generated from erosita/uds
IKI
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@ -58,14 +58,14 @@ maxiters=10
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with open(ignored_rev_file, 'rb') as fp:
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ignored_rev = pickle.load(fp)
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print(ignored_rev)
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#print(ignored_rev)
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print("{} orbits ignored".format(len(ignored_rev)))
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ign=ignored_rev.tolist()
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glon, step = np.linspace(-lon_max, lon_max, num=lon_nbin, endpoint=False,retstep=True)
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print(glon,step)
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#print(glon,step)
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#
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@ -99,6 +99,8 @@ lat_arr=[]
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for i in range(lon_nbin):
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dkey="{:04d}".format(i)
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#if(i != 5):
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# continue
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df0 = df.query('LON > {} & LON <= {} & LAT > {} & LAT < {} & REV != @ign'.format(glon[i],glon[i]+step,-lat_max,lat_max))
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@ -124,7 +126,7 @@ for i in range(lon_nbin):
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lon_arr.append(row['LON'])
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lat_arr.append(row['LAT'])
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#sys.exit()
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if not os.path.exists(profdir):
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@ -1,4 +1,4 @@
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./03_grxe_galprof.py E01 71
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./03_grxe_galprof.py E01 51
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./03_grxe_galprof.py E13 17
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./03_grxe_galprof.py E14 21
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@ -4,7 +4,7 @@ __author__ = "Roman Krivonos"
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__copyright__ = "Space Research Institute (IKI)"
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from astropy.table import Table, Column
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from matplotlib import ticker
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import matplotlib.pyplot as plt
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import sys
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@ -51,30 +51,38 @@ ax1.ticklabel_format(style='sci', axis='y', scilimits=(0,0))
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ax2.ticklabel_format(style='sci', axis='y', scilimits=(0,0))
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ax3.ticklabel_format(style='sci', axis='y', scilimits=(0,0))
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ax1.xaxis.set_minor_locator(ticker.MultipleLocator(10))
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ax2.xaxis.set_minor_locator(ticker.MultipleLocator(10))
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ax3.xaxis.set_minor_locator(ticker.MultipleLocator(10))
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ax1.yaxis.set_minor_locator(ticker.MultipleLocator(0.2))
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ax2.yaxis.set_minor_locator(ticker.MultipleLocator(0.2))
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ax3.yaxis.set_minor_locator(ticker.MultipleLocator(0.2))
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lon=(df1['LON1']+df1['LON2'])/2
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ax1.errorbar(lon, df1['GRXE_SIM_FLUX']/scale,
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yerr=df1['GRXE_SIM_ERROR']/scale,
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xerr=(df1['LON2']-df1['LON1'])/2,
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fmt='o' )
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fmt='o', color='black')
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ax1.grid(visible=True)
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lon=(df2['LON1']+df2['LON2'])/2
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ax2.errorbar(lon, df2['GRXE_SIM_FLUX']/scale,
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yerr=df2['GRXE_SIM_ERROR']/scale,
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xerr=(df2['LON2']-df2['LON1'])/2,fmt='o' )
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xerr=(df2['LON2']-df2['LON1'])/2,fmt='o' , color='black')
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ax2.grid(visible=True)
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lon=(df3['LON1']+df3['LON2'])/2
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ax3.errorbar(lon, df3['GRXE_SIM_FLUX']/scale,
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yerr=df3['GRXE_SIM_ERROR']/scale,
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xerr=(df3['LON2']-df3['LON1'])/2, fmt='o' )
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xerr=(df3['LON2']-df3['LON1'])/2, fmt='o' , color='black')
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ax3.grid(visible=True)
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#x = np.arange(-10, 10, 0.001)
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#plot normal distribution with mean 0 and standard deviation 1
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#plt.plot(x, norm.pdf(x, 0, 1), color='red', linewidth=2)
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plt.xlabel('Galactic Longitude',fontsize=14, fontweight='normal')
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plt.xlabel('Galactic Longitude, deg.',fontsize=14, fontweight='normal')
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ax2.set_ylabel('GRXE flux, x100 mCrab',fontsize=14, fontweight='normal')
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#plt.xscale('linear')
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