np.array() |
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np.arange(start, end, step) |
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np.linspace(start, end, count) |
from start to end, equal margin |
np.copy() |
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np.hstack(tuple) |
Stack arrays in sequence horizontally (column wise) |
np.vstack(tuple) |
Stack arrays in sequence vertically (row wise) |
numpy.random.rand(d0,d1,d2,...,dN) |
d is dimention,float values betweent 0 and 1 |
numpy.zeros(shape, dtype=float, order=‘C‘) |
order = ‘C‘ is row-major, F is column-major storage in memory |
numpy.nditer() |
iterator for array |
np.dot() |
dot product |
np.cross() |
cross product |
np.max() |
get maximum value from tensor |
np.amax(arr, axis) |
get maximum value from given axis |
np.sum(arr, axis) |
sum of all elements if using default axis |
np.average(arr, axis,weights) |
average of all elements if using default axis |
np.mean(arr, axis) |
equal to np.average while weights is 1 |
np.std() |
standard deviation |
np.tolist() |
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