matplotlib example plot multiple line graphs (snippet)

Python matplotlib example 'plot multiple line graphs'

Functions in program:

def plot_multiple_likelihood_values(likelihood_arr, x=None, time_axis=0,

Modules used in program:

import importlib
import h5py
import pdb
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib
import os
import sys
import json
import pandas as pd
import numpy as np

python plot multiple line graphs

Python matplotlib example: plot multiple line graphs

import numpy as np
import pandas as pd
import json
import sys
import os
import matplotlib
#matplotlib.use('Agg') 
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import seaborn as sns
import pdb
import h5py
import importlib

# Add root folder to sys path
sys.path.append("../")
sys.path.append("../gridworld/matthew_ja_irl/")

# %pylab inline
# inline doesn't give interactive plots
%matplotlib inline 
# %matplotlib notebook
plt.rcParams['figure.figsize'] = (6.0, 5.0) # set default size of plots
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams['image.cmap'] = 'Blues'

#sns.set_style("white")

# for auto-reloading external modules
# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython
%load_ext autoreload
%autoreload 2

sns.set()



def plot_multiple_likelihood_values(likelihood_arr, x=None, time_axis=0,
                                    save_path='', title='', xlabel='',
                                    ylabel='', colors=['red', 'green', 'blue'],
                                    labels=['red', 'green', 'blue'],
                                    use_max_min_range=True,
                                    legend_fontsize=18, xlabel_fontsize=20,
                                    ylabel_fontsize=20,
                                    figsize=(6,5)):

    assert len(likelihood_arr) <= len(colors), "Missing colors for plot."
    mean_likelihood, std_likelihood = [], []
    min_likelihood, max_likelihood = [], []
    if time_axis >= 0:
        for l in likelihood_arr:
            mean_likelihood.append(np.mean(l, axis=time_axis))
            std_likelihood.append(np.std(l, axis=time_axis))
            min_likelihood.append(np.min(l, axis=time_axis))
            max_likelihood.append(np.max(l, axis=time_axis))
    else:
        assert len(likelihood_arr[0].shape) == 1, \
            "Can only plot vector with -ve time axis"
        mean_likelihood = likelihood_arr
        std_likelihood = [np.zeros(likelihood_arr[0].shape)] * len(likelihood_arr)

    if x is None:
        x = range(len(mean_likelihood[0]))

    fig = plt.figure(figsize=figsize)
    ax = fig.add_subplot(111)
    plots = []
    for i in xrange(len(mean_likelihood)):
        m, s = mean_likelihood[i], std_likelihood[i]
        min_val, max_val = min_likelihood[i], max_likelihood[i]
        c = colors[i]
        p, = ax.plot(x, m, 'k', color=c, label=labels[i])
        if use_max_min_range:
            ax.fill_between(x, min_val, max_val,
                             alpha=0.2, edgecolor=c, facecolor=c,                         
                             linewidth=4, linestyle='dashdot', antialiased=True)
        else:
            ax.fill_between(x, m - s, m + s,
                             alpha=0.2, edgecolor=c, facecolor=c,                         
                             linewidth=4, linestyle='dashdot', antialiased=True)
        plots.append(p)

    ax.legend(handles=plots, fontsize=legend_fontsize)
    ax.set_title(title)
    ax.set_xlabel(xlabel, fontsize=xlabel_fontsize)
    ax.set_ylabel(ylabel, fontsize=ylabel_fontsize)

    if len(save_path) > 0:
        plt.savefig(save_path, bbox_inches='tight')
    plt.show()

Python links

Learn Python: https://pythonbasics.org/
Python Tutorial: https://pythonprogramminglanguage.com