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small improvments to displays

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resolve addition of display improvments
This commit is contained in:
Thibault Barnouin
2025-03-07 10:48:55 +01:00
parent a0545a219f
commit bf910a9632
4 changed files with 51 additions and 181 deletions
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211
package/lib/plots.py
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@@ -428,7 +428,7 @@ def polarization_map(
P_cut = 0.99
else:
# MaskP on the confidence value
SNRp_cut = 5.0
SNRp_cut = 3.0
maskP = confP > P_cut
mask = np.logical_and(maskI, maskP)
@@ -504,72 +504,32 @@ def polarization_map(
if display.lower() in ["i", "intensity"]:
# If no display selected, show intensity map
display = "i"
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),
)
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),
)
else:
if flux_lim is not None:
vmin, vmax = flux_lim
im = ax.imshow(
stkI * convert_flux,
norm=LogNorm(vmin, vmax),
aspect="equal",
cmap=kwargs["cmap"],
alpha=1.0,
)
fig.colorbar(
im,
ax=ax,
aspect=30,
shrink=0.60,
pad=0.025,
label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]",
)
elif 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)
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)
im = ax.imshow(stkI * convert_flux, norm=LogNorm(vmin, vmax), aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
levelsI = np.array([0.8, 2.0, 5.0, 10.0, 20.0, 50.0]) / 100.0 * vmax
print("Flux density contour levels : ", levelsI)
ax.contour(stkI * convert_flux, levels=levelsI, colors="grey", linewidths=0.5)
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:
if flux_lim is not None:
vmin, vmax = flux_lim
pfmax = (stkI[stkI > 0.0] * pol[stkI > 0.0] * convert_flux).max()
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=30,
shrink=0.60,
pad=0.025,
label=r"$F_{\lambda} \cdot P$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]",
)
# levelsPf = np.linspace(0.0175, 0.50, 5) * pfmax
elif 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()
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=0.60, pad=0.025, label=r"$F_{\lambda} \cdot P$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
# levelsPf = np.linspace(0.0.60, 0.50, 5) * pfmax
levelsPf = np.array([1.73, 13.0, 33.0, 66.0]) / 100.0 * pfmax
print("Polarized flux density contour levels : ", levelsPf)
ax.contour(stkI * convert_flux * pol, levels=levelsPf, colors="grey", linewidths=0.5)
@@ -577,52 +537,24 @@ def polarization_map(
# Display polarization degree map
display = "p"
vmin, vmax = 0.0, 100.0
im = ax.imshow(
pol * 100.0,
vmin=vmin,
vmax=vmax,
aspect="equal",
cmap=kwargs["cmap"],
alpha=1.0,
)
fig.colorbar(im, ax=ax, aspect=30, shrink=0.60, pad=0.025, label=r"$P$ [%]")
im = ax.imshow(pol * 100.0, vmin=vmin, vmax=vmax, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$P$ [%]")
elif display.lower() in ["pa", "pang", "pol_ang"]:
# Display polarization degree map
display = "pa"
vmin, vmax = 0.0, 180.0
im = ax.imshow(
princ_angle(pang),
vmin=vmin,
vmax=vmax,
aspect="equal",
cmap=kwargs["cmap"],
alpha=1.0,
)
fig.colorbar(im, ax=ax, aspect=30, shrink=0.60, pad=0.025, label=r"$\theta_P$ [°]")
im = ax.imshow(princ_angle(pang), vmin=vmin, vmax=vmax, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$\theta_P$ [°]")
elif display.lower() in ["s_p", "pol_err", "pol_deg_err"]:
# Display polarization degree error map
display = "s_p"
if (SNRp > P_cut).any():
vmin, vmax = 0.0, np.max([pol_err[SNRp > P_cut].max(), 1.0]) * 100.0
im = ax.imshow(
pol_err * 100.0,
vmin=vmin,
vmax=vmax,
aspect="equal",
cmap="inferno_r",
alpha=1.0,
)
im = ax.imshow(pol_err * 100.0, vmin=vmin, vmax=vmax, aspect="equal", cmap="inferno_r", alpha=1.0)
else:
vmin, vmax = 0.0, 100.0
im = ax.imshow(
pol_err * 100.0,
vmin=vmin,
vmax=vmax,
aspect="equal",
cmap="inferno_r",
alpha=1.0,
)
fig.colorbar(im, ax=ax, aspect=30, shrink=0.60, pad=0.025, label=r"$\sigma_P$ [%]")
im = ax.imshow(pol_err * 100.0, vmin=vmin, vmax=vmax, aspect="equal", cmap="inferno_r", alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$\sigma_P$ [%]")
elif display.lower() in ["s_i", "i_err"]:
# Display intensity error map
display = "s_i"
@@ -631,73 +563,34 @@ def polarization_map(
1.0 / 2.0 * np.median(np.sqrt(stk_cov[0, 0][stk_cov[0, 0] > 0.0]) * convert_flux),
np.max(np.sqrt(stk_cov[0, 0][stk_cov[0, 0] > 0.0]) * convert_flux),
)
im = ax.imshow(
np.sqrt(stk_cov[0, 0]) * convert_flux,
norm=LogNorm(vmin, vmax),
aspect="equal",
cmap="inferno_r",
alpha=1.0,
)
im = ax.imshow(np.sqrt(stk_cov[0, 0]) * convert_flux, norm=LogNorm(vmin, vmax), aspect="equal", cmap="inferno_r", alpha=1.0)
else:
im = ax.imshow(
np.sqrt(stk_cov[0, 0]) * convert_flux,
aspect="equal",
cmap=kwargs["cmap"],
alpha=1.0,
)
fig.colorbar(
im,
ax=ax,
aspect=30,
shrink=0.60,
pad=0.025,
label=r"$\sigma_I$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]",
)
im = ax.imshow(np.sqrt(stk_cov[0, 0]) * convert_flux, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$\sigma_I$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
elif display.lower() in ["snri"]:
# Display I_stokes signal-to-noise map
display = "snri"
vmin, vmax = 0.0, np.max(SNRi[np.isfinite(SNRi)])
if vmax * 0.99 > SNRi_cut:
im = ax.imshow(
SNRi,
vmin=vmin,
vmax=vmax,
aspect="equal",
cmap=kwargs["cmap"],
alpha=1.0,
)
im = ax.imshow(SNRi, vmin=vmin, vmax=vmax, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
levelsSNRi = np.linspace(SNRi_cut, vmax * 0.99, 5).astype(int)
print("SNRi contour levels : ", levelsSNRi)
ax.contour(SNRi, levels=levelsSNRi, colors="grey", linewidths=0.5)
else:
im = ax.imshow(SNRi, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(
im,
ax=ax,
aspect=30,
shrink=0.60,
pad=0.025,
label=r"$I_{Stokes}/\sigma_{I}$",
)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$I_{Stokes}/\sigma_{I}$")
elif display.lower() in ["snr", "snrp"]:
# Display polarization degree signal-to-noise map
display = "snrp"
vmin, vmax = 0.0, np.max(SNRp[np.isfinite(SNRp)])
if vmax * 0.99 > SNRp_cut:
im = ax.imshow(
SNRp,
vmin=vmin,
vmax=vmax,
aspect="equal",
cmap=kwargs["cmap"],
alpha=1.0,
)
im = ax.imshow(SNRp, vmin=vmin, vmax=vmax, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
levelsSNRp = np.linspace(P_cut, vmax * 0.99, 5).astype(int)
print("SNRp contour levels : ", levelsSNRp)
ax.contour(SNRp, levels=levelsSNRp, colors="grey", linewidths=0.5)
else:
im = ax.imshow(SNRp, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=30, shrink=0.60, pad=0.025, label=r"$P/\sigma_{P}$")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$P/\sigma_{P}$")
elif display.lower() in ["conf", "confp"]:
# Display polarization degree signal-to-noise map
display = "confp"
@@ -706,34 +599,17 @@ def polarization_map(
levelsconfp = np.array([0.500, 0.900, 0.990, 0.999])
print("confp contour levels : ", levelsconfp)
ax.contour(confP, levels=levelsconfp, colors="grey", linewidths=0.5)
fig.colorbar(im, ax=ax, aspect=30, shrink=0.60, pad=0.025, label=r"$Conf_{P}$")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$Conf_{P}$")
else:
# Defaults to intensity map
if mask.sum() > 0.0:
vmin, vmax = (
1.0 * np.mean(np.sqrt(stk_cov[0, 0][mask]) * convert_flux),
np.max(stkI[stkI > 0.0] * convert_flux),
)
if flux_lim is not None:
vmin, vmax = flux_lim
elif mask.sum() > 0.0:
vmin, vmax = 1.0 * np.mean(np.sqrt(stk_cov[0, 0][mask]) * convert_flux), np.max(stkI[stkI > 0.0] * convert_flux)
else:
vmin, vmax = (
1.0 * np.mean(np.sqrt(stk_cov[0, 0][stkI > 0.0]) * convert_flux),
np.max(stkI[stkI > 0.0] * convert_flux),
)
im = ax.imshow(
stkI * convert_flux,
norm=LogNorm(vmin, vmax),
aspect="equal",
cmap=kwargs["cmap"],
alpha=1.0,
)
fig.colorbar(
im,
ax=ax,
aspect=30,
shrink=0.60,
pad=0.025,
label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]",
)
vmin, vmax = 1.0 * np.mean(np.sqrt(stk_cov[0, 0][stkI > 0.0]) * convert_flux), np.max(stkI[stkI > 0.0] * convert_flux)
im = ax.imshow(stkI * convert_flux, norm=LogNorm(vmin, vmax), aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]")
# Get integrated flux values from sum
I_diluted = stkI[data_mask].sum()
@@ -3148,12 +3024,7 @@ class pol_map(object):
self.snr_conf = 0
b_snr_conf.label.set_text("Conf")
self.s_P_cut = Slider(
self.ax_P_cut,
r"$SNR^{P}_{cut}$",
1.0,
int(SNRp_max * 0.95),
valstep=1,
valinit=self.P_cut if P_cut >= 1.0 else 3,
self.ax_P_cut, r"$SNR^{P}_{cut}$", 1.0, max(int(SNRp_max * 0.95), 3), valstep=1, valinit=self.P_cut if P_cut >= 1.0 else 3
)
else:
self.snr_conf = 1