Source code for xripl.pltDefaults

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 27 02:37:12 2017

Default plotting parameters

@author: Pawel M. Kozlowski
"""

# importing Python modules
import numpy as np
import matplotlib 
import matplotlib.pyplot as plt
from itertools import cycle


# listing all functions declared in this file so that sphinx-automodapi
# correctly documents them and doesn't document imported functions.
__all__ = ["plot_line_shaded",
           "plot_scatter_bars",
           ]


# setting default plot properties
plotFont = {'family' : 'serif',
            'weight' : 'normal',
            'size'   : 16}
plt.rc('font', **plotFont)
plt.rc('lines', linewidth=2)
plt.rc('lines', markersize=8)
#plt.rc('text', usetex=True)
#plt.rc('text', usetex=False)
# setting default figure size
matplotlib.rcParams['figure.figsize'] = 10, 6

validMathTextFonts = ['dejavusans',
                      'dejavuserif',
                      'cm',
                      'stix',
                      'stixsans',
                      'custom']

# setting latex rendered fonts to be same as regular fonts
try:
    matplotlib.rcParams['mathtext.fontset'] = 'dejavuserif'
    matplotlib.rcParams['mathtext.rm'] = 'DejaVu Serif'
    matplotlib.rcParams['mathtext.it'] = 'DejaVu Serif:italic'
    matplotlib.rcParams['mathtext.bf'] = 'DejaVu Serif:bold'
except:
    print("Couldn't load dejavuserif fonts for plot defaults."
          "Falling back to stix fonts.")
    try:
        matplotlib.rcParams['mathtext.fontset'] = 'stix'
        matplotlib.rcParams['font.family'] = 'STIXGeneral'
    except:
        print("Couldn't load stix fonts for plot defaults.")

# for testing whether matplotlib and python fonts match
#plt.title(r'cm$\rm cm^{-3}$')


#%% convenience functions for plotting

# shaded error bars for line plot
[docs]def plot_line_shaded(xData, yData, yErrs, label="", **kwargs): """ Generate a line plot with shaded region representing y-error bars. Can be run multiple times before plt.show(), to plot multiple data sets on the same axes. x axis data points y axis data points y axis errors """ # check that arrays are 1D # check that arrays are equal length if not len(xData) == len(yData) == len(yErrs): raise ValueError("Arrays must of equal length!") # line plot ax = kwargs.pop('ax', plt.gca()) base_line, = ax.plot(xData, yData, label=label, **kwargs) # shaded error region plt.fill_between(xData, yData - yErrs, yData + yErrs, alpha=0.5, edgecolor=base_line.get_color(), facecolor=base_line.get_color()) return
# error bars for scatter plot
[docs]def plot_scatter_bars(xData, yData, yErrs, label="", **kwargs): """ Generate a scatter plot with y-error bars. Can be run multiple times before plt.show(), to plot multiple data sets on the same axes. x axis data points y axis data points y axis errors """ # check that arrays are 1D # check that arrays are equal length if not len(xData) == len(yData) == len(yErrs): raise ValueError("Arrays must of equal length!") # line plot ax = kwargs.pop('ax', plt.gca()) ax.errorbar(xData, yData, yerr=yErrs, label=label, fmt='o', fillstyle='none', capsize=4, elinewidth=1, **kwargs) return
#%% style cycling # printing default colors default_colors = matplotlib.colors.cnames.keys() #print(f"Colors: {default_colors}") # printing default linestyles default_lines = matplotlib.lines.lineStyles.keys() #print(f"Lines: {default_lines}") # printing default marker styles default_markers = matplotlib.markers.MarkerStyle.markers.keys() #print(f"Markers: {default_markers}") # custom list of linestyles (excluding blank line styles) lines = ["-","--","-.",":"] linecycler = cycle(lines) #plt.figure() #for i in range(10): # x = range(i,i+10) # plt.plot(range(10),x,next(linecycler)) #plt.show()