }}" type="button"  class="btn btn-default">{{ forloop.counter }}</button>
+                     {% endfor %}
+                   </div>
                  </div>
-               </div>
+               </div>
                <br>
-               {% include "abs_pattern.html" %}
-               <br>
+               {% if beam %}
+                 {% include "abs_pattern.html" %}
+               {% endif %}
              {% else %}
                <div>
                </div>
              {% endif %}
-             {% endblock %}
              <script>
-             function ChangeColor() {
-                 document.getElementById("button_1").style.backgroundColor = "#2c3e50";
-                 document.getElementById("button_1").style.color = "#ecf0f1";
+             }
+             {% for abs_beam in abs_beams %}
+               $("#bt_beam{{ forloop.counter }}").click(function() {
+                 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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