Tibeuleu/FOC_Reduction
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revamp imagerie

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This commit is contained in:
Thibault Barnouin
2022-06-22 11:53:48 +02:00
parent 30ea3db89d
commit d1e0a0d3e6
42 changed files with 117 additions and 118 deletions
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127
src/lib/plots.py
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@@ -271,7 +271,7 @@ def polarization_map(Stokes, data_mask=None, rectangle=None, SNRp_cut=3., SNRi_c
if display is None:
# If no display selected, show intensity map
vmin, vmax = 0., np.max(stkI.data[stkI.data > 0.]*convert_flux)
im = ax.imshow(stkI.data*convert_flux, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = ax.imshow(stkI.data*convert_flux, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
levelsI = np.linspace(vmax*0.01, vmax*0.99, 10)
print("Total flux contour levels : ", levelsI)
@@ -281,7 +281,7 @@ def polarization_map(Stokes, data_mask=None, rectangle=None, SNRp_cut=3., SNRi_c
# Display polarisation flux
pf_mask = (stkI.data > 0.) * (pol.data > 0.)
vmin, vmax = 0., np.max(stkI.data[pf_mask]*convert_flux*pol.data[pf_mask])
im = ax.imshow(stkI.data*convert_flux*pol.data, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = ax.imshow(stkI.data*convert_flux*pol.data, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda} \cdot P$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
levelsPf = np.linspace(vmax*0.01, vmax*0.99, 10)
print("Polarized flux contour levels : ", levelsPf)
@@ -290,24 +290,24 @@ def polarization_map(Stokes, data_mask=None, rectangle=None, SNRp_cut=3., SNRi_c
elif display.lower() in ['p','pol','pol_deg']:
# Display polarization degree map
vmin, vmax = 0., 100.
im = ax.imshow(pol.data*100., vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = ax.imshow(pol.data*100., vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$P$ [%]")
elif display.lower() in ['s_p','pol_err','pol_deg_err']:
# Display polarization degree error map
vmin, vmax = 0., 10.
p_err = deepcopy(pol_err.data)
p_err[p_err > vmax/100.] = np.nan
im = ax.imshow(p_err*100., vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = ax.imshow(p_err*100., vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$\sigma_P$ [%]")
elif display.lower() in ['s_i','i_err']:
# Display intensity error map
vmin, vmax = 0., np.max(np.sqrt(stk_cov.data[0,0][stk_cov.data[0,0] > 0.])*convert_flux)
im = ax.imshow(np.sqrt(stk_cov.data[0,0])*convert_flux, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = ax.imshow(np.sqrt(stk_cov.data[0,0])*convert_flux, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$\sigma_I$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
elif display.lower() in ['snr','snri']:
# Display I_stokes signal-to-noise map
vmin, vmax = 0., np.max(SNRi[SNRi > 0.])
im = ax.imshow(SNRi, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = ax.imshow(SNRi, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$I_{Stokes}/\sigma_{I}$")
levelsSNRi = np.linspace(SNRi_cut, vmax*0.99, 10)
print("SNRi contour levels : ", levelsSNRi)
@@ -316,7 +316,7 @@ def polarization_map(Stokes, data_mask=None, rectangle=None, SNRp_cut=3., SNRi_c
elif display.lower() in ['snrp']:
# Display polarization degree signal-to-noise map
vmin, vmax = SNRp_cut, np.max(SNRp[SNRp > 0.])
im = ax.imshow(SNRp, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = ax.imshow(SNRp, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$P/\sigma_{P}$")
levelsSNRp = np.linspace(SNRp_cut, vmax*0.99, 10)
print("SNRp contour levels : ", levelsSNRp)
@@ -325,7 +325,7 @@ def polarization_map(Stokes, data_mask=None, rectangle=None, SNRp_cut=3., SNRi_c
else:
# Defaults to intensity map
vmin, vmax = 0., np.max(stkI.data[stkI.data > 0.]*convert_flux*2.)
im = ax.imshow(stkI.data*convert_flux, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = ax.imshow(stkI.data*convert_flux, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]")
if (display is None) or not(display.lower() in ['default']):
@@ -398,7 +398,7 @@ class align_maps(object):
elif self.wcs_map.naxis == 3:
self.wcs_map = WCS(self.map[0],naxis=[1,2]).deepcopy()
self.map[0].data = self.map[0].data[1]
self.wcs_other = WCS(self.other_map[0]).deepcopy()
if self.wcs_other.naxis == 4:
self.wcs_other = WCS(self.other_map[0],naxis=[1,2]).deepcopy()
@@ -406,7 +406,7 @@ class align_maps(object):
elif self.wcs_other.naxis == 3:
self.wcs_other = WCS(self.other_map[0],naxis=[1,2]).deepcopy()
self.other_map[0].data = self.other_map[0].data[1]
try:
convert_flux = self.map[0].header['photflam']
except KeyError:
@@ -415,7 +415,7 @@ class align_maps(object):
other_convert = self.other_map[0].header['photflam']
except KeyError:
other_convert = 1.
#Get data
data = self.map[0].data
other_data = self.other_map[0].data
@@ -427,13 +427,13 @@ class align_maps(object):
self.ax1.set_facecolor('k')
vmin, vmax = 0., np.max(data[data > 0.]*convert_flux)
im1 = self.ax1.imshow(data*convert_flux, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im1 = self.ax1.imshow(data*convert_flux, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
fontprops = fm.FontProperties(size=16)
px_size = self.wcs_map.wcs.get_cdelt()[0]*3600.
px_sc = AnchoredSizeBar(self.ax1.transData, 1./px_size, '1 arcsec', 3, pad=0.5, sep=5, borderpad=0.5, frameon=False, size_vertical=0.005, color='w', fontproperties=fontprops)
self.ax1.add_artist(px_sc)
try:
north_dir1 = AnchoredDirectionArrows(self.ax1.transAxes, "E", "N", length=-0.08, fontsize=0.025, loc=1, aspect_ratio=-1, sep_y=0.01, sep_x=0.01, back_length=0., head_length=10., head_width=10., angle=-self.map[0].header['orientat'], color='white', text_props={'ec': None, 'fc': 'w', 'alpha': 1, 'lw': 0.4}, arrow_props={'ec': None,'fc':'w','alpha': 1,'lw': 1})
self.ax1.add_artist(north_dir1)
@@ -454,14 +454,14 @@ class align_maps(object):
test = kwargs[key]
except KeyError:
for key_i, val_i in value:
kwargs[key_i] = val_i
im2 = self.ax2.imshow(other_data*other_convert, aspect='auto', **kwargs)
kwargs[key_i] = val_i
im2 = self.ax2.imshow(other_data*other_convert, aspect='equal', **kwargs)
fontprops = fm.FontProperties(size=16)
px_size = self.wcs_other.wcs.get_cdelt()[0]*3600.
px_sc = AnchoredSizeBar(self.ax2.transData, 1./px_size, '1 arcsec', 3, pad=0.5, sep=5, borderpad=0.5, frameon=False, size_vertical=0.005, color='w', fontproperties=fontprops)
self.ax2.add_artist(px_sc)
try:
north_dir2 = AnchoredDirectionArrows(self.ax2.transAxes, "E", "N", length=-0.08, fontsize=0.03, loc=1, aspect_ratio=-1, sep_y=0.01, sep_x=0.01, angle=-self.other_map[0].header['orientat'], color='w', arrow_props={'ec': None, 'fc': 'w', 'alpha': 1,'lw': 2})
self.ax2.add_artist(north_dir2)
@@ -477,7 +477,7 @@ class align_maps(object):
self.bapply = Button(self.axapply, 'Apply reference')
self.axreset = self.fig.add_axes([0.60, 0.01, 0.1, 0.04])
self.breset = Button(self.axreset, 'Leave as is')
def get_aligned_wcs(self):
return self.wcs_map, self.wcs_other
@@ -489,14 +489,14 @@ class align_maps(object):
self.cr_map.set(data=[x,y])
self.fig.canvas.draw_idle()
if (event.inaxes is not None) and (event.inaxes == self.ax2):
x = event.xdata
y = event.ydata
self.cr_other.set(data=[x,y])
self.fig.canvas.draw_idle()
def reset_align(self, event):
self.wcs_map.wcs.crpix = WCS(self.map[0].header).wcs.crpix[:2]
self.wcs_other.wcs.crpix = WCS(self.other_map[0].header).wcs.crpix[:2]
@@ -504,7 +504,7 @@ class align_maps(object):
if self.aligned:
plt.close()
self.aligned = True
def apply_align(self, event):
@@ -515,13 +515,13 @@ class align_maps(object):
if self.aligned:
plt.close()
self.aligned = True
def on_close_align(self, event):
self.aligned = True
#print(self.get_aligned_wcs())
def align(self):
self.fig.canvas.draw()
self.fig.canvas.mpl_connect('button_press_event', self.onclick_ref)
@@ -547,7 +547,7 @@ class overplot_radio(align_maps):
pol = self.Stokes_UV[np.argmax([self.Stokes_UV[i].header['datatype']=='Pol_deg_debiased' for i in range(len(self.Stokes_UV))])]
pol_err = self.Stokes_UV[np.argmax([self.Stokes_UV[i].header['datatype']=='Pol_deg_err' for i in range(len(self.Stokes_UV))])]
pang = self.Stokes_UV[np.argmax([self.Stokes_UV[i].header['datatype']=='Pol_ang' for i in range(len(self.Stokes_UV))])]
other_data = self.other_map[0].data
other_convert = 1.
other_unit = self.other_map[0].header['bunit']
@@ -555,7 +555,7 @@ class overplot_radio(align_maps):
other_unit = r"mJy/Beam"
other_convert = 1e3
other_freq = self.other_map[0].header['crval3']
convert_flux = self.Stokes_UV[0].header['photflam']
#Compute SNR and apply cuts
@@ -575,7 +575,7 @@ class overplot_radio(align_maps):
#Display UV intensity map with polarization vectors
vmin, vmax = 0., np.max(stkI.data[stkI.data > 0.]*convert_flux)
im = self.ax.imshow(stkI.data*convert_flux, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
im = self.ax.imshow(stkI.data*convert_flux, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
cbar_ax = self.fig2.add_axes([0.95, 0.12, 0.01, 0.75])
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
@@ -600,12 +600,12 @@ class overplot_radio(align_maps):
north_dir = AnchoredDirectionArrows(self.ax.transAxes, "E", "N", length=-0.08, fontsize=0.03, loc=1, aspect_ratio=-1, sep_y=0.01, sep_x=0.01, angle=-self.Stokes_UV[0].header['orientat'], color='w', arrow_props={'ec': None, 'fc': 'w', 'alpha': 1,'lw': 2})
self.ax.add_artist(north_dir)
if not(savename is None):
self.fig2.savefig(savename,bbox_inches='tight',dpi=200)
self.fig2.canvas.draw()
def plot(self, levels, SNRp_cut=3., SNRi_cut=30., savename=None) -> None:
self.align()
if self.aligned:
@@ -628,9 +628,9 @@ class overplot_pol(align_maps):
pol = self.Stokes_UV[np.argmax([self.Stokes_UV[i].header['datatype']=='Pol_deg_debiased' for i in range(len(self.Stokes_UV))])]
pol_err = self.Stokes_UV[np.argmax([self.Stokes_UV[i].header['datatype']=='Pol_deg_err' for i in range(len(self.Stokes_UV))])]
pang = self.Stokes_UV[np.argmax([self.Stokes_UV[i].header['datatype']=='Pol_ang' for i in range(len(self.Stokes_UV))])]
convert_flux = self.Stokes_UV[0].header['photflam']
other_data = self.other_map[0].data
try:
other_convert = self.other_map[0].header['photflam']
@@ -654,9 +654,9 @@ class overplot_pol(align_maps):
#Display Stokes I as contours
levels_stkI = np.rint(np.linspace(10,99,10))/100.*np.max(stkI.data[stkI.data > 0.]*convert_flux)
cont_stkI = self.ax.contour(stkI.data*convert_flux, transform=self.ax.get_transform(self.wcs_UV), levels=levels_stkI, colors='grey')
self.ax.clabel(cont_stkI, inline=True, fontsize=8)
cont_stkI = self.ax.contour(stkI.data*convert_flux, transform=self.ax.get_transform(self.wcs_UV), levels=levels_stkI, colors='grey', alpha=0.)
#self.ax.clabel(cont_stkI, inline=True, fontsize=8)
self.ax.autoscale(False)
#Display full size polarization vectors
@@ -673,27 +673,27 @@ class overplot_pol(align_maps):
test = kwargs[key]
except KeyError:
for key_i, val_i in value:
kwargs[key_i] = val_i
kwargs[key_i] = val_i
im = self.ax.imshow(other_data*other_convert, transform=self.ax.get_transform(self.wcs_other), alpha=1., **kwargs)
cbar_ax = self.fig2.add_axes([0.95, 0.12, 0.01, 0.75])
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
#Display pixel scale and North direction
fontprops = fm.FontProperties(size=16)
px_size = self.wcs_other.wcs.get_cdelt()[0]*3600.
px_size = self.wcs_UV.wcs.get_cdelt()[0]*3600.
px_sc = AnchoredSizeBar(self.ax.transData, 1./px_size, '1 arcsec', 3, pad=0.5, sep=5, borderpad=0.5, frameon=False, size_vertical=0.005, color='w', fontproperties=fontprops)
self.ax.add_artist(px_sc)
north_dir = AnchoredDirectionArrows(self.ax.transAxes, "E", "N", length=-0.08, fontsize=0.03, loc=1, aspect_ratio=-1, sep_y=0.01, sep_x=0.01, angle=-self.Stokes_UV[0].header['orientat'], color='w', arrow_props={'ec': None, 'fc': 'w', 'alpha': 1,'lw': 2})
self.ax.add_artist(north_dir)
self.ax.set(xlabel="Right Ascension (J2000)", ylabel="Declination (J2000)", title="{0:s} overplotted with polarization vectors and Stokes I contours from HST/FOC".format(obj))
if not(savename is None):
self.fig2.savefig(savename,bbox_inches='tight',dpi=200)
self.fig2.canvas.draw()
def plot(self, SNRp_cut=3., SNRi_cut=30., savename=None, **kwargs) -> None:
self.align()
if self.aligned:
@@ -711,7 +711,7 @@ class crop_map(object):
self.hdul = hdul
self.header = deepcopy(self.hdul[0].header)
self.wcs = WCS(self.header).deepcopy()
self.data = deepcopy(self.hdul[0].data)
try:
self.convert_flux = self.header['photflam']
@@ -758,16 +758,16 @@ class crop_map(object):
wcs = self.wcs
if convert_flux is None:
convert_flux = self.convert_flux
vmin, vmax = 0., np.max(data[data > 0.]*convert_flux)
if hasattr(self, 'im'):
self.im.remove()
self.im = self.ax.imshow(data*convert_flux, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=self.mask_alpha, origin='lower')
self.im = self.ax.imshow(data*convert_flux, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=self.mask_alpha, origin='lower')
if hasattr(self, 'cr'):
self.cr[0].set_data(*wcs.wcs.crpix)
else:
self.cr = self.ax.plot(*wcs.wcs.crpix, 'r+')
self.fig.canvas.draw_idle()
self.fig.canvas.draw_idle()
return self.im
@property
@@ -811,10 +811,10 @@ class crop_map(object):
header = self.header
data = self.data
wcs = self.wcs
vertex = self.RSextent.astype(int)
shape = vertex[1::2] - vertex[0::2]
extent = np.array(self.im.get_extent())
shape_im = extent[1::2] - extent[0::2]
if (shape_im.astype(int) != shape).any() and (self.RSextent != self.extent).any():
@@ -827,7 +827,7 @@ class crop_map(object):
else:
self.wcs_crop.wcs.crval = wcs.wcs_pix2world([self.RScenter],1)[0]
self.wcs_crop.wcs.crpix = self.RScenter-self.RSextent[::2]
# Crop dataset
self.data_crop = deepcopy(data[vertex[2]:vertex[3], vertex[0]:vertex[1]])
@@ -853,7 +853,7 @@ class crop_map(object):
self.rect_selector = RectangleSelector(self.ax, self.onselect_crop,
drawtype='box', button=[1], interactive=True)
self.fig.canvas.draw_idle()
def on_close(self, event) -> None:
if not hasattr(self, 'hdul_crop'):
self.hdul_crop = self.hdul
@@ -890,7 +890,7 @@ class crop_Stokes(crop_map):
hdul = self.hdul
data = self.data
wcs = self.wcs
vertex = self.RSextent.astype(int)
shape = vertex[1::2] - vertex[0::2]
@@ -907,7 +907,7 @@ class crop_Stokes(crop_map):
else:
self.wcs_crop.wcs.crval = wcs.wcs_pix2world([self.RScenter],1)[0]
self.wcs_crop.wcs.crpix = self.RScenter-self.RSextent[::2]
# Crop dataset
for dataset in self.hdul_crop:
if dataset.header['datatype']=='IQU_cov_matrix':
@@ -941,7 +941,7 @@ class crop_Stokes(crop_map):
self.rect_selector = RectangleSelector(self.ax, self.onselect_crop,
drawtype='box', button=[1], interactive=True)
self.fig.canvas.draw_idle()
@property
def data_mask(self):
return self.hdul_crop[-1].data
@@ -967,13 +967,13 @@ class image_lasso_selector:
self.ax = ax
self.mask_alpha = 0.1
self.embedded = True
self.displayed = self.ax.imshow(self.img, vmin=self.vmin, vmax=self.vmax, aspect='auto', cmap='inferno',alpha=self.mask_alpha)
self.displayed = self.ax.imshow(self.img, vmin=self.vmin, vmax=self.vmax, aspect='equal', cmap='inferno',alpha=self.mask_alpha)
plt.ion()
lineprops = {'color': 'grey', 'linewidth': 1, 'alpha': 0.8}
self.lasso = LassoSelector(self.ax, self.onselect,props=lineprops, useblit=False)
self.lasso.set_visible(True)
pix_x = np.arange(self.img.shape[0])
pix_y = np.arange(self.img.shape[1])
xv, yv = np.meshgrid(pix_y,pix_x)
@@ -993,10 +993,10 @@ class image_lasso_selector:
p = Path(verts)
self.indices = p.contains_points(self.pix, radius=0).reshape(self.img.shape[:2])
self.update_mask()
def update_mask(self):
self.displayed.remove()
self.displayed = self.ax.imshow(self.img, vmin=self.vmin, vmax=self.vmax, aspect='auto', cmap='inferno',alpha=self.mask_alpha)
self.displayed = self.ax.imshow(self.img, vmin=self.vmin, vmax=self.vmax, aspect='equal', cmap='inferno',alpha=self.mask_alpha)
array = self.displayed.get_array().data
self.mask = np.zeros(self.img.shape[:2],dtype=bool)
@@ -1040,14 +1040,14 @@ class pol_map(object):
self.ax = self.fig.add_subplot(111,projection=self.wcs)
self.ax_cosmetics()
self.cbar_ax = self.fig.add_axes([0.925, 0.12, 0.01, 0.75])
#Display selected data (Default to total flux)
self.display()
#Display polarization vectors in SNR_cut
self.pol_vector()
#Display integrated values in ROI
self.pol_int()
#Set axes for sliders (SNRp_cut, SNRi_cut)
ax_I_cut = self.fig.add_axes([0.125, 0.080, 0.35, 0.01])
ax_P_cut = self.fig.add_axes([0.125, 0.055, 0.35, 0.01])
@@ -1121,7 +1121,7 @@ class pol_map(object):
b_crop = Button(ax_crop,"Crop")
self.cropped = False
b_crop_reset = Button(ax_crop_reset,"Reset")
def crop(event):
if self.cropped:
self.cropped = False
@@ -1284,7 +1284,7 @@ class pol_map(object):
b_snrp.on_clicked(d_snrp)
plt.show()
@property
def wcs(self):
return deepcopy(WCS(self.Stokes[0].header))
@@ -1312,7 +1312,7 @@ class pol_map(object):
@property
def data_mask(self):
return self.Stokes[np.argmax([self.Stokes[i].header['datatype']=='Data_mask' for i in range(len(self.Stokes))])].data
def set_data_mask(self, mask):
self.Stokes[np.argmax([self.Stokes[i].header['datatype']=='Data_mask' for i in range(len(self.Stokes))])].data = mask.astype(float)
@@ -1337,7 +1337,7 @@ class pol_map(object):
ax.coords[1].set_axislabel_position('l')
ax.coords[1].set_ticklabel_position('l')
ax.axis('equal')
#Display scales and orientation
fontprops = fm.FontProperties(size=14)
px_size = self.wcs.wcs.cdelt[0]*3600.
@@ -1357,7 +1357,7 @@ class pol_map(object):
def display(self, fig=None, ax=None):
if self.display_selection is None:
self.display_selection = "total_flux"
if self.display_selection.lower() in ['total_flux']:
self.data = self.I*self.convert_flux
vmin, vmax = 0., np.max(self.data[self.data > 0.])
@@ -1390,12 +1390,12 @@ class pol_map(object):
ax = self.ax
if hasattr(self, 'im'):
self.im.remove()
self.im = ax.imshow(self.data, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno')
self.im = ax.imshow(self.data, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno')
self.cbar = plt.colorbar(self.im, cax=self.cbar_ax, label=label)
fig.canvas.draw_idle()
return self.im
else:
im = ax.imshow(self.data, vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno')
im = ax.imshow(self.data, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno')
ax.set_xlim(0,self.data.shape[1])
ax.set_ylim(0,self.data.shape[0])
plt.colorbar(im, pad=0.025, aspect=80, label=label)
@@ -1419,7 +1419,7 @@ class pol_map(object):
else:
ax.quiver(X, Y, XY_U, XY_V, units='xy', scale=0.5, scale_units='xy', pivot='mid', headwidth=0., headlength=0., headaxislength=0., width=0.1, color='white')
fig.canvas.draw_idle()
def pol_int(self, fig=None, ax=None):
if self.region is None:
n_pix = self.I.size
@@ -1475,4 +1475,3 @@ class pol_map(object):
if not self.region is None:
ax.contour(self.region.astype(float),levels=[0.5], colors='white', linewidths=0.8)
fig.canvas.draw_idle()

32
src/lib/reduction.py
View File

@@ -482,7 +482,7 @@ def get_error(data_array, headers, error_array=None, data_mask=None, sub_shape=N
err_flat = data_array[i]*0.03
error_array[i] = np.sqrt(error_array[i]**2 + error_bkg[i]**2 + err_wav**2 + err_psf**2 + err_flat**2)
background[i] = sub_image.sum()
if (data_array[i] < 0.).any():
print(data_array[i])
@@ -808,7 +808,7 @@ def align_data(data_array, headers, error_array=None, upsample_factor=1.,
shifts.append(shift)
errors.append(error)
shifts = np.array(shifts)
errors = np.array(errors)
@@ -818,7 +818,7 @@ def align_data(data_array, headers, error_array=None, upsample_factor=1.,
for i in range(len(headers_wcs)):
headers_wcs[i].wcs.crpix = new_crpix[0]
headers[i].update(headers_wcs[i].to_header())
data_mask = rescaled_mask.all(axis=0)
data_array, error_array, data_mask, headers = crop_array(rescaled_image, headers, rescaled_error, data_mask)
@@ -926,7 +926,7 @@ def smooth_data(data_array, error_array, data_mask, headers, FWHM=1.,
else:
raise ValueError("{} is not a valid smoothing option".format(smoothing))
return smoothed, error
@@ -1039,7 +1039,7 @@ def polarizer_avg(data_array, error_array, data_mask, headers, FWHM=None,
err60 = np.sqrt(np.sum(err60_array**2,axis=0))
err120 = np.sqrt(np.sum(err120_array**2,axis=0))
polerr_array = np.array([err0, err60, err120])
# Update headers
for header in headers:
if header['filtnam1']=='POL0':
@@ -1186,12 +1186,12 @@ def compute_Stokes(data_array, error_array, data_mask, headers,
Q_stokes = np.zeros(pol_array[0].shape)
U_stokes = np.zeros(pol_array[0].shape)
Stokes_cov = np.zeros((3,3,I_stokes.shape[0],I_stokes.shape[1]))
for i in range(I_stokes.shape[0]):
for j in range(I_stokes.shape[1]):
I_stokes[i,j], Q_stokes[i,j], U_stokes[i,j] = np.dot(coeff_stokes, pol_flux[:,i,j]).T
Stokes_cov[:,:,i,j] = np.dot(coeff_stokes, np.dot(pol_cov[:,:,i,j], coeff_stokes.T))
mask = (Q_stokes**2 + U_stokes**2) > I_stokes**2
if mask.any():
print("WARNING : found {0:d} pixels for which I_pol > I_stokes".format(I_stokes[mask].size))
@@ -1201,17 +1201,17 @@ def compute_Stokes(data_array, error_array, data_mask, headers,
dI_dtheta2 = 2.*pol_eff[1]/A*(pol_eff[0]*np.cos(-2.*theta[0]+2.*theta[1])*(pol_flux[2]-I_stokes) - pol_eff[2]*np.cos(-2.*theta[1]+2.*theta[2])*(pol_flux[0]-I_stokes))
dI_dtheta3 = 2.*pol_eff[2]/A*(pol_eff[1]*np.cos(-2.*theta[1]+2.*theta[2])*(pol_flux[0]-I_stokes) - pol_eff[0]*np.cos(-2.*theta[2]+2.*theta[0])*(pol_flux[1]-I_stokes))
dI_dtheta = np.array([dI_dtheta1, dI_dtheta2, dI_dtheta3])
dQ_dtheta1 = 2.*pol_eff[0]/A*(np.cos(2.*theta[0])*(pol_flux[1]-pol_flux[2]) - (pol_eff[2]*np.cos(-2.*theta[2]+2.*theta[0]) - pol_eff[1]*np.cos(-2.*theta[0]+2.*theta[1]))*Q_stokes)
dQ_dtheta2 = 2.*pol_eff[1]/A*(np.cos(2.*theta[1])*(pol_flux[2]-pol_flux[0]) - (pol_eff[0]*np.cos(-2.*theta[0]+2.*theta[1]) - pol_eff[2]*np.cos(-2.*theta[1]+2.*theta[2]))*Q_stokes)
dQ_dtheta3 = 2.*pol_eff[2]/A*(np.cos(2.*theta[2])*(pol_flux[0]-pol_flux[1]) - (pol_eff[1]*np.cos(-2.*theta[1]+2.*theta[2]) - pol_eff[0]*np.cos(-2.*theta[2]+2.*theta[0]))*Q_stokes)
dQ_dtheta = np.array([dQ_dtheta1, dQ_dtheta2, dQ_dtheta3])
dU_dtheta1 = 2.*pol_eff[0]/A*(np.sin(2.*theta[0])*(pol_flux[1]-pol_flux[2]) - (pol_eff[2]*np.cos(-2.*theta[2]+2.*theta[0]) - pol_eff[1]*np.cos(-2.*theta[0]+2.*theta[1]))*U_stokes)
dU_dtheta2 = 2.*pol_eff[1]/A*(np.sin(2.*theta[1])*(pol_flux[2]-pol_flux[0]) - (pol_eff[0]*np.cos(-2.*theta[0]+2.*theta[1]) - pol_eff[2]*np.cos(-2.*theta[1]+2.*theta[2]))*U_stokes)
dU_dtheta3 = 2.*pol_eff[2]/A*(np.sin(2.*theta[2])*(pol_flux[0]-pol_flux[1]) - (pol_eff[1]*np.cos(-2.*theta[1]+2.*theta[2]) - pol_eff[0]*np.cos(-2.*theta[2]+2.*theta[0]))*U_stokes)
dU_dtheta = np.array([dU_dtheta1, dU_dtheta2, dU_dtheta3])
# Compute the uncertainty associated with the polarizers' orientation (see Kishimoto 1999)
s_I2_axis = np.sum([dI_dtheta[i]**2 * sigma_theta[i]**2 for i in range(len(sigma_theta))],axis=0)
s_Q2_axis = np.sum([dQ_dtheta[i]**2 * sigma_theta[i]**2 for i in range(len(sigma_theta))],axis=0)
@@ -1221,7 +1221,7 @@ def compute_Stokes(data_array, error_array, data_mask, headers,
Stokes_cov[0,0] += s_I2_axis
Stokes_cov[1,1] += s_Q2_axis
Stokes_cov[2,2] += s_U2_axis
if not(FWHM is None) and (smoothing.lower() in ['weighted_gaussian_after','weight_gauss_after','gaussian_after','gauss_after']):
smoothing = smoothing.lower()[:-6]
Stokes_array = np.array([I_stokes, Q_stokes, U_stokes])
@@ -1233,7 +1233,7 @@ def compute_Stokes(data_array, error_array, data_mask, headers,
I_stokes, Q_stokes, U_stokes = Stokes_array
Stokes_cov[0,0], Stokes_cov[1,1], Stokes_cov[2,2] = Stokes_error**2
#Compute integrated values for P, PA before any rotation
mask = np.logical_and(data_mask.astype(bool), (I_stokes > 0.))
n_pix = I_stokes[mask].size
@@ -1419,11 +1419,11 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
mrot = np.array([[1., 0., 0.],
[0., np.cos(2.*alpha), np.sin(2.*alpha)],
[0, -np.sin(2.*alpha), np.cos(2.*alpha)]])
old_center = np.array(I_stokes.shape)/2
shape = np.fix(np.array(I_stokes.shape)*np.sqrt(2.5)).astype(int)
new_center = np.array(shape)/2
I_stokes = zeropad(I_stokes, shape)
Q_stokes = zeropad(Q_stokes, shape)
U_stokes = zeropad(U_stokes, shape)
@@ -1433,7 +1433,7 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
new_Q_stokes = np.zeros(shape)
new_U_stokes = np.zeros(shape)
new_Stokes_cov = np.zeros((*Stokes_cov.shape[:-2],*shape))
for i in range(shape[0]):
for j in range(shape[1]):
new_I_stokes[i,j], new_Q_stokes[i,j], new_U_stokes[i,j] = np.dot(mrot, np.array([I_stokes[i,j], Q_stokes[i,j], U_stokes[i,j]])).T
@@ -1554,7 +1554,7 @@ def rotate_data(data_array, error_array, data_mask, headers, ang):
old_center = np.array(data_array[0].shape)/2
shape = np.fix(np.array(data_array[0].shape)*np.sqrt(2.5)).astype(int)
new_center = np.array(shape)/2
data_array = zeropad(data_array, [data_array.shape[0],*shape])
error_array = zeropad(error_array, [error_array.shape[0],*shape])
data_mask = zeropad(data_mask, shape)