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Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com> |
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README.md |
Piecewise
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* TOC {:toc}Top
Questions to David Rotermund
numpy.piecewise
numpy.piecewise(x, condlist, funclist, *args, **kw)
Evaluate a piecewise-defined function.
Given a set of conditions and corresponding functions, evaluate each function on the input data wherever its condition is true.
import numpy as np
a = np.arange(1, 11)
b = np.piecewise(a, [a < 5, a == 0, a > 5], [-1, 0, 1])
print(a) # -> [ 1 2 3 4 5 6 7 8 9 10]
print(b) # -> [-1 -1 -1 -1 0 1 1 1 1 1]
Instead of values we can use functions (Or you can use lambda functions...):
import numpy as np
def function_a(input):
return input**2
def function_b(input):
return np.sqrt(input)
a = np.arange(1, 11)
b = np.piecewise(a, [a < 5, a == 0, a > 5], [function_a, 0, function_b])
print(a) # -> [ 1 2 3 4 5 6 7 8 9 10]
print(b) # -> [ 1 4 9 16 0 2 2 2 3 3]
However, the results for the sqrt are strange. Here we see a case where the automatic dtype switch to float64 failed. This is why I overzealously mange / define the dtypes.
import numpy as np
def function_a(input):
return input**2
def function_b(input):
return np.sqrt(input)
a = np.arange(1, 11).astype(dtype=np.float32)
b = np.piecewise(a, [a < 5, a == 0, a > 5], [function_a, 0, function_b])
print(a) # -> [ 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.]
print(b) # -> [ 1. 4. 9. 16. 0. 2.45 2.65 2.83 3. 3.16]