def main():
parser = argparse.ArgumentParser(
description='----- find_stretch_all_runs.py ---------')
parser.add_argument('vname', help='variable we want to look at, e.g. psf_sigma1,\
psf_sigma2, airmass, neff_psf, psf_nstar, psf_width')
parser.add_argument('-pvfrac', type=float, default=0.1,
help='tolerance on peak-to-peak variation, \
default=0.1')
parser.add_argument('-rmsfrac', type=float, default=0.05,
help='tolerance on RMS of the stretch, default=0.05')
parser.add_argument('-fitsoff', help='w/o reading in data from fits files',
action='store_true')
parser.add_argument('-tableoff', help='w/o creating the stretchTable',
action='store_true')
args = parser.parse_args()
start1 = time.time()
objlist = np.loadtxt('data/Stripe82RunList.dat')
sdss = sdssinst()
outTable = 'output/stretchTable.txt'
if (not args.tableoff):
if os.path.isfile(outTable):
os.remove(outTable)
fz = open(outTable, 'ab')
runcount = 0
for line in objlist:
start = time.time()
run = int(line[0])
runcount += 1
print('-- running on run# %d (seq.# %d)---------' % (
run, runcount))
myRun = sdssrun(run)
a3dfile = 'output/temp/run%d_%s.txt' % (myRun.runNo, args.vname)
if (not args.fitsoff):
a3d = myRun.getBCFtable(sdss, args.vname)
myTools.savetxt3d(a3dfile, a3d)
else:
a3d = np.loadtxt(a3dfile)
a3d = a3d.reshape(sdss.nBand, sdss.nCamcol, -1)
stretchTable = myRun.findStretch(
sdss, a3d, args.pvfrac, args.rmsfrac)
np.savetxt(fz, stretchTable, fmt='%d')
end = time.time()
print('--- done with run# %d, time elapsed: %8.2fs---' % (
run, (end - start)))
fz.close()
nrun = len(objlist)
tableData = np.loadtxt(outTable)
maxbyrun = np.zeros(nrun)
runNo = objlist[:, 0].astype(int)
for i in np.arange(nrun):
# last column in tableTable is the length of the stretch
maxbyrun[i] = np.max(tableData[tableData[:, 0] == runNo[i], -1])
plt.plot(runNo, maxbyrun, # label='',
marker='o', color='r', markersize=10)
plt.xlabel('Run No.')
plt.ylabel('Longest Stretch')
plt.savefig('output/maxStretch_%s.png' % (args.vname))
for iRecord in range(0,2): #number of records to print out
maxRow = np.where(tableData[:, -1] == np.max(tableData[:, -1]))
runSeq = np.arange(1, nrun + 1)
for irow in maxRow[0]:
irun = tableData[irow, 0]
print('longest stretch found in run %d (seq# %d), \
field range = (%d, %d), %d runs' % (
irun,
runSeq[irun == runNo],
tableData[irow, 1], tableData[irow, 2], tableData[irow, 3]))
rmRow = np.where(tableData[:, 0] == irun)
tableData[rmRow[0], -1] = 0
# sys.exit()
end1 = time.time()
print('--- Total time elapsed: %8.2fs---' % ((end1 - start1)))
E.g. for some run
# field camCol filter FWHMvK (other SDSS params)
"""
parser = argparse.ArgumentParser(
description='-----makeMasterTXT_pool.py------')
parser.add_argument('-p', dest='numproc', default=1, type=int,
help='Number of Processors to use')
parser.add_argument('-run', dest='run', type=int, default=-1,
help='run number. use -1 to run over all runs. default=-1')
args = parser.parse_args()
objlist = np.loadtxt('data/Stripe82RunList.dat')
# objlist = objlist[0:3,:] #for test
sdss = sdssinst()
start = time.time()
def write1run(argList):
sdss = argList[0]
run = argList[1]
runcount = argList[2]
print('-- running on run# %d (seq.# %d)---------' % (run, runcount))
myRun = sdssrun(run)
txtfile = 'SDSSdata/masterTXT/run%d.txt' % (myRun.runNo)
myRun.writeMasterTXT(sdss, txtfile)
def main():
parser = argparse.ArgumentParser(
description='----- fwhm_check_eff.py ---------')
parser.add_argument('vname', choices=('fwhmeff', 'neff'),
help='variable we want to look at')
parser.add_argument('irun', type=int,
help='Run Number')
args = parser.parse_args()
objlist = np.loadtxt('data/Stripe82RunList.dat')
sdss = sdssinst()
runcount = 0
f, ax1 = plt.subplots(sdss.nBand, sdss.nCamcol, sharex='col',
sharey='row', figsize=(12, 8)) # a plot is for a run
for line in objlist:
run = int(line[0])
if run != args.irun:
continue
runcount += 1
print('-- running on run# %d (seq.# %d)---------' % (run, runcount))
myRun = sdssrun(run)
txtfile = 'SDSSdata/masterTXT/run%d.txt' % (run)
txtdata = np.loadtxt(txtfile)
calc = np.zeros(txtdata.shape[0])
if args.vname == 'fwhmeff':
myv = txtdata[:, 4]
else:
myv = txtdata[:, 8]
if (1):
icount = 0
# the loops below need to conform with masterTXT files
# filter changes first, then field, then camcol
for camcol in range(1, sdss.nCamcol + 1):
print('running on camcol#%d' % camcol)
datafile = myRun.fitsdir + \
"photoField-%06d-%d.fits" % (run, camcol)
hdulist = fits.open(datafile)
hdu1 = hdulist[1].data
# for ifield in range(myRun.nfields-530): #for plotting tests
for ifield in range(myRun.nfields):
if ifield % 100 == 0:
print('field No. = %d/%d' % (ifield, myRun.nfields))
for iBand in range(0, sdss.nBand):
data = hdu1[ifield]
sigG1 = data['psf_sigma1'][iBand]
sigG2 = data['psf_sigma2'][iBand]
b = data['psf_b'][iBand]
p0 = data['psf_p0'][iBand]
beta = data['psf_beta'][iBand]
sigP = data['psf_sigmap'][iBand]
pixScale = data['pixScale'][iBand]
#grid1d = np.linspace(-30, 30, 601) # arcsec
grid1d = np.linspace(-50, 50, 1001)
x, y = np.meshgrid(grid1d, grid1d)
# for fits, radius must be in pixels
r2 = (x * x + y * y) * (1 / pixScale)**2
psfG1 = np.exp(-0.5 * r2 / (sigG1 * sigG1))
psfG2 = b * np.exp(-0.5 * r2 / (sigG2 * sigG2))
# note division by beta! below:
psfW = p0 * (1 + r2 / (sigP * sigP) / beta)**(-0.5 * beta)
psfG = psfG1 + psfG2
# normalized to 1 at r=0 by definition
psfModel = (psfG + psfW) / (1 + b + p0)
psfModel = psfModel / np.sum(psfModel)
neff = 1 / np.sum(psfModel**2) / (pixScale / 0.1)**2
if args.vname == 'neff':
calc[icount] = neff
elif args.vname == 'fwhmeff':
# 0.4 arcsec/pixel
calc[icount] = 0.664 * pixScale * np.sqrt(neff)
icount += 1
for camcol in range(1, sdss.nCamcol + 1):
for iBand in range(0, sdss.nBand):
idx = (txtdata[:, 1] == camcol) & (txtdata[:, 2] == iBand)
ax1[iBand, camcol - 1].plot(myv[idx], calc[idx],
'r', marker='.', linestyle='None')
if iBand == 0 and runcount == 1:
ax1[iBand, camcol - 1].set_title('camcol=%d' % camcol)
if args.vname == 'neff':
if camcol == 1 and runcount == 1:
text = 'band: %s' % sdss.band[iBand]
ax1[iBand, camcol -
1].text(30, 16, text, fontsize=15, ha='left',
va='center')
ax1[iBand, camcol - 1].plot([0, 70], [0, 70],
color='k', linestyle='-',
linewidth=2)
elif args.vname == 'fwhmeff':
if camcol == 1 and runcount == 1:
text = 'band: %s' % sdss.band[iBand]
ax1[iBand, camcol -
1].text(1.0, 0.8, text, fontsize=15, ha='left',
va='center')
ax1[iBand, camcol - 1].plot([0.5, 2.5], [0.5, 2.5],
color='k', linestyle='-',
linewidth=2)
ax1[iBand, camcol - 1].grid()
if iBand == sdss.nBand - 1:
ax1[iBand, camcol - 1].set_xlabel(args.vname)
if camcol == 1:
ax1[iBand, camcol - 1].set_ylabel('My calculation')
# plt.suptitle('All units in arcsec ')
plt.tight_layout()
# plt.show()
plt.savefig('output/run%d_check_%s.png' % (run, args.vname))
def main():
parser = argparse.ArgumentParser(
description='----- find_long_wild_runs.py ---------')
parser.add_argument('vname', help='variable we want to look at, e.g. psf_sigma1,\
psf_sigma2, airmass, neff_psf, psf_nstar, psf_width')
parser.add_argument('-fitsoff', help='w/o reading in data from fits files',
action='store_true')
parser.add_argument('-tableoff', help='w/o creating the stretchTable',
action='store_true')
args = parser.parse_args()
start1 = time.time()
objlist = np.loadtxt('data/Stripe82RunList.dat')
sdss = sdssinst()
outTable = 'output/longWildRuns.txt'
if (not args.tableoff):
if os.path.isfile(outTable):
os.remove(outTable)
fz = open(outTable, 'ab')
runcount = 0
for line in objlist:
start = time.time()
run = int(line[0])
runcount += 1
print('-- running on run# %d (seq.# %d)---------' % (
run, runcount))
myRun = sdssrun(run)
a3dfile = 'output/temp/run%d_%s.txt' % (myRun.runNo, args.vname)
if (not args.fitsoff):
a3d = myRun.getBCFtable(sdss, args.vname)
myTools.savetxt3d(a3dfile, a3d)
else:
a3d = np.loadtxt(a3dfile)
a3d = a3d.reshape(sdss.nBand, sdss.nCamcol, -1)
longWildTable = myRun.findLongWild(sdss, a3d)
np.savetxt(fz, longWildTable, fmt='%d %d %d %d %9.6f %9.6f')
end = time.time()
print('--- done with run# %d, time elapsed: %8.2fs---' % (
run, (end - start)))
fz.close()
nrun = len(objlist)
tableData = np.loadtxt(outTable)
prodbyrun = np.zeros(nrun)
nfieldsbyrun = np.zeros(nrun)
pvbyrun = np.zeros(nrun)
rmsbyrun = np.zeros(nrun)
runNo = objlist[:, 0].astype(int)
for i in np.arange(nrun):
idx = tableData[:, 0] == runNo[i]
nfieldsbyrun[i] = np.mean(tableData[idx, 1])
pvbyrun[i] = np.mean(tableData[idx, 4])
rmsbyrun[i] = np.mean(tableData[idx, 5])
prodbyrun[i] = nfieldsbyrun[i] * pvbyrun[i] * rmsbyrun[i]
plt.plot(runNo, nfieldsbyrun, label='nfields',
marker='.', color='g', markersize=10)
plt.plot(runNo, prodbyrun, label='nfields*PV*RMS (arcsec$^2$)',
marker='o', color='k', markersize=5)
plt.plot(runNo, pvbyrun * 100, label='PV (arcsec) x 100',
marker='v', color='b', markersize=5)
plt.plot(runNo, rmsbyrun * 100, label='RMS (arcsec) x 100',
marker='*', color='r', markersize=10)
plt.xlabel('Run No.')
plt.ylabel('runs & psf_width variations')
plt.legend(loc="upper right", fontsize=10)
plt.savefig('output/longWildRun_%s.png' % (args.vname))
maxRun = runNo[np.where(prodbyrun == np.max(prodbyrun))]
runSeq = np.arange(1, nrun + 1)
for irun in maxRun: # mostly likely there is only 1 number in maxRun
idx = tableData[:, 0] == irun
print('longest run with largest %s variation: run %d (seq# %d), \
nfield = %d, \n\
averaged over band and camcol: PV = %9.6f, RMS = %9.6f' % (
args.vname,
irun,
runSeq[irun == runNo],
np.mean(tableData[idx, 1]),
np.mean(tableData[idx, 4]),
np.mean(tableData[idx, 5])))
# sys.exit()
end1 = time.time()
print('--- Total time elapsed: %8.2fs---' % ((end1 - start1)))
def main():
parser = argparse.ArgumentParser(description="----- fwhm_vk_psfwidth.py ---------")
parser.add_argument(
"run",
type=int,
default=94,
help="run number; use -1 for all runs together;\
-9 for all runs individually",
)
args = parser.parse_args()
runNo = args.run
objlist = np.loadtxt("data/Stripe82RunList.dat")
if runNo > 0:
# remove all lines but one
objlist = objlist[objlist[:, 0] == runNo, :]
sdss = sdssinst()
runcount = 0
# vk = np.loadtxt('data/vonK1.0.txt', unpack='True')
# vk = vk / np.sum(vk)
# vkneff = 1 / np.sum(vk**2)
# vkfwhm = 0.664 * 0.1 * np.sqrt(vkneff)
f, ax1 = plt.subplots(sdss.nBand, sdss.nCamcol, sharex="col", sharey="row", figsize=(12, 8)) # a plot is for a run
for line in objlist:
run = int(line[0])
runcount += 1
print("-- running on run# %d (seq.# %d)---------" % (run, runcount))
txtfile = "SDSSdata/masterTXT/run%d.txt" % (run)
txtdata = np.loadtxt(txtfile)
fwhmvk = txtdata[:, 3]
psf_width = txtdata[:, 4]
if runNo < -5:
# a plot is for a run
f, ax1 = plt.subplots(sdss.nBand, sdss.nCamcol, sharex="col", sharey="row", figsize=(12, 8))
for camcol in range(1, sdss.nCamcol + 1):
for iBand in range(0, sdss.nBand):
idx = (txtdata[:, 1] == camcol) & (txtdata[:, 2] == iBand)
ax1[iBand, camcol - 1].scatter(psf_width[idx], fwhmvk[idx], s=2, c="r", edgecolors="r")
if iBand == 0 and runcount == 1:
ax1[iBand, camcol - 1].set_title("camcol=%d" % camcol)
if camcol == 1 and runcount == 1:
text = "band: %s" % sdss.band[iBand]
ax1[iBand, camcol - 1].text(1.0, 0.8, text, fontsize=15, ha="left", va="center")
ax1[iBand, camcol - 1].plot([0.5, 2.5], [0.5, 2.5], color="k", linestyle="-", linewidth=2)
ax1[iBand, camcol - 1].grid()
if iBand == sdss.nBand - 1:
ax1[iBand, camcol - 1].set_xlabel("psf_width")
if camcol == 1:
ax1[iBand, camcol - 1].set_ylabel("FWHMvK")
if runNo < -5:
plt.tight_layout()
plt.savefig("output/fwhmvk_psfwidth/run%d_fwhmvk_psfwidth.png" % (run))
plt.close()
if runNo > -5:
plt.tight_layout()
if runNo < 0:
plt.savefig("output/fwhmvk_psfwidth/runAll_fwhmvk_psfwidth.png")
else:
plt.savefig("output/fwhmvk_psfwidth/run%d_fwhmvk_psfwidth.png" % (runNo))
plt.close()
def main():
parser = argparse.ArgumentParser(
description='----- fwhm_lambda.py ---------')
parser.add_argument('run', type=int, default=94,
help='run number; -9 for all runs individually; \
makes no sense to plot all runs together')
parser.add_argument('yscale', choices=(
'log', 'linear'), help='yscale of the plots')
parser.add_argument('-ugri', help='run ugri bands only; w/o z',
action='store_true')
parser.add_argument('-startfield', dest='startfield', default=0, type=int,
help='field# to start with')
parser.add_argument('-endfield', dest='endfield', default=99999, type=int,
help='field# to end with (note indexing \
starts from 0)')
parser.add_argument('-doubleG', help='use psf_width from the double Gau fits',
action='store_true')
args = parser.parse_args()
if args.ugri == 1:
bands = 'ugri'
else:
bands = 'ugriz'
runNo = args.run
objlist = np.loadtxt('data/Stripe82RunList.dat')
if runNo > 0:
# remove all lines but one
objlist = objlist[objlist[:, 0] == runNo, :]
sdss = sdssinst()
runcount = 0
nRow = 2
nCol = np.uint8(np.ceil(sdss.nCamcol / nRow))
f, ax1 = plt.subplots(nRow, nCol, sharex='col',
sharey='row', figsize=(12, 8)) # a plot is for a run
if runNo < 0:
outTXTfile = 'output/fwhm_lambda/power_%s.txt' % bands
fidw = open(outTXTfile, 'w')
xlambda = np.arange(300, 1000, 10)
for line in objlist:
run = int(line[0])
runcount += 1
print('-- running on run# %d (seq.# %d)---------' % (run, runcount))
txtfile = 'SDSSdata/masterTXT/run%d.txt' % (run)
txtdata = np.loadtxt(txtfile)
idx = (txtdata[:, 0] >= args.startfield) & (
txtdata[:, 0] < args.endfield)
txtdata = txtdata[idx, :]
if args.doubleG:
fwhmStr = 'fwhm2G'
fwhm = txtdata[:, 4]
else:
fwhmStr = 'fwhm'
fwhm = txtdata[:, 3] / 1.222 # convert FWHMeff into FWHM
airmass = txtdata[:, 5]
fwhm = fwhm/airmass**0.6
startfield = args.startfield
endfield = np.uint16(np.max(txtdata[:, 0]))
if runNo < 0:
# a plot is for a run
f, ax1 = plt.subplots(nRow, nCol, sharex='col',
sharey='row', figsize=(12, 8))
for camcol in range(1, sdss.nCamcol + 1):
iRow = np.uint8(np.ceil(camcol / nCol)) - 1
iCol = np.mod(camcol - 1, nCol)
# print(iRow, iCol)
# scanning order is r-i-u-z-g
idx = (txtdata[:, 1] == camcol) & \
(((txtdata[:, 2] == 0) & (txtdata[:, 0] > startfield + 3) & (
txtdata[:, 0] < endfield - 4)) |
((txtdata[:, 2] == 1) & (txtdata[:, 0] < endfield - 8)) |
((txtdata[:, 2] == 2) & (txtdata[:, 0] > startfield + 7)) |
((txtdata[:, 2] == 3) & (txtdata[:, 0] > startfield + 5) & (
txtdata[:, 0] < endfield - 2)) |
((txtdata[:, 2] == 4) & (txtdata[:, 0] > startfield + 1) & (
txtdata[:, 0] < endfield - 6)))
if args.ugri == 1:
idx = idx & (txtdata[:, 2] != 4) # remove z band data
fwhmfit = fwhm[idx]
Leffnparray = np.array(sdss.Leff)
Lefffit = Leffnparray[np.uint8(txtdata[idx, 2])]
popt, pcov = optimize.curve_fit(
lambda Leff, norm: fwhm_lambda_dep(Leff, norm, -0.2),
Lefffit, fwhmfit, p0=[5])
norm02 = popt[0]
y02 = fwhm_lambda_dep(xlambda, norm02, -0.2)
ax1[iRow, iCol].plot(xlambda, y02, '-b', label='power = -0.2')
popt, pcov = optimize.curve_fit(
lambda Leff, norm: fwhm_lambda_dep(Leff, norm, -0.3),
Lefffit, fwhmfit, p0=[5])
norm03 = popt[0]
y03 = fwhm_lambda_dep(xlambda, norm03, -0.3)
ax1[iRow, iCol].plot(xlambda, y03, '-g', label='power = -0.3')
popt, pcov = optimize.curve_fit(
fwhm_lambda_dep,
Lefffit, fwhmfit, p0=[5, -0.25])
normfit = popt[0]
powerfit = popt[1]
yfit = fwhm_lambda_dep(xlambda, normfit, powerfit)
ax1[iRow, iCol].plot(xlambda, yfit, '-k',
label='power (fit) = %5.2f' % powerfit)
print('camcol=%d, power (fit) = %5.2f' % (camcol, powerfit))
if runNo < 0:
if camcol == 1:
fidw.write('%d\t' % run)
fidw.write('%5.2f\t' % powerfit)
if camcol == sdss.nCamcol:
fidw.write('\n')
# scanning order is r-i-u-z-g
for ufield in range(startfield + 4, endfield - 4 + 1):
gfield = ufield - 4
rfield = ufield + 4
ifield = ufield + 2
zfield = ufield - 2
idxu = (txtdata[:, 0] == ufield) & (
txtdata[:, 1] == camcol) & (txtdata[:, 2] == 0)
idxg = (txtdata[:, 0] == gfield) & (
txtdata[:, 1] == camcol) & (txtdata[:, 2] == 1)
idxr = (txtdata[:, 0] == rfield) & (
txtdata[:, 1] == camcol) & (txtdata[:, 2] == 2)
idxi = (txtdata[:, 0] == ifield) & (
txtdata[:, 1] == camcol) & (txtdata[:, 2] == 3)
idxz = (txtdata[:, 0] == zfield) & (
txtdata[:, 1] == camcol) & (txtdata[:, 2] == 4)
if args.ugri == 1:
fwhmt = np.hstack(
(fwhm[idxu], fwhm[idxg], fwhm[idxr], fwhm[idxi]))
ax1[iRow, iCol].plot(sdss.Leff[0:4], fwhmt, '-ro')
else:
fwhmt = np.hstack((fwhm[idxu], fwhm[idxg], fwhm[
idxr], fwhm[idxi], fwhm[idxz]))
ax1[iRow, iCol].plot(sdss.Leff, fwhmt, '-ro')
ax1[iRow, iCol].grid()
ax1[iRow, iCol].set_title('camcol=%d' % camcol)
ax1[iRow, iCol].plot(xlambda, y02, '-b')
ax1[iRow, iCol].plot(xlambda, y03, '-g')
ax1[iRow, iCol].plot(xlambda, yfit, '-k')
ax1[iRow, iCol].set_xlabel('Effective wavelength (nm)')
ax1[iRow, iCol].set_ylabel(fwhmStr)
ax1[iRow, iCol].legend(loc="upper right", fontsize=10)
if args.yscale == 'log':
ax1[iRow, iCol].set_yscale('log')
ax1[iRow, iCol].set_xscale('log')
ax1[iRow, iCol].set_xlim([300, 1000])
ax1[iRow, iCol].set_ylim(
[np.min(fwhm) - 0.1, np.max(fwhm) + 0.3])
if runNo < 0:
# plt.tight_layout()
plt.savefig('output/fwhm_lambda/run%d_%s_lambda_%s_%s.png' %
(run, fwhmStr, bands, args.yscale))
plt.close()
if runNo > 0:
# plt.tight_layout()
if (args.startfield == 0 and args.endfield == 99999):
plt.savefig('output/fwhm_lambda/run%d_%s_lambda_%s_%s.png' %
(runNo, fwhmStr, bands, args.yscale))
else:
plt.savefig(
'output/fwhm_lambda/run%d_%s_lambda_%s_%s_%d_%d.png' %
(runNo, fwhmStr, bands, args.yscale, args.startfield, args.endfield))
plt.close()
if runNo < 0:
fidw.close()
def main():
parser = argparse.ArgumentParser(
description='----- correlate_temporal.py ---------')
parser.add_argument('run', type=int, default=94,
help='run number; -9 for all runs individually; \
makes no sense to plot all runs together')
parser.add_argument('iBand', type=int, default=0, help='band, 0,1,2,3,4 for ugriz')
parser.add_argument('-doubleG', help='use psf_width from the double Gau fits',
action='store_true')
parser.add_argument('-startfield', dest='startfield', default=0, type=int,
help='field# to start with')
parser.add_argument('-endfield', dest='endfield', default=99999, type=int,
help='field# to end with (note indexing \
starts from 0)')
args = parser.parse_args()
runNo = args.run
objlist = np.loadtxt('data/Stripe82RunList.dat')
if runNo > 0:
# remove all lines but one
objlist = objlist[objlist[:, 0] == runNo, :]
sdss = sdssinst()
runcount = 0
for line in objlist:
run = int(line[0])
runcount += 1
print('-- running on run# %d (seq.# %d)---------' % (run, runcount))
txtfile = 'SDSSdata/masterTXT/run%d.txt' % (run)
txtdata = np.loadtxt(txtfile)
idx = (txtdata[:, 0] >= args.startfield) & (
txtdata[:, 0] < args.endfield)
txtdata = txtdata[idx, :]
if args.doubleG:
fwhmStr = 'fwhm2G'
fwhm = txtdata[:, 4]
else:
fwhmStr = 'fwhm'
fwhm = txtdata[:, 3] # FWHMeff
airmass = txtdata[:, 5]
fwhm = fwhm/airmass**0.6
startfield = args.startfield
endfield = np.uint16(np.max(txtdata[:, 0]))
nfields = endfield - startfield + 1
nRow = 2
nCol = np.uint8(np.ceil(sdss.nCamcol / nRow))
f, ax1 = plt.subplots(nRow, nCol, sharex='col',
sharey='row', figsize=(12, 8)) # a plot is for a run
for camcol in range(1, sdss.nCamcol + 1):
iRow = np.uint8(np.ceil(camcol / nCol)) - 1
iCol = np.mod(camcol - 1, nCol)
idx = (txtdata[:, 1] == camcol) & (txtdata[:, 2] == args.iBand)
result = np.correlate(fwhm[idx], fwhm[idx], mode='full')
autoCorr = result[result.size/2:]
autoCorr = autoCorr/max(autoCorr)
ax1[iRow, iCol].plot(autoCorr, marker='.')
#SFFT = np.fft.fftshift(np.fft.fft(np.fft.fftshift(fwhm[idx])))
#SFFT = abs(np.fft.fftshift(np.fft.fft(fwhm[idx])))
#ax1[iRow, iCol].plot(SFFT, marker='.')
#N = nfields
## sample spacing
#T = 1.0 / N /2
#x = np.linspace(0.0, N*T, N)
#y = fwhm[idx]
#yf = np.fft.fft(y)
#xf = np.fft.fftfreq(N, T)
#xf = np.fft.fftshift(xf)
#yplot = np.fft.fftshift(yf)
#ax1[iRow, iCol].semilogy(xf, 1.0/N * np.abs(yplot))
#ax1[iRow, iCol].set_xlim(0, nfields+1)
ax1[iRow, iCol].set_title('run%d, %s, %s, camcol=%s' %
(runNo, fwhmStr, sdss.band[args.iBand], camcol))
ax1[iRow, iCol].set_xlabel('time (ifield)')
#ax1[iRow, iCol].set_ylabel('Covariance (arcsec^2)')
#ax1[iRow, iCol].set_ylabel('Correlation coefficients')
ax1[iRow, iCol].set_ylabel('FFT')
ax1[iRow, iCol].grid()
#plt.show()
# plt.tight_layout()
if (args.startfield == 0 and args.endfield == 99999):
plt.savefig('output/correlate_temporal/run%d_%s_%s.png' %
(runNo, fwhmStr, sdss.band[args.iBand]))
else:
plt.savefig(
'output/correlate_temporal/run%d_%s_%s_fld_%d_%d.png' %
(runNo, fwhmStr, sdss.band[args.iBand],args.startfield, args.endfield))
plt.close()
def main():
parser = argparse.ArgumentParser(
description='----- correlate_spatial.py ---------')
parser.add_argument('run', type=int, default=94,
help='run number; -9 for all runs individually; \
makes no sense to plot all runs together')
parser.add_argument('-doubleG', help='use psf_width from the double Gau fits',
action='store_true')
parser.add_argument('-startfield', dest='startfield', default=0, type=int,
help='field# to start with')
parser.add_argument('-endfield', dest='endfield', default=99999, type=int,
help='field# to end with (note indexing \
starts from 0)')
args = parser.parse_args()
runNo = args.run
objlist = np.loadtxt('data/Stripe82RunList.dat')
if runNo > 0:
# remove all lines but one
objlist = objlist[objlist[:, 0] == runNo, :]
sdss = sdssinst()
runcount = 0
for line in objlist:
run = int(line[0])
runcount += 1
print('-- running on run# %d (seq.# %d)---------' % (run, runcount))
txtfile = 'SDSSdata/masterTXT/run%d.txt' % (run)
txtdata = np.loadtxt(txtfile)
idx = (txtdata[:, 0] >= args.startfield) & (
txtdata[:, 0] < args.endfield)
txtdata = txtdata[idx, :]
if args.doubleG:
fwhmStr = 'fwhm2G'
fwhm = txtdata[:, 4]
else:
fwhmStr = 'fwhm'
fwhm = txtdata[:, 3] # FWHMeff
airmass = txtdata[:, 5]
fwhm = fwhm/airmass**0.6
startfield = args.startfield
endfield = np.uint16(np.max(txtdata[:, 0]))
nfields = endfield - startfield + 1
nRow = 2
nCol = 3
f, ax1 = plt.subplots(nRow, nCol, sharex='col',
sharey='row', figsize=(12, 8)) # a plot is for a run
for iBand in range(0, sdss.nBand):
iRow = np.uint8(np.ceil((iBand+1) / nCol)) - 1
iCol = np.mod(iBand, nCol)
fwhmArray = np.zeros((nfields, sdss.nCamcol))
for camcol in range(1, sdss.nCamcol + 1):
idx = (txtdata[:, 1] == camcol) & (txtdata[:, 2] == iBand)
fwhmArray[:, camcol-1] = fwhm[idx]
#myCovSquare=np.cov(fwhmArray, rowvar=0)
myCovSquare=np.corrcoef(fwhmArray, rowvar=0)
myCov = np.zeros(15)
mySep = np.zeros(15)
i = 0
for iCamcol in range(1, sdss.nCamcol + 1):
for jCamcol in range(iCamcol+1, sdss.nCamcol + 1):
myCov[i] = myCovSquare[iCamcol-1, jCamcol-1]
mySep[i] = jCamcol - iCamcol
i += 1
ax1[iRow, iCol].plot(mySep, myCov, 'xr',markersize=15)
ax1[iRow, iCol].set_xlim(0, sdss.nCamcol)
ax1[iRow, iCol].set_title('run%d, %s, %s' %
(runNo, fwhmStr, sdss.band[iBand]))
ax1[iRow, iCol].set_xlabel('Spatial separation')
#ax1[iRow, iCol].set_ylabel('Covariance (arcsec^2)')
ax1[iRow, iCol].set_ylabel('Correlation coefficients')
ax1[iRow, iCol].grid()
#plt.show()
# plt.tight_layout()
if (args.startfield == 0 and args.endfield == 99999):
plt.savefig('output/correlate_spatial/run%d_%s.png' %
(runNo, fwhmStr))
else:
plt.savefig(
'output/correlate_spatial/run%d_%s_fld_%d_%d.png' %
(runNo, fwhmStr, args.startfield, args.endfield))
plt.close()
