EBR-43: resolve sonar warnings

dev/Dockerfile

@@ -1,10 +1,10 @@
-FROM continuumio/miniconda3
+FROM continuumio/miniconda3:master
 
 ARG TVB_USER=tvb_user
 ARG USER_HOME=/home/$TVB_USER
 ARG JUPYTER_CONFIG=$USER_HOME/.jupyter
 
-RUN useradd -ms /bin/bash $TVB_USER
+RUN useradd -ms /bin/bash "$TVB_USER"
 WORKDIR $USER_HOME
 
 USER root

dev/notebook_runner.py

@@ -37,7 +37,7 @@ def execute_notebook(in_path, notebook):
     if not os.getenv('CLB_AUTH'):
         os.environ['CLB_AUTH'] = 'abc'
 
-    notebooks = [file for file in os.listdir(in_path) if file[-6:] == ".ipynb"]
+    notebooks = [file for file in os.listdir(in_path) if file.endswith(".ipynb")]
 
     # start as many threads as logical cpus
     with ThreadPool(cpu_count()) as pool:

tvbwidgets/tests/test_drive_widget.py

@@ -104,7 +104,7 @@ def mockk(token):
     assert len(widget.files_list.options) == 1
 
     with pytest.raises(AttributeError):
-        assert widget.get_selected_file_content()
+        widget.get_selected_file_content()
 
 
 def test_storage_widget(mocker):

tvbwidgets/tests/ts/test_data_wrappers.py

@@ -5,6 +5,7 @@
 # (c) 2022-2023, TVB Widgets Team
 #
 
+import math
 import numpy as np
 import pytest
 
@@ -17,7 +18,8 @@
 @pytest.fixture
 def wrapper_np():
     """ Returns an initialized Numpy wrapper with 3 dimensions """
-    numpy_array = np.random.rand(30000, 4, 50)
+    rng = np.random.default_rng()
+    numpy_array = rng.random(size=(30000, 4, 50))
     wrapper_np = WrapperNumpy(numpy_array, 0.01, ch_idx=2)
     return wrapper_np
 
@@ -37,7 +39,7 @@
 
 
 def test_get_sample_rate_np(wrapper_np):
-    assert wrapper_np.get_ts_sample_rate() == 0.01
+    assert math.isclose(wrapper_np.get_ts_sample_rate(), 0.01)
 
 
 def test_build_raw_np(wrapper_np):
@@ -92,7 +94,7 @@
     assert len(ch_names) == len(ch_order) == len(ch_type) == 76
 
     assert wrapper_tvb.displayed_time_points == 3000
-    assert wrapper_tvb.get_ts_period() == 0.75
+    assert math.isclose(wrapper_tvb.get_ts_period(), 0.75)
     assert wrapper_tvb.get_ts_sample_rate() == 4000
 
     raw = wrapper_tvb.build_raw()
@@ -120,7 +122,7 @@
 
 def test_get_ts_period_tvb(wrapper_tvb):
     ts_period = wrapper_tvb.get_ts_period()
-    assert ts_period == 0.75
+    assert math.isclose(ts_period, 0.75)
 
 
 def test_get_ts_sample_rate_tvb(wrapper_tvb):

tvbwidgets/tests/ts/test_mne_widget.py

@@ -5,6 +5,7 @@
 # (c) 2022-2023, TVB Widgets Team
 #
 
+import math
 import numpy as np
 import pytest
 import logging
@@ -43,7 +44,7 @@
 # =========================================== WIDGET CREATION ==========================================================
 def test_get_widget(tsw_tvb_data):
     tsw_tvb_data.get_widget()
-    assert type(tsw_tvb_data) == TimeSeriesWidgetMNE
+    assert isinstance(tsw_tvb_data, TimeSeriesWidgetMNE)
 
 
 def test_create_ts_widget(tsw):
@@ -67,7 +68,7 @@
 
     assert tsw.data == wrapper_tvb
     assert tsw.sample_freq == 4000
-    assert tsw.displayed_period == 0.75
+    assert math.isclose(tsw.displayed_period, 0.75)
     assert len(tsw.ch_names) == len(tsw.ch_order) == len(tsw.ch_types) == 76
     assert tsw.raw.get_data().shape == (76, 4000)
 
@@ -104,7 +105,8 @@
 
 def test_dimensions_selection_update(tsw_tvb_data):
     # simulate unchecking of some checkboxes
-    false_cb_idx = list(np.random.choice(76, size=3, replace=False))
+    rng = np.random.default_rng()
+    false_cb_idx = list(rng.choice(76, size=3, replace=False))
     false_cb_names = [f'sig {x}' for x in false_cb_idx]
     for cb_name in false_cb_names:
         tsw_tvb_data.checkboxes[cb_name].value = False

tvbwidgets/tests/ts/test_plotly_widget.py

@@ -5,6 +5,7 @@
 # (c) 2022-2023, TVB Widgets Team
 #
 
+import math
 import pytest
 
 import ipywidgets as widgets
@@ -44,7 +45,7 @@ def tsw_tvb_data(tsr_4d):
 # =========================================== WIDGET CREATION ==========================================================
 def test_get_widget(tsw_tvb_data):
     tsw_tvb_data.get_widget()
-    assert type(tsw_tvb_data) == TimeSeriesWidgetPlotly
+    assert isinstance(tsw_tvb_data, TimeSeriesWidgetPlotly)
 
 
 def test_create_ts_widget(tsw):
@@ -64,7 +65,7 @@ def test_populate_from_data_wrapper_tvb(tsw, wrapper_tvb):
 
     assert tsw.data == wrapper_tvb
     assert tsw.sample_freq == 4000
-    assert tsw.displayed_period == 0.75
+    assert math.isclose(tsw.displayed_period, 0.75)
     assert len(tsw.ch_names) == 76
     assert tsw.raw.get_data().shape == (76, 4000)
 

tvbwidgets/tests/ts/ts_generator.py

@@ -97,8 +97,9 @@
 
 def _generate_connectivity(no_of_regions):
     labels = np.array(['sig ' + str(i) for i in range(no_of_regions)])
-    conn = connectivity.Connectivity(centres=np.random.rand(no_of_regions, 3),
+    rng = np.random.default_rng()
+    conn = connectivity.Connectivity(centres=rng.random(size=(no_of_regions, 3)),
                                      region_labels=labels,
-                                     weights=np.random.rand(no_of_regions, no_of_regions),
-                                     tract_lengths=np.random.rand(no_of_regions, no_of_regions))
+                                     weights=rng.random(size=(no_of_regions, no_of_regions)),
+                                     tract_lengths=rng.random(size=(no_of_regions, no_of_regions)))
     return conn

tvbwidgets/ui/connectivity_ipy/operations.py

@@ -150,13 +150,13 @@ def __cut_nodes(self, selected=True):
         Create a new connectivity using only the selected nodes
         """
         regions = CONTEXT.connectivity.region_labels
-        selected_regions = [numpy.where(regions == label)[0][0] for label in self.selected_regions]
+        selected_regions = [numpy.nonzero(regions == label)[0][0] for label in self.selected_regions]
         new_conn = self.__cut_connectivity_nodes(selected_regions, selected)
         CONTEXT.connectivity = new_conn
 
     def __cut_edges(self, selected=False):
         regions = CONTEXT.connectivity.region_labels
-        selected_regions = numpy.array([numpy.where(regions == label)[0][0] for label in self.selected_regions])
+        selected_regions = numpy.array([numpy.nonzero(regions == label)[0][0] for label in self.selected_regions])
         new_conn = self.__cut_connectivity_edges(selected_regions, selected)
         CONTEXT.connectivity = new_conn