Merge pull request #77 from cokelaer/add_python39

Fixing deprecated function of Scipy.

.github/workflows/main.yml

@@ -13,7 +13,8 @@ jobs:
     strategy:
       max-parallel: 5
       matrix:
-        python: [3.6, 3.7, 3.8]
+        python: [3.7, 3.8,3.9]
+      fail-fast: false
 
     steps:
     - uses: actions/checkout@v2
@@ -23,17 +24,12 @@ jobs:
         python-version: ${{ matrix.python }}
     - name: Install the package itself
       run: |
-          pip install .
-          
+          pip install .[testing]
     - name: Test with pytest
       run: |
-        pip install easydev
-        pip install pytest
-        pip install pytest-cov
-        pip install coverage
         pytest --cov-report term --cov=spectrum
 
-    - name: coveralls            
+    - name: coveralls
       run: |
         pip install coveralls
         coveralls --service=github

README.rst

@@ -70,6 +70,20 @@ Contributions
 
 Please see `github <http://github.com/cokelaer/spectrum>`_ for any issues/bugs/comments/contributions.
 
+Changelog (summary)
+===================
+
+========== ==========================================================
+release    description
+========== ==========================================================
+0.8.1      * move CI to github actions
+           * include python 3.9 support
+           * include PR from tikuma-lshhsc contributor to speedup 
+             eigenfre module
+           * fix deprecated warnings
+========== ==========================================================
+
+
 
 Some notebooks (external contributions)
 -------------------------------------------

doc/ChangeLog.rst

@@ -4,6 +4,12 @@ ChangeLog Summary
 Version 0.8 (2020) 
 ------------------
 
+* 0.8.1: Jul 2021
+
+   * move CI to github actions
+   * include PR from tikuma-lshhsc contributor to speedup eigenfre module
+   * fix deprecated warnings
+
 * 0.8.0: Nov 2020
 
    * Fixed documentation related to https://github.com/cokelaer/spectrum/issues/57

requirements.txt

@@ -1,3 +1,4 @@
+easydev
 numpy
 scipy
 matplotlib

setup.cfg

@@ -6,10 +6,10 @@ upload_dir=doc/build/html/
 [upload_sphinx]
 upload-dir = doc/build/html
 
-[aliases]
-test=pytest
 
-[tool:pytest]
+
+
+#[tool:pytest]
 # do not use --cov because it interfers with travis command
-addopts= --durations=10 --verbose --cov spectrum --cov-report term-missing
+#addopts= --durations=10 --verbose --cov spectrum --cov-report term-missing
 

setup.py

@@ -7,7 +7,7 @@
 
 _MAJOR               = 0
 _MINOR               = 8
-_MICRO               = 0
+_MICRO               = 1
 version              = '%d.%d.%d' % (_MAJOR, _MINOR, _MICRO)
 release              = '%d.%d' % (_MAJOR, _MINOR)
 
@@ -35,10 +35,23 @@
     # Dependencies
     install_requires=open("requirements.txt").read(),
     extras_require={
-        'plot': ['matplotlib']
+        'plot': ['matplotlib'],
+        "testing": [
+            "pytest",
+            "pytest-cov",
+            "pytest-xdist",
+            "pytest-mock",
+            "pytest-timeout",
+            "pytest-runner",
+            "coveralls",
+        ],
+        "doc": [
+            'sphinx',
+            'sphinx_rtd_theme'
+        ]
+
     },
-    # specific packages for testing
-    tests_require = open('requirements-dev.txt').read().split(),
+
 
     package_data = {
         'spectrum.data' : ['*'],

src/spectrum/mtm.py

@@ -324,12 +324,11 @@ def dpss(N, NW=None, k=None):
     if k is None:
         k = min(round(2*NW),N)
         k = int(max(k,1))
-    from numpy import dot, zeros, arange, sqrt
     mtspeclib.multitap.restype = None
 
-    lam = zeros(k, dtype=float)
-    tapers = zeros(k*N, dtype=float)
-    tapsum = zeros(k, dtype=float)
+    lam = np.zeros(k, dtype=float)
+    tapers = np.zeros(k*N, dtype=float)
+    tapsum = np.zeros(k, dtype=float)
 
     res = mtspeclib.multitap(
         c_int(N),
@@ -341,7 +340,7 @@ def dpss(N, NW=None, k=None):
         )
 
     # normalisation by sqtr(N). It is required to have normalised windows
-    tapers = tapers.reshape(k,N).transpose() / sqrt(N)
+    tapers = tapers.reshape(k,N).transpose() / np.sqrt(N)
 
     for i in range(k):
         # By convention (Percival and Walden, 1993 pg 379)
@@ -362,11 +361,11 @@ def dpss(N, NW=None, k=None):
 
     # The values returned in lam are not exacly the same as in the following methods.
     acvs = _autocov(tapers.transpose(), debias=False) * N
-    nidx = arange(N)
+    nidx = np.arange(N)
     W = float(NW)/N
     r = 4*W*np.sinc(2*W*nidx)
     r[0] = 2*W
-    eigvals = dot(acvs, r)
+    eigvals = np.dot(acvs, r)
 
     #return (tapers, lam)
     return [tapers, eigvals]
@@ -540,8 +539,13 @@ def _fftconvolve(in1, in2, mode="full", axis=None):
     """
     #Locally import stuff only required for this:
     from scipy.fftpack import fftn, fft, ifftn, ifft
-    from scipy.signal.signaltools import _centered
     from numpy import array, product
+    try:
+        from scipy.signal._signaltools import _centered
+    except ModuleNotFoundError:
+        from scipy.signal.signaltools import _centered
+
+
 
 
     s1 = array(in1.shape)