def rawintensityplot(pklrep):
#pklrep = '/home/james/files4CSFPA/qbdataioOUTFILES/' + plotfname
MagXarr, PhaXarr, ReXarr, ImXarr, MagYarr, PhaYarr, ReYarr, ImYarr, vtxcntarr, PixCenX, PixCenY, IntX, IntY, IntT, Ix, Iy, IT, xycoords, filename, freq = RetrieveVars(
pklrep)
######################Total Intensity plot - Normalised
print("filename : ", filename)
GPow = GridPowerCalc(pklrep)
print("max GPow from plot function ", max(GPow))
plt.figure()
plt.suptitle('Frequency - {} GHz'.format(freq))
plt.scatter(xycoords[:, 1],
xycoords[:, 0],
c=GPow,
cmap='jet',
marker='.',
s=1)
plt.axis([-60, 60, -60, 60])
plt.axis('equal')
plt.title("Model Power Data", fontsize=10)
plt.subplots_adjust(bottom=0.1, right=0.8, top=0.9)
cax = plt.axes([0.85, 0.1, 0.05, 0.8])
plt.colorbar(cax=cax, label="Intensity (1 W Source)")
plt.show()
os.system('spd-say "BING! BING! BING!"')
return float(max(GPow))
def TotalIntensityPlot(plotfname):
pklrep = '/home/james/files4CSFPA/qbdataioOUTFILES/' + plotfname
MagXarr, PhaXarr, ReXarr, ImXarr, MagYarr, PhaYarr, ReYarr, ImYarr, vtxcntarr, PixCenX, PixCenY, IntX, IntY, IntT, Ix, Iy, IT, xycoords, filename = RetrieveVars(
pklrep)
######################Total Intensity plot - Normalised
TESPower = TESPowerCalc(plotfname)
GPow = GridPowerCalc(plotfname)
plt.figure()
plt.subplot(121)
plt.scatter(PixCenX * 1000,
PixCenY * 1000,
c=TESPower,
cmap='jet',
marker='s')
plt.axis([-60, 60, -60, 60])
plt.axis('equal')
plt.title("Bolometers Total Intensity", fontsize=10)
plt.subplot(122)
plt.scatter(xycoords[:, 1],
xycoords[:, 0],
c=GPow,
cmap='jet',
marker='.',
s=1)
plt.axis([-60, 60, -60, 60])
plt.axis('equal')
plt.title("Model Power Data", fontsize=10)
plt.subplots_adjust(bottom=0.1, right=0.8, top=0.9)
cax = plt.axes([0.85, 0.1, 0.05, 0.8])
plt.colorbar(cax=cax, label="Intensity (1 W Source)")
plt.show()
os.system('spd-say "BING! BING! BING!"')
return
def PoynICompPlot(mpath, gpath):
#prep MODAL data
df = pd.read_csv(mpath, sep='\t', header=0)
garea, parea = GetMODALGridPixArea(mpath)
#prep GRASP
MagXarr, PhaXarr, ReXarr, ImXarr, MagYarr, PhaYarr, ReYarr, ImYarr, vtxcntarr, PixCenX, PixCenY, IntX, IntY, IntT, Ix, Iy, IT, xycoords, filename = RetrieveVars(
gpath)
gfile = os.path.basename(gpath)
GPow = GridPowerCalc(gfile)
#calculate %diff
comp = ((abs(df.PoynZ * parea) - abs(GPow)) / abs(GPow)) * 100
#comp = np.isclose(GPow, df.PoynZ*parea, atol=1e-6)
fourpi = 4 * np.pi
#do multi plots
fig = plt.figure(facecolor='xkcd:pale green')
fig.suptitle("FP Comparison")
ax1 = fig.add_subplot(221, facecolor='#d8dcd6', aspect='equal')
ax1.set_title("MODAL FP from Poynting Z")
sc = ax1.scatter(df.X, df.Y, c=df.PoynZ * parea, cmap='jet', marker='.')
cbar = fig.colorbar(sc, label="MODAL Poynting (W)")
ax2 = fig.add_subplot(222, facecolor='#d8dcd6', aspect='equal')
ax2.set_title("GRASP FP from Total Intensity")
sc = ax2.scatter(xycoords[:, 1] * 1000,
xycoords[:, 0] * 1000,
c=GPow,
cmap='jet',
marker='.')
cbar = fig.colorbar(sc, label="GRASP Total Intensity (W)")
#plot %diff between models
ax3 = fig.add_subplot(223, facecolor='#d8dcd6', aspect='equal')
ax3.set_title("Difference between Softwares")
sc = ax3.scatter(xycoords[:, 1] * 1000,
xycoords[:, 0] * 1000,
c=comp,
cmap='RdPu',
marker='.') #Both useful PiYG & RdPu
cbar = fig.colorbar(sc, label="Difference")
#plot histogram of %diff per pixel
ax4 = fig.add_subplot(224, facecolor='#d8dcd6')
ax4.set_title("% Difference Histogram")
n, bins, patches = ax4.hist(comp)
print "hist data", n, bins, patches
#calcualte sum of power
print "Poynting Sum W = ", sum(
df.PoynZ *
parea), "% Diff from 1 W = ", ((sum(df.PoynZ * parea) - 1) / 1) * 100
print "modal values: max, mean ", max(df.PoynZ * parea), np.mean(df.PoynZ *
parea)
print "grasp values: max, mean ", max(GPow), np.mean(GPow)
return
def GraspFull(gqbfile, gpath):
#load file
df = pd.read_csv(gqbfile, sep='\t', header=0)
#load pkl, and calculate normalised power from total intensity
gfile = os.path.basename(gpath)
GPow = GridPowerCalc(gfile)
#make figure
fig = plt.figure(facecolor='xkcd:pale green')
fig.suptitle("Full View of Data")
#MagX plot
ax1 = fig.add_subplot(241, facecolor='#d8dcd6', aspect='equal')
ax1.set_title("Magnitude X")
sc = ax1.scatter(df.Xpos, df.Ypos, c=df.Xamp, cmap='jet', marker='.')
cbar = fig.colorbar(sc, label="Mag X")
#MagY plot
ax2 = fig.add_subplot(242, facecolor='#d8dcd6', aspect='equal')
ax2.set_title("Magnitude Y")
sc = ax2.scatter(df.Xpos, df.Ypos, c=df.Yamp, cmap='jet', marker='.')
cbar = fig.colorbar(sc, label="Mag Y")
#Xphase
ax3 = fig.add_subplot(243, facecolor='#d8dcd6', aspect='equal')
ax3.set_title("Phase X")
sc = ax3.scatter(df.Xpos, df.Ypos, c=df.Xpha, cmap='jet', marker='.')
cbar = fig.colorbar(sc, label="Phase X")
#yphase
ax4 = fig.add_subplot(244, facecolor='#d8dcd6', aspect='equal')
ax4.set_title("Phase Y")
sc = ax4.scatter(df.Xpos, df.Ypos, c=df.Ypha, cmap='jet', marker='.')
cbar = fig.colorbar(sc, label="Phase Y")
#Zamp
ax5 = fig.add_subplot(245, facecolor='#d8dcd6', aspect='equal')
ax5.set_title("Magnitude Z")
sc = ax5.scatter(df.Xpos, df.Ypos, c=df.Zamp, cmap='jet', marker='.')
cbar = fig.colorbar(sc, label="Mag Z")
#zphase
ax6 = fig.add_subplot(246, facecolor='#d8dcd6', aspect='equal')
ax6.set_title("Phase Z")
sc = ax6.scatter(df.Xpos, df.Ypos, c=df.Zpha, cmap='jet', marker='.')
cbar = fig.colorbar(sc, label="Phase Z")
#normalised total intensity
ax7 = fig.add_subplot(247, facecolor='#d8dcd6', aspect='equal')
ax7.set_title("Total Intensity")
sc = ax7.scatter(df.Xpos, df.Ypos, c=GPow, cmap='jet', marker='.')
cbar = fig.colorbar(sc, label="Watts")
return
def TESPowPlot(plotfname):
rep = '/home/james/files4CSFPA/qbdataioOUTFILES/'
repfile = rep + plotfname
#load pickle data
MagXarr, PhaXarr, ReXarr, ImXarr, MagYarr, PhaYarr, ReYarr, ImYarr, vtxcntarr, PixCenX, PixCenY, IntX, IntY, IntT, Ix, Iy, IT, xycoords, filename = RetrieveVars(
repfile)
#load qbdata for TES and Save function
qbrep = '/home/james/files4CSFPA/Fromqbdataio/'
qbrepfile = qbrep + filename
#load TES power array
TESPower = TESPowerCalc(plotfname)
GPow = GridPowerCalc(plotfname)
#plot tes power
fig = plt.figure(facecolor='xkcd:pale green')
fig.suptitle("File Analysis: '{}'".format(plotfname), fontsize=12)
ax1 = fig.add_subplot(221, facecolor='#d8dcd6', aspect='equal')
ax1.set_title("Bolometers Total Instensity", fontsize=10)
sc = ax1.scatter(PixCenX, PixCenY, c=TESPower, cmap='jet', marker='s', s=4)
cbar = fig.colorbar(sc, label="Intensity per Bolometer (W)")
ax2 = fig.add_subplot(222, facecolor='#d8dcd6', aspect='equal')
sc = ax2.scatter(xycoords[:, 0],
xycoords[:, 1],
c=GPow,
cmap='jet',
marker='.')
ax2.set_title("RAW Grasp Total Instensity", fontsize=10)
cbar = fig.colorbar(sc, label="Intensity per GRASP data point (W)")
ax3 = fig.add_subplot(212, facecolor='#d8dcd6')
tp = ax3.plot(TESPower, marker='_', linestyle="", markersize=0.75)
ax3.set_title("TES Detector Power Plot")
ax3.set_ylabel("Intensity per Bolometer (W)")
ax3.set_xlabel("TES Bolometer Number (qubicsoft order)")
ax3.set_xlim(1, 992)
plt.show()
#output TES Power to file + use filename for file naming system
OutputTESPower(TESPower, filename)
return
def TESPowAnalysis(plotfname):
pklrep = '/home/james/files4CSFPA/qbdataioOUTFILES/' + plotfname
MagXarr, PhaXarr, ReXarr, ImXarr, MagYarr, PhaYarr, ReYarr, ImYarr, vtxcntarr, PixCenX, PixCenY, IntX, IntY, IntT, Ix, Iy, IT, xycoords, filename = RetrieveVars(
pklrep)
######################Total Intensity plot - Normalised
TESPower = TESPowerCalc(plotfname)
GPow = GridPowerCalc(plotfname)
plt.figure(facecolor='xkcd:pale green')
plt.subplot(221, facecolor='#d8dcd6')
plt.scatter(PixCenX * 1000,
PixCenY * 1000,
c=TESPower,
cmap='jet',
marker='s',
s=4)
plt.axis([-60, 60, -60, 60])
plt.axis('equal')
plt.title("{} Bolometers Total Instensity".format(plotfname), fontsize=10)
plt.subplot(222, facecolor='#d8dcd6')
plt.scatter(xycoords[:, 0], xycoords[:, 1], c=GPow, cmap='jet', marker='.')
plt.axis([-60, 60, -60, 60])
plt.axis('equal')
plt.title("RAW - {}".format(filename), fontsize=10)
plt.subplot(212, facecolor='#d8dcd6')
plt.plot(TESPower, marker='_', linestyle="", markersize=0.75)
#output TES Power to file
OutputTESPower(TESPower, filename)
plt.subplots_adjust(bottom=0.1, right=0.8, top=0.9)
cax = plt.axes([0.85, 0.1, 0.05, 0.8])
plt.colorbar(cax=cax, label="Intensity")
plt.show()
os.system('spd-say "BING! BING! BING!"')
return