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[v638][Python] Fix TF1 Pythonization test for NumPy 2.4.0 #20776

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guitargeek merged 2 commits into from
Dec 24, 2025
Merged

[v638][Python] Fix TF1 Pythonization test for NumPy 2.4.0 #20776

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3223c93
[Python] Fix TF1 Pythonization test for NumPy 2.4.0
guitargeek Dec 23, 2025
efed5b4
[Python] Format code in tf_pycallables.py
guitargeek Dec 23, 2025
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54 changes: 24 additions & 30 deletions bindings/pyroot/pythonizations/test/tf_pycallables.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,8 +5,8 @@
Cppyy that creates a C++ wrapper to invoke the Python callable.
"""

import unittest
import math
import unittest

import ROOT

Expand All @@ -23,14 +23,17 @@ class pyf_tf1_callable:
def __call__(self, x, p):
return p[0] * x[0] + p[1]


def pyf_func(x, pars):
return pars[0] * x[0] * x[2] + x[1] * pars[1]


def pyf_tf1_gauss(x, p):
return p[0] * 1.0 / math.sqrt(2.0 * math.pi * p[2]**2) * math.exp(-(x[0] - p[1])**2 / 2.0 / p[2]**2)
return p[0] * 1.0 / math.sqrt(2.0 * math.pi * p[2] ** 2) * math.exp(-((x[0] - p[1]) ** 2) / 2.0 / p[2] ** 2)


def pyf_tf1_coulomb(x, p):
return p[1] * x[0] * x[1] / (p[0]**2) * math.exp(-p[2] / p[0])
return p[1] * x[0] * x[1] / (p[0] ** 2) * math.exp(-p[2] / p[0])


class TF1(unittest.TestCase):
Expand Down Expand Up @@ -73,24 +76,23 @@ def test_callable(self):
for x in [0.0, -1.0, 42.0]:
self.assertEqual(f.Eval(x), pycallable([x], [par1, par2]))


def test_fitgauss(self):
"""
Test fitting a histogram to a Python function
"""
# Gaus function
f = ROOT.TF1("tf1_fitgauss", pyf_tf1_gauss, -4, 4, 3)
f.SetParameter(0, 10.0) # scale
f.SetParameter(1, -1.0) # mean
f.SetParameter(2, 2.0) # standard deviation
f.SetParameter(0, 10.0) # scale
f.SetParameter(1, -1.0) # mean
f.SetParameter(2, 2.0) # standard deviation

# Sample gauss in histogram
h = ROOT.TH1F("h", "test", 100, -4, 4)
h.FillRandom("gaus", 100000)
h.Scale(1.0 / 100000.0 * 100.0 / 8.0) # Normalize as density
h.Scale(1.0 / 100000.0 * 100.0 / 8.0) # Normalize as density

# Fit to histogram and get parameters
h.Fit( f, "0Q" )
h.Fit(f, "0Q")
scale = f.GetParameter(0)
mean = f.GetParameter(1)
std = f.GetParameter(2)
Expand All @@ -108,27 +110,23 @@ def test_evalpar(self):
rtf1_coulomb = ROOT.TF1("my_func", pyf_tf1_coulomb, -10, 10)

# x dataset: 5 pairs of particle charges
x = np.array([
[1.0, 10, 2.0],
[1.5, 10, 2.5],
[2.0, 10, 3.0],
[2.5, 10, 3.5],
[3.0, 10, 4.0]
])

params = np.array([
[1.0], # Distance between charges r
[8.99e9], # Coulomb constant k (in N·m²/C²)
[0.1] # Additional factor for modulation
])
x = np.array([[1.0, 10, 2.0], [1.5, 10, 2.5], [2.0, 10, 3.0], [2.5, 10, 3.5], [3.0, 10, 4.0]])

params = np.array(
[
1.0, # Distance between charges r
8.99e9, # Coulomb constant k (in N·m²/C²)
0.1, # Additional factor for modulation
]
)

# Slice to avoid the dummy column of 10's
res = rtf1_coulomb.EvalPar(x[:, ::2], params)

for i in range(len(x)):
expected_value = pyf_tf1_coulomb(x[i, ::2], params)
self.assertEqual(res[i], expected_value)

def test_evalpar_dynamic(self):
"""
Test the 2D NumPy pythonizations with dynamic TF1 data dimensions
Expand All @@ -139,12 +137,9 @@ def test_evalpar_dynamic(self):
rtf1_func = ROOT.TF1("my_func", pyf_func, -10, 10)

# x dataset with ndims 3
x = np.array([[2., 2, 1],
[1., 2, 3],
[2., 2, 1],
[4., 3, 2]])
x = np.array([[2.0, 2, 1], [1.0, 2, 3], [2.0, 2, 1], [4.0, 3, 2]])

pars = np.array([2., 3.])
pars = np.array([2.0, 3.0])
res = rtf1_func.EvalPar(x, pars)

for i in range(len(x)):
Expand Down Expand Up @@ -204,6 +199,5 @@ def test_params(self):
self.assertEqual(f.Eval(*x), pyf_tf2_params(x, [par1, par2, par3, par4]))


if __name__ == '__main__':
if __name__ == "__main__":
unittest.main()

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