Sorted imports and applied black formatting.

Author: ZviBaratz

tests/test_1_smoketest.py

@@ -1,9 +1,9 @@
 """test suite for rtanalysis
 """
-
 import pytest
 from rtanalysis.rtanalysis import RTAnalysis
 
+
 def test_rtanalysis_smoke():
     rta = RTAnalysis()
     assert rta is not None

tests/test_2_fit.py

@@ -3,10 +3,9 @@
 - in this test, we will create a simulated dataset and fit
 it, ensuring that the answers are correct
 """
-
 import numpy as np
-from rtanalysis.rtanalysis import RTAnalysis
 from rtanalysis.generate_testdata import generate_test_df
+from rtanalysis.rtanalysis import RTAnalysis
 
 
 def test_rtanalysis_fit():

tests/test_3_type_fail.py

@@ -2,10 +2,9 @@
 test for rtanalysis
 - in this test, we will ensure that the function raises a ValueError
 """
-
 import pytest
-from rtanalysis.rtanalysis import RTAnalysis
 from rtanalysis.generate_testdata import generate_test_df
+from rtanalysis.rtanalysis import RTAnalysis
 
 
 # This xfail decorator tells pytest to run the test

tests/test_3_type_success.py

@@ -2,10 +2,9 @@
 test for rtanalysis
 - in this test, we will ensure that the function raises a ValueError
 """
-
 import pytest
-from rtanalysis.rtanalysis import RTAnalysis
 from rtanalysis.generate_testdata import generate_test_df
+from rtanalysis.rtanalysis import RTAnalysis
 
 
 def test_dataframe_error_with_raises():

tests/test_4_fixture.py

@@ -4,11 +4,10 @@
 and use it across multiple tests
 - we also create a separate fixture to hold the parameters
 """
-
-import pytest
 import numpy as np
-from rtanalysis.rtanalysis import RTAnalysis
+import pytest
 from rtanalysis.generate_testdata import generate_test_df
+from rtanalysis.rtanalysis import RTAnalysis
 
 
 @pytest.fixture

tests/test_5_parametric.py

@@ -4,11 +4,11 @@
 and make sure that the function properly raises
 and exception is accuracy is zero
 """
-
-import pytest
 import numpy as np
-from rtanalysis.rtanalysis import RTAnalysis
+import pytest
 from rtanalysis.generate_testdata import generate_test_df
+from rtanalysis.rtanalysis import RTAnalysis
+
 
 @pytest.mark.parametrize("meanRT, sdRT, meanAcc",
                          [(1.5, 1.0, 0.9), (1500, 1000, 0.9),
@@ -22,4 +22,4 @@ def test_rtanalysis_parameteric(meanRT, sdRT, meanAcc):
         assert np.allclose(meanAcc, rta.meanacc_)
     else:
         with pytest.raises(ValueError):
-            rta.fit(test_df.rt, test_df.accuracy)
+            rta.fit(test_df.rt, test_df.accuracy)