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Archive for March 27th, 2020

Matplotlib is a plotting library for python. Matplotlib was originally written by John D Hunter during his post-doctoral research in neurobiology to visualize electrocorticography (ECoG) data of epilepsy patients. Then Michael Droettboom lead the development project after John Hunter passed away in August 2012.
Matplotlib version 2.0.x support python version 2.7 – 3.6.
Starting 2020, Matplotlib does not support python 2 anymore.

Using Matplotlib with python is easy.

I will show you how to visualize a simple graph.
In this tutorial, I use IDLE as python editor.
If you don’t have it, you can install using command below from your Linux Terminal.
$ sudo apt-get install idle

Run the idle.
plot00

From menu, select File>New File to display the Editor.
Type the code below and press F5 to run the code.

import matplotlib.pyplot as plt
x=[1,2,3,4]
y=[5,6,7,8]
plt.plot(x,y)
plt.show()

plot01plot02
You have your first graph with Matplotlib.
It’s easy, right?
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Slicing is accessing parts of array content.

The syntax is:
start:stop:step

x[1:5]      → display 1 until 5 → 1,2,3,4,5
x[5:]        → display all after 5 → 6,7,8,9
x[:6]        → display from beginning until 6 → 1,2,3,4,5,6,7,8,9
x[:]          → display all → 1,2,3,4,5,6,7,8,9
x[1:9:2]  → display between 1 to 9, step 2 → 2,4,6,8
x[-1]        → display last item → 9
x[-2]        → display 2nd item from the last → 8
x[:-3]      → display all except the 3 items. → 1,2,3,4,5,6
x[::-1]     → display all in reversed → 9,8,7,6,5,4,3,2,1
x[2::-1]   → display first 3 items, reversed → 3,2,1
x[:-4:-1]  → display the last 3 items, reversed → 9,8,7
x[-2::-1]  → display all except the 1 item, reversed → 8,7,6,5,4,3,2,1

Open your Linux Terminal and practice it.

$ python3
Python 3.6.9 (default, Nov 7 2019, 10:44:02)
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> x=np.array([1,2,3,4,5,6,7,8,9])
>>> x
array([1, 2, 3, 4, 5, 6, 7, 8, 9])
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In this article, I will show you how to do basic operation in array.

>>> import numpy as np
>>> x=np.array([[1,2,3,4],[5,6,7,8]])
>>> x
array([[1, 2, 3, 4],
[5, 6, 7, 8]])
>>> x.ravel()
array([1, 2, 3, 4, 5, 6, 7, 8])

ravel() function will create all array into 1 demensional array.

>>> x
array([[1, 2, 3, 4],
[5, 6, 7, 8]])

But the operation will not change the original array value.

>>> x.min()
1

Minimum data in the array

>>> x.max()
8

Maximum data in the array

>>> x.mean()
4.5

Average data in the array

>>> x.sum()
36

Total value in the array

>>> x.sum(axis=0)
array([ 6, 8, 10, 12])
>>> x.sum(axis=1)
array([10, 26])

math02

>>> np.sqrt(x)
array([[1. , 1.41421356, 1.73205081, 2. ],
[2.23606798, 2.44948974, 2.64575131, 2.82842712]])

Square root each data value in the array.

>>> y=np.array([[1,1,1,1],[1,1,1,1]])
>>> y
array([[1, 1, 1, 1],
[1, 1, 1, 1]])
>>> x+y
array([[2, 3, 4, 5],
[6, 7, 8, 9]])
>>> x-y
array([[0, 1, 2, 3],
[4, 5, 6, 7]])
>>> x*y
array([[1, 2, 3, 4],
[5, 6, 7, 8]])
>>>

math01

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