def plot(i, pol):
ii12 = analyse.loadfits(qdir+fits12[i][:-5]+'.qlook.ii.fits')
ii13 = analyse.loadfits(qdir+fits13[i][:-5]+'.qlook.ii.fits')
ii18 = analyse.loadfits(qdir+fits18[i][:-5]+'.qlook.ii.fits')
rms12 = analyse.loadfits(qdir+fits12[i][:-5]+'.qlook.rms.fits')
rms13 = analyse.loadfits(qdir+fits13[i][:-5]+'.qlook.rms.fits')
rms18 = analyse.loadfits(qdir+fits18[i][:-5]+'.qlook.rms.fits')
sp12 = analyse.loadfits(qdir+fits12[i][:-5]+'.qlook.data.fits')
sp13 = analyse.loadfits(qdir+fits13[i][:-5]+'.qlook.data.fits')
sp18 = analyse.loadfits(qdir+fits18[i][:-5]+'.qlook.data.fits')
fig = pylab.figure(figsize=(25,25))
fig.suptitle(name, fontsize=22)
plot = analyse.custom_draw_map(figure=fig, xspacing=0.2, yspacing=0.2,
tick_labels_size=12, colorber_font_size=11, show=False)
splt = functools.partial(analyse.draw_otf_spectrum, figure=fig, tick_labels_size=12,
xlim=(-150,150), show=False)
plot(ii12, subplot=331, title='12CO(2-1): mom0')
plot(ii13, subplot=331+3, title='13CO(2-1): mom0')
plot(ii18, subplot=331+6, title='C18O(2-1): mom0')
plot(rms12, subplot=332, title='12CO(2-1): rms')
plot(rms13, subplot=332+3, title='13CO(2-1): rms')
plot(rms18, subplot=332+6, title='C18O(2-1): rms')
splt(sp12, subplot=333, title='12CO(2-1): spectrum')
splt(sp13, subplot=333+3, title='13CO(2-1): spectrum')
splt(sp18, subplot=333+6, title='C18O(2-1): spectrum')
fig.savefig(dirpath+name+'_%s_test.png'%(pol), dpi=70)
fig.savefig(savepath+'qlook_obs_otf_'+timestamp+'_%s.png'%(pol.upper()))
pylab.close(fig)
def qlook_radiop(dirpath, savepath='./'):
import numpy
import os
import pylab
import analyse
import analyse.basefunc.analyse_radiop
import analyse.plotter.plot_radiop
import pylab
if dirpath[-1]!='/': dirpath += '/'
files = sorted(os.listdir(dirpath))
fits_files = []
# file check
for f in files:
if f.split('.')[-1]!='fits':
continue
fits_files.append(f)
continue
fits_files.sort()
# load analysed data
ana_data = []
for f in fits_files:
hdu = analyse.loadfits(dirpath+f)
ana_data.append(analyse.basefunc.analyse_radiop.analyse_radiop(hdu))
d = ana_data
#import plot_radiop
fig = pylab.figure(figsize=(12,5))
name = f.split('_')[2]
target = d[0][0]['target']
pylab.rcParams['legend.fontsize'] = 5
pylab.rcParams['figure.subplot.hspace'] = 0.5
pylab.rcParams['figure.subplot.wspace'] = 0.5
pylab.rcParams['font.size'] = 6
ax1,ax2,fig = analyse.plotter.plot_radiop.draw_radiop(d[0][0], iso = '12CO_H', color='b',fig=fig,ax1_plot=221, ax2_plot=223,show=False)
ax1,ax2,fig = analyse.plotter.plot_radiop.draw_radiop(d[2][0], iso = '13CO_H', color='g',fig=fig,ax1=ax1, ax2=ax2,show=False)
ax1,ax2,fig = analyse.plotter.plot_radiop.draw_radiop(d[4][0], iso = 'C18O_H', color='c',fig=fig,ax1=ax1, ax2=ax2,show=False)
ax1,ax2,fig = analyse.plotter.plot_radiop.draw_radiop(d[1][0], iso = '12CO_V', color='r',fig=fig,ax1=ax1, ax2=ax2,show=False)
ax1,ax2,fig = analyse.plotter.plot_radiop.draw_radiop(d[3][0], iso = '13CO_V', color='m',fig=fig,ax1=ax1, ax2=ax2,show=False)
ax1,ax2,fig = analyse.plotter.plot_radiop.draw_radiop(d[5][0], iso = 'C18O_V', color='y',fig=fig,ax1=ax1, ax2=ax2,show=False)
ax3 = None
ax4 = None
ax3,ax4,fig = analyse.plotter.plot_radiop.draw_radiop(d[0][1], iso = '12CO_H', color='b',fig=fig, ax1=ax3, ax2=ax4, ax1_plot=144, ax2_plot=143,show=False, vertical=True)
ax3,ax4,fig = analyse.plotter.plot_radiop.draw_radiop(d[2][1], iso = '13CO_H', color='g',fig=fig,ax1=ax3, ax2=ax4,show=False, vertical=True)
ax3,ax4,fig = analyse.plotter.plot_radiop.draw_radiop(d[4][1], iso = 'C18O_H', color='c',fig=fig,ax1=ax3, ax2=ax4,show=False, vertical=True)
ax3,ax4,fig = analyse.plotter.plot_radiop.draw_radiop(d[1][1], iso = '12CO_V', color='r',fig=fig,ax1=ax3, ax2=ax4,show=False, vertical=True)
ax3,ax4,fig = analyse.plotter.plot_radiop.draw_radiop(d[3][1], iso = '13CO_V', color='m',fig=fig,ax1=ax3, ax2=ax4,show=False, vertical=True)
ax3,ax4,fig = analyse.plotter.plot_radiop.draw_radiop(d[5][1], iso = 'C18O_V', color='y',fig=fig,ax1=ax3, ax2=ax4,show=False, vertical=True)
ax1.legend()
ax2.legend()
ax3.legend()
ax4.legend()
fig.text(0.5,0.975, target + ' cross scan results ' + name, horizontalalignment='center',verticalalignment='top')
pylab.savefig(savepath+'qlook_radiop_' + name + '.png')
#pylab.savefig('qlook_radiop' + name + '.pdf')
pylab.close(fig)
return
def easy_analyse(fitspath, output_dir, flag=None, plot=False, save=False):
import analyse
print('make_cube: %s'%(fitspath.split('/')[-1]))
raw_data = analyse.loadfits(fitspath)
cw_data = analyse.makespec(raw_data)
if flag is None:
fitted_data, flag = analyse.basefit(cw_data)
else:
flag = analyse.loadfits(flag)
fitted_data = analyse.basefit_flag(cw_data, None, flag)
pass
convolved_data = analyse.convolve(fitted_data, 2)
fitted_data = analyse.basefit_flag(convolved_data, None, flag)
ii = analyse.make_2d_map(fitted_data, flag)
rms = analyse.make_2d_map(fitted_data, flag, 'rms')
if save:
savepath = output_dir + fitspath.split('/')[-1].split('.fits')[0]
analyse.savefits(fitted_data, savepath+'.qlook.data.fits', clobber=True)
analyse.savefits(flag, savepath+'.qlook.flag.fits', clobber=True)
analyse.savefits(ii, savepath+'.qlook.ii.fits', clobber=True)
analyse.savefits(rms, savepath+'.qlook.rms.fits', clobber=True)
pass
if plot:
savepath = output_dir + fitspath.split('/')[-1].split('.fits')[0]
isotope = fitspath.split('_')[-2]
plot = analyse.custom_draw_map(figure=(8,8), xspacing=0.2, yspacing=0.2,
tick_labels_size=12, colorber_font_size=11, show=False)
plot(ii, title='mom0: '+isotope).save(savepath+'.qlook.ii.png')
plot(rms, title='rms: '+isotope).save(savepath+'.qlook.rms.png')
analyse.draw_otf_spectrum(fitted_data, figure=(12,5), title='spectra: '+isotope,
show=False).savefig(savepath+'.qlook.spectrum.png')
pass
raw_data.data = None
cw_data.data = None
return fitted_data, flag
def easy_analyse(fitspath, save=False, savepath='./'):
import analyse
print('make_cube: %s'%(fitspath.split('/')[-1]))
raw_data = analyse.loadfits(fitspath)
cw_data = analyse.makespec(raw_data)
fitted_data, flag = analyse.basefit(cw_data)
convolved_data = analyse.convolve(fitted_data, 2)
fitted_data, flag = analyse.basefit(convolved_data, 'auto')
savepath = savepath + fitspath.split('.fits')[0]
if save:
analyse.savefits(fitted_data, savepath+'.qlook.data.fits', clobber=True)
analyse.savefits(flag, savepath+'.qlook.flag.fits', clobber=True)
pass
raw_data.data = None
cw_data.data = None
del(raw_data)
del(cw_data)
return fitted_data
def qlook_ss(dirpath, filesave=False, savepath='./'):
import os
import pylab
import analyse
if dirpath[-1]!='/': dirpath += '/'
files = sorted(os.listdir(dirpath))
if len(files)<10:
print('6 FITS files are required.')
print(files)
return
fits_files = []
# file check
for f in files:
if f.split('_')[0]!='ps':
continue
if f.split('.')[-1]!='fits':
continue
if f.split('.')[-3]=='qlook':
continue
fits_files.append(f)
continue
name = files[4].split('_12CO_H.fits')[0]
timestamp = dirpath.split('/')[-2]
for f in fits_files:
os.system('python %s %s'%(__file__, dirpath+f))
continue
isotope = ['12CO', '13CO', 'C18O']
fig = pylab.figure(figsize=(20,12))
fig.suptitle(name+'_H')
for i, f in enumerate(fits_files[::2]):
_name = dirpath+f.split('.fits')[0]
raw = analyse.loadfits(_name+'.fits')
d = analyse.makespec(raw)
cube, flag = analyse.basefit(d[0])
#cube = analyse.loadfits(_name+'.qlook.data.fits')
#flag = analyse.loadfits(_name+'.qlook.flag.fits')
analyse.draw_ps_raw(raw, figure=fig, subplot=231+i, title='raw: '+isotope[i], show=False)
analyse.draw_ss_spectrum(cube, flag, figure=fig, subplot=234+i, title='spectrum: '+isotope[i], show=False)
continue
fig.savefig(savepath+'qlook_standardsource_'+timestamp+'_H.png')
pylab.close(fig)
#pylab.show()
fig = pylab.figure(figsize=(20,12))
fig.suptitle(name+'_V')
for i, f in enumerate(fits_files[1::2]):
_name = dirpath+f.split('.fits')[0]
raw = analyse.loadfits(_name+'.fits')
d = analyse.makespec(raw)
cube, flag = analyse.basefit(d[0])
#cube = analyse.loadfits(_name+'.qlook.data.fits')
#flag = analyse.loadfits(_name+'.qlook.flag.fits')
analyse.draw_ps_raw(raw, figure=fig, subplot=231+i, title='raw: '+isotope[i], show=False)
analyse.draw_ss_spectrum(cube, flag, figure=fig, subplot=234+i, title='spectrum: '+isotope[i], show=False)
continue
fig.savefig(savepath+'qlook_standardsource_'+timestamp+'_V.png')
pylab.close(fig)
#pylab.show()
return
def qlook_skydip(dirpath, savepath='./'):
import os
import pylab
import analyse
import analyse.basefunc.analyse_skydip
import analyse.plotter.plot_skydip
import pylab
if dirpath[-1]!='/': dirpath += '/'
files = sorted(os.listdir(dirpath))
fits_files = []
# file check
for f in files:
if f.split('.')[-1]!='fits':
continue
fits_files.append(f)
continue
fits_files.sort()
# load analysed data
ana_data = []
for f in fits_files:
hdu = analyse.loadfits(dirpath+f)
ana_data.append(analyse.basefunc.analyse_skydip.analyse_skydip(hdu))
# plot
name = f.split('_')[2]
pylab.rcParams['legend.fontsize']=5.5
pylab.rcParams['figure.subplot.hspace']=0.5
fig = pylab.figure(figsize=(8,5))
ax = analyse.plotter.plot_skydip.draw_skydip(ana_data[0],fig=fig,show=False,iso='12CO H',color='b')
ax = analyse.plotter.plot_skydip.draw_skydip(ana_data[2],fig=fig,ax=ax,show=False,iso='13CO H',color='g')
ax = analyse.plotter.plot_skydip.draw_skydip(ana_data[4],fig=fig,ax=ax,show=False,iso='C18O H',color='c')
ax = analyse.plotter.plot_skydip.draw_skydip(ana_data[1],fig=fig,ax=ax,show=False,iso='12CO V',color='r')
ax = analyse.plotter.plot_skydip.draw_skydip(ana_data[3],fig=fig,ax=ax,show=False,iso='13CO V',color='m')
ax = analyse.plotter.plot_skydip.draw_skydip(ana_data[5],fig=fig,ax=ax,show=False,iso='C18O V',color='y')
ax.set_title('skydip results ' + name)
ax.legend()
#----------- plot raw data ---------------
data12H = analyse.loadfits(dirpath+fits_files[0]).data
data12V = analyse.loadfits(dirpath+fits_files[1]).data
data13H = analyse.loadfits(dirpath+fits_files[2]).data
data13V = analyse.loadfits(dirpath+fits_files[3]).data
data18H = analyse.loadfits(dirpath+fits_files[4]).data
data18V = analyse.loadfits(dirpath+fits_files[5]).data
print('-------sum 13 12 18 spectra------')
import numpy
x = numpy.linspace(0., 1.0, 16383)
ax1 = fig.add_subplot(212)
for i in range(len(data12H)):
d_H = numpy.concatenate((data18H[i]['data'], data12H[i]['data'], data13H[i]['data']))
d_V = numpy.concatenate((data18V[i]['data'], data12V[i]['data'], data13V[i]['data']))
ax1.plot(x, d_H,'b--')
ax1.plot(x, d_V,'r--')
ax1.set_ylabel('IF Power')
ax1.set_xlabel('Frequency [GHz]')
ax1.set_title('IFpower (blue:Hpol red:Vpol)')
ax1.grid()
pylab.savefig(savepath+'qlook_skydip_' + name + '.png')
pylab.close(ax.figure)
#pylab.show()
return
