correct a bug where rotation doesn't update header when wcs.pc is identity

src/FOC_reduction.py

@@ -16,94 +16,99 @@ from lib.deconvolve import from_file_psf
 import matplotlib.pyplot as plt
 from astropy.wcs import WCS
 
+##### User inputs
+## Input and output locations
+#globals()['data_folder'] = "../data/NGC1068_x274020/"
+#globals()['infiles'] = ['x274020at_c0f.fits','x274020bt_c0f.fits','x274020ct_c0f.fits',
+#   'x274020dt_c0f.fits','x274020et_c0f.fits','x274020ft_c0f.fits',
+#   'x274020gt_c0f.fits','x274020ht_c0f.fits','x274020it_c0f.fits']
+##psf_file = 'NGC1068_f253m00.fits'
+#globals()['plots_folder'] = "../plots/NGC1068_x274020/"
+
+#globals()['data_folder'] = "../data/IC5063_x3nl030/"
+#globals()['infiles'] = ['x3nl0301r_c0f.fits','x3nl0302r_c0f.fits','x3nl0303r_c0f.fits']
+##psf_file = 'IC5063_f502m00.fits'
+#globals()['plots_folder'] = "../plots/IC5063_x3nl030/"
+
+#globals()['data_folder'] = "../data/NGC1068_x14w010/"
+#globals()['infiles'] = ['x14w0101t_c0f.fits','x14w0102t_c0f.fits','x14w0103t_c0f.fits',
+#   'x14w0104t_c0f.fits','x14w0105p_c0f.fits','x14w0106t_c0f.fits']
+#globals()['plots_folder'] = "../plots/NGC1068_x14w010/"
+
+#globals()['data_folder'] = "../data/3C405_x136060/"
+#globals()['infiles'] = ['x1360601t_c0f.fits','x1360602t_c0f.fits','x1360603t_c0f.fits']
+#globals()['plots_folder'] = "../plots/3C405_x136060/"
+
+#globals()['data_folder'] = "../data/CygnusA_x43w0/"
+#globals()['infiles'] = ['x43w0101r_c0f.fits', 'x43w0102r_c0f.fits', 'x43w0103r_c0f.fits',
+#   'x43w0104r_c0f.fits', 'x43w0105r_c0f.fits', 'x43w0106r_c0f.fits',
+#   'x43w0107r_c0f.fits', 'x43w0108r_c0f.fits', 'x43w0109r_c0f.fits']
+#globals()['infiles'] = ['x43w0201r_c0f.fits', 'x43w0202r_c0f.fits', 'x43w0203r_c0f.fits',
+#   'x43w0204r_c0f.fits', 'x43w0205r_c0f.fits', 'x43w0206r_c0f.fits']
+#globals()['plots_folder'] = "../plots/CygnusA_x43w0/"
+
+#globals()['data_folder'] = "../data/3C109_x3mc010/"
+#globals()['infiles'] = ['x3mc0101m_c0f.fits','x3mc0102m_c0f.fits','x3mc0103m_c0f.fits']
+#globals()['plots_folder'] = "../plots/3C109_x3mc010/"
+
+#globals()['data_folder'] = "../data/MKN463_x2rp030/"
+#globals()['infiles'] = ['x2rp0201t_c0f.fits', 'x2rp0202t_c0f.fits', 'x2rp0203t_c0f.fits',
+#   'x2rp0204t_c0f.fits', 'x2rp0205t_c0f.fits', 'x2rp0206t_c0f.fits',
+#   'x2rp0207t_c0f.fits', 'x2rp0301t_c0f.fits', 'x2rp0302t_c0f.fits',
+#   'x2rp0303t_c0f.fits', 'x2rp0304t_c0f.fits', 'x2rp0305t_c0f.fits',
+#   'x2rp0306t_c0f.fits', 'x2rp0307t_c0f.fits']
+#globals()['plots_folder'] = "../plots/MKN463_x2rp030/"
+
+#globals()['data_folder'] = "../data/PG1630+377_x39510/"
+#globals()['infiles'] = ['x3990201m_c0f.fits', 'x3990205m_c0f.fits', 'x3995101r_c0f.fits',
+#   'x3995105r_c0f.fits', 'x3995109r_c0f.fits', 'x3995201r_c0f.fits',
+#   'x3995205r_c0f.fits', 'x3990202m_c0f.fits', 'x3990206m_c0f.fits',
+#   'x3995102r_c0f.fits', 'x3995106r_c0f.fits', 'x399510ar_c0f.fits',
+#   'x3995202r_c0f.fits','x3995206r_c0f.fits']
+#globals()['plots_folder'] = "../plots/PG1630+377_x39510/"
+
+#globals()['data_folder'] = "../data/MKN3_x3nl010/"
+#globals()['infiles'] = ['x3nl0101r_c0f.fits','x3nl0102r_c0f.fits','x3nl0103r_c0f.fits']
+#globals()['plots_folder'] = "../plots/MKN3_x3nl010/"
+
+#globals()['data_folder'] = "../data/MKN3_x3md010/"
+#globals()['infiles'] = ['x3md0101r_c0f.fits', 'x3md0102r_c0f.fits', 'x3md0103r_c0f.fits']
+#globals()['infiles'] = ['x3md0104r_c0f.fits', 'x3md0105r_c0f.fits', 'x3md0106r_c0f.fits']
+#globals()['plots_folder'] = "../plots/MKN3_x3md010/"
+
+#globals()['data_folder'] = "../data/MKN78_x3nl020/"
+#globals()['infiles'] = ['x3nl0201r_c0f.fits','x3nl0202r_c0f.fits','x3nl0203r_c0f.fits']
+#globals()['plots_folder'] = "../plots/MKN78_x3nl020/"
+
+#globals()['data_folder'] = "../data/3C273_x0u20/"
+#globals()['infiles'] = ['x0u20101t_c0f.fits','x0u20102t_c0f.fits','x0u20103t_c0f.fits',
+#   'x0u20104t_c0f.fits','x0u20105t_c0f.fits','x0u20106t_c0f.fits',
+#   'x0u20201t_c0f.fits','x0u20202t_c0f.fits','x0u20203t_c0f.fits',
+#   'x0u20204t_c0f.fits','x0u20205t_c0f.fits','x0u20206t_c0f.fits',
+#   'x0u20301t_c0f.fits','x0u20302t_c0f.fits','x0u20303t_c0f.fits',
+#   'x0u20304t_c0f.fits','x0u20305t_c0f.fits','x0u20306t_c0f.fits']
+#globals()['plots_folder'] = "../plots/3C273_x0u20/"
+
+#BEWARE: 5 observations separated by 1 year each (1995, 1996, 1997, 1998, 1999)
+#globals()['data_folder'] = "../data/M87/POS1/"
+#globals()['infiles'] = ['x2py010ct_c0f.fits','x2py010dt_c0f.fits','x2py010et_c0f.fits','x2py010ft_c0f.fits'] #1995
+#globals()['infiles'] = ['x3be010ct_c0f.fits','x3be010dt_c0f.fits','x3be010et_c0f.fits','x3be010ft_c0f.fits'] #1996
+#globals()['infiles'] = ['x43r010km_c0f.fits','x43r010mm_c0f.fits','x43r010om_c0f.fits','x43r010rm_c0f.fits'] #1997
+#globals()['infiles'] = ['x43r110kr_c0f.fits','x43r110mr_c0f.fits','x43r110or_c0f.fits','x43r110rr_c0f.fits'] #1998
+#globals()['infiles'] = ['x43r210kr_c0f.fits','x43r210mr_c0f.fits','x43r210or_c0f.fits','x43r210rr_c0f.fits'] #1999
+#globals()['plots_folder'] = "../plots/M87/POS1/"
+
+#BEWARE: 5 observations separated by 1 year each (1995, 1996, 1997, 1998, 1999)
+globals()['data_folder'] = "../data/M87/POS3/"
+globals()['infiles'] = ['x2py030at_c0f.fits','x2py030bt_c0f.fits','x2py030ct_c0f.fits','x2py0309t_c0f.fits'] #1995
+#globals()['infiles'] = ['x3be030at_c0f.fits','x3be030bt_c0f.fits','x3be030ct_c0f.fits','x3be0309t_c0f.fits'] #1996
+#globals()['infiles'] = ['x43r030em_c0f.fits','x43r030gm_c0f.fits','x43r030im_c0f.fits','x43r030lm_c0f.fits'] #1997
+#globals()['infiles'] = ['x43r130er_c0f.fits','x43r130fr_c0f.fits','x43r130ir_c0f.fits','x43r130lr_c0f.fits'] #1998
+#globals()['infiles'] = ['x43r230er_c0f.fits','x43r230fr_c0f.fits','x43r230ir_c0f.fits','x43r230lr_c0f.fits'] #1999
+globals()['plots_folder'] = "../plots/M87/POS3/"
+
 
 def main():
-    ##### User inputs
-    ## Input and output locations
-#    globals()['data_folder'] = "../data/NGC1068_x274020/"
-#    infiles = ['x274020at_c0f.fits','x274020bt_c0f.fits','x274020ct_c0f.fits',
-#            'x274020dt_c0f.fits','x274020et_c0f.fits','x274020ft_c0f.fits',
-#            'x274020gt_c0f.fits','x274020ht_c0f.fits','x274020it_c0f.fits']
-##    psf_file = 'NGC1068_f253m00.fits'
-#    globals()['plots_folder'] = "../plots/NGC1068_x274020/"
-
-#    globals()['data_folder'] = "../data/IC5063_x3nl030/"
-#    infiles = ['x3nl0301r_c0f.fits','x3nl0302r_c0f.fits','x3nl0303r_c0f.fits']
-##    psf_file = 'IC5063_f502m00.fits'
-#    globals()['plots_folder'] = "../plots/IC5063_x3nl030/"
-
-#    globals()['data_folder'] = "../data/NGC1068_x14w010/"
-#    infiles = ['x14w0101t_c0f.fits','x14w0102t_c0f.fits','x14w0103t_c0f.fits',
-#            'x14w0104t_c0f.fits','x14w0105p_c0f.fits','x14w0106t_c0f.fits']
-#    globals()['plots_folder'] = "../plots/NGC1068_x14w010/"
-
-#    globals()['data_folder'] = "../data/3C405_x136060/"
-#    infiles = ['x1360601t_c0f.fits','x1360602t_c0f.fits','x1360603t_c0f.fits']
-#    globals()['plots_folder'] = "../plots/3C405_x136060/"
-
-#    globals()['data_folder'] = "../data/CygnusA_x43w0/"
-#    infiles = ['x43w0101r_c0f.fits', 'x43w0102r_c0f.fits', 'x43w0103r_c0f.fits',
-#            'x43w0104r_c0f.fits', 'x43w0105r_c0f.fits', 'x43w0106r_c0f.fits',
-#            'x43w0107r_c0f.fits', 'x43w0108r_c0f.fits', 'x43w0109r_c0f.fits']
-#    infiles = ['x43w0201r_c0f.fits', 'x43w0202r_c0f.fits', 'x43w0203r_c0f.fits',
-#            'x43w0204r_c0f.fits', 'x43w0205r_c0f.fits', 'x43w0206r_c0f.fits']
-#    globals()['plots_folder'] = "../plots/CygnusA_x43w0/"
-
-#    globals()['data_folder'] = "../data/3C109_x3mc010/"
-#    infiles = ['x3mc0101m_c0f.fits','x3mc0102m_c0f.fits','x3mc0103m_c0f.fits']
-#    globals()['plots_folder'] = "../plots/3C109_x3mc010/"
-
-#    globals()['data_folder'] = "../data/MKN463_x2rp030/"
-#    infiles = ['x2rp0201t_c0f.fits', 'x2rp0202t_c0f.fits', 'x2rp0203t_c0f.fits',
-#            'x2rp0204t_c0f.fits', 'x2rp0205t_c0f.fits', 'x2rp0206t_c0f.fits',
-#            'x2rp0207t_c0f.fits', 'x2rp0301t_c0f.fits', 'x2rp0302t_c0f.fits',
-#            'x2rp0303t_c0f.fits', 'x2rp0304t_c0f.fits', 'x2rp0305t_c0f.fits',
-#            'x2rp0306t_c0f.fits', 'x2rp0307t_c0f.fits']
-#    globals()['plots_folder'] = "../plots/MKN463_x2rp030/"
-
-#    globals()['data_folder'] = "../data/PG1630+377_x39510/"
-#    infiles = ['x3990201m_c0f.fits', 'x3990205m_c0f.fits', 'x3995101r_c0f.fits',
-#            'x3995105r_c0f.fits', 'x3995109r_c0f.fits', 'x3995201r_c0f.fits',
-#            'x3995205r_c0f.fits', 'x3990202m_c0f.fits', 'x3990206m_c0f.fits',
-#            'x3995102r_c0f.fits', 'x3995106r_c0f.fits', 'x399510ar_c0f.fits',
-#            'x3995202r_c0f.fits','x3995206r_c0f.fits']
-#    globals()['plots_folder'] = "../plots/PG1630+377_x39510/"
-
-#    globals()['data_folder'] = "../data/MKN3_x3nl010/"
-#    infiles = ['x3nl0101r_c0f.fits','x3nl0102r_c0f.fits','x3nl0103r_c0f.fits']
-#    globals()['plots_folder'] = "../plots/MKN3_x3nl010/"
-
-#    globals()['data_folder'] = "../data/MKN3_x3md010/"
-#    infiles = ['x3md0101r_c0f.fits', 'x3md0102r_c0f.fits', 'x3md0103r_c0f.fits']
-#    infiles = ['x3md0104r_c0f.fits', 'x3md0105r_c0f.fits', 'x3md0106r_c0f.fits']
-#    globals()['plots_folder'] = "../plots/MKN3_x3md010/"
-
-#    globals()['data_folder'] = "../data/MKN78_x3nl020/"
-#    infiles = ['x3nl0201r_c0f.fits','x3nl0202r_c0f.fits','x3nl0203r_c0f.fits']
-#    globals()['plots_folder'] = "../plots/MKN78_x3nl020/"
-
-#    globals()['data_folder'] = "../data/3C273_x0u20/"
-#    infiles = ['x0u20101t_c0f.fits','x0u20102t_c0f.fits','x0u20103t_c0f.fits','x0u20104t_c0f.fits','x0u20105t_c0f.fits','x0u20106t_c0f.fits','x0u20201t_c0f.fits','x0u20202t_c0f.fits','x0u20203t_c0f.fits','x0u20204t_c0f.fits','x0u20205t_c0f.fits','x0u20206t_c0f.fits','x0u20301t_c0f.fits','x0u20302t_c0f.fits','x0u20303t_c0f.fits','x0u20304t_c0f.fits','x0u20305t_c0f.fits','x0u20306t_c0f.fits']
-#    globals()['plots_folder'] = "../plots/3C273_x0u20/"
-
-#BEWARE: 5 observations separated by 1 year each (1995, 1996, 1997, 1998, 1999)
-    globals()['data_folder'] = "../data/M87/POS1/"
-#    infiles = ['x2py010ct_c0f.fits','x2py010dt_c0f.fits','x2py010et_c0f.fits','x2py010ft_c0f.fits'] #1995
-#    infiles = ['x3be010ct_c0f.fits','x3be010dt_c0f.fits','x3be010et_c0f.fits','x3be010ft_c0f.fits'] #1996
-#    infiles = ['x43r010km_c0f.fits','x43r010mm_c0f.fits','x43r010om_c0f.fits','x43r010rm_c0f.fits'] #1997
-#    infiles = ['x43r110kr_c0f.fits','x43r110mr_c0f.fits','x43r110or_c0f.fits','x43r110rr_c0f.fits'] #1998
-    infiles = ['x43r210kr_c0f.fits','x43r210mr_c0f.fits','x43r210or_c0f.fits','x43r210rr_c0f.fits'] #1999
-    globals()['plots_folder'] = "../plots/M87/POS1/"
-
-#BEWARE: 5 observations separated by 1 year each (1995, 1996, 1997, 1998, 1999)
-#    globals()['data_folder'] = "../data/M87/POS3/"
-#    infiles = ['x2py030at_c0f.fits','x2py030bt_c0f.fits','x2py030ct_c0f.fits','x2py0309t_c0f.fits'] #1995
-#    infiles = ['x3be030at_c0f.fits','x3be030bt_c0f.fits','x3be030ct_c0f.fits','x3be0309t_c0f.fits'] #1996
-#    infiles = ['x43r030em_c0f.fits','x43r030gm_c0f.fits','x43r030im_c0f.fits','x43r030lm_c0f.fits'] #1997
-#    infiles = ['x43r130er_c0f.fits','x43r130fr_c0f.fits','x43r130ir_c0f.fits','x43r130lr_c0f.fits'] #1998
-#    infiles = ['x43r230er_c0f.fits','x43r230fr_c0f.fits','x43r230ir_c0f.fits','x43r230lr_c0f.fits'] #1999
-#    globals()['plots_folder'] = "../plots/M87/POS3/"
-
     ## Reduction parameters
     # Deconvolution
     deconvolve = False
@@ -123,7 +128,7 @@ def main():
     # Data binning
     rebin = True
     if rebin:
-        pxsize = 0.20
+        pxsize = 0.05
         px_scale = 'arcsec'         #pixel, arcsec or full
         rebin_operation = 'sum'     #sum or average
     # Alignement
@@ -131,7 +136,7 @@ def main():
     display_data = False
     # Smoothing
     smoothing_function = 'combine'  #gaussian_after, weighted_gaussian_after, gaussian, weighted_gaussian or combine
-    smoothing_FWHM = 0.20           #If None, no smoothing is done
+    smoothing_FWHM = 0.07           #If None, no smoothing is done
     smoothing_scale = 'arcsec'      #pixel or arcsec
     # Rotation
     rotate_stokes = True            #rotation to North convention can give erroneous results
@@ -140,8 +145,8 @@ def main():
     crop = False                    #Crop to desired ROI
     final_display = True
     # Polarization map output
-    figname = 'M87_POS1_1999_FOC'         #target/intrument name
+    figname = 'M87_POS3_1995_FOC'         #target/intrument name
-    figtype = '_combine_FWHM020'    #additionnal informations
+    figtype = '_combine_FWHM005'    #additionnal informations
     SNRp_cut = 3.    #P measurments with SNR>3
     SNRi_cut = 30.   #I measurments with SNR>30, which implies an uncertainty in P of 4.7%.
     step_vec = 0    #plot all vectors in the array. if step_vec = 2, then every other vector will be plotted
@@ -198,8 +203,7 @@ def main():
     ## Step 3:
     # Rotate images to have North up
     if rotate_stokes:
-        alpha = headers[0]['orientat']
+        I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers = proj_red.rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers, SNRi_cut=None)
-        I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers = proj_red.rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers, -alpha, SNRi_cut=None)
 
     # Compute polarimetric parameters (polarization degree and angle).
     P, debiased_P, s_P, s_P_P, PA, s_PA, s_PA_P = proj_red.compute_pol(I_stokes, Q_stokes, U_stokes, Stokes_cov, headers)

src/lib/fits.py

@@ -52,25 +52,20 @@ def get_obs_data(infiles, data_folder="", compute_flux=False):
         new_wcs = wcs.WCS(header).deepcopy()
         if new_wcs.wcs.has_cd() or (new_wcs.wcs.cdelt == np.array([1., 1.])).all():
             # Update WCS with relevant information
-            HST_aper = 2400.    # HST aperture in mm
-            f_ratio = header['f_ratio']
-            px_dim = np.array([25., 25.])   # Pixel dimension in µm
-            if header['pxformt'].lower() == 'zoom':
-                px_dim[0] = 50.
-            #new_cdelt = 206.3/3600.*px_dim/(f_ratio*HST_aper)
-            new_cdelt = np.abs(np.linalg.eig(new_wcs.wcs.cd)[0])
             if new_wcs.wcs.has_cd():
                 old_cd = new_wcs.wcs.cd
                 del new_wcs.wcs.cd
                 keys = list(new_wcs.to_header().keys())+['CD1_1','CD1_2','CD2_1','CD2_2']
                 for key in keys:
                     header.remove(key, ignore_missing=True)
+                new_cdelt = np.linalg.eig(old_cd)[0]
             elif (new_wcs.wcs.cdelt == np.array([1., 1.])).all() and \
                     (new_wcs.array_shape in [(512, 512),(1024,512),(512,1024),(1024,1024)]):
                 old_cd = new_wcs.wcs.pc
             new_wcs.wcs.pc = np.dot(old_cd, np.diag(1./new_cdelt))
             new_wcs.wcs.cdelt = new_cdelt
-            header.update(new_wcs.to_header())
+            for key, val in new_wcs.to_header().items():
+                header[key] = val
 
     if compute_flux:
         for i in range(len(infiles)):

src/lib/plots.py

@@ -462,8 +462,8 @@ class align_maps(object):
         data = self.map[0].data
         other_data = self.other_map[0].data
 
-        plt.rcParams.update({'font.size': 16})
+        plt.rcParams.update({'font.size': 10})
-        self.fig = plt.figure(figsize=(25,15))
+        self.fig = plt.figure(figsize=(10,10))
         #Plot the UV map
         self.ax1 = self.fig.add_subplot(121, projection=self.wcs_map)
         self.ax1.set_facecolor('k')
@@ -522,8 +522,10 @@ class align_maps(object):
         #Selection button
         self.axapply = self.fig.add_axes([0.80, 0.01, 0.1, 0.04])
         self.bapply = Button(self.axapply, 'Apply reference')
+        self.bapply.label.set_fontsize(8)
         self.axreset = self.fig.add_axes([0.60, 0.01, 0.1, 0.04])
         self.breset = Button(self.axreset, 'Leave as is')
+        self.breset.label.set_fontsize(8)
 
     def get_aligned_wcs(self):
         return self.wcs_map, self.wcs_other
@@ -751,7 +753,8 @@ class overplot_pol(align_maps):
 
 class align_pol(object):
     def __init__(self, maps, **kwargs):
-        maps = np.array(maps)
+        order = np.argsort(np.array([curr[0].header['mjd-obs'] for curr in maps]))
+        maps = np.array(maps)[order]
         self.ref_map, self.other_maps = maps[0], maps[1:]
 
         self.wcs = WCS(self.ref_map[0].header)
@@ -797,13 +800,16 @@ class align_pol(object):
         plt.rcdefaults()
         fig = plt.figure(figsize=(10,10))
         ax = fig.add_subplot(111, projection=wcs)
-        ax.set(xlabel="Right Ascension (J2000)", ylabel="Declination (J2000)", facecolor='k')
+        ax.set(xlabel="Right Ascension (J2000)", ylabel="Declination (J2000)", facecolor='k',
+            title="target {0:s} observed on {1:s}".format(curr_map[0].header['targname'], curr_map[0].header['date-obs']))
         fig.subplots_adjust(hspace=0, wspace=0, right=0.9)
         cbar_ax = fig.add_axes([0.95, 0.12, 0.01, 0.75])
 
         if not ax_lim is None:
             lim = np.concatenate([wcs.world_to_pixel(ax_lim[i]) for i in range(len(ax_lim))])
             x_lim, y_lim = lim[0::2], lim[1::2]
+            print(x_lim[0], y_lim[0], wcs.pixel_to_world(x_lim[0], y_lim[0]))
+            print(x_lim[1], y_lim[1], wcs.pixel_to_world(x_lim[1], y_lim[1]))
             ax.set(xlim=x_lim,ylim=y_lim)
 
         if v_lim is None:
@@ -856,9 +862,11 @@ class align_pol(object):
         vmin, vmax = np.min([vmin, np.min(self.ref_map[0].data[self.ref_map[0].data > 0.])]), np.max([vmax, np.max(self.ref_map[0].data[self.ref_map[0].data > 0.])])
         v_lim = np.array([vmin, vmax])
 
-        fig, ax = self.single_plot(self.ref_map, self.wcs, v_lim = v_lim, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, savename=savename, **kwargs)
+        fig, ax = self.single_plot(self.ref_map, self.wcs, v_lim = v_lim, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, savename=savename+'_0', **kwargs)
         x_lim, y_lim = ax.get_xlim(), ax.get_ylim()
         ax_lim = np.array([self.wcs.pixel_to_world(x_lim[i], y_lim[i]) for i in range(len(x_lim))])
+        print(x_lim[0], y_lim[0], ax_lim[0])
+        print(x_lim[1], y_lim[1], ax_lim[1])
         
         for i, curr_map in enumerate(self.other_maps):
             self.single_plot(curr_map, self.wcs_other[i], v_lim=v_lim, ax_lim=ax_lim, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, savename=savename+'_'+str(i+1), **kwargs)

src/lib/reduction.py

@@ -651,7 +651,7 @@ def rebin_array(data_array, error_array, headers, pxsize, scale,
             if scale.lower() in ['px', 'pixel']:
                 Dxy = np.array([pxsize,]*2)
             elif scale.lower() in ['arcsec','arcseconds']:
-                Dxy = np.floor(pxsize/w.wcs.cdelt/3600.).astype(int)
+                Dxy = np.floor(pxsize/np.abs(w.wcs.cdelt)/3600.).astype(int)
             elif scale.lower() in ['full','integrate']:
                 Dxy = np.floor(image.shape).astype(int)
             else:
@@ -1389,7 +1389,7 @@ def compute_pol(I_stokes, Q_stokes, U_stokes, Stokes_cov, headers):
 
 
 def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
-                ang, SNRi_cut=None):
+                ang=None, SNRi_cut=None):
     """
     Use scipy.ndimage.rotate to rotate I_stokes to an angle, and a rotation
     matrix to rotate Q, U of a given angle in degrees and update header
@@ -1411,9 +1411,10 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
         2D boolean array delimiting the data to work on.
     headers : header list
         List of headers corresponding to the reduced images.
-    ang : float
+    ang : float, optional
         Rotation angle (in degrees) that should be applied to the Stokes
-        parameters
+        parameters. If None, will rotate to have North up.
+        Defaults to None.
     SNRi_cut : float, optional
         Cut that should be applied to the signal-to-noise ratio on I.
         Any SNR < SNRi_cut won't be displayed. If None, cut won't be applied.
@@ -1450,6 +1451,11 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
                     U_stokes[i,j] = eps*np.sqrt(Stokes_cov[2,2][i,j])
 
     #Rotate I_stokes, Q_stokes, U_stokes using rotation matrix
+    if ang is None:
+        ang = np.zeros((len(headers),))
+        for i,head in enumerate(headers):
+            ang[i] = -head['orientat']
+        ang = ang.mean()
     alpha = ang*np.pi/180.
     mrot = np.array([[1., 0., 0.],
                     [0., np.cos(2.*alpha), np.sin(2.*alpha)],
@@ -1490,33 +1496,22 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
     #Update headers to new angle
     new_headers = []
     mrot = np.array([[np.cos(-alpha), -np.sin(-alpha)],
-        [np.sin(-alpha), np.cos(-alpha)]])
+                    [np.sin(-alpha), np.cos(-alpha)]])
     for header in headers:
         new_header = deepcopy(header)
         new_header['orientat'] = header['orientat'] + ang
         new_wcs = WCS(header).deepcopy()
-        if new_wcs.wcs.has_cd():    # CD matrix
+
-            # Update WCS with relevant information
+        new_wcs.wcs.pc = np.dot(mrot, new_wcs.wcs.pc)
-            HST_aper = 2400.    # HST aperture in mm
+        print(new_wcs.wcs.pc)
-            f_ratio = header['f_ratio']
-            px_dim = np.array([25., 25.])   # Pixel dimension in µm
-            if ref_header['pxformt'].lower() == 'zoom':
-                px_dim[0] = 50.
-            #new_cdelt = 206.3/3600.*px_dim/(f_ratio*HST_aper)
-            new_cdelt = np.abs(np.linalg.eig(new_wcs.wcs.cd)[0])
-            old_cd = new_wcs.wcs.cd
-            del new_wcs.wcs.cd
-            keys = ['CD1_1','CD1_2','CD2_1','CD2_2']
-            for key in keys:
-                new_header.remove(key, ignore_missing=True)
-            new_wcs.wcs.pc = np.dot(mrot, np.dot(old_cd, np.diag(1./new_cdelt)))
-            new_wcs.wcs.cdelt = new_cdelt
-        elif new_wcs.wcs.has_pc():      # PC matrix + CDELT
-            newpc = np.dot(mrot, new_wcs.wcs.get_pc())
-            new_wcs.wcs.pc = newpc
         new_wcs.wcs.crpix = np.dot(mrot, new_wcs.wcs.crpix - old_center[::-1]) + new_center[::-1]
         new_wcs.wcs.set()
-        new_header.update(new_wcs.to_header())
+        for key, val in new_wcs.to_header().items():
+            new_header.set(key,val)
+        if new_wcs.wcs.pc[0,0] == 1.:
+            new_header.set('PC1_1',1.)
+        if new_wcs.wcs.pc[1,1] == 1.:
+            new_header.set('PC2_2',1.)
 
         new_headers.append(new_header)
 
@@ -1619,33 +1614,18 @@ def rotate_data(data_array, error_array, data_mask, headers, ang):
     #Update headers to new angle
     new_headers = []
     mrot = np.array([[np.cos(-alpha), -np.sin(-alpha)],
-        [np.sin(-alpha), np.cos(-alpha)]])
+            [np.sin(-alpha), np.cos(-alpha)]])
     for header in headers:
         new_header = deepcopy(header)
         new_header['orientat'] = header['orientat'] + ang
 
         new_wcs = WCS(header).deepcopy()
-        if new_wcs.wcs.has_cd():    # CD matrix
+
-            # Update WCS with relevant information
+        new_wcs.wcs.pc = np.dot(mrot, new_wcs.wcs.pc)
-            HST_aper = 2400.    # HST aperture in mm
-            f_ratio = ref_header['f_ratio']
-            px_dim = np.array([25., 25.])   # Pixel dimension in µm
-            if ref_header['pxformt'].lower() == 'zoom':
-                px_dim[0] = 50.
-            new_cdelt = 206.3/3600.*px_dim/(f_ratio*HST_aper)
-            old_cd = new_wcs.wcs.cd
-            del new_wcs.wcs.cd
-            keys = ['CD1_1','CD1_2','CD2_1','CD2_2']
-            for key in keys:
-                new_header.remove(key, ignore_missing=True)
-            new_wcs.wcs.pc = np.dot(mrot, np.dot(old_cd, np.diag(1./new_cdelt)))
-            new_wcs.wcs.cdelt = new_cdelt
-        elif new_wcs.wcs.has_pc():      # PC matrix + CDELT
-            newpc = np.dot(mrot, new_wcs.wcs.get_pc())
-            new_wcs.wcs.pc = newpc
         new_wcs.wcs.crpix = np.dot(mrot, new_wcs.wcs.crpix - old_center[::-1]) + new_center[::-1]
         new_wcs.wcs.set()
-        new_header.update(new_wcs.to_header())
+        for key, val in new_wcs.to_header().items():
+            new_header[key] = val
 
         new_headers.append(new_header)
     globals()['theta'] = theta - alpha

src/overplot.py

@@ -45,15 +45,28 @@ from matplotlib.colors import LogNorm
 #G = overplot_pol(Stokes_UV, Stokes_IR, norm=LogNorm(vmin=1e-17,vmax=5e-15), cmap='inferno_r')
 #G.plot(SNRp_cut=3.0, SNRi_cut=60.0, savename='../plots/IC5063_x3nl030/IR_overplot_forced.png', norm=LogNorm(vmin=1e-17,vmax=5e-15), cmap='inferno_r')
 
-data_folder = "../data/M87/POS1/"
+#data_folder1 = "../data/M87/POS1/"
-plots_folder = "../plots/M87/POS1/"
+#plots_folder1 = "../plots/M87/POS1/"
-basename = "M87_005_log_core"
+#basename1 = "test"
-M87_95 = fits.open(data_folder+"M87_POS1_1995_FOC_combine_FWHM005.fits")
+#M87_1_95 = fits.open(data_folder1+"M87_POS1_1995_FOC_combine_FWHM005.fits")
-M87_96 = fits.open(data_folder+"M87_POS1_1996_FOC_combine_FWHM005.fits")
+#M87_1_96 = fits.open(data_folder1+"M87_POS1_1996_FOC_combine_FWHM005.fits")
-M87_97 = fits.open(data_folder+"M87_POS1_1997_FOC_combine_FWHM005.fits")
+#M87_1_97 = fits.open(data_folder1+"M87_POS1_1997_FOC_combine_FWHM005.fits")
-M87_98 = fits.open(data_folder+"M87_POS1_1998_FOC_combine_FWHM005.fits")
+#M87_1_98 = fits.open(data_folder1+"M87_POS1_1998_FOC_combine_FWHM005.fits")
-M87_99 = fits.open(data_folder+"M87_POS1_1999_FOC_combine_FWHM005.fits")
+#M87_1_99 = fits.open(data_folder1+"M87_POS1_1999_FOC_combine_FWHM005.fits")
+#
+#H = align_pol(np.array([M87_1_95,M87_1_96,M87_1_97,M87_1_98,M87_1_99]))#, norm=LogNorm())
+#H.plot(SNRp_cut=3.0, SNRi_cut=30.0, savename=plots_folder1+'animated_loop/'+basename1, norm=LogNorm())
+#command("convert -delay 20 -loop 0 {0:s}animated_loop/{1:s}*.png {0:s}animated_loop/{1:s}.gif && rm {0:s}animated_loop/{1:s}*.png".format(plots_folder1, basename1))
 
-H = align_pol(np.array([M87_95,M87_96,M87_97,M87_98,M87_99]), norm=LogNorm())
+data_folder3 = "../data/M87/POS3/"
-H.plot(SNRp_cut=3.0, SNRi_cut=30.0, savename=plots_folder+'animated_loop/'+basename, norm=LogNorm())
+plots_folder3 = "../plots/M87/POS3/"
-command("convert -delay 20 -loop 0 {0:s}animated_loop/{1:s}*.png {0:s}animated_loop/{1:s}.gif && rm {0:s}animated_loop/{1:s}*.png".format(plots_folder, basename))
+basename3 = "test"
+M87_3_95 = fits.open(data_folder3+"M87_POS3_1995_FOC_combine_FWHM005.fits")
+M87_3_96 = fits.open(data_folder3+"M87_POS3_1996_FOC_combine_FWHM005.fits")
+M87_3_97 = fits.open(data_folder3+"M87_POS3_1997_FOC_combine_FWHM005.fits")
+M87_3_98 = fits.open(data_folder3+"M87_POS3_1998_FOC_combine_FWHM005.fits")
+M87_3_99 = fits.open(data_folder3+"M87_POS3_1999_FOC_combine_FWHM005.fits")
+
+I = align_pol(np.array([M87_3_95,M87_3_96,M87_3_97,M87_3_98,M87_3_99]))#, norm=LogNorm())
+I.plot(SNRp_cut=3.0, SNRi_cut=30.0, savename=plots_folder3+'animated_loop/'+basename3, norm=LogNorm())
+command("convert -delay 20 -loop 0 {0:s}animated_loop/{1:s}*.png {0:s}animated_loop/{1:s}.gif && rm {0:s}animated_loop/{1:s}*.png".format(plots_folder3, basename3))