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Acknowledgements

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This commit is contained in:
Roman Krivonos 2024-12-05 17:12:01 +03:00
parent b6392efbf9
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4 changed files with 7 additions and 30 deletions
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scripts/03_grxe_flux.sh
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scripts/03_grxe_galprof.py
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@ -110,8 +110,8 @@ for i in range(lon_nbin):
sg_mean,sg_sem,skew_val,skew_err = get_spec(df0, sigma=sigma, grxe_err_cut=grxe_err_cut, enkey=enkey, plotme=True, nscw_min=nscw_min, gaussfit=True) sg_mean,sg_sem,skew_val,skew_err = get_spec(df0, sigma=sigma, grxe_err_cut=grxe_err_cut, enkey=enkey, plotme=True, nscw_min=nscw_min, gaussfit=True)
nsel = int(df0.shape[0]*simfrac/100) #nsel = int(df0.shape[0]*simfrac/100)
print("lon {:.2f} ".format(glon[i]),"nsel=",nsel,df0.shape[0]) #print("lon {:.2f} ".format(glon[i]),"nsel=",nsel,df0.shape[0])
#print('sg_sem',sg_sem) #print('sg_sem',sg_sem)
mean_map[i] = sg_mean mean_map[i] = sg_mean

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scripts/03_grxe_map.py
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@ -143,7 +143,7 @@ for i in range(sx):
#print('sg_sem',sg_sem) #print('sg_sem',sg_sem)
mean_map[j][i] = sg_mean mean_map[j][i] = sg_mean
sem_map[j][i] = sg_sem sem_map[j][i] = sg_sem
sign_map[j][i] = sg_mean/sg_sem #sign_map[j][i] = sg_mean/sg_sem
cnt_map[j][i] = df0.shape[0] cnt_map[j][i] = df0.shape[0]
""" Filter by error map """ """ Filter by error map """

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scripts/README.md
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@ -16,11 +16,11 @@ Calibrates Crab detector count rate model.
### 01_crabmodel_plot_poly.py ### 01_crabmodel_plot_poly.py
Plot long-term Crab detector count rate approximated by cubic polynomial function (Fig. B7 in paper). Plot long-term Crab detector count rate approximated by cubic polynomial function (Fig. B8 in paper).
### 01_crabmodel_plot_sys.py ### 01_crabmodel_plot_sys.py
Plots the normalized distribution of the residuals between the IBIS/ISGRI Crab count rate and the corresponding polynomial fit (Fig. B8 in the paper). The distribution is approximated with a Gaussian function. Plots the normalized distribution of the residuals between the IBIS/ISGRI Crab count rate and the corresponding polynomial fit (Fig. B9 in the paper). The distribution is approximated with a Gaussian function.
### 02_grxe_resid.py/02_grxe_resid.sh ### 02_grxe_resid.py/02_grxe_resid.sh
@ -28,9 +28,9 @@ Calculates difference between detector count rate and that predicted by backgrou
### 02_grxe_resid_plot.py ### 02_grxe_resid_plot.py
Plots normalized distribution of the relative residuals of the background model obtained in three energy bands for BKG region (Figs. A5 and A6 in the paper). Plots normalized distribution of the relative residuals of the background model obtained in three energy bands for BKG region (Figs. A6 and A7 in the paper).
### 02_grxe_map.py/03_grxe_map.sh ### 03_grxe_map.py
Makes the map of the residuals in mCrab units (not shown in the paper). Makes the map of the residuals in mCrab units (not shown in the paper).