"""

Template for drawing plots with matplotlib

"""

# if this script generates this error:

# _tkinter.TclError: no display name and no $DISPLAY environment variable

# uncomment these 2 lines

#import matplotlib

#matplotlib.use("Agg")

import matplotlib.pyplot as plt

import numpy as np

# Concepts:

# - pyplot create Figures, figures create Axes.

# - Artist are the actual rendered stuff (rendered on canvas)

# - All plotting functions except `np.array` as input.

x = np.arange(0, 10, 0.2)

y = np.sin(x)

fig, ax = plt.subplots()

ax.plot(x, y)

plt.show()

# multiple subplot example.

# I prefer this way: by calling plot function of axis object.

np.random.seed(19680801)

data = np.random.randn(2, 100)

fig, axs = plt.subplots(2, 2, figsize=(5, 5))

axs[0, 0].hist(data[0])

axs[1, 0].scatter(data[0], data[1])

axs[0, 1].plot(data[0], data[1])

axs[1, 1].hist2d(data[0], data[1])

# on a ssh terminal, usually we can't have interactive plots.

# let's save the image to disk.

fig.savefig("test.png")

# another example of using axis.

# one may use Axis.set() to setup Figure title, label, ... etc

x1 = np.linspace(0.0, 5.0)

x2 = np.linspace(0.0, 2.0)

y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)

y2 = np.cos(2 * np.pi * x2)

# Create two subplots sharing y axis

fig, (ax1, ax2) = plt.subplots(2, sharey=True)

ax1.plot(x1, y1, 'ko-')

ax.set(xlabel='', ylabel='Damped oscillation',

title='A tale of 2 subplots')

ax2.plot(x2, y2, 'r.-')

ax2.set(xlabel='time (s)', ylabel='Undamped')

plt.show()

# Usually people from Matlab would expect a state-machine-like enviornment (MATLAB-style)

# and most commands are invoke by pyplot. Plots are added to current figure/axes, by default

# But we don't have to always go with this. There is also a OO interface for plotting.

# a template for a plot function

def my_plotter(ax, data1, data2, param_dict):

"""

A helper function to make a graph

Parameters

----------

ax : Axes

The axes to draw to

data1 : array

The x data

data2 : array

The y data

param_dict : dict

Dictionary of kwargs to pass to ax.plot

Returns

-------

out : list

list of artists added

"""

out = ax.plot(data1, data2, **param_dict)

return out

# which you would then use as:

data1, data2, data3, data4 = np.random.randn(4, 100)

fig, ax = plt.subplots(1, 1)

my_plotter(ax, data1, data2, {'marker': 'x'})

# a list of plotting functions

# ax.annotate - text annotations Annotate ax.texts

# ax.bar - bar charts Rectangle ax.patches

# ax.errorbar - error bar plots Line2D and Rectangle ax.lines and ax.patches

# ax.fill - shared area Polygon ax.patches

# ax.hist - histograms Rectangle ax.patches

# ax.imshow - image data AxesImage ax.images

# ax.legend - axes legends Legend ax.legends

# ax.plot - xy plots Line2D ax.lines

# ax.scatter - scatter charts PolygonCollection ax.collections

# ax.text - text Text ax.texts

# set canvas size

# gcf() gca(): get current figure/axes

# clf() cla(): clear current figure/axes

# MATLAB-style of drawing multiple subplots

# subplot() takes 3 positional arguemnts: nrows, ncols, index

# `index` begins from 1 and increases left to right, top to bottom, as this

# _______

# |_1_|_2_|

# |_3_|_4_|

# |_5_|_6_|

#

def f(t):

return np.exp(-t) * np.cos(2*np.pi*t)

t1 = np.arange(0.0, 5.0, 0.1)

t2 = np.arange(0.0, 5.0, 0.02)

plt.figure()

plt.subplot(211)

plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')

plt.subplot(212)

plt.plot(t2, np.cos(2*np.pi*t2), 'r--')

plt.show()