automatic import of python-csaps

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+/csaps-1.1.0.tar.gz
diff --git a/python-csaps.spec b/python-csaps.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-csaps
+Version:	1.1.0
+Release:	1
+Summary:	Cubic spline approximation (smoothing)
+License:	MIT
+URL:		https://github.com/espdev/csaps
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/f3/de/ef40ae9b0485b36c0128d0d0065e065d7dc8fa3c2334a886548dc70e8ad7/csaps-1.1.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+Requires:	python3-sphinx
+Requires:	python3-matplotlib
+Requires:	python3-numpydoc
+Requires:	python3-m2r2
+Requires:	python3-pytest
+Requires:	python3-coverage
+Requires:	python3-pytest-cov
+Requires:	python3-coveralls
+
+%description
+<p align="center">
+  <a href="https://github.com/espdev/csaps"><img src="https://user-images.githubusercontent.com/1299189/76571441-8d97e400-64c8-11ea-8c05-58850f8311a1.png" alt="csaps" width="400" /></a><br>
+</p>
+
+<p align="center">
+  <a href="https://pypi.python.org/pypi/csaps"><img src="https://img.shields.io/pypi/v/csaps.svg" alt="PyPI version" /></a>
+  <a href="https://pypi.python.org/pypi/csaps"><img src="https://img.shields.io/pypi/pyversions/csaps.svg" alt="Supported Python versions" /></a>
+  <a href="https://github.com/espdev/csaps"><img src="https://github.com/espdev/csaps/workflows/main/badge.svg" alt="GitHub Actions (Tests)" /></a>
+  <a href="https://csaps.readthedocs.io/en/latest/?badge=latest"><img src="https://readthedocs.org/projects/csaps/badge/?version=latest" alt="Documentation Status" /></a>
+  <a href="https://coveralls.io/github/espdev/csaps?branch=master"><img src="https://coveralls.io/repos/github/espdev/csaps/badge.svg?branch=master" alt="Coverage Status" /></a>
+  <a href="https://choosealicense.com/licenses/mit/"><img src="https://img.shields.io/pypi/l/csaps.svg" alt="License" /></a>
+</p>
+
+**csaps** is a Python package for univariate, multivariate and n-dimensional grid data approximation using cubic smoothing splines.
+The package can be useful in practical engineering tasks for data approximation and smoothing.
+
+## Installing
+
+Use pip for installing:
+
+```
+pip install -U csaps
+```
+
+The module depends only on NumPy and SciPy. Python 3.6 or above is supported.
+
+## Simple Examples
+
+Here is a couple of examples of smoothing data.
+
+An univariate data smoothing:
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+
+from csaps import csaps
+
+np.random.seed(1234)
+
+x = np.linspace(-5., 5., 25)
+y = np.exp(-(x/2.5)**2) + (np.random.rand(25) - 0.2) * 0.3
+xs = np.linspace(x[0], x[-1], 150)
+
+ys = csaps(x, y, xs, smooth=0.85)
+
+plt.plot(x, y, 'o', xs, ys, '-')
+plt.show()
+```
+
+<p align="center">
+  <img src="https://user-images.githubusercontent.com/1299189/72231304-cd774380-35cb-11ea-821d-d5662cc1eedf.png" alt="univariate" />
+<p/>
+
+A surface data smoothing:
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+
+from csaps import csaps
+
+np.random.seed(1234)
+xdata = [np.linspace(-3, 3, 41), np.linspace(-3.5, 3.5, 31)]
+i, j = np.meshgrid(*xdata, indexing='ij')
+ydata = (3 * (1 - j)**2. * np.exp(-(j**2) - (i + 1)**2)
+         - 10 * (j / 5 - j**3 - i**5) * np.exp(-j**2 - i**2)
+         - 1 / 3 * np.exp(-(j + 1)**2 - i**2))
+ydata = ydata + (np.random.randn(*ydata.shape) * 0.75)
+
+ydata_s = csaps(xdata, ydata, xdata, smooth=0.988)
+
+fig = plt.figure(figsize=(7, 4.5))
+ax = fig.add_subplot(111, projection='3d')
+ax.set_facecolor('none')
+c = [s['color'] for s in plt.rcParams['axes.prop_cycle']]
+ax.plot_wireframe(j, i, ydata, linewidths=0.5, color=c[0], alpha=0.5)
+ax.scatter(j, i, ydata, s=10, c=c[0], alpha=0.5)
+ax.plot_surface(j, i, ydata_s, color=c[1], linewidth=0, alpha=1.0)
+ax.view_init(elev=9., azim=290)
+
+plt.show()
+```
+
+<p align="center">
+  <img src="https://user-images.githubusercontent.com/1299189/72231252-7a9d8c00-35cb-11ea-8890-487b8a7dbd1d.png" alt="surface" />
+<p/>
+
+## Documentation
+
+More examples of usage and the full documentation can be found at https://csaps.readthedocs.io.
+
+## Testing
+
+We use pytest for testing.
+
+```
+cd /path/to/csaps/project/directory
+pip install -e .[tests]
+pytest
+```
+
+## Algorithm and Implementation
+
+**csaps** Python package is inspired by MATLAB [CSAPS](https://www.mathworks.com/help/curvefit/csaps.html) function that is an implementation of 
+Fortran routine SMOOTH from [PGS](http://pages.cs.wisc.edu/~deboor/pgs/) (originally written by Carl de Boor).
+
+Also the algothithm implementation in other languages:
+
+* [csaps-rs](https://github.com/espdev/csaps-rs) Rust ndarray/sprs based implementation
+* [csaps-cpp](https://github.com/espdev/csaps-cpp) C++11 Eigen based implementation (incomplete)
+
+
+## References
+
+C. de Boor, A Practical Guide to Splines, Springer-Verlag, 1978.
+
+## License
+
+[MIT](https://choosealicense.com/licenses/mit/)
+
+# Changelog
+
+## v1.1.0
+
+* Introduced optional `normalizedsmooth` argument to reduce dependence on xdata and weights [#47](https://github.com/espdev/csaps/pull/47)
+* Update numpy and scipy dependency ranges
+
+## v1.0.4 (04.05.2021)
+
+* Bump numpy dependency version
+
+## v1.0.3 (01.01.2021)
+
+* Bump scipy dependency version
+* Bump sphinx dependency version and use m2r2 sphinx extension instead of m2r
+* Add Python 3.9 to classifiers list and to Travis CI
+* Set development status classifier to "5 - Production/Stable"
+* Happy New Year!
+
+## v1.0.2 (19.07.2020)
+
+* Fix using 'nu' argument when n-d grid spline evaluating [#32](https://github.com/espdev/csaps/pull/32)
+
+## v1.0.1 (19.07.2020)
+
+* Fix n-d grid spline evaluating performance regression [#31](https://github.com/espdev/csaps/pull/31)
+
+## v1.0.0 (11.07.2020)
+
+* Use `PPoly` and `NdPPoly` base classes from SciPy interpolate module for `SplinePPForm` and `NdGridSplinePPForm` respectively.
+* Remove deprecated classes `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline`
+* Update the documentation
+
+**Notes**
+
+In this release the spline representation (the array of spline coefficients) has been changed 
+according to `PPoly`/`NdPPoly`. 
+See SciPy [PPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.PPoly.html) 
+and [NdPPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.NdPPoly.html) documentation for details.
+
+
+## v0.11.0 (28.03.2020)
+
+* Internal re-design `SplinePPForm` and `NdGridSplinePPForm` classes [#17](https://github.com/espdev/csaps/issues/17):
+    - Remove `shape` and `axis` properties and reshaping data in these classes
+    - `NdGridSplinePPForm` coefficients array for 1D grid now is 1-d instead of 2-d
+* Refactoring the code and decrease memory consumption
+* Add `overload` type-hints for `csaps` function signatures
+
+## v0.10.1 (19.03.2020)
+
+* Fix call of `numpy.pad` function for numpy <1.17 [#15](https://github.com/espdev/csaps/issues/15)
+
+## v0.10.0 (18.02.2020)
+
+* Significant performance improvements for make/evaluate splines and memory consumption optimization
+* Change format for storing spline coefficients (reshape coeffs array) to improve performance
+* Add shape property to `SplinePPForm`/`NdGridSplinePPForm` and axis property to `SplinePPForm`
+* Fix issues with the smoothing factor in nd-grid case: inverted ordering and unnable to use 0.0 value
+* Update documentation
+
+## v0.9.0 (21.01.2020)
+
+* Drop support of Python 3.5
+* `weights`, `smooth` and `axis` arguments in `csaps` function are keyword-only now
+* `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` classes are deprecated 
+  and will be removed in 1.0.0 version. Use `CubicSmoothingSpline` instead.
+
+## v0.8.0 (13.01.2020)
+
+* Add `csaps` function that can be used as the main API
+* Refactor the internal structure of the package
+* Add the [documentation](https://csaps.readthedocs.io)
+
+**Attention**
+
+This is the last version that supports Python 3.5. 
+The next versions will support Python 3.6 or above.
+
+## v0.7.0 (19.09.2019)
+
+* Add Generic-based type-hints and mypy-compatibility
+
+## v0.6.1 (13.09.2019)
+
+* A slight refactoring and extra data copies removing
+
+## v0.6.0 (12.09.2019)
+
+* Add "axis" parameter for univariate/multivariate cases
+
+## v0.5.0 (10.06.2019)
+
+* Reorganize the project to package-based structure
+* Add the interface class for all smoothing spline classes
+
+## v0.4.2 (07.09.2019)
+
+* FIX: "smooth" value is 0.0 was not used
+
+## v0.4.1 (30.05.2019)
+
+* First PyPI release
+
+
+
+
+%package -n python3-csaps
+Summary:	Cubic spline approximation (smoothing)
+Provides:	python-csaps
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-csaps
+<p align="center">
+  <a href="https://github.com/espdev/csaps"><img src="https://user-images.githubusercontent.com/1299189/76571441-8d97e400-64c8-11ea-8c05-58850f8311a1.png" alt="csaps" width="400" /></a><br>
+</p>
+
+<p align="center">
+  <a href="https://pypi.python.org/pypi/csaps"><img src="https://img.shields.io/pypi/v/csaps.svg" alt="PyPI version" /></a>
+  <a href="https://pypi.python.org/pypi/csaps"><img src="https://img.shields.io/pypi/pyversions/csaps.svg" alt="Supported Python versions" /></a>
+  <a href="https://github.com/espdev/csaps"><img src="https://github.com/espdev/csaps/workflows/main/badge.svg" alt="GitHub Actions (Tests)" /></a>
+  <a href="https://csaps.readthedocs.io/en/latest/?badge=latest"><img src="https://readthedocs.org/projects/csaps/badge/?version=latest" alt="Documentation Status" /></a>
+  <a href="https://coveralls.io/github/espdev/csaps?branch=master"><img src="https://coveralls.io/repos/github/espdev/csaps/badge.svg?branch=master" alt="Coverage Status" /></a>
+  <a href="https://choosealicense.com/licenses/mit/"><img src="https://img.shields.io/pypi/l/csaps.svg" alt="License" /></a>
+</p>
+
+**csaps** is a Python package for univariate, multivariate and n-dimensional grid data approximation using cubic smoothing splines.
+The package can be useful in practical engineering tasks for data approximation and smoothing.
+
+## Installing
+
+Use pip for installing:
+
+```
+pip install -U csaps
+```
+
+The module depends only on NumPy and SciPy. Python 3.6 or above is supported.
+
+## Simple Examples
+
+Here is a couple of examples of smoothing data.
+
+An univariate data smoothing:
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+
+from csaps import csaps
+
+np.random.seed(1234)
+
+x = np.linspace(-5., 5., 25)
+y = np.exp(-(x/2.5)**2) + (np.random.rand(25) - 0.2) * 0.3
+xs = np.linspace(x[0], x[-1], 150)
+
+ys = csaps(x, y, xs, smooth=0.85)
+
+plt.plot(x, y, 'o', xs, ys, '-')
+plt.show()
+```
+
+<p align="center">
+  <img src="https://user-images.githubusercontent.com/1299189/72231304-cd774380-35cb-11ea-821d-d5662cc1eedf.png" alt="univariate" />
+<p/>
+
+A surface data smoothing:
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+
+from csaps import csaps
+
+np.random.seed(1234)
+xdata = [np.linspace(-3, 3, 41), np.linspace(-3.5, 3.5, 31)]
+i, j = np.meshgrid(*xdata, indexing='ij')
+ydata = (3 * (1 - j)**2. * np.exp(-(j**2) - (i + 1)**2)
+         - 10 * (j / 5 - j**3 - i**5) * np.exp(-j**2 - i**2)
+         - 1 / 3 * np.exp(-(j + 1)**2 - i**2))
+ydata = ydata + (np.random.randn(*ydata.shape) * 0.75)
+
+ydata_s = csaps(xdata, ydata, xdata, smooth=0.988)
+
+fig = plt.figure(figsize=(7, 4.5))
+ax = fig.add_subplot(111, projection='3d')
+ax.set_facecolor('none')
+c = [s['color'] for s in plt.rcParams['axes.prop_cycle']]
+ax.plot_wireframe(j, i, ydata, linewidths=0.5, color=c[0], alpha=0.5)
+ax.scatter(j, i, ydata, s=10, c=c[0], alpha=0.5)
+ax.plot_surface(j, i, ydata_s, color=c[1], linewidth=0, alpha=1.0)
+ax.view_init(elev=9., azim=290)
+
+plt.show()
+```
+
+<p align="center">
+  <img src="https://user-images.githubusercontent.com/1299189/72231252-7a9d8c00-35cb-11ea-8890-487b8a7dbd1d.png" alt="surface" />
+<p/>
+
+## Documentation
+
+More examples of usage and the full documentation can be found at https://csaps.readthedocs.io.
+
+## Testing
+
+We use pytest for testing.
+
+```
+cd /path/to/csaps/project/directory
+pip install -e .[tests]
+pytest
+```
+
+## Algorithm and Implementation
+
+**csaps** Python package is inspired by MATLAB [CSAPS](https://www.mathworks.com/help/curvefit/csaps.html) function that is an implementation of 
+Fortran routine SMOOTH from [PGS](http://pages.cs.wisc.edu/~deboor/pgs/) (originally written by Carl de Boor).
+
+Also the algothithm implementation in other languages:
+
+* [csaps-rs](https://github.com/espdev/csaps-rs) Rust ndarray/sprs based implementation
+* [csaps-cpp](https://github.com/espdev/csaps-cpp) C++11 Eigen based implementation (incomplete)
+
+
+## References
+
+C. de Boor, A Practical Guide to Splines, Springer-Verlag, 1978.
+
+## License
+
+[MIT](https://choosealicense.com/licenses/mit/)
+
+# Changelog
+
+## v1.1.0
+
+* Introduced optional `normalizedsmooth` argument to reduce dependence on xdata and weights [#47](https://github.com/espdev/csaps/pull/47)
+* Update numpy and scipy dependency ranges
+
+## v1.0.4 (04.05.2021)
+
+* Bump numpy dependency version
+
+## v1.0.3 (01.01.2021)
+
+* Bump scipy dependency version
+* Bump sphinx dependency version and use m2r2 sphinx extension instead of m2r
+* Add Python 3.9 to classifiers list and to Travis CI
+* Set development status classifier to "5 - Production/Stable"
+* Happy New Year!
+
+## v1.0.2 (19.07.2020)
+
+* Fix using 'nu' argument when n-d grid spline evaluating [#32](https://github.com/espdev/csaps/pull/32)
+
+## v1.0.1 (19.07.2020)
+
+* Fix n-d grid spline evaluating performance regression [#31](https://github.com/espdev/csaps/pull/31)
+
+## v1.0.0 (11.07.2020)
+
+* Use `PPoly` and `NdPPoly` base classes from SciPy interpolate module for `SplinePPForm` and `NdGridSplinePPForm` respectively.
+* Remove deprecated classes `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline`
+* Update the documentation
+
+**Notes**
+
+In this release the spline representation (the array of spline coefficients) has been changed 
+according to `PPoly`/`NdPPoly`. 
+See SciPy [PPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.PPoly.html) 
+and [NdPPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.NdPPoly.html) documentation for details.
+
+
+## v0.11.0 (28.03.2020)
+
+* Internal re-design `SplinePPForm` and `NdGridSplinePPForm` classes [#17](https://github.com/espdev/csaps/issues/17):
+    - Remove `shape` and `axis` properties and reshaping data in these classes
+    - `NdGridSplinePPForm` coefficients array for 1D grid now is 1-d instead of 2-d
+* Refactoring the code and decrease memory consumption
+* Add `overload` type-hints for `csaps` function signatures
+
+## v0.10.1 (19.03.2020)
+
+* Fix call of `numpy.pad` function for numpy <1.17 [#15](https://github.com/espdev/csaps/issues/15)
+
+## v0.10.0 (18.02.2020)
+
+* Significant performance improvements for make/evaluate splines and memory consumption optimization
+* Change format for storing spline coefficients (reshape coeffs array) to improve performance
+* Add shape property to `SplinePPForm`/`NdGridSplinePPForm` and axis property to `SplinePPForm`
+* Fix issues with the smoothing factor in nd-grid case: inverted ordering and unnable to use 0.0 value
+* Update documentation
+
+## v0.9.0 (21.01.2020)
+
+* Drop support of Python 3.5
+* `weights`, `smooth` and `axis` arguments in `csaps` function are keyword-only now
+* `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` classes are deprecated 
+  and will be removed in 1.0.0 version. Use `CubicSmoothingSpline` instead.
+
+## v0.8.0 (13.01.2020)
+
+* Add `csaps` function that can be used as the main API
+* Refactor the internal structure of the package
+* Add the [documentation](https://csaps.readthedocs.io)
+
+**Attention**
+
+This is the last version that supports Python 3.5. 
+The next versions will support Python 3.6 or above.
+
+## v0.7.0 (19.09.2019)
+
+* Add Generic-based type-hints and mypy-compatibility
+
+## v0.6.1 (13.09.2019)
+
+* A slight refactoring and extra data copies removing
+
+## v0.6.0 (12.09.2019)
+
+* Add "axis" parameter for univariate/multivariate cases
+
+## v0.5.0 (10.06.2019)
+
+* Reorganize the project to package-based structure
+* Add the interface class for all smoothing spline classes
+
+## v0.4.2 (07.09.2019)
+
+* FIX: "smooth" value is 0.0 was not used
+
+## v0.4.1 (30.05.2019)
+
+* First PyPI release
+
+
+
+
+%package help
+Summary:	Development documents and examples for csaps
+Provides:	python3-csaps-doc
+%description help
+<p align="center">
+  <a href="https://github.com/espdev/csaps"><img src="https://user-images.githubusercontent.com/1299189/76571441-8d97e400-64c8-11ea-8c05-58850f8311a1.png" alt="csaps" width="400" /></a><br>
+</p>
+
+<p align="center">
+  <a href="https://pypi.python.org/pypi/csaps"><img src="https://img.shields.io/pypi/v/csaps.svg" alt="PyPI version" /></a>
+  <a href="https://pypi.python.org/pypi/csaps"><img src="https://img.shields.io/pypi/pyversions/csaps.svg" alt="Supported Python versions" /></a>
+  <a href="https://github.com/espdev/csaps"><img src="https://github.com/espdev/csaps/workflows/main/badge.svg" alt="GitHub Actions (Tests)" /></a>
+  <a href="https://csaps.readthedocs.io/en/latest/?badge=latest"><img src="https://readthedocs.org/projects/csaps/badge/?version=latest" alt="Documentation Status" /></a>
+  <a href="https://coveralls.io/github/espdev/csaps?branch=master"><img src="https://coveralls.io/repos/github/espdev/csaps/badge.svg?branch=master" alt="Coverage Status" /></a>
+  <a href="https://choosealicense.com/licenses/mit/"><img src="https://img.shields.io/pypi/l/csaps.svg" alt="License" /></a>
+</p>
+
+**csaps** is a Python package for univariate, multivariate and n-dimensional grid data approximation using cubic smoothing splines.
+The package can be useful in practical engineering tasks for data approximation and smoothing.
+
+## Installing
+
+Use pip for installing:
+
+```
+pip install -U csaps
+```
+
+The module depends only on NumPy and SciPy. Python 3.6 or above is supported.
+
+## Simple Examples
+
+Here is a couple of examples of smoothing data.
+
+An univariate data smoothing:
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+
+from csaps import csaps
+
+np.random.seed(1234)
+
+x = np.linspace(-5., 5., 25)
+y = np.exp(-(x/2.5)**2) + (np.random.rand(25) - 0.2) * 0.3
+xs = np.linspace(x[0], x[-1], 150)
+
+ys = csaps(x, y, xs, smooth=0.85)
+
+plt.plot(x, y, 'o', xs, ys, '-')
+plt.show()
+```
+
+<p align="center">
+  <img src="https://user-images.githubusercontent.com/1299189/72231304-cd774380-35cb-11ea-821d-d5662cc1eedf.png" alt="univariate" />
+<p/>
+
+A surface data smoothing:
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+
+from csaps import csaps
+
+np.random.seed(1234)
+xdata = [np.linspace(-3, 3, 41), np.linspace(-3.5, 3.5, 31)]
+i, j = np.meshgrid(*xdata, indexing='ij')
+ydata = (3 * (1 - j)**2. * np.exp(-(j**2) - (i + 1)**2)
+         - 10 * (j / 5 - j**3 - i**5) * np.exp(-j**2 - i**2)
+         - 1 / 3 * np.exp(-(j + 1)**2 - i**2))
+ydata = ydata + (np.random.randn(*ydata.shape) * 0.75)
+
+ydata_s = csaps(xdata, ydata, xdata, smooth=0.988)
+
+fig = plt.figure(figsize=(7, 4.5))
+ax = fig.add_subplot(111, projection='3d')
+ax.set_facecolor('none')
+c = [s['color'] for s in plt.rcParams['axes.prop_cycle']]
+ax.plot_wireframe(j, i, ydata, linewidths=0.5, color=c[0], alpha=0.5)
+ax.scatter(j, i, ydata, s=10, c=c[0], alpha=0.5)
+ax.plot_surface(j, i, ydata_s, color=c[1], linewidth=0, alpha=1.0)
+ax.view_init(elev=9., azim=290)
+
+plt.show()
+```
+
+<p align="center">
+  <img src="https://user-images.githubusercontent.com/1299189/72231252-7a9d8c00-35cb-11ea-8890-487b8a7dbd1d.png" alt="surface" />
+<p/>
+
+## Documentation
+
+More examples of usage and the full documentation can be found at https://csaps.readthedocs.io.
+
+## Testing
+
+We use pytest for testing.
+
+```
+cd /path/to/csaps/project/directory
+pip install -e .[tests]
+pytest
+```
+
+## Algorithm and Implementation
+
+**csaps** Python package is inspired by MATLAB [CSAPS](https://www.mathworks.com/help/curvefit/csaps.html) function that is an implementation of 
+Fortran routine SMOOTH from [PGS](http://pages.cs.wisc.edu/~deboor/pgs/) (originally written by Carl de Boor).
+
+Also the algothithm implementation in other languages:
+
+* [csaps-rs](https://github.com/espdev/csaps-rs) Rust ndarray/sprs based implementation
+* [csaps-cpp](https://github.com/espdev/csaps-cpp) C++11 Eigen based implementation (incomplete)
+
+
+## References
+
+C. de Boor, A Practical Guide to Splines, Springer-Verlag, 1978.
+
+## License
+
+[MIT](https://choosealicense.com/licenses/mit/)
+
+# Changelog
+
+## v1.1.0
+
+* Introduced optional `normalizedsmooth` argument to reduce dependence on xdata and weights [#47](https://github.com/espdev/csaps/pull/47)
+* Update numpy and scipy dependency ranges
+
+## v1.0.4 (04.05.2021)
+
+* Bump numpy dependency version
+
+## v1.0.3 (01.01.2021)
+
+* Bump scipy dependency version
+* Bump sphinx dependency version and use m2r2 sphinx extension instead of m2r
+* Add Python 3.9 to classifiers list and to Travis CI
+* Set development status classifier to "5 - Production/Stable"
+* Happy New Year!
+
+## v1.0.2 (19.07.2020)
+
+* Fix using 'nu' argument when n-d grid spline evaluating [#32](https://github.com/espdev/csaps/pull/32)
+
+## v1.0.1 (19.07.2020)
+
+* Fix n-d grid spline evaluating performance regression [#31](https://github.com/espdev/csaps/pull/31)
+
+## v1.0.0 (11.07.2020)
+
+* Use `PPoly` and `NdPPoly` base classes from SciPy interpolate module for `SplinePPForm` and `NdGridSplinePPForm` respectively.
+* Remove deprecated classes `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline`
+* Update the documentation
+
+**Notes**
+
+In this release the spline representation (the array of spline coefficients) has been changed 
+according to `PPoly`/`NdPPoly`. 
+See SciPy [PPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.PPoly.html) 
+and [NdPPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.NdPPoly.html) documentation for details.
+
+
+## v0.11.0 (28.03.2020)
+
+* Internal re-design `SplinePPForm` and `NdGridSplinePPForm` classes [#17](https://github.com/espdev/csaps/issues/17):
+    - Remove `shape` and `axis` properties and reshaping data in these classes
+    - `NdGridSplinePPForm` coefficients array for 1D grid now is 1-d instead of 2-d
+* Refactoring the code and decrease memory consumption
+* Add `overload` type-hints for `csaps` function signatures
+
+## v0.10.1 (19.03.2020)
+
+* Fix call of `numpy.pad` function for numpy <1.17 [#15](https://github.com/espdev/csaps/issues/15)
+
+## v0.10.0 (18.02.2020)
+
+* Significant performance improvements for make/evaluate splines and memory consumption optimization
+* Change format for storing spline coefficients (reshape coeffs array) to improve performance
+* Add shape property to `SplinePPForm`/`NdGridSplinePPForm` and axis property to `SplinePPForm`
+* Fix issues with the smoothing factor in nd-grid case: inverted ordering and unnable to use 0.0 value
+* Update documentation
+
+## v0.9.0 (21.01.2020)
+
+* Drop support of Python 3.5
+* `weights`, `smooth` and `axis` arguments in `csaps` function are keyword-only now
+* `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` classes are deprecated 
+  and will be removed in 1.0.0 version. Use `CubicSmoothingSpline` instead.
+
+## v0.8.0 (13.01.2020)
+
+* Add `csaps` function that can be used as the main API
+* Refactor the internal structure of the package
+* Add the [documentation](https://csaps.readthedocs.io)
+
+**Attention**
+
+This is the last version that supports Python 3.5. 
+The next versions will support Python 3.6 or above.
+
+## v0.7.0 (19.09.2019)
+
+* Add Generic-based type-hints and mypy-compatibility
+
+## v0.6.1 (13.09.2019)
+
+* A slight refactoring and extra data copies removing
+
+## v0.6.0 (12.09.2019)
+
+* Add "axis" parameter for univariate/multivariate cases
+
+## v0.5.0 (10.06.2019)
+
+* Reorganize the project to package-based structure
+* Add the interface class for all smoothing spline classes
+
+## v0.4.2 (07.09.2019)
+
+* FIX: "smooth" value is 0.0 was not used
+
+## v0.4.1 (30.05.2019)
+
+* First PyPI release
+
+
+
+
+%prep
+%autosetup -n csaps-1.1.0
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-csaps -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..640a722
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+5eca9998a38f84edab8e22c1c24e0d36  csaps-1.1.0.tar.gz