Tibeuleu/FOC_Reduction
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modify shebang

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Thibault Barnouin
2024-11-19 13:50:23 +01:00
parent f6d62bff73
commit 3f97202a03
11 changed files with 173 additions and 118 deletions
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14
package/FOC_reduction.py
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@@ -1,4 +1,4 @@
#!/usr/bin/python
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
"""
Main script where are progressively added the steps for the FOC pipeline reduction.
@@ -30,7 +30,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# from lib.deconvolve import from_file_psf
psf = "gaussian" # Can be user-defined as well
# psf = from_file_psf(data_folder+psf_file)
psf_FWHM = 3.1
psf_FWHM = 1.55
psf_scale = "px"
psf_shape = None # (151, 151)
iterations = 1
@@ -42,7 +42,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# Background estimation
error_sub_type = "freedman-diaconis" # sqrt, sturges, rice, scott, freedman-diaconis (default) or shape (example (51, 51))
subtract_error = 1.0
display_bkg = True
display_bkg = False
# Data binning
pxsize = 0.05
@@ -51,7 +51,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# Alignement
align_center = "center" # If None will not align the images
display_align = True
display_align = False
display_data = False
# Transmittance correction
@@ -66,10 +66,10 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
rotate_North = True
# Polarization map output
P_cut = 0.99 # if >=1.0 cut on the signal-to-noise else cut on the confidence level in Q, U
SNRi_cut = 1.0 # I measurments with SNR>30, which implies an uncertainty in P of 4.7%.
P_cut = 0.999 # if >=1.0 cut on the signal-to-noise else cut on the confidence level in Q, U
SNRi_cut = 3.0 # I measurments with SNR>30, which implies an uncertainty in P of 4.7%.
flux_lim = None # lowest and highest flux displayed on plot, defaults to bkg and maximum in cut if None
scale_vec = 3
scale_vec = 2
step_vec = 1 # plot all vectors in the array. if step_vec = 2, then every other vector will be plotted if step_vec = 0 then all vectors are displayed at full length
# Pipeline start

6
package/lib/deconvolve.py
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@@ -286,11 +286,13 @@ def richardson_lucy(image, psf, iterations=20, clip=True, filter_epsilon=None):
image = image.astype(float_type, copy=False)
psf = psf.astype(float_type, copy=False)
psf /= psf.sum()
im_deconv = image.copy()
im_deconv = np.full(image.shape, 0.5, dtype=float_type)
psf_mirror = np.flip(psf)
eps = 1e-20
for _ in range(iterations):
conv = convolve(im_deconv, psf, mode="same")
conv = convolve(im_deconv, psf, mode="same") + eps
if filter_epsilon:
relative_blur = np.where(conv < filter_epsilon, 0, image / conv)
else:

226
package/lib/plots.py
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@@ -1,4 +1,4 @@
#!/usr/bin/python
#!/usr/bin/env python3
"""
Library functions for displaying informations using matplotlib
@@ -270,6 +270,7 @@ def polarization_map(
scale_vec : float, optional
Pixel length of displayed 100% polarization vector.
If scale_vec = 2, a vector of 50% polarization will be 1 pixel wide.
If scale_vec = 0, all polarization vectors will be displayed at full length.
Defaults to 2.
savename : str, optional
Name of the figure the map should be saved to. If None, the map won't
@@ -412,7 +413,7 @@ def polarization_map(
ax.set_facecolor("white")
font_color = "black"
if display.lower() in ["intensity"]:
if display.lower() in ["i", "intensity"]:
# If no display selected, show intensity map
display = "i"
if flux_lim is None:
@@ -427,19 +428,22 @@ def polarization_map(
levelsI = np.array([0.8, 2.0, 5.0, 10.0, 20.0, 50.0]) / 100.0 * vmax
print("Total flux contour levels : ", levelsI)
ax.contour(stkI * convert_flux, levels=levelsI, colors="grey", linewidths=0.5)
elif display.lower() in ["pol_flux"]:
elif display.lower() in ["pf", "pol_flux"]:
# Display polarization flux
display = "pf"
if flux_lim is None:
if mask.sum() > 0.0:
vmin, vmax = 1.0 / 2.0 * np.median(np.sqrt(stk_cov[0, 0][mask]) * convert_flux), np.max(stkI[stkI > 0.0] * convert_flux)
pfmax = (stkI[mask] * pol[mask] * convert_flux).max()
else:
vmin, vmax = 1.0 / 2.0 * np.median(np.sqrt(stk_cov[0, 0][stkI > 0.0]) * convert_flux), np.max(stkI[stkI > 0.0] * convert_flux)
pfmax = (stkI[stkI > 0.0] * pol[stkI > 0.0] * convert_flux).max()
else:
vmin, vmax = flux_lim
im = ax.imshow(stkI * convert_flux * pol, norm=LogNorm(vmin, vmax), aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.75, pad=0.025, 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)
# levelsPf = np.linspace(0.0175, 0.50, 5) * pfmax
levelsPf = np.array([1.73, 13.0, 33.0, 66.0]) / 100.0 * pfmax
print("Polarized flux contour levels : ", levelsPf)
ax.contour(stkI * convert_flux * pol, levels=levelsPf, colors="grey", linewidths=0.5)
elif display.lower() in ["p", "pol", "pol_deg"]:
@@ -548,8 +552,8 @@ def polarization_map(
arrow_props={"ec": "k", "fc": font_color, "alpha": 1, "lw": 1},
)
if display.lower() in ["i", "s_i", "snri", "pf", "p", "pa", "s_p", "snrp", "confp"]:
if step_vec == 0:
if display.lower() in ["i", "s_i", "snri", "pf", "p", "pa", "s_p", "snrp", "confp"] and step_vec != 0:
if scale_vec == -1:
poldata[np.isfinite(poldata)] = 1.0 / 2.0
step_vec = 1
scale_vec = 2.0
@@ -1359,7 +1363,7 @@ class overplot_pol(align_maps):
Inherit from class align_maps in order to get the same WCS on both maps.
"""
def overplot(self, levels=None, P_cut=0.99, SNRi_cut=1.0, scale_vec=2.0, step_vec=1, savename=None, **kwargs):
def overplot(self, levels=None, P_cut=0.99, SNRi_cut=1.0, step_vec=1, scale_vec=2.0, disptype="i", savename=None, **kwargs):
self.Stokes_UV = self.map
self.wcs_UV = self.map_wcs
# Get Data
@@ -1402,13 +1406,6 @@ class overplot_pol(align_maps):
self.ax_overplot.set_xlabel(label="Right Ascension (J2000)")
self.ax_overplot.set_ylabel(label="Declination (J2000)", labelpad=-1)
self.fig_overplot.suptitle(
"{0:s} observation from {1:s} overplotted with polarization vectors and Stokes I contours from {2:s}".format(
obj, self.other_observer, self.map_observer
),
wrap=True,
)
# Display "other" intensity map
vmin, vmax = other_data[other_data > 0.0].max() / 1e3 * self.other_convert, other_data[other_data > 0.0].max() * self.other_convert
for key, value in [
@@ -1459,59 +1456,85 @@ class overplot_pol(align_maps):
)
# Display full size polarization vectors
if scale_vec is None:
self.scale_vec = 2.0 * self.px_scale
pol[np.isfinite(pol)] = 1.0 / 2.0
else:
self.scale_vec = scale_vec * self.px_scale
self.X, self.Y = np.meshgrid(np.arange(stkI.shape[1]), np.arange(stkI.shape[0]))
self.U, self.V = pol * np.cos(np.pi / 2.0 + pang * np.pi / 180.0), pol * np.sin(np.pi / 2.0 + pang * np.pi / 180.0)
self.Q = self.ax_overplot.quiver(
self.X[::step_vec, ::step_vec],
self.Y[::step_vec, ::step_vec],
self.U[::step_vec, ::step_vec],
self.V[::step_vec, ::step_vec],
units="xy",
angles="uv",
scale=1.0 / self.scale_vec,
scale_units="xy",
pivot="mid",
headwidth=0.0,
headlength=0.0,
headaxislength=0.0,
width=kwargs["width"],
linewidth=kwargs["linewidth"],
color="white",
edgecolor="black",
transform=self.ax_overplot.get_transform(self.wcs_UV),
label="{0:s} polarization map".format(self.map_observer),
)
vecstr = ""
if step_vec != 0:
vecstr = "polarization vectors "
if scale_vec is None:
self.scale_vec = 2.0 * self.px_scale
pol[np.isfinite(pol)] = 1.0 / 2.0
else:
self.scale_vec = scale_vec * self.px_scale
self.X, self.Y = np.meshgrid(np.arange(stkI.shape[1]), np.arange(stkI.shape[0]))
self.U, self.V = pol * np.cos(np.pi / 2.0 + pang * np.pi / 180.0), pol * np.sin(np.pi / 2.0 + pang * np.pi / 180.0)
self.Q = self.ax_overplot.quiver(
self.X[::step_vec, ::step_vec],
self.Y[::step_vec, ::step_vec],
self.U[::step_vec, ::step_vec],
self.V[::step_vec, ::step_vec],
units="xy",
angles="uv",
scale=1.0 / self.scale_vec,
scale_units="xy",
pivot="mid",
headwidth=0.0,
headlength=0.0,
headaxislength=0.0,
width=kwargs["width"],
linewidth=kwargs["linewidth"],
color="white",
edgecolor="black",
transform=self.ax_overplot.get_transform(self.wcs_UV),
label="{0:s} polarization map".format(self.map_observer),
)
# Display Stokes I as contours
if levels is None:
levels = np.array([2.0, 5.0, 10.0, 20.0, 90.0]) / 100.0 * np.max(stkI[stkI > 0.0]) * self.map_convert
cont_stkI = self.ax_overplot.contour(
stkI * self.map_convert, levels=levels, colors="grey", alpha=0.75, transform=self.ax_overplot.get_transform(self.wcs_UV)
)
# self.ax_overplot.clabel(cont_stkI, inline=True, fontsize=5)
# Display Stokes as contours
disptypestr = ""
if disptype.lower() == "p":
disptypestr = "polarization degree"
if levels is None:
levels = np.array([2.0, 5.0, 10.0, 20.0, 90.0]) / 100.0 * np.max(pol[stkI > 0.0])
cont_stk = self.ax_overplot.contour(
pol * 100.0, levels=levels * 100.0, colors="grey", alpha=0.75, transform=self.ax_overplot.get_transform(self.wcs_UV)
)
if disptype.lower() == "pf":
disptypestr = "polarized flux"
if levels is None:
levels = np.array([2.0, 5.0, 10.0, 20.0, 90.0]) / 100.0 * np.max(stkI[stkI > 0.0] * pol[stkI > 0.0]) * self.map_convert
cont_stk = self.ax_overplot.contour(
stkI * pol * self.map_convert, levels=levels, colors="grey", alpha=0.75, transform=self.ax_overplot.get_transform(self.wcs_UV)
)
if disptype.lower() == "snri":
disptypestr = "Stokes I signal-to-noise"
if levels is None:
levels = np.array([2.0, 5.0, 10.0, 20.0, 90.0]) / 100.0 * np.max(SNRi[stk_cov[0, 0] > 0.0])
cont_stk = self.ax_overplot.contour(SNRi, levels=levels, colors="grey", alpha=0.75, transform=self.ax_overplot.get_transform(self.wcs_UV))
else: # default to intensity contours
disptypestr = "Stokes I"
if levels is None:
levels = np.array([2.0, 5.0, 10.0, 20.0, 90.0]) / 100.0 * np.max(stkI[stkI > 0.0]) * self.map_convert
cont_stk = self.ax_overplot.contour(
stkI * self.map_convert, levels=levels, colors="grey", alpha=0.75, transform=self.ax_overplot.get_transform(self.wcs_UV)
)
# self.ax_overplot.clabel(cont_stk, inline=False, colors="k", fontsize=7)
# Display pixel scale and North direction
fontprops = fm.FontProperties(size=16)
px_size = self.other_wcs.wcs.get_cdelt()[0] * 3600.0
px_sc = AnchoredSizeBar(
self.ax_overplot.transData,
1.0 / px_size,
"1 arcsec",
3,
pad=0.5,
sep=5,
borderpad=0.5,
frameon=False,
size_vertical=0.005,
color=font_color,
fontproperties=fontprops,
)
self.ax_overplot.add_artist(px_sc)
if step_vec != 0:
fontprops = fm.FontProperties(size=16)
px_size = self.other_wcs.wcs.get_cdelt()[0] * 3600.0
px_sc = AnchoredSizeBar(
self.ax_overplot.transData,
1.0 / px_size,
"1 arcsec",
3,
pad=0.5,
sep=5,
borderpad=0.5,
frameon=False,
size_vertical=0.005,
color=font_color,
fontproperties=fontprops,
)
self.ax_overplot.add_artist(px_sc)
north_dir = AnchoredDirectionArrows(
self.ax_overplot.transAxes,
"E",
@@ -1528,20 +1551,21 @@ class overplot_pol(align_maps):
arrow_props={"ec": "k", "fc": "w", "alpha": 1, "lw": 0.5},
)
self.ax_overplot.add_artist(north_dir)
pol_sc = AnchoredSizeBar(
self.ax_overplot.transData,
self.scale_vec,
r"$P$= 100%",
4,
pad=0.5,
sep=5,
borderpad=0.5,
frameon=False,
size_vertical=0.005,
color=font_color,
fontproperties=fontprops,
)
self.ax_overplot.add_artist(pol_sc)
if step_vec != 0:
pol_sc = AnchoredSizeBar(
self.ax_overplot.transData,
self.scale_vec,
r"$P$= 100%",
4,
pad=0.5,
sep=5,
borderpad=0.5,
frameon=False,
size_vertical=0.005,
color=font_color,
fontproperties=fontprops,
)
self.ax_overplot.add_artist(pol_sc)
(self.cr_map,) = self.ax_overplot.plot(*(self.map_wcs.celestial.wcs.crpix - (1.0, 1.0)), "r+", transform=self.ax_overplot.get_transform(self.wcs_UV))
(self.cr_other,) = self.ax_overplot.plot(*(self.other_wcs.celestial.wcs.crpix - (1.0, 1.0)), "g+")
@@ -1554,15 +1578,21 @@ class overplot_pol(align_maps):
self.legend_title = r"{0:s} image".format(self.other_observer)
handles, labels = self.ax_overplot.get_legend_handles_labels()
handles[np.argmax([li == "{0:s} polarization map".format(self.map_observer) for li in labels])] = FancyArrowPatch(
(0, 0), (0, 1), arrowstyle="-", fc="w", ec="k", lw=2
)
labels.append("{0:s} Stokes I contour".format(self.map_observer))
handles.append(Rectangle((0, 0), 1, 1, fill=False, ec=cont_stkI.get_edgecolor()[0]))
if step_vec != 0:
handles[np.argmax([li == "{0:s} polarization map".format(self.map_observer) for li in labels])] = FancyArrowPatch(
(0, 0), (0, 1), arrowstyle="-", fc="w", ec="k", lw=2
)
labels.append("{0:s} {1:s} contour".format(self.map_observer, disptypestr))
handles.append(Rectangle((0, 0), 1, 1, fill=False, ec=cont_stk.get_edgecolor()[0]))
self.legend = self.ax_overplot.legend(
handles=handles, labels=labels, bbox_to_anchor=(0.0, 1.02, 1.0, 0.102), loc="lower left", mode="expand", borderaxespad=0.0
)
self.fig_overplot.suptitle(
"{0:s} observation from {1:s} overplotted with {2:s} contours from {3:s}".format(obj, self.other_observer, vecstr + disptypestr, self.map_observer),
wrap=True,
)
if savename is not None:
if savename[-4:] not in [".png", ".jpg", ".pdf"]:
savename += ".pdf"
@@ -1570,10 +1600,10 @@ class overplot_pol(align_maps):
self.fig_overplot.canvas.draw()
def plot(self, levels=None, P_cut=0.99, SNRi_cut=1.0, scale_vec=2.0, savename=None, **kwargs) -> None:
def plot(self, levels=None, P_cut=0.99, SNRi_cut=1.0, step_vec=1, scale_vec=2.0, disptype="i", savename=None, **kwargs) -> None:
while not self.aligned:
self.align()
self.overplot(levels=levels, P_cut=P_cut, SNRi_cut=SNRi_cut, scale_vec=scale_vec, savename=savename, **kwargs)
self.overplot(levels=levels, P_cut=P_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, scale_vec=scale_vec, disptype=disptype, savename=savename, **kwargs)
plt.show(block=True)
def add_vector(self, position="center", pol_deg=1.0, pol_ang=0.0, **kwargs):
@@ -3360,8 +3390,17 @@ class pol_map(object):
+ r"$\theta_{{P}}^{{int}}$ = {0:.1f} $\pm$ {1:.1f} °".format(PA_reg, np.ceil(PA_reg_err * 10.0) / 10.0)
+ str_conf
)
self.str_cut = ""
# self.str_cut = "\n"+r"$F_{{\lambda}}^{{cut}}$({0:.0f} $\AA$) = {1} $ergs \cdot cm^{{-2}} \cdot s^{{-1}} \cdot \AA^{{-1}}$".format(self.pivot_wav, sci_not(I_cut*self.map_convert, I_cut_err*self.map_convert, 2))+"\n"+r"$P^{{cut}}$ = {0:.1f} $\pm$ {1:.1f} %".format(P_cut*100., np.ceil(P_cut_err*1000.)/10.)+"\n"+r"$\theta_{{P}}^{{cut}}$ = {0:.1f} $\pm$ {1:.1f} °".format(PA_cut, np.ceil(PA_cut_err*10.)/10.)
# self.str_cut = ""
self.str_cut = (
"\n"
+ r"$F_{{\lambda}}^{{cut}}$({0:.0f} $\AA$) = {1} $ergs \cdot cm^{{-2}} \cdot s^{{-1}} \cdot \AA^{{-1}}$".format(
self.pivot_wav, sci_not(I_cut * self.map_convert, I_cut_err * self.map_convert, 2)
)
+ "\n"
+ r"$P^{{cut}}$ = {0:.1f} $\pm$ {1:.1f} %".format(P_cut * 100.0, np.ceil(P_cut_err * 1000.0) / 10.0)
+ "\n"
+ r"$\theta_{{P}}^{{cut}}$ = {0:.1f} $\pm$ {1:.1f} °".format(PA_cut, np.ceil(PA_cut_err * 10.0) / 10.0)
)
self.an_int = ax.annotate(
self.str_int + self.str_cut,
color="white",
@@ -3387,8 +3426,17 @@ class pol_map(object):
+ r"$\theta_{{P}}^{{int}}$ = {0:.1f} $\pm$ {1:.1f} °".format(PA_reg, np.ceil(PA_reg_err * 10.0) / 10.0)
+ str_conf
)
str_cut = ""
# str_cut = "\n"+r"$F_{{\lambda}}^{{cut}}$({0:.0f} $\AA$) = {1} $ergs \cdot cm^{{-2}} \cdot s^{{-1}} \cdot \AA^{{-1}}$".format(self.pivot_wav, sci_not(I_cut*self.map_convert, I_cut_err*self.map_convert, 2))+"\n"+r"$P^{{cut}}$ = {0:.1f} $\pm$ {1:.1f} %".format(P_cut*100., np.ceil(P_cut_err*1000.)/10.)+"\n"+r"$\theta_{{P}}^{{cut}}$ = {0:.1f} $\pm$ {1:.1f} °".format(PA_cut, np.ceil(PA_cut_err*10.)/10.)
# str_cut = ""
str_cut = (
"\n"
+ r"$F_{{\lambda}}^{{cut}}$({0:.0f} $\AA$) = {1} $ergs \cdot cm^{{-2}} \cdot s^{{-1}} \cdot \AA^{{-1}}$".format(
self.pivot_wav, sci_not(I_cut * self.map_convert, I_cut_err * self.map_convert, 2)
)
+ "\n"
+ r"$P^{{cut}}$ = {0:.1f} $\pm$ {1:.1f} %".format(P_cut * 100.0, np.ceil(P_cut_err * 1000.0) / 10.0)
+ "\n"
+ r"$\theta_{{P}}^{{cut}}$ = {0:.1f} $\pm$ {1:.1f} °".format(PA_cut, np.ceil(PA_cut_err * 10.0) / 10.0)
)
ax.annotate(
str_int + str_cut,
color="white",

2
package/lib/query.py
View File

@@ -1,4 +1,4 @@
#!/usr/bin/python3
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
"""
Library function to query and download datatsets from MAST api.

6
package/lib/reduction.py
View File

@@ -416,12 +416,12 @@ def deconvolve_array(data_array, headers, psf="gaussian", FWHM=1.0, scale="px",
FWHM /= pxsize[0].min()
# Define Point-Spread-Function kernel
if psf.lower() in ["gauss", "gaussian"]:
if isinstance(psf, np.ndarray) and (len(psf.shape) == 2):
kernel = psf
elif psf.lower() in ["gauss", "gaussian"]:
if shape is None:
shape = np.min(data_array[0].shape) - 2, np.min(data_array[0].shape) - 2
kernel = gaussian_psf(FWHM=FWHM, shape=shape)
elif isinstance(psf, np.ndarray) and (len(psf.shape) == 2):
kernel = psf
else:
raise ValueError("{} is not a valid value for 'psf'".format(psf))

2
package/src/Combine.py
View File

@@ -1,4 +1,4 @@
#!/usr/bin/python
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
from pathlib import Path
from sys import path as syspath

14
package/src/emission_center.py
View File

@@ -1,4 +1,4 @@
#!/usr/bin/python
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
from pathlib import Path
from sys import path as syspath
@@ -41,18 +41,20 @@ def main(infile, target=None, output_dir=None):
target = Stokes[0].header["TARGNAME"]
fig = figure(figsize=(8, 8.5), layout="constrained")
fig, ax = polarization_map(Stokes, P_cut=0.99, step_vec=1, scale_vec=3, display="i", fig=fig, width=0.33, linewidth=0.5)
fig, ax = polarization_map(Stokes, P_cut=0.99, step_vec=1, scale_vec=3, display="pf", fig=fig, width=0.33, linewidth=0.5)
ax.plot(*Stokescenter, marker="+", color="gray", label="Best confidence for center: {0}".format(Stokespos.to_string("hmsdms")))
ax.plot(*Stokescenter, marker="+", color="k", lw=3)
ax.plot(*Stokescenter, marker="+", color="gray", lw=1.5, label="Best confidence for center: {0}".format(Stokespos.to_string("hmsdms")))
ax.contour(Stokescentconf, [0.01], colors="k", linewidths=3)
confcentcont = ax.contour(Stokescentconf, [0.01], colors="gray")
confcont = ax.contour(Stokesconf, [0.9905], colors="r")
# confcont = ax.contour(Stokesconf, [0.9905], colors="r")
# snr3cont = ax.contour(Stokessnr, [3.0], colors="b", linestyles="dashed")
# snr4cont = ax.contour(Stokessnr, [4.0], colors="b")
handles, labels = ax.get_legend_handles_labels()
labels.append(r"Center $Conf_{99\%}$ contour")
handles.append(Rectangle((0, 0), 1, 1, fill=False, ec=confcentcont.get_edgecolor()[0]))
labels.append(r"Polarization $Conf_{99\%}$ contour")
handles.append(Rectangle((0, 0), 1, 1, fill=False, ec=confcont.get_edgecolor()[0]))
# labels.append(r"Polarization $Conf_{99\%}$ contour")
# handles.append(Rectangle((0, 0), 1, 1, fill=False, ec=confcont.get_edgecolor()[0]))
# labels.append(r"$SNR_P \geq$ 3 contour")
# handles.append(Rectangle((0, 0), 1, 1, fill=False, ls="--", ec=snr3cont.get_edgecolor()[0]))
# labels.append(r"$SNR_P \geq$ 4 contour")

4
package/src/get_cdelt.py
View File

@@ -1,4 +1,4 @@
#!/usr/bin/python
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
from pathlib import Path
from sys import path as syspath
@@ -18,7 +18,7 @@ def main(infiles=None):
from numpy.linalg import eig
if infiles is None:
print('Usage: "python get_cdelt.py -f infiles"')
print('Usage: "env python3 get_cdelt.py -f infiles"')
return 1
prod = [["/".join(filepath.split("/")[:-1]), filepath.split("/")[-1]] for filepath in infiles]
data_folder = prod[0][0]

2
package/src/overplot_IC5063.py
View File

@@ -1,4 +1,4 @@
#!/usr/bin/python3
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
from pathlib import Path
from sys import path as syspath

13
package/src/overplot_MRK463E.py
View File

@@ -1,4 +1,4 @@
#!/usr/bin/python3
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
from pathlib import Path
from sys import path as syspath
@@ -26,18 +26,21 @@ Radio = fits.open("./data/MRK463E/EMERLIN/Voorwerpjes_1356+1822_1356+1822_unifor
# B.plot(levels=levels, P_cut=0.99, SNRi_cut=1.0, scale_vec=5, norm=LogNorm(8.5e-18, 2.5e-15), savename="./plots/MRK463E/IR_overplot.pdf")
# B.write_to(path1="./data/MRK463E/FOC_data_WFPC.fits", path2="./data/MRK463E/WFPC_data.fits", suffix="aligned")
levels = np.array([0.8, 2, 5, 10, 20, 50]) / 100.0 * Stokes_UV[0].header["photflam"]
# levels = np.array([0.8, 2, 5, 10, 20, 50]) / 100.0 * Stokes_UV[0].header["photflam"]
levels = np.array([5, 10, 20, 50])
C = overplot_pol(Stokes_UV, Radio, norm=LogNorm())
C.other_im.set(norm=LogNorm(1e-4, 2e-2))
C.plot(
levels=levels,
P_cut=0.999,
SNRi_cut=5.0,
P_cut=0.99,
SNRi_cut=1.0,
step_vec=0,
scale_vec=3,
norm=LogNorm(1e-4, 2e-2),
cmap="inferno_r",
width=0.5,
linewidth=0.5,
savename="./plots/MRK463E/EMERLIN_overplot.pdf",
disptype="snri",
savename="./plots/MRK463E/EMERLIN_snri_overplot.pdf",
)
C.write_to(path1="./data/MRK463E/FOC_data_EMERLIN.fits", path2="./data/MRK463E/EMERLIN_data.fits", suffix="aligned")

2
package/src/overplot_NGC1068.py
View File

@@ -1,4 +1,4 @@
#!/usr/bin/python3
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
from pathlib import Path
from sys import path as syspath