Arithmetics and elementary functions
Simple calculations are very straightforward with NumPy arrays.
Basic arithmetic operations (
+ - * / **) can all be used with arrays. The main
thing to keep in mind is that most operations are done element-wise.
a = numpy.array([1.0, 2.0, 3.0]) b = 2.0 print(a * b) # output: [ 2. 4. 6.] print(a + b) # output: [ 3. 4. 5.] print(a * a) # output: [ 1. 4. 9.]
NumPy provides also a wide range of elementary mathematical functions (sin,
cos, exp, sqrt, log, …) that work with arrays (as well as single values). In
many ways NumPy can be used as a drop-in replacement for the
import numpy, math a = numpy.linspace(-math.pi, math.pi, 8) print(a) # output: # [-3.14159265 -2.24399475 -1.34639685 -0.44879895 0.44879895 1.34639685 # 2.24399475 3.14159265] print(numpy.sin(a)) # output: # [ -1.22464680e-16 -7.81831482e-01 -9.74927912e-01 -4.33883739e-01 # 4.33883739e-01 9.74927912e-01 7.81831482e-01 1.22464680e-16] print(math.sin(a)) Traceback (most recent call last): File "<stdin>", line 1, in ? TypeError: only length-1 arrays can be converted to Python scalars
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