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# Aj St3ph@n web Page : introduction to matplotlib

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## First step : installation of the Matplotlib library

Here i will assume that you have isntalled Pycharm editor. it can be downloaded on the jetbrain webstite :

pycharm select downlaod and then pick the community version which is free

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-1- Before starting you need to have the matplotlib library installed on your python editor. this can be done from the pycharm editor by clicking the folowing menus: pycharm select preference (mac) or file and Setup (windows) ```

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-2- then you need to navigate to the python interpreter and click on the "+" sign at the bottom of the page ```

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-3- This will open a new page in which you can type the name of the librairy you are trying to install. here we want to install the "matplotlib". later you can repeat the same steps to isntall numpy, scikit-image, scikit-lear and panda

## basic structure of a figure ```

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## First plot

The basic following code can be used to plot a basic graph

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case 1 - X axis from 0-50 points

import matplotlib.pyplot as plt
import numpy as np

t = np.linspace(0,2*np.pi,50)
x = np.sin(t)
plt.figure()
plt.plot(x)
plt.show()

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case 2 - X axis from 0 to 2*PI

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0,2*np.pi,50)
y = np.sin(t)
plt.figure()
plt.plot(x,y)
plt.show()
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## 2 plots on the same figure

here are some basics details about how to create simple plots using the library matplotlib. Axis Vs Axes:
The Figure

this code would generate the following figure:

```import numpy as np                             # this is for math calculation
import matplotlib.pyplot as plt                # This is for ploting

x1 = np.linspace(0.0, 6.0)                     # linespace function will create the X axis
x2 = np.linspace(0.0, 3)

y1 = np.cos(3 * np.pi * x1) * np.exp(-x1)      # define equation of each plot
y2 = np.cos(3 * np.pi * x2)

fig, (ax1, ax2) = plt.subplots(2, 1)           # create the plot with 2 parts.
fig.suptitle('a Figure with 2 subplot')

ax1.plot(x1, y1, 'o-')                         # plot the first upper part
ax1.set_ylabel('Viscous polymer')              # set the y axis

ax2.plot(x2, y2, '.-')                         # plot the second lower part
ax2.set_xlabel('time (s)')                     # set both x axis
ax2.set_ylabel('Rigid polymer')                # set the y axis

plt.show()                                     # display the plot

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