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Fixing tidal field calculation (#68)

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* Add import

* Fix tidal calculation

* Add env to paths

* Improve plot routines

* Add env classification
This commit is contained in:
Richard Stiskalek 2023-06-16 18:31:43 +01:00 • committed by GitHub
parent ccbbbd24b4
commit cbfd1cbc99
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5 changed files with 233 additions and 34 deletions
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83
scripts_plots/plot_data.py
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@ -240,9 +240,9 @@ def load_field(kind, nsim, grid, MAS, in_rsp=False):
def plot_projected_field(kind, nsim, grid, in_rsp, MAS="PCS",
highres_only=True, pdf=False):
highres_only=True, slice_find=None, pdf=False):
"""
Plot the mean projected field.
Plot the mean projected field, however can also plot a single slice.
Parameters
----------
@ -258,6 +258,8 @@ def plot_projected_field(kind, nsim, grid, in_rsp, MAS="PCS",
Mass assignment scheme.
highres_only : bool, optional
Whether to only plot the high-resolution region.
slice_find : float, optional
Which slice to plot in fractional units (i.e. 1. is the last slice)
pdf : bool, optional
Whether to save the figure as a PDF.
@ -284,23 +286,69 @@ def plot_projected_field(kind, nsim, grid, in_rsp, MAS="PCS",
end = round(field.shape[0] * 0.73)
field = field[start:end, start:end, start:end]
if kind != "environment":
cmap = "viridis"
else:
cmap = "brg"
labels = [r"$y-z$", r"$x-z$", r"$x-y$"]
with plt.style.context(plt_utils.mplstyle):
fig, ax = plt.subplots(figsize=(3.5 * 2, 2.625), ncols=3, sharey=True,
sharex=True)
sharex="col")
fig.subplots_adjust(hspace=0, wspace=0)
for i in range(3):
img = numpy.nanmean(field, axis=i)
if slice_find is None:
img = numpy.nanmean(field, axis=i)
else:
ii = int(field.shape[i] * slice_find)
img = numpy.take(field, ii, axis=i)
if i == 0:
vmin, vmax = numpy.nanpercentile(img, [1, 99])
im = ax[i].imshow(numpy.nanmean(field, axis=i), vmin=vmin,
vmax=vmax)
im = ax[i].imshow(img, vmin=vmin, vmax=vmax, cmap=cmap)
else:
ax[i].imshow(numpy.nanmean(field, axis=i), vmin=vmin,
vmax=vmax)
ax[i].imshow(img, vmin=vmin, vmax=vmax, cmap=cmap)
if not highres_only:
theta = numpy.linspace(0, 2 * numpy.pi, 100)
rad = 155.5 / 677.7 * grid
ax[i].plot(rad * numpy.cos(theta) + grid // 2,
rad * numpy.sin(theta) + grid // 2,
lw=plt.rcParams["lines.linewidth"], zorder=1,
c="red", ls="--")
ax[i].set_title(labels[i])
if highres_only:
ncells = end - start
size = ncells / grid * 677.7
else:
ncells = grid
size = 677.7
# Get beautiful ticks
yticks = numpy.linspace(0, ncells, 6).astype(int)
yticks = numpy.append(yticks, ncells // 2)
ax[0].set_yticks(yticks)
ax[0].set_yticklabels((yticks * size / ncells - size / 2).astype(int))
ax[0].set_ylabel(r"$x_i ~ [\mathrm{Mpc} / h]$")
for i in range(3):
xticks = numpy.linspace(0, ncells, 6).astype(int)
xticks = numpy.append(xticks, ncells // 2)
xticks = numpy.sort(xticks)
if i < 2:
xticks = xticks[:-1]
ax[i].set_xticks(xticks)
ax[i].set_xticklabels(
(xticks * size / ncells - size / 2).astype(int))
ax[i].set_xlabel(r"$x_j ~ [\mathrm{Mpc} / h]$")
cbar_ax = fig.add_axes([1.0, 0.1, 0.025, 0.8])
fig.colorbar(im, cax=cbar_ax, label="Mean projected field")
if slice_find is None:
clabel = "Mean projected field"
else:
clabel = "Sliced field"
fig.colorbar(im, cax=cbar_ax, label=clabel)
fig.tight_layout(h_pad=0, w_pad=0)
for ext in ["png"] if pdf is False else ["png", "pdf"]:
@ -310,6 +358,7 @@ def plot_projected_field(kind, nsim, grid, in_rsp, MAS="PCS",
fig.savefig(fout, dpi=plt_utils.dpi, bbox_inches="tight")
plt.close()
###############################################################################
# Sky distribution #
###############################################################################
@ -461,12 +510,16 @@ if __name__ == "__main__":
plot_hmf(pdf=False)
if False:
plot_sky_distribution("radvel", 7444, 256, nside=64,
plot_groups=False, dmin=50, dmax=100,
kind = "environment"
grid = 256
plot_sky_distribution(kind, 7444, grid, nside=64,
plot_groups=False, dmin=0, dmax=25,
plot_halos=5e13, volume_weight=False)
if True:
plot_projected_field("overdensity", 7444, 1024, in_rsp=True,
highres_only=False)
plot_projected_field("overdensity", 7444, 1024, in_rsp=False,
highres_only=False)
kind = "environment"
grid = 256
# plot_projected_field("overdensity", 7444, grid, in_rsp=True,
# highres_only=False)
plot_projected_field(kind, 7444, grid, in_rsp=False,
slice_find=0.5, highres_only=False)