Graphics_OverJro.py
621 lines
| 22.7 KiB
| text/x-python
|
PythonLexer
Fiorella Quino
|
r178 | """ | ||
| The module GRAPHICS_OVERJRO.py gathers classes or/and functions to create graphics from OVER-JRO | ||||
| project (e.g. antenna patterns, skynoise, ...). | ||||
| MODULES CALLED: | ||||
| TIME, NUMPY, MATPLOTLIB, TIMETOOLS | ||||
| MODIFICATION HISTORY: | ||||
| Created by Ing. Freddy Galindo (frederickgalindo@gmail.com). ROJ Oct 18, 2009. | ||||
| """ | ||||
| import time | ||||
| import numpy | ||||
| import sys | ||||
| import os | ||||
| # set HOME environment variable to a directory the httpd server can write to | ||||
| #os.environ[ 'HOME' ] = '/usr/local/www/htdocs/overJro/tempReports' | ||||
| #os.environ[ 'HOME' ] = '/home/dsuarez/Pictures' | ||||
| #os.environ[ 'HOME' ] = '/tmp/' | ||||
| import matplotlib | ||||
| #if ide==1: | ||||
| # matplotlib.use('Qt4Agg') | ||||
| #elif ide==2: | ||||
| # matplotlib.use("Agg") | ||||
| #else: | ||||
| # matplotlib.use('TKAgg') | ||||
| #matplotlib.use("Agg") | ||||
| #matplotlib.interactive(1) | ||||
| import matplotlib.pyplot | ||||
| #import Numeric | ||||
| #import scipy | ||||
| import scipy.interpolate | ||||
| import Astro_Coords | ||||
| import TimeTools | ||||
| import Graphics_Miscens | ||||
| import Misc_Routines | ||||
| class AntPatternPlot: | ||||
| def __init__(self): | ||||
| """ | ||||
| AntPatternPlot creates an object to call methods to plot the antenna pattern. | ||||
| Modification History | ||||
| -------------------- | ||||
| Created by Freddy Galindo, ROJ, 06 October 2009. | ||||
| """ | ||||
Juan C. Espinoza
|
r180 | |||
| self.fig = matplotlib.pyplot.figure(figsize=(8,8), facecolor='white') | ||||
| self.ax = self.fig.add_subplot(111) | ||||
|
Fiorella Quino
|
r178 | |||
|
Juan C. Espinoza
|
r180 | def contPattern(self,iplot=0,gpath='',filename='',mesg='',amp=None ,x=None ,y=None ,getCut=None,title='', save=True): | ||
|
Fiorella Quino
|
r178 | """ | ||
| contPattern plots a contour map of the antenna pattern. | ||||
| Parameters | ||||
| ---------- | ||||
| iplot = A integer to specify if the plot is the first, second, ... The default va- | ||||
| lue is 0. | ||||
| Examples | ||||
| -------- | ||||
| >> Over_Jro.JroPattern(pattern=2).contPattern() | ||||
| Modification history | ||||
| -------------------- | ||||
| Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009. | ||||
| """ | ||||
| if getCut == 1: | ||||
| return | ||||
| xmax = numpy.max(x) | ||||
| xmin = numpy.min(x) | ||||
| ymax = numpy.max(y) | ||||
| ymin = numpy.min(y) | ||||
| levels = numpy.array([1e-3,1e-2,1e-1,0.5,1.0]) | ||||
| tmp = numpy.round(10*numpy.log10(levels),decimals=1) | ||||
| labels = range(5) | ||||
| for i in numpy.arange(5):labels[i] = str(numpy.int(tmp[i])) | ||||
| colors = ((0,0,1.),(0,170/255.,0),(127/255.,1.,0),(1.,109/255.,0),(128/255.,0,0)) | ||||
|
Juan C. Espinoza
|
r180 | CS = self.ax.contour(x,y,amp.transpose(),levels,colors=colors) | ||
|
Fiorella Quino
|
r178 | fmt = {} | ||
|
Juan C. Espinoza
|
r180 | for l,s in zip(CS.levels,labels): | ||
| fmt[l] = s | ||||
| self.ax.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.) | ||||
| self.ax.annotate(mesg,xy=(0,0),xytext=(0.01,0.01),xycoords='figure fraction') | ||||
| self.ax.clabel(CS,CS.levels,inline=True,fmt=fmt,fontsize=10) | ||||
| self.ax.set_xlim(xmin,xmax) | ||||
| self.ax.set_ylim(ymin,ymax) | ||||
| self.ax.set_title("Total Pattern: " + title) | ||||
| self.ax.set_xlabel("West to South") | ||||
| self.ax.set_ylabel("West to North") | ||||
| self.ax.grid(True) | ||||
| if save: | ||||
| save_fig = os.path.join(gpath,filename) | ||||
| self.fig.savefig(save_fig,format='png') | ||||
| def close(self): | ||||
| matplotlib.pyplot.close(self.fig) | ||||
| def plotRaDec(self,gpath=None,filename=None,jd=2452640.5,ra_obs=None,xg=None,yg=None,x=None,y=None, save=True): | ||||
|
Fiorella Quino
|
r178 | """ | ||
| plotRaDec draws right ascension and declination lines on a JRO plane. This function | ||||
| must call after conPattern. | ||||
| Parameters | ||||
| ---------- | ||||
| jd = A scalar giving the Julian date. | ||||
| ra_obs = Scalar giving the right ascension of the observatory. | ||||
| xg = A 3-element array to specify .. | ||||
| yg = A 3-element array to specify .. | ||||
| Examples | ||||
| -------- | ||||
| >> Over_Jro.JroPattern(pattern=2).contPattern() | ||||
| >> Over_Jro.JroPattern(pattern=2).plotRaDec(jd=jd,ra_obs=ra_obs,xg=xg,yg=yg) | ||||
| Modification history | ||||
| -------------------- | ||||
| Converted to Python by Freddy R. Galindo, ROJ, 06 October 2009. | ||||
| """ | ||||
| # Finding RA of observatory for a specific date | ||||
|
Juan C. Espinoza
|
r180 | if ra_obs is None:ra_obs = numpy.array([23.37060849]) | ||
| if xg is None:xg = numpy.array([0.62918474,-0.77725579,0.]) | ||||
| if yg is None:yg = numpy.array([0.77700346,0.62898048,0.02547905]) | ||||
|
Fiorella Quino
|
r178 | |||
| # Getting HA and DEC axes | ||||
| mindec = -28; maxdec = 4; incdec = 2. | ||||
| ndec = numpy.int((maxdec - mindec)/incdec) + 1 | ||||
| minha = -20; maxha = 20; incha = 2. | ||||
| nha = numpy.int((maxha - minha)/incha) + 1 | ||||
|
Juan C. Espinoza
|
r180 | #mcosx = numpy.zeros((nha,ndec)) | ||
| #mcosy = numpy.zeros((nha,ndec)) | ||||
|
Fiorella Quino
|
r178 | |||
| ha_axes = numpy.reshape(numpy.arange(nha)*incha + minha,(nha,1)) | ||||
| ones_dec = numpy.reshape(numpy.zeros(ndec) + 1,(ndec,1)) | ||||
| ha_axes = numpy.dot(ha_axes,ones_dec.transpose()) | ||||
| ha_axes2 = numpy.array(ra_obs - ha_axes) | ||||
| dec_axes = numpy.reshape(numpy.arange(ndec)*incdec + mindec,(ndec,1)) | ||||
| ones_ra = numpy.reshape(numpy.zeros(nha) + 1,(nha,1)) | ||||
| dec_axes = numpy.dot(ones_ra,dec_axes.transpose()) | ||||
| dec_axes2 = numpy.array(dec_axes) | ||||
| ObjHor = Astro_Coords.Equatorial(ha_axes2,dec_axes2,jd) | ||||
| [alt,az,ha] = ObjHor.change2AltAz() | ||||
| z = numpy.transpose(alt)*Misc_Routines.CoFactors.d2r ; z = z.flatten() | ||||
| az = numpy.transpose(az)*Misc_Routines.CoFactors.d2r ; az = az.flatten() | ||||
| vect = numpy.array([numpy.cos(z)*numpy.sin(az),numpy.cos(z)*numpy.cos(az),numpy.sin(z)]) | ||||
| xg = numpy.atleast_2d(xg) | ||||
| dcosx = numpy.array(numpy.dot(xg,vect)) | ||||
| yg = numpy.atleast_2d(yg) | ||||
| dcosy = numpy.array(numpy.dot(yg,vect)) | ||||
| mcosx = dcosx.reshape(ndec,nha) | ||||
| mcosy = dcosy.reshape(ndec,nha) | ||||
| # Defining NAN for points outof limits. | ||||
| xmax = numpy.max(x) | ||||
| xmin = numpy.min(x) | ||||
| ymax = numpy.max(y) | ||||
| ymin = numpy.min(y) | ||||
| factor = 1.3 | ||||
| noval = numpy.where((mcosx>(xmax*factor)) | (mcosx<(xmin*factor))) | ||||
| if noval[0].size>0:mcosx[noval] = numpy.nan | ||||
| noval = numpy.where((mcosy>(ymax*factor)) | (mcosy<(ymin*factor))) | ||||
| if noval[0].size>0:mcosy[noval] = numpy.nan | ||||
| # Plotting HA and declination grid. | ||||
| iha0 = numpy.int((0 - minha)/incha) | ||||
| idec0 = numpy.int((-14 - mindec)/incdec) | ||||
| colorgrid = (1.,109/255.,0) | ||||
|
Juan C. Espinoza
|
r180 | self.ax.plot(mcosx.transpose(),mcosy.transpose(),color=colorgrid,linestyle='--') | ||
|
Fiorella Quino
|
r178 | for idec in numpy.arange(ndec): | ||
| if idec != idec0: | ||||
| valx = (mcosx[idec,iha0]<=xmax) & (mcosx[idec,iha0]>=xmin) | ||||
| valy = (mcosy[idec,iha0]<=ymax) & (mcosy[idec,iha0]>=ymin) | ||||
| if valx & valy: | ||||
| text = str(numpy.int(mindec + incdec*idec))+'$^o$' | ||||
|
Juan C. Espinoza
|
r180 | self.ax.text(mcosx[idec,iha0],mcosy[idec,iha0],text) | ||
|
Fiorella Quino
|
r178 | |||
| matplotlib.pyplot.plot(mcosx,mcosy,color=colorgrid,linestyle='--') | ||||
| for iha in numpy.arange(nha): | ||||
| if iha != iha0: | ||||
| valx = (mcosx[idec0,iha]<=xmax) & (mcosx[idec0,iha]>=xmin) | ||||
| valy = (mcosy[idec0,iha]<=ymax) & (mcosy[idec0,iha]>=ymin) | ||||
| if valx & valy: | ||||
| text = str(4*numpy.int(minha + incha*iha))+"'" | ||||
|
Juan C. Espinoza
|
r180 | self.ax.text(mcosx[idec0,iha],mcosy[idec0,iha],text) | ||
| if save: | ||||
| save_fig = os.path.join(gpath,filename) | ||||
| matplotlib.pyplot.savefig(save_fig,format='png') | ||||
|
Fiorella Quino
|
r178 | |||
|
Juan C. Espinoza
|
r180 | def plotBField(self,gpath,filename,dcos,alpha, nlon, nlat, dcosxrange, dcosyrange, heights, alpha_i, save=True): | ||
| """ | ||||
| plotBField draws the magnetic field in a directional cosines plot. | ||||
| Parameters | ||||
| ---------- | ||||
| dcos = An 4-dimensional array giving the directional cosines of the magnetic field | ||||
| over the desired place. | ||||
| alpha = An 3-dimensional array giving the angle of the magnetic field over the desi- | ||||
| red place. | ||||
| nlon = An integer to specify the number of elements per longitude. | ||||
| nlat = An integer to specify the number of elements per latitude. | ||||
| dcosxrange = A 2-element array giving the range of the directional cosines in the | ||||
| "x" axis. | ||||
| dcosyrange = A 2-element array giving the range of the directional cosines in the | ||||
| "y" axis. | ||||
| 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. | ||||
| alpha_i = Angle to interpolate the magnetic field. | ||||
| Modification History | ||||
| -------------------- | ||||
| Converted to Python by Freddy R. Galindo, ROJ, 07 October 2009. | ||||
| """ | ||||
| handles = [] | ||||
| objects = [] | ||||
| colors = ['k','m','c','b','g','r','y'] | ||||
| marker = ['-+','-*','-D','-x','-s','->','-o','-^'] | ||||
| alpha_location = numpy.zeros((nlon,2,heights.size)) | ||||
| for ih in numpy.arange(heights.size): | ||||
| alpha_location[:,0,ih] = dcos[:,0,ih,0] | ||||
| for ilon in numpy.arange(nlon): | ||||
| myx = (alpha[ilon,:,ih])[::-1] | ||||
| myy = (dcos[ilon,:,ih,0])[::-1] | ||||
| tck = scipy.interpolate.splrep(myx,myy,s=0) | ||||
| mydcosx = scipy.interpolate.splev(alpha_i,tck,der=0) | ||||
| myx = (alpha[ilon,:,ih])[::-1] | ||||
| myy = (dcos[ilon,:,ih,1])[::-1] | ||||
| tck = scipy.interpolate.splrep(myx,myy,s=0) | ||||
| mydcosy = scipy.interpolate.splev(alpha_i,tck,der=0) | ||||
| alpha_location[ilon,:,ih] = numpy.array([mydcosx, mydcosy]) | ||||
| ObjFig, = self.ax.plot(alpha_location[:,0,ih],alpha_location[:,1,ih], | ||||
| marker[ih % 8],color=colors[numpy.int(ih/8)],ms=4.5,lw=0.5) | ||||
| handles.append(ObjFig) | ||||
| objects.append(numpy.str(heights[ih]) + ' km') | ||||
| self.ax.legend(handles,objects,loc="lower right", numpoints=1, handlelength=0.3, | ||||
| handletextpad=0.02, borderpad=0.3, labelspacing=0.1) | ||||
| if save: | ||||
| save_fig = os.path.join(gpath,filename) | ||||
| matplotlib.pyplot.savefig(save_fig,format='png') | ||||
|
Fiorella Quino
|
r178 | |||
| class BFieldPlot: | ||||
| def __init__(self): | ||||
| """ | ||||
| BFieldPlot creates an object for drawing magnetic Field lines over Jicamarca. | ||||
| Modification History | ||||
| -------------------- | ||||
| Created by Freddy Galindo, ROJ, 07 October 2009. | ||||
| """ | ||||
| self.alpha_location = 1 | ||||
| # pass | ||||
| def plotBField(self,gpath,filename,dcos,alpha, nlon, nlat, dcosxrange, dcosyrange, heights, alpha_i): | ||||
| """ | ||||
| plotBField draws the magnetic field in a directional cosines plot. | ||||
| Parameters | ||||
| ---------- | ||||
| dcos = An 4-dimensional array giving the directional cosines of the magnetic field | ||||
| over the desired place. | ||||
| alpha = An 3-dimensional array giving the angle of the magnetic field over the desi- | ||||
| red place. | ||||
| nlon = An integer to specify the number of elements per longitude. | ||||
| nlat = An integer to specify the number of elements per latitude. | ||||
| dcosxrange = A 2-element array giving the range of the directional cosines in the | ||||
| "x" axis. | ||||
| dcosyrange = A 2-element array giving the range of the directional cosines in the | ||||
| "y" axis. | ||||
| 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. | ||||
| alpha_i = Angle to interpolate the magnetic field. | ||||
| Modification History | ||||
| -------------------- | ||||
| Converted to Python by Freddy R. Galindo, ROJ, 07 October 2009. | ||||
| """ | ||||
| handles = [] | ||||
| objects = [] | ||||
| colors = ['k','m','c','b','g','r','y'] | ||||
| marker = ['-+','-*','-D','-x','-s','->','-o','-^'] | ||||
| alpha_location = numpy.zeros((nlon,2,heights.size)) | ||||
| for ih in numpy.arange(heights.size): | ||||
| alpha_location[:,0,ih] = dcos[:,0,ih,0] | ||||
| for ilon in numpy.arange(nlon): | ||||
| myx = (alpha[ilon,:,ih])[::-1] | ||||
| myy = (dcos[ilon,:,ih,0])[::-1] | ||||
| tck = scipy.interpolate.splrep(myx,myy,s=0) | ||||
| mydcosx = scipy.interpolate.splev(alpha_i,tck,der=0) | ||||
| myx = (alpha[ilon,:,ih])[::-1] | ||||
| myy = (dcos[ilon,:,ih,1])[::-1] | ||||
| tck = scipy.interpolate.splrep(myx,myy,s=0) | ||||
| mydcosy = scipy.interpolate.splev(alpha_i,tck,der=0) | ||||
| alpha_location[ilon,:,ih] = numpy.array([mydcosx, mydcosy]) | ||||
| ObjFig, = matplotlib.pyplot.plot(alpha_location[:,0,ih],alpha_location[:,1,ih], \ | ||||
| marker[ih % 8],color=colors[numpy.int(ih/8)],ms=4.5,lw=0.5) | ||||
| handles.append(ObjFig) | ||||
| objects.append(numpy.str(heights[ih]) + ' km') | ||||
| matplotlib.pyplot.xlim(dcosxrange[0],dcosxrange[1]) | ||||
| matplotlib.pyplot.ylim(dcosyrange[0],dcosyrange[1]) | ||||
| try: | ||||
| ObjlegB = matplotlib.pyplot.legend(handles,objects,loc="lower right", numpoints=1, handlelength=0.3, \ | ||||
| handletextpad=0.02, borderpad=0.3, labelspacing=0.1) | ||||
| except: | ||||
| ObjlegB = matplotlib.pyplot.legend(handles,objects,loc=[0.01,0.75], numpoints=1, handlelength=0, \ | ||||
| pad=0.015, handletextsep=0.02,labelsep=0.01) | ||||
| matplotlib.pyplot.setp(ObjlegB.get_texts(),fontsize='small') | ||||
| matplotlib.pyplot.gca().add_artist(ObjlegB) | ||||
| save_fig = os.path.join(gpath,filename) | ||||
| matplotlib.pyplot.savefig(save_fig,format='png') | ||||
| self.alpha_location = alpha_location | ||||
| class CelestialObjectsPlot: | ||||
| def __init__(self,jd,dec,tod,maxha_min,show_object=None): | ||||
| self.jd = jd | ||||
| self.dec = dec | ||||
| self.tod = tod | ||||
| self.maxha_min = maxha_min | ||||
| if show_object==None:show_object=numpy.zeros(4)+2 | ||||
| self.show_object = show_object | ||||
| self.dcosx_sun = 1 | ||||
| self.dcosy_sun = 1 | ||||
| self.ha_sun = 1 | ||||
| self.time_sun = 1 | ||||
| self.dcosx_moon = 1 | ||||
| self.dcosy_moon = 1 | ||||
| self.ha_moon = 1 | ||||
| self.time_moon = 1 | ||||
| self.dcosx_hydra = 1 | ||||
| self.dcosy_hydra = 1 | ||||
| self.ha_hydra = 1 | ||||
| self.time_hydra = 1 | ||||
| self.dcosx_galaxy = 1 | ||||
| self.dcosy_galaxy = 1 | ||||
| self.ha_galaxy = 1 | ||||
| self.time_galaxy = 1 | ||||
| def drawObject(self,glat,glon,xg,yg,dcosxrange,dcosyrange,gpath='',filename=''): | ||||
| jd = self.jd | ||||
| main_dec = self.dec | ||||
| tod = self.tod | ||||
| maxha_min = self.maxha_min | ||||
| mesg = "Drawing celestial objects over Observatory" | ||||
| # print mesg | ||||
| # if textid!=None:textid.append(mesg) | ||||
| maxlev = 24; minlev = 0; maxcol = 39; mincol = 10 | ||||
| handles = [] | ||||
| objects = ['$Sun$','$Moon$','$Hydra$','$Galaxy$'] | ||||
| marker = ['--^','--s','--*','--o'] | ||||
| # Getting RGB table to plot celestial object over Jicamarca | ||||
| colortable = Graphics_Miscens.ColorTable(table=1).readTable() | ||||
| for io in (numpy.arange(4)+1): | ||||
| if self.show_object[io]!=0: | ||||
| ObjBodies = Astro_Coords.CelestialBodies() | ||||
| if io==1: | ||||
| [ra,dec,sunlon,sunobliq] = ObjBodies.sunpos(jd) | ||||
| elif io==2: | ||||
| [ra,dec,dist,moonlon,moonlat] = ObjBodies.moonpos(jd) | ||||
| elif io==3: | ||||
| [ra,dec] = ObjBodies.hydrapos() | ||||
| elif io==4: | ||||
| [maxra,ra] = ObjBodies.skynoise_jro(dec_cut=main_dec) | ||||
| ra = maxra*15. | ||||
| dec = main_dec | ||||
| ObjEq = Astro_Coords.Equatorial(ra,dec,jd,lat=glat,lon=glon) | ||||
| [alt, az, ha] = ObjEq.change2AltAz() | ||||
| vect = numpy.array([az,alt]).transpose() | ||||
| vect = Misc_Routines.Vector(vect,direction=0).Polar2Rect() | ||||
| dcosx = numpy.array(numpy.dot(vect,xg)) | ||||
| dcosy = numpy.array(numpy.dot(vect,yg)) | ||||
| wrap = numpy.where(ha>=180.) | ||||
| if wrap[0].size>0:ha[wrap] = ha[wrap] - 360. | ||||
| val = numpy.where((numpy.abs(ha))<=(maxha_min*0.25)) | ||||
| if val[0].size>2: | ||||
| tod_1 = tod*1. | ||||
| shift_1 = numpy.where(tod>12.) | ||||
| tod_1[shift_1] = tod_1[shift_1] - 24. | ||||
| tod_2 = tod*1. | ||||
| shift_2 = numpy.where(tod<12.) | ||||
| tod_2[shift_2] = tod_2[shift_2] + 24. | ||||
| diff0 = numpy.nanmax(tod[val]) - numpy.nanmin(tod[val]) | ||||
| diff1 = numpy.nanmax(tod_1[val]) - numpy.nanmin(tod_1[val]) | ||||
| diff2 = numpy.nanmax(tod_2[val]) - numpy.nanmin(tod_2[val]) | ||||
| if ((diff0<=diff1) & (diff0<=diff2)): | ||||
| tod_0 = tod | ||||
| elif ((diff1<diff0) & (diff1<diff2)): | ||||
| tod_0 = tod_1 | ||||
| else: | ||||
| tod_0 = tod_2 | ||||
| if io==1: | ||||
| self.dcosx_sun = dcosx[val] | ||||
| self.dcosy_sun = dcosy[val] | ||||
| self.ha_sun = ha[val] | ||||
| self.time_sun = numpy.median(tod_0[val]) | ||||
| elif io==2: | ||||
| self.dcosx_moon = dcosx[val] | ||||
| self.dcosy_moon = dcosy[val] | ||||
| self.ha_moon = ha[val] | ||||
| self.time_moon = numpy.median(tod_0[val]) | ||||
| elif io==3: | ||||
| self.dcosx_hydra = dcosx[val] | ||||
| self.dcosy_hydra = dcosy[val] | ||||
| self.ha_hydra = ha[val] | ||||
| self.time_hydra = numpy.mean(tod_0[val]) | ||||
| elif io==4: | ||||
| self.dcosx_galaxy = dcosx[val] | ||||
| self.dcosy_galaxy = dcosy[val] | ||||
| self.ha_galaxy = ha[val] | ||||
| self.time_galaxy = numpy.mean(tod_0[val]) | ||||
| index = numpy.mean(tod_0[val]) - minlev | ||||
| index = (index*(maxcol - mincol)/(maxlev - minlev)) + mincol | ||||
| index = numpy.int(index) | ||||
| figobjects, = matplotlib.pyplot.plot(dcosx[val],dcosy[val],marker[io-1],\ | ||||
| lw=1,ms=7,mew=0,color=tuple(colortable[:,index])) | ||||
| handles.append(figobjects) | ||||
| xmax = numpy.max(dcosxrange[1]) | ||||
| xmin = numpy.min(dcosxrange[0]) | ||||
| ymax = numpy.max(dcosyrange[1]) | ||||
| ymin = numpy.min(dcosyrange[0]) | ||||
| matplotlib.pyplot.xlim(xmin,xmax) | ||||
| matplotlib.pyplot.ylim(ymin,ymax) | ||||
| val = numpy.where(self.show_object[1:]>0) | ||||
| objects = numpy.array(objects) | ||||
| objects = list(objects[val]) | ||||
| try: | ||||
| ObjlegC = matplotlib.pyplot.legend(handles,objects,loc="lower left", numpoints=1, handlelength=0.3, \ | ||||
| borderpad=0.3, handletextpad=0.02,labelspacing=0.1) | ||||
| except: | ||||
| ObjlegC = matplotlib.pyplot.legend(handles,objects,loc=[0.01,0.75], numpoints=1, handlelength=0, \ | ||||
| pad=0.015, handletextsep=0.02,labelsep=0.01) | ||||
| matplotlib.pyplot.setp(ObjlegC.get_texts(),fontsize='small') | ||||
| ObjlegC.isaxes = False | ||||
| save_fig = os.path.join(gpath,filename) | ||||
| matplotlib.pyplot.savefig(save_fig,format='png') | ||||
| class PatternCutPlot: | ||||
| def __init__(self,nsubplots): | ||||
| self.nsubplots = nsubplots | ||||
| self.fig = None | ||||
| self.__plot_width = 8 | ||||
| if self.nsubplots == 5: | ||||
| self.__plot_height = 11 | ||||
| if self.nsubplots == 4: | ||||
| self.__plot_height = 9 | ||||
| if self.nsubplots == 3: | ||||
| self.__plot_height = 7 | ||||
| if self.nsubplots == 2: | ||||
| self.__plot_height = 5 | ||||
| if self.nsubplots == 1: | ||||
| self.__plot_height = 3 | ||||
| self.fig = matplotlib.pyplot.figure(num = 4,figsize = (self.__plot_width, self.__plot_height)) | ||||
| if self.nsubplots < 5: | ||||
| self.__height_inch = 1.1 #altura de los subplots (pulgadas) | ||||
| top_inch = 1.5/2.7 #espacio entre el primer subplot y el limite superior del plot | ||||
| self.__vspace_plot_inch = 1.0#1.5/2 # espacio vertical entre subplots | ||||
| self.__left = 0.1 | ||||
| else: | ||||
| self.__height_inch = 1.1 #altura de los subplots (pulgadas) | ||||
| top_inch = 1.5/2.7 #espacio entre el primer subplot y el limite superior del plot | ||||
| self.__vspace_plot_inch = 1.0 # espacio vertical entre subplots | ||||
| self.__left = 0.1 | ||||
| self.__bottom_inch = self.__plot_height - (self.__height_inch + top_inch) | ||||
| self.__height = self.__height_inch/self.__plot_height | ||||
| self.__width = 0.8 | ||||
| def drawCut(self,io,patterns,npatterns,ha,otitle,subtitle,ptitle): | ||||
| t_cuts = ['B','Sun','Moon','Hydra','Galaxy'] | ||||
| self.__bottom = self.__bottom_inch/self.__plot_height | ||||
| subp = self.fig.add_axes([self.__left,self.__bottom,self.__width,self.__height]) | ||||
| on_axis_angle = -4.65562 | ||||
| for icut in numpy.arange(npatterns): | ||||
| # Getting Antenna cut. | ||||
| pattern = patterns[icut] | ||||
| power = numpy.abs(pattern/numpy.nanmax(pattern)) | ||||
| max_power_db = numpy.round(10.*numpy.log10(numpy.nanmax(pattern)),2) | ||||
| bval = numpy.where(power[:,0]==numpy.nanmax(power)) | ||||
| beta = -0.25*(ha[bval[0]] + on_axis_angle) | ||||
| # print 'Angle (deg): '+"%f"%(beta) | ||||
| subp.plot(ha,power) | ||||
| xmax = numpy.max(numpy.nanmin(ha)) | ||||
| xmin = numpy.min(numpy.nanmax(ha)) | ||||
| ymax = numpy.max(1) | ||||
| ymin = numpy.min(0) | ||||
| subp.set_xlim(xmin, xmax) | ||||
| subp.set_ylim(ymin, ymax) | ||||
| subp.set_title(otitle + ' ' + ptitle,size="medium") | ||||
| subp.text(0.5, 1.26,subtitle[0], | ||||
| horizontalalignment='center', | ||||
| verticalalignment='center', | ||||
| transform = subp.transAxes) | ||||
| xlabels = subp.get_xticks() | ||||
| subp.set_xticklabels(xlabels,size="small") | ||||
| ylabels = subp.get_yticks() | ||||
| subp.set_yticklabels(ylabels,size="small") | ||||
| subp.set_xlabel('Hour angle (min) (+ve to West)',size="small") | ||||
| subp.set_ylabel("Power [Max: " + str(max_power_db) + ' dB]',size="small") | ||||
| subp.grid() | ||||
| self.__bottom_inch = self.__bottom_inch - (self.__height_inch + self.__vspace_plot_inch) | ||||
| class SkyNoisePlot: | ||||
| def __init__(self,date,powr,time,time_lst): | ||||
| """ | ||||
| SkyNoisePlot class creates an object which represents the SkyNoise Object to genera- | ||||
| te a SkyNoise map. | ||||
| Parameters | ||||
| ---------- | ||||
| date = A List of 3 elements to define the desired date ([year, month, day]). | ||||
| powr = An array giving the SkyNoise power for the desired time. | ||||
| time = An array giving the number of seconds since 1970 to the desired time. | ||||
| time_lst = Set this input to an array to define the Local Sidereal Time of the desi- | ||||
| red time. | ||||
| Modification History | ||||
| -------------------- | ||||
| Created by Freddy Galindo, ROJ, 18 October 2009. | ||||
| """ | ||||
| self.date = date | ||||
| self.powr = powr | ||||
| self.time = time | ||||
| self.time_lst = time_lst | ||||