pltparams 1.0.0

Sets matplotlib parameters for scientific publishing.

Scientific style for matplotlib on import

The default font, font size, figure size, color shceme, linewidth, marker size etc. are not suited for scientific publications. This package sets the defaults to suitable parameters on import, and offers some handy functions for setting new defaults or cycling props.

Install

Use pip package

pip install pltparams

Or download the repo to your computer

cd path/to/pltparams
pip install .

Usage

import pltparams

sets the appropriate rc params for scientific style.

Alternatively:

import pltparams
pltparams.set_params()

The defualt colorscheme has some hard to see colors for white backgrounds, especially if it defaults to the darkmode theme. The 'tab10'colorshcme is good for white background, and is defualt here. Call use_tab10_color to revert back to it.

For black and white, we call use_classic_bw_style() for different linestyles and markers instead of color. This is probably the most useful command.

There's also an alternate use_okabe_ito_color() if you prefer the okabe ito color scheme.

Cycle through the markers by simply calling next(pltparams.marker_cycle). This is the easiest way, as setting default markers will also impose them on plot()in addition to scatter().

# Plot single column (Default style )
fig, ax = plt.subplots(1,1,figsize = pltparams.figsize_single)
plot_example(ax)

For the "classic" black and white style

pltparams.use_classic_bw_lines()
fig, ax = plt.subplots(1,1,figsize = pltparams.figsize_single)
plot_example(ax)

Alternate okabe ito color scheme

pltparams.use_okabe_ito_color()
fig, ax = plt.subplots(1,1,figsize = pltparams.figsize_single)
plot_example(ax)

Cycle props

We can fetch the next marker using next(marker_cycle), to easily grab the next markers. This is the easiest way to do this, as marker prop cycles can not be set in the defualt RCParams.

ax.scatter(x_scatter, y_scatter, marker = next(pltparams.marker_cycle), label="data 1 scatter")

There's also a letter_labels_lc and letter_labels_uc for lower case, and upper case, letters. This is handy for subplots.

ax.set_title(pltparams.letter_labels_lc[j]+") : "+subplot_labels[j], loc='left')

Alternatively copy paste this

These are the params the package will change, feel free to copy/paste if you prefer that

params = {"ytick.color" : "black",
          "xtick.color" : "black",
          "axes.labelcolor" : "black",
          "axes.edgecolor" : "black",
          "text.usetex" : True,
          "font.family" : "serif",
          "font.serif" : ["Computer Modern Serif"],
          "axes.labelsize": 10,
          "axes.titlesize": 10,
          "xtick.labelsize": 10,
          "ytick.labelsize": 10,
          "legend.fontsize": 7,
          "figure.figsize": figsize/ 25.4,
          'figure.constrained_layout.use': True,
          'figure.constrained_layout.hspace': 0.01,
          'figure.constrained_layout.wspace': 0.01,
          'figure.constrained_layout.h_pad':  0.02167,
          'figure.constrained_layout.w_pad':  0.02167,
          #'figure.autolayout': True,
          'lines.linewidth' : 0.5,
          'figure.facecolor' : "white",
          'axes.facecolor' : "white",
          'text.color' : 'black',
          'axes.titlecolor' : 'black',
          'savefig.facecolor' : 'white',
          'savefig.dpi' : '300',
          'savefig.format' : 'pdf',

          }
plt.rcParams.update(params)
plt.rcParams['figure.constrained_layout.use'] = True