Matplotlib

Python

Olmo S. Zavala Romero

Numpy ndarray create Slicing 1D Slicing 2D Filtering Arange Random Meshgrid 2D image Where

Matplotlib

Olmo S. Zavala Romero

Center of Atmospheric Sciences, UNAM

September 7, 2016

NumPy basics

Python

Olmo S. Zavala Romero

Numpy ndarray create Slicing 1D Slicing 2D Filtering Arange Random Meshgrid 2D image Where

ndarray, a fast and space-efficient multidimensional array providing vectorized arithmetic operations and sophisticated broadcasting capabilities

Standard mathematical functions for fast operations on entire arrays of data without having to write loops

Tools for reading and writing array data to disk and working with memory-mapped files

Linear algebra, random number generation, and Fourier transform capabilities

McKinney, Wes. Python for Data Analysis. Beijing: OReilly, 2013.

ndarray basics

Python

Olmo S. Zavala Romero

Numpy ndarray create Slicing 1D Slicing 2D Filtering Arange Random Meshgrid 2D image Where

methods

Some useful methods: max, min, mean, nonzero, round, sort, sum, transpose We create arrays using the array method. We can perform +,* vectorized operations. Basic properties: 1 shape size of the matrix 2 dtype type of the matrix

import numpy as np

x = np.array([10,20,30]) y = np.array([1,2,3])

print('x.shape:',x.shape) print('x.dtype:',x.dtype) print('x+10:',x+10) print('x*10:',x*10) print('x+y:',x+y) print('x*y:',x*y)

ndarray basics

Python

Olmo S. Zavala Romero

Numpy ndarray create Slicing 1D Slicing 2D Filtering Arange Random Meshgrid 2D image Where

methods

Some useful methods: max, min, mean, nonzero, round, sort, sum, transpose We create arrays using the array method. We can perform +,* vectorized operations. Basic properties: 1 shape size of the matrix 2 dtype type of the matrix Exercise: function that receives two arrays and computes the dot product.

import numpy as np

x = np.array([10,20,30]) y = np.array([1,2,3])

print('x.shape:',x.shape) print('x.dtype:',x.dtype) print('x+10:',x+10) print('x*10:',x*10) print('x+y:',x+y) print('x*y:',x*y)

How to create ndarrays

Python

Olmo S. Zavala Romero

Numpy ndarray create Slicing 1D Slicing 2D Filtering Arange Random Meshgrid 2D image Where

We create arrays using the array[list] method. Or zero(d1) or zero((d1,d2,. . . )) method. Or ones(d1) or ones((d1,d2,. . . )) method. Or the arange(min,max) method, similar as range in python. Or the eye(rows,cols) method, creates identity matrices.

x = np.array([[10,20,30],[1,2,3]])

print(np.zeros(3),'\n') print(np.ones((2,3)),'\n') print(np.arange(1,3),'\n') print(np.eye(3,3),'\n')

 ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download