Skip to content

fixing a numpy compatibility issue #4

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
htjb merged 4 commits into from
Dec 4, 2025
Merged

fixing a numpy compatibility issue #4

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
12f09d0
fixing a numpy compatibility issue
htjb Dec 4, 2025
a93c0cb
updating workflow to target more modern versions of python
htjb Dec 4, 2025
f94be6e
ugggh something wrong with the old test suit
htjb Dec 4, 2025
b0c1542
fixing numpy bug in tests
htjb Dec 4, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 2 additions & 3 deletions .github/workflows/CI.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -15,8 +15,7 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: [3.6, 3.7, 3.8, 3.9]

python-version: ["3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
Expand All @@ -36,6 +35,6 @@ jobs:
flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
- name: Test with pytest
run: |
coverage run --source=maxsmooth -m py.test
coverage run --source=maxsmooth -m pytest
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v1
2 changes: 1 addition & 1 deletion README.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@ Introduction

:maxsmooth: Derivative Constrained Function Fitting
:Author: Harry Thomas Jones Bevins
:Version: 1.2.1
:Version: 1.2.2
:Homepage: https://github.com/htjb/maxsmooth
:Documentation: https://maxsmooth.readthedocs.io/

Expand Down
21 changes: 11 additions & 10 deletions maxsmooth/derivatives.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
import numpy as np
from scipy.special import lpmv
import math


class derivative_class(object):
Expand Down Expand Up @@ -33,38 +34,38 @@ def mth_order_derivatives(m):
mth_order_derivative_term = (
self.y[self.pivot_point] /
self.x[self.pivot_point]) * \
np.math.factorial(m+i) / \
np.math.factorial(i) * \
math.factorial(m+i) / \
math.factorial(i) * \
self.params[int(m)+i]*(self.x)**i / \
(self.x[self.pivot_point])**(i+1)
mth_order_derivative.append(
mth_order_derivative_term)
if self.model_type == 'polynomial':
mth_order_derivative_term = \
np.math.factorial(m+i) / \
np.math.factorial(i) * \
math.factorial(m+i) / \
math.factorial(i) * \
self.params[int(m)+i]*(self.x)**i
mth_order_derivative.append(
mth_order_derivative_term)
if self.model_type == 'log_polynomial':
mth_order_derivative_term = \
np.math.factorial(m+i) / \
np.math.factorial(i) * \
math.factorial(m+i) / \
math.factorial(i) * \
self.params[int(m) + i] * \
np.log10(self.x/self.x[self.pivot_point])**i
mth_order_derivative.append(
mth_order_derivative_term)
if self.model_type == 'loglog_polynomial':
mth_order_derivative_term = \
np.math.factorial(m+i) / \
np.math.factorial(i) * \
math.factorial(m+i) / \
math.factorial(i) * \
self.params[int(m)+i]*np.log10(self.x)**i
mth_order_derivative.append(
mth_order_derivative_term)
if self.model_type == 'difference_polynomial':
mth_order_derivative_term = \
np.math.factorial(m+i) / \
np.math.factorial(i) * \
math.factorial(m+i) / \
math.factorial(i) * \
self.params[int(m)+i] * \
(self.x-self.x[self.pivot_point])**i
mth_order_derivative.append(
Expand Down
21 changes: 11 additions & 10 deletions maxsmooth/qp.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
import numpy as np
import warnings
from scipy.special import legendre, lpmv
import math

warnings.simplefilter('always', UserWarning)

Expand Down Expand Up @@ -49,26 +50,26 @@ def constraint_prefactors(m):
mth_order_derivative_term = (
self.y[self.pivot_point] /
self.x[self.pivot_point]) \
* np.math.factorial(m + i) \
/ np.math.factorial(i) * \
* math.factorial(m + i) \
/ math.factorial(i) * \
(self.x)**i/(self.x[self.pivot_point])**(i + 1)
derivatives.append(mth_order_derivative_term)
if self.model_type == 'polynomial':
mth_order_derivative_term = np.math.factorial(m+i)\
/ np.math.factorial(i) * (self.x)**i
mth_order_derivative_term = math.factorial(m+i)\
/ math.factorial(i) * (self.x)**i
derivatives.append(mth_order_derivative_term)
if self.model_type == 'log_polynomial':
mth_order_derivative_term = np.math.factorial(m+i)\
/ np.math.factorial(i) * \
mth_order_derivative_term = math.factorial(m+i)\
/ math.factorial(i) * \
np.log10(self.x/self.x[self.pivot_point])**i
derivatives.append(mth_order_derivative_term)
if self.model_type == 'loglog_polynomial':
mth_order_derivative_term = np.math.factorial(m+i)\
/ np.math.factorial(i) * np.log10(self.x)**i
mth_order_derivative_term = math.factorial(m+i)\
/ math.factorial(i) * np.log10(self.x)**i
derivatives.append(mth_order_derivative_term)
if self.model_type == 'difference_polynomial':
mth_order_derivative_term = np.math.factorial(m+i)\
/ np.math.factorial(i) * (
mth_order_derivative_term = math.factorial(m+i)\
/ math.factorial(i) * (
self.x - self.x[self.pivot_point])**i
derivatives.append(mth_order_derivative_term)

Expand Down
2 changes: 1 addition & 1 deletion setup.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ def readme(short=False):

setup(
name='maxsmooth',
version='1.2.1',
version='1.2.2',
description='maxsmooth:Derivative Constrained Function Fitting',
long_description=readme(),
author='Harry T. J. Bevins',
Expand Down
17 changes: 9 additions & 8 deletions tests/test_param_plotter.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import numpy as np
import math
import pytest
import os
import shutil
Expand Down Expand Up @@ -152,8 +153,8 @@ def derivative(m, x, y, N, pivot_point, params, *args):
if i <= m - 1:
mth_order_derivative.append([0]*len(x))
for i in range(N - m):
mth_order_derivative_term = args[1]*np.math.factorial(m+i) / \
np.math.factorial(i) * \
mth_order_derivative_term = args[1]*math.factorial(m+i) / \
math.factorial(i) * \
params[int(m)+i]*(x)**i / \
(args[0])**(i + 1)
mth_order_derivative.append(
Expand All @@ -168,8 +169,8 @@ def derivative_pre(m, x, y, N, pivot_point, *args):
if i <= m - 1:
mth_order_derivative.append([0]*len(x))
for i in range(N - m):
mth_order_derivative_term = args[1]*np.math.factorial(m+i) / \
np.math.factorial(i) * \
mth_order_derivative_term = args[1]*math.factorial(m+i) / \
math.factorial(i) * \
(x)**i / \
(args[0])**(i + 1)
mth_order_derivative.append(
Expand Down Expand Up @@ -234,8 +235,8 @@ def derivative(m, x, y, N, pivot_point, params, *args):
if i <= m - 1:
mth_order_derivative.append([0]*len(x))
for i in range(N - m):
mth_order_derivative_term = np.math.factorial(m+i) / \
np.math.factorial(i) * \
mth_order_derivative_term = math.factorial(m+i) / \
math.factorial(i) * \
params[int(m)+i]*(x)**i
mth_order_derivative.append(
mth_order_derivative_term)
Expand All @@ -249,8 +250,8 @@ def derivative_pre(m, x, y, N, pivot_point, *args):
if i <= m - 1:
mth_order_derivative.append([0]*len(x))
for i in range(N - m):
mth_order_derivative_term = np.math.factorial(m+i) / \
np.math.factorial(i) * \
mth_order_derivative_term = math.factorial(m+i) / \
math.factorial(i) * \
(x)**i
mth_order_derivative.append(
mth_order_derivative_term)
Expand Down
17 changes: 9 additions & 8 deletions tests/test_smooth.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import numpy as np
import math
import pytest
import os
import shutil
Expand Down Expand Up @@ -207,8 +208,8 @@ def derivative(m, x, y, N, pivot_point, params, *args):
if i <= m - 1:
mth_order_derivative.append([0]*len(x))
for i in range(N - m):
mth_order_derivative_term = args[1]*np.math.factorial(m+i) / \
np.math.factorial(i) * \
mth_order_derivative_term = args[1]*math.factorial(m+i) / \
math.factorial(i) * \
params[int(m)+i]*(x)**i / \
(args[0])**(i + 1)
mth_order_derivative.append(
Expand All @@ -224,8 +225,8 @@ def derivative_pre(m, x, y, N, pivot_point, *args):
if i <= m - 1:
mth_order_derivative.append([0]*len(x))
for i in range(N - m):
mth_order_derivative_term = args[1]*np.math.factorial(m+i) / \
np.math.factorial(i) * \
mth_order_derivative_term = args[1]*math.factorial(m+i) / \
math.factorial(i) * \
(x)**i / \
(args[0])**(i + 1)
mth_order_derivative.append(
Expand Down Expand Up @@ -277,8 +278,8 @@ def derivative(m, x, y, N, pivot_point, params, *args):
if i <= m - 1:
mth_order_derivative.append([0]*len(x))
for i in range(N - m):
mth_order_derivative_term = np.math.factorial(m+i) / \
np.math.factorial(i) * \
mth_order_derivative_term = math.factorial(m+i) / \
math.factorial(i) * \
params[int(m)+i]*(x)**i
mth_order_derivative.append(
mth_order_derivative_term)
Expand All @@ -292,8 +293,8 @@ def derivative_pre(m, x, y, N, pivot_point, *args):
if i <= m - 1:
mth_order_derivative.append([0]*len(x))
for i in range(N - m):
mth_order_derivative_term = np.math.factorial(m+i) / \
np.math.factorial(i) * \
mth_order_derivative_term = math.factorial(m+i) / \
math.factorial(i) * \
(x)**i
mth_order_derivative.append(
mth_order_derivative_term)
Expand Down