MAINT: remove optional dependence on SciPy for FFT operations (#791)

Author: agriyakhetarpal

.coveragerc

@@ -7,7 +7,6 @@ omit =
     */pywt/_doc_utils.py*
     */pywt/_pytesttester.py*
     */pywt/_pytest.py*
-    */pywt/data/create_dat.py
     *.pxd
     stringsource
 plugins = Cython.Coverage

.github/workflows/tests.yml

@@ -23,7 +23,6 @@ env:
   CYTHONSPEC: cython
   NUMPY_MIN: numpy==1.23.0
   CYTHON_MIN: cython==3.0.4
-  SCIPY_MIN: scipy==1.9.0
 
 jobs:
   test_pywavelets_linux:
@@ -36,7 +35,6 @@ jobs:
         runs-on: [ubuntu-latest] # Arm runner tested separately, see below
         python-version: ["3.10", "3.13"]
         MINIMUM_REQUIREMENTS: [0]
-        USE_SCIPY: [0]
         USE_SDIST: [0]
         REFGUIDE_CHECK: [1]
         PIP_FLAGS: [""]
@@ -52,8 +50,6 @@ jobs:
             OPTIONS_NAME: "minimum-req"
           - runs-on: ubuntu-latest
             python-version: "3.10"
-            USE_SCIPY: 1
-            OPTIONS_NAME: "with-scipy"
           - runs-on: ubuntu-latest
             python-version: "3.10"
             USE_SDIST: 1
@@ -81,7 +77,6 @@ jobs:
           MINIMUM_REQUIREMENTS: ${{ matrix.MINIMUM_REQUIREMENTS }}
           PIP_FLAGS: ${{ matrix.PIP_FLAGS }}
           USE_SDIST: ${{ matrix.USE_SDIST }}
-          USE_SCIPY: ${{ matrix.USE_SCIPY }}
           REFGUIDE_CHECK: ${{ matrix.REFGUIDE_CHECK }}
           OPTIONS_NAME: ${{ matrix.OPTIONS_NAME }}
         run: |
@@ -97,11 +92,9 @@ jobs:
           if [ "${MINIMUM_REQUIREMENTS}" == "1" ]; then
               pip install ${CYTHON_MIN}
               pip install ${NUMPY_MIN}
-              if [ "${USE_SCIPY}" == "1" ]; then pip install ${SCIPY_MIN}; fi
           else
               pip install ${PIP_FLAGS} cython
               pip install ${PIP_FLAGS} numpy
-              if [ "${USE_SCIPY}" == "1" ]; then pip install ${PIP_FLAGS} scipy; fi
           fi
           pip install ${PIP_FLAGS} matplotlib pytest
 
@@ -147,7 +140,7 @@ jobs:
           popd
 
   test_pywavelets_linux_free_threaded:
-    name: linux-cp313t-with-scipy
+    name: linux-cp313t-default
     runs-on: ubuntu-latest
     strategy:
       # Ensure that a wheel builder finishes even if another fails
@@ -169,7 +162,7 @@ jobs:
           python --version
           pip install --upgrade pip build
           # We need nightly wheels for free-threaded support and latest fixes
-          pip install --pre -i https://pypi.anaconda.org/scientific-python-nightly-wheels/simple cython numpy scipy
+          pip install --pre -i https://pypi.anaconda.org/scientific-python-nightly-wheels/simple cython numpy
           pip install pytest meson-python ninja
           pip install . -v --no-build-isolation
 
@@ -190,7 +183,6 @@ jobs:
       matrix:
         python-version: ["3.10", "3.13"]
         MINIMUM_REQUIREMENTS: [0]
-        USE_SCIPY: [0]
         USE_SDIST: [0]
         REFGUIDE_CHECK: [0]
         PIP_FLAGS: [""]
@@ -219,7 +211,6 @@ jobs:
           MINIMUM_REQUIREMENTS: ${{ matrix.MINIMUM_REQUIREMENTS }}
           PIP_FLAGS: ${{ matrix.PIP_FLAGS }}
           USE_SDIST: ${{ matrix.USE_SDIST }}
-          USE_SCIPY: ${{ matrix.USE_SCIPY }}
           REFGUIDE_CHECK: ${{ matrix.REFGUIDE_CHECK }}
           CC: /usr/bin/clang
           CXX: /usr/bin/clang++
@@ -233,10 +224,8 @@ jobs:
           # Set numpy version first, other packages link against it
           if [ "${MINIMUM_REQUIREMENTS}" == "1" ]; then
               pip install ${CYTHON_MIN} ${NUMPY_MIN}
-              if [ "${USE_SCIPY}" == "1" ]; then pip install ${SCIPY_MIN}; fi
           else
               pip install ${PIP_FLAGS} cython numpy
-              if [ "${USE_SCIPY}" == "1" ]; then pip install ${PIP_FLAGS} scipy; fi
           fi
           pip install ${PIP_FLAGS} matplotlib pytest
 

.github/workflows/wheel_tests_and_release.yml

@@ -49,7 +49,7 @@ jobs:
         if: ${{ matrix.cibw_python }} == "cp313t"
         run: |
           PYPI_URL="https://pypi.anaconda.org/scientific-python-nightly-wheels/simple"
-          CIBW_DEPS="pip install --pre -i $PYPI_URL cython scipy &&\
+          CIBW_DEPS="pip install --pre -i $PYPI_URL cython &&\
                      pip install numpy pytest meson-python ninja"
           NO_BUILD_ISOLATION="pip; args: --no-build-isolation"
           echo "CIBW_BEFORE_BUILD=$CIBW_DEPS" >> "$GITHUB_ENV"
@@ -136,7 +136,7 @@ jobs:
         if: ${{ matrix.cibw_python }} == "cp313t"
         run: |
           PYPI_URL="https://pypi.anaconda.org/scientific-python-nightly-wheels/simple"
-          CIBW_DEPS="pip install --pre -i $PYPI_URL cython scipy &&\
+          CIBW_DEPS="pip install --pre -i $PYPI_URL cython &&\
                      pip install numpy pytest meson-python ninja"
           NO_BUILD_ISOLATION="pip; args: --no-build-isolation"
           echo "CIBW_BEFORE_BUILD=$CIBW_DEPS" >> "$GITHUB_ENV"

README.rst

@@ -67,9 +67,7 @@ Installation
 
 PyWavelets supports `Python`_ >=3.10, and is only dependent on `NumPy`_
 (supported versions are currently ``>= 1.23.0``). To pass all of the tests,
-`Matplotlib`_ is also required. `SciPy`_ is also an optional dependency. When
-present, FFT-based continuous wavelet transforms will use FFTs from SciPy
-rather than NumPy.
+`Matplotlib`_ is also required.
 
 There are binary wheels for Intel Linux, Windows and macOS / OSX on PyPi.  If
 you are on one of these platforms, you should get a binary (precompiled)

doc/source/dev/conduct/code_of_conduct.rst

@@ -165,7 +165,7 @@ Endnotes
 We are thankful to the SciPy developers for creating the code of conduct we
 have adapted here.
 
-- `Scipy Code of Conduct <http://scipy.github.io/devdocs/dev/conduct/code_of_conduct.html>`_
+- `SciPy Code of Conduct <http://scipy.github.io/devdocs/dev/conduct/code_of_conduct.html>`_
 
 The SciPy code of conduct was in turn inspired by the following documents:
 

doc/source/install.rst

@@ -40,8 +40,7 @@ For the requirements needed to build from source are (Python, NumPy and Cython
 minimum versions in particular), see ``pyproject.toml``.
 
 To run all the tests for PyWavelets, you will also need to install the
-Matplotlib_ package. If SciPy_ is available, FFT-based continuous wavelet
-transforms will use the FFT implementation from SciPy instead of NumPy.
+Matplotlib_ package.
 
 .. seealso::  The :ref:`Development guide <dev-index>` section contains more
               information on building and installing from source code.

pyproject.toml

@@ -50,9 +50,6 @@ classifiers = [
     "Topic :: Software Development :: Libraries :: Python Modules"
 ]
 
-[project.optional-dependencies]
-optional = ["scipy>=1.9"]
-
 [project.urls]
 homepage = "https://github.com/PyWavelets/pywt"
 source = "https://github.com/PyWavelets/pywt"

pywt/_cwt.py

@@ -14,24 +14,14 @@
 
 import numpy as np
 
-try:
-    import scipy
-    fftmodule = scipy.fft
-    next_fast_len = fftmodule.next_fast_len
-except ImportError:
-    fftmodule = np.fft
-
-    # provide a fallback so scipy is an optional requirement
-    # note: numpy.fft in numpy 2.0 is as fast as scipy.fft, so could be used
-    # unconditionally once the minimum supported numpy version is >=2.0
-    def next_fast_len(n):
-        """Round up size to the nearest power of two.
-
-        Given a number of samples `n`, returns the next power of two
-        following this number to take advantage of FFT speedup.
-        This fallback is less efficient than `scipy.fftpack.next_fast_len`
-        """
-        return 2**ceil(np.log2(n))
+
+def next_fast_len(n):
+    """Round up size to the nearest power of two.
+
+    Given a number of samples `n`, returns the next power of two
+    following this number to take advantage of FFT speedup.
+    """
+    return 2**ceil(np.log2(n))
 
 
 def cwt(data, scales, wavelet, sampling_period=1., method='conv', axis=-1):
@@ -177,10 +167,10 @@ def cwt(data, scales, wavelet, sampling_period=1., method='conv', axis=-1):
             )
             if size_scale != size_scale0:
                 # Must recompute fft_data when the padding size changes.
-                fft_data = fftmodule.fft(data, size_scale, axis=-1)
+                fft_data = np.fft.fft(data, size_scale, axis=-1)
             size_scale0 = size_scale
-            fft_wav = fftmodule.fft(int_psi_scale, size_scale, axis=-1)
-            conv = fftmodule.ifft(fft_wav * fft_data, axis=-1)
+            fft_wav = np.fft.fft(int_psi_scale, size_scale, axis=-1)
+            conv = np.fft.ifft(fft_wav * fft_data, axis=-1)
             conv = conv[..., :data.shape[-1] + int_psi_scale.size - 1]
 
         coef = - np.sqrt(scale) * np.diff(conv, axis=-1)

pywt/data/create_dat.py renamed to util/create_dat.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 
-"""Helper script for creating image .dat files by numpy.save
+"""Helper script for creating image .dat files by numpy.save.
 
 Usage:
 
@@ -10,7 +10,7 @@
 
     python create_dat.py aero.png aero.dat
 
-Requires Scipy and PIL.
+Requires SciPy and PIL, which need to be installed separately.
 """