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Fix remaining style errors
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@haticekaratay
haticekaratay committed Oct 17, 2023
1 parent 0cdf5bd commit ae95dd6
Showing 1 changed file with 26 additions and 26 deletions.
52 changes: 26 additions & 26 deletions notebooks/NIRISS_WFSS_postpipeline/00_Optimal_extraction.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -132,12 +132,11 @@
"\n",
"# Image array from direct image. This is for optimal extraction and masking.\n",
"# This image should already be sky-subtracted; otherwise, you will encounter a wrong result with optimal extraction.\n",
"# fixed\n",
"\n",
"infile = f'{DIR_DATA}l3_nis_{filt_det}_i2d_skysub.fits'\n",
"hdu = fits.open(infile)\n",
"\n",
"# This is just for error array;\n",
"# fixed\n",
"infile = f'{DIR_DATA}l3_nis_{filt_det}_i2d.fits'\n",
"hdu_err = fits.open(infile)\n",
"\n",
Expand Down Expand Up @@ -251,15 +250,14 @@
"# Which filter, grating, and object?\n",
"filt = 'f200w'\n",
"\n",
"#grism = 'G150R'\n",
"# grism = 'G150R'\n",
"grism = 'G150C'\n",
"\n",
"id = '00004'\n",
"\n",
"# Zero-indexed number for dither --- the test data here has two dither positions, so 0 or 1.\n",
"ndither = 0\n",
"print(DIR_DATA)\n",
"# fixed\n",
"\n",
"file_2d = f'{DIR_DATA}l3_nis_{filt}_{grism}_s{id}_cal.fits'\n",
"hdu_2d = fits.open(file_2d)\n",
"\n",
Expand Down Expand Up @@ -372,7 +370,7 @@
"outputs": [],
"source": [
"# Sum along x (disperse) direction\n",
"flux_y = np.zeros(len(sci_rot[:,0]), 'float')\n",
"flux_y = np.zeros(len(sci_rot[:, 0]), 'float')\n",
"for ii in range(sci_rot.shape[0]):\n",
" flux_y[ii] = np.sum(sci_rot[ii, :])\n",
"\n",
Expand Down Expand Up @@ -450,17 +448,17 @@
" # 1. DQ array\n",
" # 2. error value\n",
" # 3. CR detection\n",
" mask_tmp = (dq_2d[:, ii] == 0) & (err_2d[:, ii]>0) & ( (data_2d[:, ii] - flux_y[:] * flux_disp1[ii])**2 < sig**2 * err_2d[:, ii]**2)\n",
" mask_tmp = (dq_2d[:, ii] == 0) & (err_2d[:, ii] > 0) & ((data_2d[:, ii] - flux_y[:] * flux_disp1[ii])**2 < sig**2 * err_2d[:, ii]**2)\n",
" ivar = 1. / err_2d[:, ii]**2\n",
"\n",
" num = flux_y[:] * data_2d[:, ii] * ivar\n",
" den = flux_y[:]**2 * ivar\n",
" flux_disp[ii] = num[mask_tmp].sum(axis=0) / den[mask_tmp].sum(axis=0)\n",
" err_disp[ii] = np.sqrt(1./den[mask_tmp].sum(axis=0))\n",
" wave_disp[ii] = wave_2d[0,ii]\n",
" wave_disp[ii] = wave_2d[0, ii]\n",
" \n",
"plt.errorbar(wave_disp, flux_disp, yerr=err_disp)\n",
"plt.xlim(1.7,2.3)"
"plt.xlim(1.7, 2.3)"
]
},
{
Expand Down Expand Up @@ -516,7 +514,7 @@
"for ii in range(sci_rot.shape[0]):\n",
" flux_tmp = sci_rot[ii, :]\n",
" xx_tmp = np.arange(0, len(sci_rot[ii, :]), 1)\n",
" plt.plot(xx_tmp, flux_tmp, label='y=%d'%(ii))\n",
" plt.plot(xx_tmp, flux_tmp, label=f'y={ii}')\n",
" \n",
"plt.legend(loc=1, fontsize=8)\n",
"plt.xlabel('Wavelength direction')\n",
Expand Down Expand Up @@ -562,19 +560,21 @@
"outputs": [],
"source": [
"# Fitting function with Moffat\n",
"\n",
"# Moffat fnc.\n",
"\n",
"def moffat(xx, A, x0, gamma, alp):\n",
" yy = A * (1. + (xx-x0)**2/gamma**2)**(-alp)\n",
" return yy\n",
"\n",
"\n",
"def fit_mof(xx, lsf):\n",
" #xx = lsf * 0\n",
" #for ii in range(len(lsf)):\n",
" # xx = lsf * 0\n",
" # for ii in range(len(lsf)):\n",
" # xx[ii] = ii - len(lsf)/2.\n",
" popt, pcov = curve_fit(moffat, xx, lsf)\n",
" return popt\n",
"\n",
"\n",
"def LSF_mof(xsf, lsf, f_plot=True):\n",
" '''\n",
" Input:\n",
Expand All @@ -594,13 +594,13 @@
" A, xm, gamma, alpha = -1, -1, -1, -1\n",
" pass\n",
"\n",
" if A>0:\n",
" if A > 0:\n",
" lsf_mod = moffat(xsf, A, 0, gamma, alpha)\n",
" \n",
" if f_plot:\n",
" yy = moffat(xsf, A, xm, gamma, alpha)\n",
" plt.plot(xsf, yy, 'r.', ls='-', label='Data')\n",
" plt.plot(xsf, lsf_mod, 'b+', ls='-', label='Model:$gamma=%.2f$\\n$alpha=%.2f$'%(gamma, alpha))\n",
" plt.plot(xsf, lsf_mod, 'b+', ls='-', label=f'Model: gamma={gamma:2f}\\nalpha={alpha:2f}')\n",
" plt.legend()\n",
" plt.show()\n",
" \n",
Expand Down Expand Up @@ -630,7 +630,7 @@
"fm = open(f'{DIR_OUT}l3_nis_{filt}_{grism}_s{id}_moffat.txt', 'w')\n",
"fm.write('# A x0 gamma alp\\n')\n",
"fm.write('# Moffat function\\n')\n",
"fm.write('%.3f %.3f %.3f %.3f\\n'%(A, xm, gamma, alpha))\n",
"fm.write(f'{A:.3f} {xm:.3f} {gamma:.3f} {alpha:.3f}\\n')\n",
"\n",
"fm.close()"
]
Expand Down Expand Up @@ -726,12 +726,12 @@
" fm = open(f'{DIR_OUT}l3_nis_{filt}_{grism}_s{id}_moffat.txt', 'w')\n",
" fm.write('# A x0 gamma alp\\n')\n",
" fm.write('# Moffat function\\n')\n",
" fm.write('%.3f %.3f %.3f %.3f\\n'%(A, xm, gamma, alpha))\n",
" fm.write(f'{A:.3f} {xm:.3f} {gamma:.3f} {alpha:.3f}\\n')\n",
" fm.close()\n",
"\n",
" # This is for Optimal extraction;\n",
" # Sum along x (disperse) direction\n",
" flux_y = np.zeros(len(sci_rot[:,0]), 'float')\n",
" flux_y = np.zeros(len(sci_rot[:, 0]), 'float')\n",
" for ii in range(sci_rot.shape[0]):\n",
" flux_y[ii] = np.sum(sci_rot[ii, :])\n",
" \n",
Expand All @@ -755,10 +755,10 @@
" den = flux_y[:]**2 * ivar\n",
" flux_disp[ii] = num[mask_tmp].sum(axis=0)/den[mask_tmp].sum(axis=0)\n",
" err_disp[ii] = np.sqrt(1./den[mask_tmp].sum(axis=0))\n",
" wave_disp[ii] = wave_2d[0,ii]\n",
" wave_disp[ii] = wave_2d[0, ii]\n",
"\n",
" plt.close()\n",
" con_plot = (wave_disp>0)\n",
" con_plot = (wave_disp > 0)\n",
" plt.errorbar(wave_disp[con_plot], flux_disp[con_plot], yerr=err_disp[con_plot])\n",
" plt.ylim(-0, 3000)\n",
" plt.show()\n",
Expand Down Expand Up @@ -796,11 +796,11 @@
"outputs": [],
"source": [
"grism = 'G150C'\n",
"id = '00003'\n",
"id = '00003'\n",
"DIR_OUT = './output/'\n",
"\n",
"filts = ['f115w', 'f150w', 'f200w']\n",
"ndithers = np.arange(0,2,1) # There are four dithers in the data set;\n",
"filts = ['f115w', 'f150w', 'f200w']\n",
"ndithers = np.arange(0, 2, 1) # There are four dithers in the data set;\n",
"\n",
"sig = 5.0\n",
"\n",
Expand Down Expand Up @@ -866,12 +866,12 @@
" fm = open(f'{DIR_OUT}l3_nis_{filt}_{grism}_s{id}_moffat.txt', 'w')\n",
" fm.write('# A x0 gamma alp\\n')\n",
" fm.write('# Moffat function\\n')\n",
" fm.write('%.3f %.3f %.3f %.3f\\n'%(A, xm, gamma, alpha))\n",
" fm.write(f'{A:.3f} {xm:.3f} {gamma:.3f} {alpha:.3f}\\n')\n",
" fm.close()\n",
"\n",
" # This is for Optimal extraction;\n",
" # Sum along x (disperse) direction\n",
" flux_y = np.zeros(len(sci_rot[:,0]), 'float')\n",
" flux_y = np.zeros(len(sci_rot[:, 0]), 'float')\n",
" for ii in range(sci_rot.shape[0]):\n",
" flux_y[ii] = np.sum(sci_rot[ii, :])\n",
" \n",
Expand All @@ -895,7 +895,7 @@
" den = flux_y[:]**2 * ivar\n",
" flux_disp[ii] = num[mask_tmp].sum(axis=0)/den[mask_tmp].sum(axis=0)\n",
" err_disp[ii] = np.sqrt(1./den[mask_tmp].sum(axis=0))\n",
" wave_disp[ii] = wave_2d[0,ii]\n",
" wave_disp[ii] = wave_2d[0, ii]\n",
"\n",
" plt.close()\n",
" con_plot = (wave_disp > 0)\n",
Expand Down

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