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python Programming Glossary: np.append

Image transformation in OpenCV

http://stackoverflow.com/questions/10364201/image-transformation-in-opencv

destination source grid_x grid_y method 'cubic' map_x np.append ar 1 for ar in grid_z .reshape 150 150 map_y np.append ar 0.. np.append ar 1 for ar in grid_z .reshape 150 150 map_y np.append ar 0 for ar in grid_z .reshape 150 150 map_x_32 map_x.astype..

RAM full in numpy sagemath

http://stackoverflow.com/questions/18317974/ram-full-in-numpy-sagemath

np.array for kkkkk in cant_de_cadenas cantidad_de_cadenas np.append cantidad_de_cadenas kkkkk cantidad_de_cadenas np.transpose cantidad_de_cadenas.. array_y2 array_y1 array_lambdas 1 array_x1 np.append array_x1 b 2 b 2 b 2 b 2 array_y1 np.append array_y1 h 2 h 2.. 1 array_x1 np.append array_x1 b 2 b 2 b 2 b 2 array_y1 np.append array_y1 h 2 h 2 h 2 h 2 array_x2 np.append array_x2 b 2 b 2..

Concatenate Numpy arrays without copying

http://stackoverflow.com/questions/7869095/concatenate-numpy-arrays-without-copying

In Numpy I can concatenate two arrays end to end with np.append or np.concatenate X np.array 1 2 3 Y np.array 1 2 3 4 5 6 Z.. np.concatenate X np.array 1 2 3 Y np.array 1 2 3 4 5 6 Z np.append X Y axis 0 Z array 1 2 3 1 2 3 4 5 6 But these make copies of..

What's the simplest way to extend a numpy array in 2 dimensions?

http://stackoverflow.com/questions/877479/whats-the-simplest-way-to-extend-a-numpy-array-in-2-dimensions

first question. import numpy as np p np.array 1 2 3 4 p np.append p 5 6 0 p np.append p 7 8 9 1 p array 1 2 7 3 4 8 5 6 9 And.. numpy as np p np.array 1 2 3 4 p np.append p 5 6 0 p np.append p 7 8 9 1 p array 1 2 7 3 4 8 5 6 9 And the for the second question.. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n 2 p np.append p n p n 1 0 p np.append p ... n p ... n 1 1 p array 0 1 3 4..

Simple Digit Recognition OCR in OpenCV-Python

http://stackoverflow.com/questions/9413216/simple-digit-recognition-ocr-in-opencv-python

int chr key sample roismall.reshape 1 100 samples np.append samples sample 0 responses np.array responses np.float32 responses..