V: 0.35.dev0; require Python 3.8

.travis.yml

@@ -5,16 +5,16 @@ env:
 matrix:
   include:
     - os: osx  # https://github.com/travis-ci/travis-ci/issues/2312
-      python: 3.7
+      python: 3.8
       sudo: false
       env: CONDA_OS="MacOSX" KMP_DUPLICATE_LIB_OK=TRUE CC=g++ CXX=g++
     - os: linux
-      python: 3.7
+      python: 3.8
       sudo: false
       env: CONDA_OS="Linux"
       addons: {apt: {packages: [libwebkitgtk-dev]}}
     - os: linux
-      python: 3.8
+      python: 3.9
       sudo: false
       env: CONDA_OS="Linux"
       addons: {apt: {packages: [libwebkitgtk-dev]}}

eelbrain/__init__.py

@@ -40,4 +40,4 @@
 from .fmtxt import Report
 
 
-__version__ = '0.34.dev0'
+__version__ = '0.35.dev0'

eelbrain/_data_obj.py

@@ -100,7 +100,7 @@
 from copy import copy, deepcopy
 import fnmatch
 from functools import partial
-from itertools import chain, product, repeat, zip_longest
+from itertools import chain, combinations, product, repeat, zip_longest
 from keyword import iskeyword
 from math import ceil, floor, log
 from numbers import Integral, Number
@@ -7364,11 +7364,11 @@ def head(self, n=10):
         return self.as_table(cases=n)
 
     # checking model properties
-    def check(self, v=True):
+    def check(self):
         "Shortcut to check linear independence and orthogonality"
-        return self.lin_indep(v) + self.orthogonal(v)
+        return self.lin_indep() + self.orthogonal()
 
-    def lin_indep(self, v=True):
+    def lin_indep(self):
         "Check the Model for linear independence of its factors"
         msg = []
         ne = len(self.effects)
@@ -7379,31 +7379,21 @@ def lin_indep(self, v=True):
                 e2 = self.effects[j]
                 x = np.hstack((codes[i], codes[j]))
                 if rank(x) < x.shape[1]:
-                    if v:
-                        errtxt = "Linear Dependence Warning: {0} and {1}"
-                        msg.append(errtxt.format(e1.name, e2.name))
+                    msg.append(f"Linear Dependence Warning: {e1.name} and {e2.name}")
         return msg
 
-    def orthogonal(self, v=True):
+    def orthogonal(self):
         "Check the Model for orthogonality of its factors"
         msg = []
         ne = len(self.effects)
         codes = [e.as_effects for e in self.effects]
-        for i in range(ne):
-            for j in range(i + 1, ne):
-                ok = True
-                e1 = self.effects[i]
-                e2 = self.effects[j]
-                e1e = codes[i]
-                e2e = codes[j]
-                for i1 in range(e1.df):
-                    for i2 in range(e2.df):
-                        dotp = np.dot(e1e[:, i1], e2e[:, i2])
-                        if dotp != 0:
-                            ok = False
-#                            allok = False
-                if v and (not ok):
+        for i, j in combinations(range(ne), 2):
+            e1 = self.effects[i]
+            e2 = self.effects[j]
+            for i1, i2 in product(range(e1.df), range(e2.df)):
+                if np.dot(codes[i][:, i1], codes[j][:, i2]) != 0:
                     msg.append(f"Not orthogonal: {e1.name} and {e2.name}")
+                    break
         return msg
 
     def _parametrize(self, method='effect'):

eelbrain/_io/tests/test_pickle.py

@@ -1,14 +1,12 @@
 # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
 from eelbrain import datasets, load
-from eelbrain._utils import IS_OSX
 from eelbrain.testing import assert_dataobj_equal, file_path
 
 
 def test_pickle():
     ds = datasets.get_uts()
 
-    decimal = None if IS_OSX else 15
     ds_2 = load.unpickle(file_path('uts-py2.pickle'))
-    assert_dataobj_equal(ds_2, ds, decimal)
+    assert_dataobj_equal(ds_2, ds, 15)
     ds_3 = load.unpickle(file_path('uts-py3.pickle'))
-    assert_dataobj_equal(ds_3, ds, decimal)
+    assert_dataobj_equal(ds_3, ds, 15)

eelbrain/tests/test_ndvar.py

@@ -120,16 +120,14 @@ def test_find_intervals():
 def test_find_peaks():
     scalar = Scalar('scalar', range(9))
     time = UTS(0, .1, 12)
-    v = NDVar(np.zeros((9, 12)), (scalar, time))
+    v = NDVar.zeros((scalar, time))
     wsize = [0, 0, 1, 2, 3, 2, 1, 0, 0]
     for i, s in enumerate(wsize):
         if s:
             v.x[i, 5 - s: 5 + s] += np.hamming(2 * s)
 
     peaks = find_peaks(v)
-    x, y = np.where(peaks.x)
-    assert_array_equal(x, [4])
-    assert_array_equal(y, [5])
+    assert_array_equal(np.where(peaks.x), ([4, 4], [4, 5]))
 
 
 def test_frequency_response():

env-dev.yml

@@ -5,7 +5,7 @@ name: eeldev
 channels:
 - conda-forge
 dependencies:
-- python >= 3.7
+- python >= 3.8
 - pip
 - twine
 - libblas=*=*mkl  # openblas produces incorrect results for ICA in iMac Pro
@@ -14,7 +14,7 @@ dependencies:
 - numpy
 - scipy >= 1.3
 - numba
-- matplotlib-base >= 3, <3.1  # https://github.com/matplotlib/matplotlib/issues/15410
+- matplotlib-base >= 3.3.4  # https://github.com/matplotlib/matplotlib/issues/15410
 - pyarrow
 - pillow
 - psutil
@@ -31,7 +31,7 @@ dependencies:
 - colormath >= 2.1
 - tqdm >= 4.40
 - keyring >= 5
-- wxpython >= 4.0.3
+- wxpython >= 4.0.3, < 4.1  # double install of libraries
 # building
 - setuptools >= 17
 - cython

readthedocs.yml

@@ -2,6 +2,6 @@
 build:
     image: latest
 python:
-   version: 3.7
+   version: 3.8
    pip_install: true
 requirements_file: readthedocs_requirements.txt

setup.py

@@ -69,7 +69,7 @@
     author_email='christianbrodbeck@nyu.edu',
     license='BSD (3-clause)',
     long_description=DESC,
-    python_requires='>=3.7',
+    python_requires='>=3.8',
     setup_requires=[
         "numpy >= 1.11",
         "cython >= 0.21",
@@ -84,8 +84,8 @@
             'tqdm >= 4.8',
         ],
         'full': [
-            'numpy >= 1.8',
-            'scipy >= 0.17',
+            'numpy >= 1.20',
+            'scipy >= 1.3',
             'matplotlib >= 2.1',
         ],
         'plot.brain': [