k = 0 for junk, o, junk, junk, sl, junk in data_800: if np.shape(data_700[data_700[:, 0] == o, 1])[0] > 0: corrected_700[k] = o, data_700[data_700[:, 0] == o, 4][0] / sl else: corrected_700[k] = o, data_700[data_700[:, 0] < o, 4][-1] / sl if np.shape(data_620[data_620[:, 1] == o, 1])[0] > 0: corrected_620[k] = o, data_620[data_620[:, 0] == o, 4][0] / sl else: corrected_620[k] = o, data_620[data_620[:, 0] < o, 4][-1] / sl k += 1 xx = data_800[:, 1] / param.last_orbits[orbit_id] * 365. xx = figures.convert_date(xx) fig = plt.figure() ax = plt.subplot(111) # zooms ax.yaxis.set_major_locator(MultipleLocator(0.5)) ax.yaxis.set_minor_locator(MultipleLocator(0.1)) #pax.yaxis.set_major_locator(MultipleLocator(1.)) #pax.yaxis.set_minor_locator(MultipleLocator(0.5)) #ax.xaxis.set_major_locator(MultipleLocator(20.)) ax.xaxis.grid(True, 'minor') ax.yaxis.grid(True, 'minor') ax.xaxis.grid(True, 'major', linewidth=2)
fig = plt.figure() ax = plt.subplot(111) maxy = 0. miny = 0. for orbit_id, legend in zip(orbit_ids, legends): folder_flux, folder_figures, folder_misc = init_folders(orbit_id) data = np.loadtxt('%d_misc/%s' % (orbit_id, error_file), delimiter=',') dates = data[:, 0] / param.last_orbits[orbit_id] * 365. values = data[:, 1] if np.amax(values) > maxy: maxy = np.amax(values) if np.min(values) < miny: miny = np.amin(values) dates = figures.convert_date(dates) ax.plot(dates, values, label=legend, linewidth=2) fig.autofmt_xdate() plt.ylim([miny * 0.95, maxy * 1.05]) plt.grid() ax.xaxis.grid(True, 'major', linewidth=2) ax.yaxis.grid(True, 'major', linewidth=2) plt.legend(loc='upper center') folder_figures = 'all_figures/' if average == '': plt.ylabel( r'$\mathrm{Mean\ stray\ light\ flux\ }\left[\frac{\mathrm{ph}}{\mathrm{px}\cdot\mathrm{s}}\right]$' )
print >> f, 'error_mean:', np.mean(data[:,3]) print >> f, 'error_std:', np.std(data[:,3]) fig=plt.figure() ax=plt.subplot(111) ax.yaxis.set_major_locator(MultipleLocator(5)) ax.yaxis.set_minor_locator(MultipleLocator(1)) ax.xaxis.grid(True,'minor') ax.yaxis.grid(True,'minor') ax.xaxis.grid(True,'major',linewidth=2) ax.yaxis.grid(True,'major',linewidth=2) xx = data[:,1]/param.last_orbits[orbit_id]*365. xx = figures.convert_date(xx) plt.plot(xx, data[:,3]*100, linewidth=1.5) plt.plot([xx[0],xx[-1]], [p*100., p*100.], color='r', lw=3) fig.autofmt_xdate() plt.ylim([0, 15]) plt.ylabel(r'$\mathrm{Error\ to\ previous\ step\ [\%]}$') # Saves the figure fname = '%serror_evolution_%d_%d' % (folder_figures,orbit_id,sl_angle) figures.savefig(fname,fig,fancy) ############ STRAY LIGHT print >> f, '# STRAY LIGHT'
fig=plt.figure() ax=plt.subplot(111) maxy = 0. miny = 0. for orbit_id, legend in zip(orbit_ids,legends): folder_flux, folder_figures, folder_misc = init_folders(orbit_id) data = np.loadtxt('%d_misc/%s' % (orbit_id, error_file), delimiter=',') dates = data[:,0]/param.last_orbits[orbit_id]*365. values= data[:,1] if np.amax(values) > maxy: maxy = np.amax(values) if np.min(values) < miny: miny = np.amin(values) dates = figures.convert_date(dates) ax.plot(dates, values,label=legend, linewidth=2) fig.autofmt_xdate() plt.ylim([miny*0.95,maxy*1.05]) plt.grid() ax.xaxis.grid(True,'major',linewidth=2) ax.yaxis.grid(True,'major',linewidth=2) plt.legend(loc='upper center') folder_figures= 'all_figures/' if average == '' : plt.ylabel(r'$\mathrm{Mean\ stray\ light\ flux\ }\left[\frac{\mathrm{ph}}{\mathrm{px}\cdot\mathrm{s}}\right]$') if average == '_max' : plt.ylabel(r'$\mathrm{Mean\ maximum\ stray\ light\ flux\ }\left[\frac{\mathrm{ph}}{\mathrm{px}\cdot\mathrm{s}}\right]$') if average == '_maxdir' : plt.ylabel(r'$\mathrm{Flux\ in\ worst\ direction}\left[\frac{\mathrm{ph}}{\mathrm{px}\cdot\mathrm{s}}\right]$')