cosmoplots 0.2.1

Routines to get a sane default configuration for production quality plots.

cosmoplots

Routines to get a sane default configuration for production quality plots. Used by complex systems modelling group at UiT.

Installation

The package is published to PyPI and can be installed with

pip install cosmoplots

If you want the development version you must first clone the repo to your local machine, then install the project and its dependencies with poetry:

git clone https://github.com/uit-cosmo/cosmoplots.git
cd cosmoplots
poetry install

Usage

Set your rcparams before plotting in your code, for example:

import cosmoplots

axes_size = cosmoplots.set_rcparams_dynamo(plt.rcParams, num_cols=1, ls="thin")

change_log_axis_base

import matplotlib.pyplot as plt
import numpy as np
import cosmoplots

axes_size = cosmoplots.set_rcparams_dynamo(plt.rcParams, num_cols=1, ls="thin")
a = np.exp(np.linspace(-3, 5, 100))
fig = plt.figure()
ax = fig.add_axes(axes_size)
ax.set_xlabel("X Axis")
ax.set_ylabel("Y Axis")
base = 2  # Default is 10, but 2 works equally well
cosmoplots.change_log_axis_base(ax, "x", base=base)
# Do plotting ...
# If you use "plot", the change_log_axis_base can be called at the top (along with add_axes
# etc.), but using loglog, semilogx, semilogy will re-set, and the change_log_axis_base
# function must be called again.
ax.plot(a)
plt.show()

matplotlib vs. cosmoplots defaults

import matplotlib.pyplot as plt
import numpy as np
import cosmoplots

# Matplotlib --------------------------------------------------------------------------- #
a = np.exp(np.linspace(-3, 5, 100))
fig = plt.figure()
ax = fig.add_subplot()
ax.set_xlabel("X Axis")
ax.set_ylabel("Y Axis")
ax.semilogy(a)
# plt.savefig("assets/matplotlib.png")
plt.show()

# Cosmoplots --------------------------------------------------------------------------- #
axes_size = cosmoplots.set_rcparams_dynamo(plt.rcParams, num_cols=1, ls="thin")
a = np.exp(np.linspace(-3, 5, 100))
fig = plt.figure()
ax = fig.add_axes(axes_size)
ax.set_xlabel("X Axis")
ax.set_ylabel("Y Axis")
cosmoplots.change_log_axis_base(ax, "y")
ax.semilogy(a)
# Commenting out the below line result in the default base10 ticks
cosmoplots.change_log_axis_base(ax, "y")
# plt.savefig("assets/cosmoplots.png")
plt.show()

matplotlib	cosmoplots

generate_hex_colors

This function generates the hex numbers for the colours extracted from a matplotlib colour map based on the number of points of interest. The colors change gradually from bright to dark or vice versa.

import matplotlib.pyplot as plt
import cosmoplots

axes_size = cosmoplots.set_rcparams_dynamo(plt.rcParams, num_cols=1, ls="thin")


color_list = cosmoplots.generate_hex_colors(5, 'viridis', show_swatch=True, ascending=True)
plt.savefig("./assets/hex_colors.png")

# Print color_list to retrieve the hex numbers
print(color_list) #['#fde725', '#5ec962', '#21918c', '#3b528b', '#440154']

fig = plt.figure()
ax = fig.add_axes(axes_size)
for i, color in enumerate(color_list):
    ax.plot([1,2],[i,i+1], c = color)

plt.savefig("./assets/hex_colors_example.png")
plt.show()

hex_colors.png	hex_colors_example.png