Merge branch 'master' into test-coverage

.travis.yml

@@ -0,0 +1,68 @@
+language: shell
+
+env:
+  global:
+    - CIBW_SKIP="cp27*"
+    - CIBW_BEFORE_BUILD="pip install cython numpy"
+    - TWINE_USERNAME=__token__
+    # TWINE_PASSWORD should be set to an API token in the Travis settings
+  jobs:
+    - CONDA_PYTHON=3.5
+    - CONDA_PYTHON=3.6
+    - CONDA_PYTHON=3.7
+    - CONDA_PYTHON=3.8
+
+os:
+  - linux
+  - windows
+  - osx
+
+stages:
+  - test
+  - name: deploy
+    if: tag IS PRESENT AND repo = sintefmath/Splipy
+
+before_install:
+  - source ./ci/before_install.sh
+
+install:
+  - source ./ci/install.sh
+  - conda install -y python=${CONDA_PYTHON}
+  - pip install -r requirements.txt
+  - pip install twine cibuildwheel==1.1.0
+  - |-
+    if [[ "$TRAVIS_OS_NAME" != "windows" ]]; then
+        pip install opencv-python
+    fi
+  - conda list
+
+script:
+  - python setup.py install
+  - pytest test --benchmark-skip
+
+jobs:
+  include:
+    - stage: deploy
+      name: Deploy source distribution
+      script: python setup.py sdist --formats=gztar
+      after_success: python -m twine upload --skip-existing dist/*.tar.gz
+    - stage: deploy
+      name: Build and deploy Linux wheels
+      services: docker
+      script: python -m cibuildwheel --output-dir wheelhouse
+      after_success: python -m twine upload --skip-existing wheelhouse/*.whl
+    - stage: deploy
+      name: Build and deploy OSX wheels
+      os: osx
+      script: python -m cibuildwheel --output-dir wheelhouse
+      after_success: python -m twine upload --skip-existing wheelhouse/*.whl
+    - stage: deploy
+      name: Build and deploy Windows wheels
+      os: windows
+      script: python -m cibuildwheel --output-dir wheelhouse
+      after_success: python -m twine upload --skip-existing wheelhouse/*.whl
+
+notifications:
+  email:
+    on_success: never
+    on_failure: always

MANIFEST.in

@@ -0,0 +1,2 @@
+global-include *.pyx
+global-include *.pxd

README.rst

@@ -36,7 +36,8 @@ Dependencies
 
 **Required**
 
-This library requires numpy and scipy. E.g. on Ubuntu::
+This library requires numpy and scipy. For building, cython is also
+required. E.g. on Ubuntu::
 
     pip install numpy
     pip install scipy
@@ -124,17 +125,7 @@ number, create a commit and a tag. To push this to github, use::
 
     git push --tags
 
-After that, to create the actual packages, run::
-
-    rm -rf dist
-    python setup.py sdist
-    python setup.py bdist_wheel --universal
-
-to create a source distribution and a wheel. These can then be uploaded where
-they need to be uploaded. The recommended way to do that is using `twine
-<https://pypi.python.org/pypi/twine>`_::
-
-    twine upload dist/* -r <index>
-
-Where `index` is the name of the index in your `~/.pypirc` where you want to
-upload.
+After that, Travis CI should automatically build and deploy the
+packages to PyPi. It would be helpful to monitor the Travis build so
+that errors can be fixed quickly. See the `list of builds
+<https://travis-ci.org/sintefmath/Splipy/builds>`_.

ci/before_install.sh

@@ -0,0 +1,27 @@
+# Set conda path info
+if [[ "$TRAVIS_OS_NAME" != "windows" ]]; then
+    export MINICONDA_PATH=$HOME/miniconda;
+    export MINICONDA_SUB_PATH=$MINICONDA_PATH/bin;
+elif [[ "$TRAVIS_OS_NAME" == "windows" ]]; then
+    export MINICONDA_PATH=$HOME/miniconda;
+    export MINICONDA_PATH_WIN=`cygpath --windows $MINICONDA_PATH`;
+    export MINICONDA_SUB_PATH=$MINICONDA_PATH/Scripts;
+fi;
+export MINICONDA_LIB_BIN_PATH=$MINICONDA_PATH/Library/bin;
+
+# Obtain miniconda installer
+if [[ "$TRAVIS_OS_NAME" != "windows" ]]; then
+    mkdir -p $HOME/download;
+    if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then
+        echo "downloading miniconda.sh for linux";
+        wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O $HOME/download/miniconda.sh;
+    elif  [[ "$TRAVIS_OS_NAME" == "osx" ]]; then
+        echo "downloading miniconda.sh for osx";
+        wget https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O $HOME/download/miniconda.sh;
+    fi;
+fi;
+
+# Install openssl for Windows
+if [[ "$TRAVIS_OS_NAME" == "windows" ]]; then
+    choco install openssl.light;
+fi;

ci/install.sh

@@ -0,0 +1,40 @@
+# Installing miniconda
+if [[ "$TRAVIS_OS_NAME" != "windows" ]]; then
+    echo "installing miniconda for posix";
+    bash $HOME/download/miniconda.sh -b -u -p $MINICONDA_PATH;
+elif  [[ "$TRAVIS_OS_NAME" == "windows" ]]; then
+    echo "folder $MINICONDA_SUB_PATH does not exist"
+    echo "installing miniconda for windows";
+    choco install miniconda3 --params="'/JustMe /AddToPath:1 /D:$MINICONDA_PATH_WIN'";
+fi;
+
+export PATH="$MINICONDA_PATH:$MINICONDA_SUB_PATH:$MINICONDA_LIB_BIN_PATH:$PATH";
+
+# Checking miniconda existance
+echo "checking if folder $MINICONDA_SUB_PATH exists"
+if [[ -d $MINICONDA_SUB_PATH ]]; then
+    echo "folder $MINICONDA_SUB_PATH exists"
+else
+    echo "folder $MINICONDA_SUB_PATH does not exist"
+fi;
+
+source $MINICONDA_PATH/etc/profile.d/conda.sh;
+hash -r;
+echo $TRAVIS_OS_NAME
+echo $CONDA_PYTHON
+python --version
+conda config --set always_yes yes --set changeps1 no;
+conda update -q conda;
+
+# Free channel has Python < 3.7
+conda config --set restore_free_channel true;
+
+# Useful for debugging any issues with conda
+conda info -a
+
+# See if test-environment already available
+echo "create test-environment";
+conda create -n test-environment;
+
+conda activate test-environment
+conda list

requirements.txt

@@ -0,0 +1,8 @@
+Cython==0.29.15
+numpy==1.18.1
+pytest==5.3.5
+scipy==1.4.1
+pytest-benchmark==3.2.3
+h5py==2.10.0
+tqdm==4.41.1
+nutils==4.1

setup.py

@@ -1,7 +1,8 @@
 #!/usr/bin/env python3
 
 from setuptools import setup
-# import numpy as np
+from Cython.Build import cythonize
+import numpy as np
 
 with open('PyPI_text.md') as f:
     long_description = f.read()
@@ -29,7 +30,8 @@
         'FiniteElement': ["nutils>=4.0"],
         'Images':        ["opencv-python>=4.0"],
     },
-    # include_dirs=[np.get_include()],
+    ext_modules=cythonize("splipy/basis_eval.pyx"),
+    include_dirs=[np.get_include()],
     classifiers=[
         'Development Status :: 4 - Beta',
         'Topic :: Multimedia :: Graphics :: 3D Modeling',

splipy/BSplineBasis.py

@@ -5,6 +5,7 @@
 from bisect import bisect_right, bisect_left
 import numpy as np
 import copy
+from splipy import basis_eval
 from scipy.sparse import csr_matrix
 
 __all__ = ['BSplineBasis']
@@ -106,6 +107,34 @@ def greville(self, index=None):
 
     def evaluate(self, t, d=0, from_right=True, sparse=False):
         """  Evaluate all basis functions in a given set of points.
+
+        :param t: The parametric coordinate(s) in which to evaluate
+        :type t: float or [float]
+        :param int d: Number of derivatives to compute
+        :param bool from_right: True if evaluation should be done in the limit
+            from above
+        :param bool sparse: True if computed matrix should be returned as sparse
+        :return: A matrix *N[i,j]* of all basis functions *j* evaluated in all
+            points *i*
+        :rtype: numpy.array
+        """
+        # for single-value input, wrap it into a list so it don't crash on the loop below
+        t = ensure_listlike(t)
+        t = np.array(t, dtype=np.float64)
+        basis_eval.snap(self.knots, t, state.knot_tolerance)
+
+        if self.order <= d: # requesting more derivatives than polymoial degree: return all zeros
+            return np.matrix(np.zeros((len(t), self.num_functions())))
+
+        (data, size) = basis_eval.evaluate(self.knots, self.order, t, self.periodic, state.knot_tolerance, d, from_right)
+
+        N = csr_matrix(data, size)
+        if not sparse:
+            N = N.todense()
+        return N
+
+    def evaluate_old(self, t, d=0, from_right=True, sparse=False):
+        """  Evaluate all basis functions in a given set of points.
         :param t: The parametric coordinate(s) in which to evaluate
         :type t: float or [float]
         :param int d: Number of derivatives to compute
@@ -135,16 +164,14 @@ def evaluate(self, t, d=0, from_right=True, sparse=False):
             for i in range(len(t)):
                 if t[i] < self.start() or t[i] > self.end():
                     t[i] = (t[i] - self.start()) % (self.end() - self.start()) + self.start()
-                if abs(t[i] - self.start()) < state.knot_tolerance and not from_right:
-                    t[i] = self.end()
         for i in range(len(t)):
             right = from_right
             evalT = t[i]
             # Special-case the endpoint, so the user doesn't need to
             if abs(t[i] - self.end()) < state.knot_tolerance:
                 right = False
             # Skip non-periodic evaluation points outside the domain
-            if t[i] < self.start() or t[i] > self.end() or (abs(t[i]-self.start()) < state.knot_tolerance and not right):
+            if t[i] < self.start() or t[i] > self.end():
                 continue
 
             # mu = index of last non-zero basis function