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update user privileges, correct and add axis error estimation, replot for NGC1068

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Thibault Barnouin
2021-09-13 17:38:22 +02:00
parent 4e0861129d
commit 5f3d86a55c
311 changed files with 172 additions and 36 deletions
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100
src/lib/plots.py
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@@ -9,9 +9,11 @@ prototypes :
Plots polarization map of polarimetric parameters saved in an HDUList
"""
import copy
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.widgets import RectangleSelector
import matplotlib.font_manager as fm
from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar, AnchoredDirectionArrows
from astropy.wcs import WCS
@@ -167,8 +169,102 @@ def plot_Stokes(Stokes, savename=None, plots_folder=""):
return 0
def polarization_map(Stokes, data_mask, rectangle=None, SNRp_cut=3., SNRi_cut=30., step_vec=1,
savename=None, plots_folder="", display=None):
class crop_map(object):
"""
Class to interactively crop I_stokes map to desired Region of Interest
"""
def __init__(self, Stokes, data_mask, SNRp_cut=3., SNRi_cut=30.):
#Get data
stkI = Stokes[np.argmax([Stokes[i].header['datatype']=='I_stokes' for i in range(len(Stokes))])]
stk_cov = Stokes[np.argmax([Stokes[i].header['datatype']=='IQU_cov_matrix' for i in range(len(Stokes))])]
pol = Stokes[np.argmax([Stokes[i].header['datatype']=='Pol_deg_debiased' for i in range(len(Stokes))])]
pol_err = Stokes[np.argmax([Stokes[i].header['datatype']=='Pol_deg_err' for i in range(len(Stokes))])]
self.Stokes = Stokes
self.data_mask = data_mask
wcs = WCS(Stokes[0]).deepcopy()
#Compute SNR and apply cuts
pol.data[pol.data == 0.] = np.nan
SNRp = pol.data/pol_err.data
SNRp[np.isnan(SNRp)] = 0.
pol.data[SNRp < SNRp_cut] = np.nan
SNRi = stkI.data/np.sqrt(stk_cov.data[0,0])
SNRi[np.isnan(SNRi)] = 0.
pol.data[SNRi < SNRi_cut] = np.nan
convert_flux = Stokes[0].header['photflam']
#Plot the map
plt.rcParams.update({'font.size': 16})
self.fig = plt.figure(figsize=(15,15))
self.ax = self.fig.add_subplot(111, projection=wcs)
self.ax.set_facecolor('k')
self.fig.subplots_adjust(hspace=0, wspace=0, right=0.9)
cbar_ax = self.fig.add_axes([0.95, 0.12, 0.01, 0.75])
self.extent = [-stkI.data.shape[1]/2.,stkI.data.shape[1]/2.,-stkI.data.shape[0]/2.,stkI.data.shape[0]/2.]
self.center = [stkI.data.shape[1]/2.,stkI.data.shape[0]/2.]
vmin, vmax = 0., np.max(stkI.data[stkI.data > 0.]*convert_flux)
im = self.ax.imshow(stkI.data*convert_flux,extent=self.extent, vmin=vmin, vmax=vmax, aspect='auto', 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(SNRi_cut, np.max(SNRi[SNRi > 0.]), 10)
cont = self.ax.contour(SNRi, extent=self.extent, levels=levelsI, colors='grey', linewidths=0.5)
fontprops = fm.FontProperties(size=16)
px_size = wcs.wcs.get_cdelt()[0]
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)
self.ax.set_title(
"Click and drag to crop to desired Region of Interest.\n"
"Press 'c' to toggle the selector on and off")
def onselect_crop(self, eclick, erelease) -> None:
# Obtain (xmin, xmax, ymin, ymax) values
self.RSextent = self.rect_selector.extents
self.RScenter = [self.center[i]+self.rect_selector.center[i] for i in range(2)]
# Zoom to selection
print("CROP TO : ",self.RSextent)
print("CENTER : ",self.RScenter)
#self.ax.set_xlim(self.extent[0], self.extent[1])
#self.ax.set_ylim(self.extent[2], self.extent[3])
def run(self) -> None:
self.rect_selector = RectangleSelector(self.ax, self.onselect_crop,
drawtype='box', button=[1], interactive=True)
#self.fig.canvas.mpl_connect('key_press_event', self.toggle_selector)
plt.show()
def crop(self):
Stokes_crop = copy.deepcopy(self.Stokes)
# Data sets to crop
stkI = Stokes_crop[np.argmax([Stokes_crop[i].header['datatype']=='I_stokes' for i in range(len(Stokes_crop))])]
stkQ = Stokes_crop[np.argmax([Stokes_crop[i].header['datatype']=='Q_stokes' for i in range(len(Stokes_crop))])]
stkU = Stokes_crop[np.argmax([Stokes_crop[i].header['datatype']=='U_stokes' for i in range(len(Stokes_crop))])]
stk_cov = Stokes_crop[np.argmax([Stokes_crop[i].header['datatype']=='IQU_cov_matrix' for i in range(len(Stokes_crop))])]
pol = Stokes_crop[np.argmax([Stokes_crop[i].header['datatype']=='Pol_deg_debiased' for i in range(len(Stokes_crop))])]
pol_err = Stokes_crop[np.argmax([Stokes_crop[i].header['datatype']=='Pol_deg_err' for i in range(len(Stokes_crop))])]
pang = Stokes_crop[np.argmax([Stokes_crop[i].header['datatype']=='Pol_ang' for i in range(len(Stokes_crop))])]
pang_err = Stokes_crop[np.argmax([Stokes_crop[i].header['datatype']=='Pol_ang_err' for i in range(len(Stokes_crop))])]
# Crop datasets
vertex = [int(self.RScenter[0]+self.RSextent[0]), int(self.RScenter[0]+self.RSextent[1]), int(self.RScenter[1]+self.RSextent[2]), int(self.RScenter[1]+self.RSextent[3])]
for dataset in [stkI, stkQ, stkU, pol, pol_err, pang, pang_err]:
dataset.data = dataset.data[vertex[2]:vertex[3], vertex[0]:vertex[1]]
data_mask = self.data_mask[vertex[2]:vertex[3], vertex[0]:vertex[1]]
new_stk_cov = np.zeros((3,3,stkI.data.shape[0],stkI.data.shape[1]))
for i in range(3):
for j in range(3):
new_stk_cov[i,j] = stk_cov.data[i,j][vertex[2]:vertex[3], vertex[0]:vertex[1]]
stk_cov.data = new_stk_cov
return Stokes_crop, data_mask
def polarization_map(Stokes, data_mask, rectangle=None, SNRp_cut=3., SNRi_cut=30.,
step_vec=1, savename=None, plots_folder="", display=None):
"""
Plots polarization map from Stokes HDUList.
----------