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numerical operations on numpy arrays
Elementwise operations
Basic operation with scalars:
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Elementwise operations (2)
All arithmetic operates elementwise:
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Elementwise operations (3)
Warning : 2D array multiplication is not matrix multiplication:
Out[1]: array([2, 3, 4, 5])
Out[2]: array([ 0.5, 1. , 1.5, 2. ])
Out[3]: (array([ 2, 4, 8, 16]), array([ 1, 4, 9, 16]))
Out[4]: array([-1., 0., 1., 2.])
Out[5]: array([^ 2.,^ 4.,^ 6.,^ 8.])
Out[6]: array([ 2, 3, 6, 13, 28])
# sum of a scalar import numpy as np a = np.array([1, 2, 3, 4]) a + 1
# division by a scalar a / 2
# exponentiation 2 ****** a, a ****** 2
# difference of 2 arrays b = np.ones(4) + 1 # b = array([2.,2.,2.,2.]) a - b
# multiplication of 2 arrays a ***** b
# a more complex operation j = np.arange(5) 2 ****** (j + 1) - j
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Matrix multiplication:
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Other elementwise operations
Comparisons:
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Other elementwise operations (2)
Logical operations:
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Other elementwise operations (3)
Transcendental functions:
Out[7]: array([[ 1., 1., 1.], [ 1., 1., 1.], [ 1., 1., 1.]])
Out[8]: array([[ 3., 3., 3.], [ 3., 3., 3.], [ 3., 3., 3.]])
Out[9]: array([False, True, False, True], dtype=bool)
Out[10]: array([False, False, True, False], dtype=bool)
Out[11]: array([ True, True, True, False], dtype=bool)
Out[12]: array([ True, False, False, False], dtype=bool)
c = np.ones((3, 3)) c ***** c # NOT matrix multiplication!
c.dot(c)
a = np.array([1, 2, 3, 4]) b = np.array([4, 2, 2, 4]) a == b
a > b
# the truth value of a OR b element-wise a = np.array([1, 1, 0, 0], dtype=bool) b = np.array([1, 0, 1, 0], dtype=bool) np.logical_or(a, b)
# the truth value of a AND b element-wise np.logical_and(a, b)
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Logical operations:
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Can be used for array comparisons:
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Array comparisons: another example
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Sorting data
Sorting along an axis:
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Out[21]: 1
Out[22]: False
Out[23]: True
Out[24]: False
Out[25]: True
Out[26]: True
Out[27]: array([[4, 3, 5], [1, 2, 1]])
x.argmax() # index of maximum
np.all([ True , True , False ])
np.any([ True , True , False ])
a = np.zeros((100, 100)) np.any(a! = 0)
np.all(a == a)
a = np.array([1, 2, 3, 2]) b = np.array([2, 2, 3, 2]) c = np.array([6, 4, 4, 5]) ((a < = b) & (b < = c)).all()
a = np.array([[4, 3, 5], [1, 2, 1]]) a
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Out[28]: array([[3, 4, 5], [1, 1, 2]])
# Sort inplace a.sort(axis=1) a
