Fix travis based on new pysap flow and add support to python3.8 (#107)

* Remove unwanted travis installs and add python 3.8 * Version bump and point to right repositories * Adon bump for pypi release * Fix Commit for travis pytest runner * Update codes for circleci * Move clock() call to perf_counter() * Adding extra to queue just in case, and also keeping rtol=1e-5 * Update config.yml * Remove upgrade option as we not moved to latest * Adding caching for faster build * Remove support for n_jobs for ISAP wavelets * Fix PEP8 errors * Minute fix for #102 * add upgrade as clearing cache will take long Co-authored-by: chaithyagr <[email protected]>
CEA-COSMIC · Jul 7, 2020 · b79a5da · b79a5da
1 parent 3bccf77
commit b79a5da
Show file tree

Hide file tree

Showing 9 changed files with 39 additions and 56 deletions.
diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -29,12 +29,7 @@ jobs:
             python3 -m venv venv
             . venv/bin/activate
             pip install --upgrade pip
-            pushd ../
-            git clone https://github.com/CEA-COSMIC/pysap
-            cd pysap
-            python setup.py install
-            echo "export PATH=$PATH:$PWD/build/temp.linux-x86_64-3.6/extern/bin" >> $BASH_ENV
-            popd
+            pip install --upgrade git+https://github.com/cea-cosmic/pysap
             pip install -r doc/requirements.txt
             pip list > doc/state.txt
       - save_cache:

diff --git a/.travis.yml b/.travis.yml
@@ -1,27 +1,22 @@
 sudo: required
 dist: xenial
 language: python
-
+cache: pip
 matrix:
     include:
         - python: 3.5
         - python: 3.6
         - python: 3.7
+        - python: 3.8
           dist: xenial
           sudo: true
 
 before_install:
     - sudo apt-get update
     - sudo updatedb
     - wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
-    - if [ $TRAVIS_PYTHON_VERSION == "3.5" ]; then
-        export CPLUS_INCLUDE_PATH=/opt/python/3.5.6/include/python3.5m;
-      fi
-    - if [ $TRAVIS_PYTHON_VERSION == "3.6" ]; then
-        export CPLUS_INCLUDE_PATH=/opt/python/3.6.3/include/python3.6m;
-      fi
-    - if [ $TRAVIS_PYTHON_VERSION == "3.7" ]; then
-        export CPLUS_INCLUDE_PATH=/opt/python/3.7.1/include/python3.7m;
+    - if [ $TRAVIS_OS_NAME = 'linux' ]; then
+        export CPLUS_INCLUDE_PATH=$(cd /opt/python/3.*/include/python3.*; pwd);
       fi
     - chmod +x miniconda.sh
     - ./miniconda.sh -b -p $HOME/miniconda
@@ -40,28 +35,11 @@ install:
     - ln -s $HOME/.local/share/pysap/pysap-data/pysap-data/* $HOME/.local/share/pysap
     - ls -l $HOME/.local/share/pysap
     - pip install --upgrade pip
-    - pip install matplotlib
-    - pip install coverage nose pytest pytest-cov
-    - pip install coveralls
-    - pip install pycodestyle
-    - pip install pybind11 nibabel pyqt5 pyqtgraph astropy 
+    - pip install coverage nose pytest pytest-cov coveralls pycodestyle
     - pip install git+https://github.com/CEA-COSMIC/ModOpt.git
     - pip install git+https://github.com/AGrigis/pysphinxdoc.git
     - pip install sphinx==2.2.1
-    - pushd ../
-    - git clone https://github.com/CEA-COSMIC/pysap
-    - cd pysap
-    - python setup.py install
-    - if [ $TRAVIS_PYTHON_VERSION == "3.5" ]; then
-        export PATH=$PATH:$PWD/build/temp.linux-x86_64-3.5/extern/bin;
-      fi
-    - if [ $TRAVIS_PYTHON_VERSION == "3.6" ]; then
-        export PATH=$PATH:$PWD/build/temp.linux-x86_64-3.6/extern/bin;
-      fi
-    - if [ $TRAVIS_PYTHON_VERSION == "3.7" ]; then
-        export PATH=$PATH:$PWD/build/temp.linux-x86_64-3.7/extern/bin;
-      fi
-    - popd
+    - pip install git+https://github.com/CEA-COSMIC/pysap.git
     - export PYTHONPATH=$TRAVIS_BUILD_DIR/install:$PYTHONPATH
     - pip install -b $TRAVIS_BUILD_DIR/build -t $TRAVIS_BUILD_DIR/install --no-clean --upgrade .
 

diff --git a/examples/gridsearch_launch.py b/examples/gridsearch_launch.py
@@ -8,7 +8,7 @@
 to carry out grid search. We will search for best regularisation weight
 and the best wavelet for reconstruction.
 For this the search space works on :
-mu          ==> 5 Values on log scale between 1e-8 and 1e-9
+mu          ==> 5 Values on log scale between 1e-8 and 1e-6
 Wavelets    ==> sym8 and sym12
 nb_scale    ==> 3 and 4
 """

diff --git a/mri/info.py b/mri/info.py
@@ -10,7 +10,7 @@
 # Module current version
 version_major = 0
 version_minor = 2
-version_micro = 0
+version_micro = 2
 
 # Expected by setup.py: string of form "X.Y.Z"
 __version__ = "{0}.{1}.{2}".format(version_major, version_minor, version_micro)

diff --git a/mri/operators/linear/wavelet.py b/mri/operators/linear/wavelet.py
@@ -18,11 +18,13 @@
 import pysap
 from pysap.base.utils import flatten
 from pysap.base.utils import unflatten
+from pysap.utils import wavelist
 
 # Third party import
 import joblib
 from joblib import Parallel, delayed
 import numpy as np
+import warnings
 
 
 class WaveletN(OperatorBase):
@@ -66,6 +68,13 @@ def __init__(self, wavelet_name, nb_scale=4, verbose=0, dim=2,
         n_proc = self.n_jobs
         if n_proc < 0:
             n_proc = joblib.cpu_count() + self.n_jobs + 1
+        if n_proc > 0:
+            if wavelet_name in wavelist()['isap-2d'] or \
+                    wavelet_name in wavelist()['isap-3d']:
+                warnings.warn("n_jobs is currently unsupported "
+                              "for ISAP wavelets, setting n_jobs=1")
+                self.n_jobs = 1
+                n_proc = 1
         # Create transform queue for parallel execution
         for i in range(min(n_proc, self.n_coils)):
             self.transform_queue.append(transform_klass(

diff --git a/mri/optimizers/forward_backward.py b/mri/optimizers/forward_backward.py
@@ -63,7 +63,7 @@ def fista(gradient_op, linear_op, prox_op, cost_op,
     metrics: dict
         the requested metrics values during the optimization.
     """
-    start = time.clock()
+    start = time.perf_counter()
 
     # Define the initial primal and dual solutions
     if x_init is None:
@@ -111,7 +111,7 @@ def fista(gradient_op, linear_op, prox_op, cost_op,
     if verbose > 0:
         print("Starting optimization...")
     opt.iterate(max_iter=max_nb_of_iter)
-    end = time.clock()
+    end = time.perf_counter()
     if verbose > 0:
         # cost_op.plot_cost()
         if hasattr(cost_op, "cost"):
@@ -170,7 +170,7 @@ def pogm(gradient_op, linear_op, prox_op, cost_op=None,
     metrics: dict
         the requested metrics values during the optimization.
     """
-    start = time.clock()
+    start = time.perf_counter()
 
     # Define the initial values
     im_shape = (gradient_op.linear_op.n_coils, *gradient_op.fourier_op.shape)
@@ -214,7 +214,7 @@ def pogm(gradient_op, linear_op, prox_op, cost_op=None,
     if verbose > 0:
         print("Starting optimization...")
     opt.iterate(max_iter=max_nb_of_iter)
-    end = time.clock()
+    end = time.perf_counter()
     if verbose > 0:
         # cost_op.plot_cost()
         if hasattr(cost_op, "cost"):

diff --git a/mri/optimizers/primal_dual.py b/mri/optimizers/primal_dual.py
@@ -87,7 +87,7 @@ def condatvu(gradient_op, linear_op, dual_regularizer, cost_op,
         the estimated dual CONDAT-VU solution
     """
     # Check inputs
-    start = time.clock()
+    start = time.perf_counter()
     if std_est_method not in (None, "primal", "dual"):
         raise ValueError(
             "Unrecognize std estimation method '{0}'.".format(std_est_method))
@@ -206,7 +206,7 @@ def condatvu(gradient_op, linear_op, dual_regularizer, cost_op,
         opt.iterate(max_iter=max_nb_of_iter)
 
     # Goodbye message
-    end = time.clock()
+    end = time.perf_counter()
     if verbose > 0:
         if hasattr(cost_op, "cost"):
             print(" - final iteration number: ", cost_op._iteration)

diff --git a/mri/tests/test_wavelet_adjoint.py b/mri/tests/test_wavelet_adjoint.py
@@ -51,7 +51,7 @@ def test_Wavelet2D_ISAP(self):
                 I_p = wavelet_op_adj.adj_op(f)
                 x_d = np.vdot(Img, I_p)
                 x_ad = np.vdot(f_p, f)
-                np.testing.assert_allclose(x_d, x_ad, rtol=1e-6)
+                np.testing.assert_allclose(x_d, x_ad, rtol=1e-5)
         print(" Wavelet2 adjoint test passes")
 
     def test_Wavelet2D_PyWt(self):
@@ -77,7 +77,7 @@ def test_Wavelet2D_PyWt(self):
                 I_p = wavelet_op_adj.adj_op(f)
                 x_d = np.vdot(Img, I_p)
                 x_ad = np.vdot(f_p, f)
-                np.testing.assert_allclose(x_d, x_ad, rtol=1e-6)
+                np.testing.assert_allclose(x_d, x_ad, rtol=1e-5)
         print(" Wavelet2 adjoint test passes")
 
     def test_Wavelet3D_PyWt(self):
@@ -105,7 +105,7 @@ def test_Wavelet3D_PyWt(self):
                 I_p = wavelet_op_adj.adj_op(f)
                 x_d = np.vdot(Img, I_p)
                 x_ad = np.vdot(f_p, f)
-                np.testing.assert_allclose(x_d, x_ad, rtol=1e-6)
+                np.testing.assert_allclose(x_d, x_ad, rtol=1e-5)
         print(" Wavelet3 adjoint test passes")
 
     def test_Wavelet_UD_2D(self):
@@ -128,7 +128,7 @@ def test_Wavelet_UD_2D(self):
                 i_p = wavelet_op.adj_op(f)
                 x_d = np.vdot(img, i_p)
                 x_ad = np.vdot(f_p, f)
-                np.testing.assert_allclose(x_d, x_ad, rtol=1e-6)
+                np.testing.assert_allclose(x_d, x_ad, rtol=1e-5)
         print("Undecimated Wavelet 2D adjoint test passes")
 
 

diff --git a/setup.py b/setup.py
@@ -30,7 +30,7 @@
 Philippe Ciuciu <[email protected]>
 """
 # Write setup
-setup_requires = ["numpy", "cython", "pytest-runner", "scikit-image"]
+setup_requires = ["numpy>=1.16.4", "cython>=0.27.3", "pytest-runner"]
 
 pip_main(['install'] + setup_requires)
 
@@ -42,17 +42,18 @@
     classifiers="CLASSIFIERS",
     author=AUTHOR,
     author_email="XXX",
-    version="0.1.1",
+    version="0.2.2",
     url="https://github.com/CEA-COSMIC/pysap-mri",
     packages=find_packages(),
     setup_requires=setup_requires,
-    install_requires=["scikit-learn",
-                      "progressbar2",
-                      "joblib",
-                      "scipy<=1.3.3",
-                      "psutil",
-                      "pynfft@git+https://github.com/ghisvail/pyNFFT@master"],
-    dependency_links=['https://github.com/ghisvail/pyNFFT/tarball/master#egg=pynfft-1.3.0'],
-    tests_require=['pytest>=5.0.1', 'pytest-cov>=2.7.1', 'pytest-pep8'],
+    install_requires=[
+        "scikit-learn>=0.19.1",
+        "progressbar2>=3.34.3",
+        "joblib",
+        "scipy>=1.3.0",
+        "pynfft2>=1.3.3",
+        "scikit-image",
+    ],
+    tests_require=['pytest>=5.0.1', 'pytest-cov>=2.7.1', 'pytest-pep8', 'pytest-runner'],
     platforms="OS Independent"
 )