np.save(writeOut+'nice',np.array([xs,
avg[0],std[0], #Psi_1
avg[1],std[1], #Psi_2
avg[2],std[2], #A
avg[3],std[3], #B
avg[4],std[4], #par
avg[5],std[5]])) #perp
np.save(writeOut+'all',allData)
if __name__ == "__main__":
start = time.time()
arrrghs = common.parseCmdArgs([['settings'],['-o','--override']
],
['Settings json file','array indices in the format a:b to extract from infile list'
],
[str,str])
main(arrrghs)
print("That took {:.1f} s".format(time.time()-start))
#ADD a setting to settings to control whether we're dealing with npy
#or dat
velocities = [galaxy.v for galaxy in galaxies]
#get a list of all the galaxies' velocities. This will let us send it directly to the histogram
bins_orig = genBins(binsize, chop)
#Make a histogram using pylab histogram function.
n, bins, patches = pylab.hist(
velocities,
bins_orig,
histtype="stepfilled",
label="Galaxy Distribution,\n binsize={:.2f}Mpc".format(binsize))
#Change visual properties of the histogram
pylab.setp(patches, 'facecolor', 'g', 'alpha', 0.75)
#Add axis labels
pylab.ylabel("Galaxy count")
pylab.xlabel("Radial Velocity, km/s")
pylab.title("Distribution of Galaxy radial velocities")
pylab.axis([0, chop, 0, 1000])
with pdfback.PdfPages(outputFile + str(binsize)) as pdf:
pdf.savefig(fig)
pylab.show()
pylab.close('all')
if __name__ == "__main__":
args = common.parseCmdArgs([['settings']], ['Settings json file'], [str])
statsrun(args)
phi
] #latitude degrees - -90 - 90
outCF2String = outCF2String + '{} {} {} {} {} {}'.format(
*cf2row)
if use_dvs:
dvs = np.random.normal(peculiarVel,
rho * hubble_constant * 0.2, 20)
for x in dvs:
outCF2String = outCF2String + ' {}'.format(x)
outCF2String = outCF2String + '\n'
with open(survey['name'] + '_cf2.txt', 'w') as cf2outfile:
cf2outfile.write(outCF2String)
def transpose(args):
print("Loading survey...")
survey_info = common.getdict(args.survey_file)
print("Success!")
with Pool(processes=12) as pool:
pool.map(proconesurvey, survey_info)
if __name__ == "__main__":
arrrghs = common.parseCmdArgs(
[['survey_file']],
['Survey .json file with surveys and their centers'], [str])
transpose(arrrghs)
# (r1[2]-r2[2])**2)
# for r1,r2 in zip(itertools.repeat(galaxyCoord),surveys)]
if len(surveys) != 0:
distances = space.distance.cdist([galaxyCoord], surveys)
else:
distances = np.array([])
if np.all(distances > separation):
#All is officially the 'coolest function ever.' All of an empty list is true!
surveys.append(galaxyCoord)
break
else:
numCatches += 1
if numCatches % 500 == 0:
print("So far we have tried {} times, and have {} surveys".
format(numCatches, len(surveys)))
#if numCatches > 100000:
# raise RuntimeError("We're probably in an infinite loop. Try reducing the number of surveys to make.")
print("Caught {}!".format(numCatches))
print([list(survey) for survey in surveys])
return surveys
if __name__ == "__main__":
arrrghs = common.parseCmdArgs(
[['settings'], ['-g', '--gpu']],
['Settings json file', 'use pyCUDA when GPU is available'],
[str, 'bool'])
selectrun(arrrghs)