import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from tqdm.auto import tqdm
# functions
[docs]def use_cait_style(x_size=7.2, y_size=4.45, fontsize=18, autolayout=True, dpi=None):
"""
Use the pyplot plot style that is used within the Cait plotting routines.
:param x_size: The width of the plot in cm.
:type x_size: float
:param y_size: The height of the plot in cm.
:type y_size: float
:param fontsize: The font size of the plot.
:type fontsize: int
:param autolayout: Activate autolayout.
:type autolayout: bool
:param dpi: The dots per inch for the plot.
:type dpi: int
"""
plt.style.use('seaborn-paper')
mpl.rcParams['xtick.labelsize'] = fontsize
mpl.rcParams['ytick.labelsize'] = fontsize
mpl.rcParams['font.size'] = fontsize
if autolayout is not None:
mpl.rcParams['figure.autolayout'] = autolayout
mpl.rcParams['figure.figsize'] = (x_size, y_size)
if dpi is not None:
mpl.rcParams['figure.dpi'] = dpi
mpl.rcParams['axes.titlesize'] = fontsize
mpl.rcParams['axes.labelsize'] = fontsize
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.markersize'] = 6
mpl.rcParams['legend.fontsize'] = fontsize
mpl.rcParams['mathtext.fontset'] = 'stix'
mpl.rcParams['font.family'] = 'STIXGeneral'
if dpi is not None:
mpl.rcParams['savefig.dpi'] = dpi
[docs]def make_grid(ax=None):
"""
Produce the pyplot plot grid that is used within the Cait plotting routines.
:param ax: A pyplot axis object, optional.
:type ax: object
"""
if ax is None:
# major grid lines
plt.grid(which='major', color='gray', alpha=0.6, linestyle='dashdot', lw=1.5)
# minor grid lines
plt.minorticks_on()
plt.grid(which='minor', color='beige', alpha=0.8, ls='-', lw=1)
else:
# major grid lines
ax.grid(which='major', color='gray', alpha=0.6, linestyle='dashdot', lw=1.5)
# minor grid lines
ax.minorticks_on()
ax.grid(which='minor', color='beige', alpha=0.8, ls='-', lw=1)
[docs]def scatter_img(x_data, y_data, height=2800, width=2800, alpha=0.3, xlims=None, ylims=None):
"""
Produce a scatter plot to plot as an image with pyplot.imshow.
:param x_data: The values for the x axis.
:type x_data: 1D array
:param y_data: The values for the x axis.
:type y_data: 1D array
:param height: The number of pixels on the x axis.
:type height: int
:param width: The number of pixels on the y axis.
:type width: int
:param alpha: The occupacity of one event inside a pixel, between 0 and 1.
:type alpha: float
:param xlims: The limits on the x axis.
:type xlims: 2-tuple
:param ylims: The limits on the y axis.
:type ylims: 2-tuple
:return: List of the x limits, the y limits and the density values for the image plot.
:rtype: list of (2-tuple, 2-tuple, 2D matrix)
"""
if xlims is None:
xlims = (x_data.min(), x_data.max())
if ylims is None:
ylims = (y_data.min(), y_data.max())
dxl = xlims[1] - xlims[0]
dyl = ylims[1] - ylims[0]
buffer = np.zeros((height + 1, width + 1))
for i, (x, y) in enumerate(tqdm(zip(x_data, y_data))):
x0 = int(round(((x - xlims[0]) / dxl) * width))
y0 = int(round((1 - (y - ylims[0]) / dyl) * height))
if x0 > 0 and x0 < width + 1 and y0 > 0 and y0 < height + 1:
buffer[y0, x0] += alpha
if buffer[y0, x0] > 1.0: buffer[y0, x0] = 1.0
return xlims, ylims, buffer