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import numpy as np def split(arr, cond): return [arr[cond], arr[~cond]] a = np.array([1,3,5,7,2,4,6,8]) print split(a, a<5) a = np.array([[1,2,3],[4,5,6],[7,8,9],[2,4,7]]) print split(a, a[:,0]<3) This produces the following output:
numpy.split(ary, indices_or_sections, axis=0) [source] #. Split an array into multiple sub-arrays as views into ary. Parameters: aryndarray. Array to be divided into sub-arrays. indices_or_sectionsint or 1-D array. If indices_or_sections is an integer, N, the array will be divided into N equal arrays along axis.
21 kwi 2021 · Try numpy.array_split. From the documentation: >>> x = np.arange(8.0) >>> np.array_split(x, 3) [array([ 0., 1., 2.]), array([ 3., 4., 5.]), array([ 6., 7.])] Identical to numpy.split, but won't raise an exception if the groups aren't equal length.
Split array into multiple sub-arrays of equal size. Examples >>> import numpy as np >>> x = np . arange ( 8.0 ) >>> np . array_split ( x , 3 ) [array([0., 1., 2.]), array([3., 4., 5.]), array([6., 7.])]
6 lut 2024 · In NumPy, to split an array (ndarray), the following functions are used: np.split(): For splitting into equal parts or at specific positions; np.array_split(): For splitting as equally as possible; np.vsplit(): For vertical splitting; np.hsplit(): For horizontal splitting; np.dsplit(): For splitting along the depth
22 gru 2023 · This example showcases the application of numpy.split() in dividing a 2D array into equal parts along a specified axis. Similar concepts can be applied to numpy.array_split for uneven splitting. numpy.split ( array, 3, axis=1 ) splits the array into three equal parts along the second axis.
numpy.split #. Split an array into multiple sub-arrays as views into ary. Array to be divided into sub-arrays. If indices_or_sections is an integer, N, the array will be divided into N equal arrays along axis. If such a split is not possible, an error is raised.
