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| NumPy is a package that defines a multi-dimensional array object and associated fast math functions that operate on it. It also provides simple routines for linear algebra and fft and sophisticated random-number generation. NumPy replaces both Numeric and Numarray. https://numeric.scipy.org | NumPy is a package that defines a multi-dimensional array object and associated fast math functions that operate on it. It also provides simple routines for linear algebra and fft and sophisticated random-number generation. NumPy replaces both Numeric and Numarray. https://www.scipy.org and https://www.numpy.org/ A very complete manual by the principal author of Numpy, Travis Oliphant, is [[https://csc.ucdavis.edu/~chaos/courses/nlp/Software/NumPyBook.pdf|available]] for free (although donations are accepted). Note that the online documentation via docstring is rather complete and not stripped in any way. Further documentation is available from https://docs.scipy.org/doc/ Many examples of numpy usage can be found at https://wiki.scipy.org/Numpy_Example_List '''numpy Example''' {{{ from numpy import * from PIL import Image ar = ones((100,100),float32) ar = ar * 100 for i in range(0,100): ar[i,:] = 100 + (i * 1.5) im = Image.fromarray(ar,"F") }}} |
NumPy is a package that defines a multi-dimensional array object and associated fast math functions that operate on it. It also provides simple routines for linear algebra and fft and sophisticated random-number generation. NumPy replaces both Numeric and Numarray. https://www.scipy.org and https://www.numpy.org/
A very complete manual by the principal author of Numpy, Travis Oliphant, is available for free (although donations are accepted). Note that the online documentation via docstring is rather complete and not stripped in any way. Further documentation is available from https://docs.scipy.org/doc/
Many examples of numpy usage can be found at https://wiki.scipy.org/Numpy_Example_List
numpy Example
from numpy import *
from PIL import Image
ar = ones((100,100),float32)
ar = ar * 100
for i in range(0,100):
ar[i,:] = 100 + (i * 1.5)
im = Image.fromarray(ar,"F")