/
plottools.py
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/
plottools.py
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import numpy
from mpl_toolkits.axes_grid1 import make_axes_locatable
from matplotlib import colors
from generaltools import from_eta_to_k_par
from generaltools import from_u_to_k_perp
from generaltools import from_jansky_to_milikelvin
def colorbar(mappable, extend = 'neither'):
ax = mappable.axes
fig = ax.figure
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
return fig.colorbar(mappable, cax=cax, extend = extend)
def plot_power_spectrum(u_bins, eta_bins, nu, data, norm = None, title=None, axes=None,
colormap = "viridis", axes_label_font=20, tickfontsize=15, xlabel_show=False, ylabel_show=False,
zlabel_show=False, z_label = None, return_norm = False, colorbar_show = False, colorbar_limits = 'neither',
ratio = False, diff = False, x_range = None, y_range = None):
central_frequency = nu[int(len(nu) / 2)]
x_values = from_u_to_k_perp(u_bins, central_frequency)
y_values = from_eta_to_k_par(eta_bins, central_frequency)
if ratio:
z_values = data
else:
z_values = from_jansky_to_milikelvin(data, nu)
x_label = r"$k_{\perp}$ [$h$Mpc$^{-1}$]"
y_label = r"$k_{\parallel}$ [$h$Mpc$^{-1}$]"
if z_label is None:
z_label = r"Variance [mK$^2$ $h^{-3}$Mpc$^3$ ]"
elif z_label == False:
z_label = None
if x_range is None:
axes.set_xlim(9e-3, 3e-1)
else:
axes.set_xlim(x_range[0], x_range[1])
if y_range is None:
axes.set_ylim(9e-3, 1.2e0)
else:
axes.set_ylim(y_range[0], y_range[1])
if diff:
pass
else:
z_values[data < 0] = numpy.nan
if norm is None:
norm = colors.LogNorm(vmin=numpy.real(z_values).min(), vmax=numpy.real(z_values).max())
if title is not None:
axes.set_title(title)
psplot = axes.pcolor(x_values, y_values, z_values.T, cmap=colormap, rasterized=True, norm=norm)
if colorbar_show:
cax = colorbar(psplot, extend=colorbar_limits)
cax.ax.tick_params(axis='both', which='major', labelsize=tickfontsize)
cax.set_label(z_label, fontsize=axes_label_font)
axes.set_xscale('log')
axes.set_yscale('log')
if xlabel_show:
axes.set_xlabel(x_label, fontsize=axes_label_font)
if ylabel_show:
axes.set_ylabel(y_label, fontsize=axes_label_font)
axes.tick_params(axis='both', which='major', labelsize=tickfontsize)
return norm if return_norm else None