TST: rework and add tests in test_timeseries

- subsitute old tests by parametrized test for CrossRecurrencePlot
- add parametrized test for InterSystemRecurrenceNetwork
- testing agains issues pik-copan#128 and pik-copan#145
- add fixture params for fixed recurrence rate mode when pik-copan#188 is solved

tests/test_timeseries/test_timeseries.py

@@ -19,11 +19,12 @@
 Simple tests for the timeseries class.
 """
 
+import pytest
 import numpy as np
 from numpy.testing import assert_array_almost_equal
 
-from pyunicorn.timeseries import CrossRecurrencePlot, VisibilityGraph, \
-    Surrogates
+from pyunicorn.timeseries import CrossRecurrencePlot, \
+    InterSystemRecurrenceNetwork, Surrogates, VisibilityGraph
 from pyunicorn.core.data import Data
 from pyunicorn.core._ext.types import DFIELD
 
@@ -35,7 +36,6 @@
 def create_test_data():
     # Create test time series
     tdata = Data.SmallTestData().observable()
-    n_index, n_times = tdata.shape
     # subtract means form the input data
     tdata -= np.mean(tdata, axis=1)[:, None]
     # normalize the data
@@ -48,42 +48,59 @@ def create_test_data():
 # -----------------------------------------------------------------------------
 
 
-def testCrossRecurrencePlot():
-    tdata = create_test_data()
-    CrossRecurrencePlot(x=tdata, y=tdata, threshold=0.2)
-
-
-def testDistanceMatrix():
-    tdata = create_test_data()
-    crp = CrossRecurrencePlot(x=tdata, y=tdata, threshold=1.0)
-    crp.distance_matrix(tdata.T, tdata.T, metric='manhattan')
-
+@pytest.mark.parametrize("met", ["supremum", "euclidean", "manhattan"])
+@pytest.mark.parametrize(
+    "thresh, rr", [(.2, None)]) # add (None, .2) when #188 solved
+def testCrossRecurrencePlot(thresh, rr, met):
+    # create two instances of the same test dataset
+    tdata1 = create_test_data(); x1 = tdata1[:,0]; y1 = tdata1[:,1]
+    tdata2 = create_test_data(); x2 = tdata2[:,0]; y2 = tdata2[:,1]
+    # create CrossRecurrencePlot for both
+    crp1 = CrossRecurrencePlot(
+            x1, y1, threshold=thresh, recurrence_rate=rr, metric=met)
+    crp2 = CrossRecurrencePlot(
+            x2, y2, threshold=thresh, recurrence_rate=rr, metric=met)
+    # get respective distance matrices
+    dist_1 = crp1.distance_matrix(crp1.x_embedded, crp1.y_embedded, met)
+    dist_2 = crp2.distance_matrix(crp2.x_embedded, crp2.y_embedded, met)
+    # get respective recurrence matrices
+    CR1 = crp1.recurrence_matrix()
+    CR2 = crp2.recurrence_matrix()
+
+    assert np.allclose(dist_1, dist_2, atol=1e-04)
+    assert CR1.shape == CR2.shape
+    assert CR1.shape == (len(x1), len(y1))
+    assert CR1.dtype == CR2.dtype 
+    assert CR1.dtype == np.int8
 
-def testManhattanDistanceMatrix():
-    tdata = create_test_data()
-    n_index, n_times = tdata.shape
-    crp = CrossRecurrencePlot(x=tdata, y=tdata, threshold=1.0)
-    manh_dist_1 = crp.manhattan_distance_matrix(tdata.T, tdata.T)
-    manh_dist_2 = crp.manhattan_distance_matrix(tdata.T, tdata.T)
-    assert np.allclose(manh_dist_1, manh_dist_2, atol=1e-04)
 
-
-def testEuclideanDistanceMatrix():
-    tdata = create_test_data()
-    n_index, n_times = tdata.shape
-    crp = CrossRecurrencePlot(x=tdata, y=tdata, threshold=1.0)
-    eucl_dist_1 = crp.euclidean_distance_matrix(tdata.T, tdata.T)
-    eucl_dist_2 = crp.euclidean_distance_matrix(tdata.T, tdata.T)
-    assert np.allclose(eucl_dist_1, eucl_dist_2, atol=1e-04)
+# -----------------------------------------------------------------------------
+# inter_system_recurrence_network
+# -----------------------------------------------------------------------------
 
 
-def testSupremumDistanceMatrix():
-    tdata = create_test_data()
-    n_index, n_times = tdata.shape
-    crp = CrossRecurrencePlot(x=tdata, y=tdata, threshold=1.0)
-    supr_dist_1 = crp.supremum_distance_matrix(tdata.T, tdata.T)
-    supr_dist_2 = crp.supremum_distance_matrix(tdata.T, tdata.T)
-    assert np.allclose(supr_dist_1, supr_dist_2, atol=1e-04)
+@pytest.mark.parametrize("met", ["supremum", "euclidean", "manhattan"])
+@pytest.mark.parametrize(
+    "thresh, rr", [((.2, .3, .2), None)]
+    ) # add (None, (.2, .3, .2) when #188 solved
+def testInterSystemRecurrenceNetwork(thresh, rr, met):
+    # create two instances of the same test dataset
+    tdata1 = create_test_data(); x1 = tdata1[:,0]; y1 = tdata1[:,1]
+    tdata2 = create_test_data(); x2 = tdata2[:,0]; y2 = tdata2[:,1]
+    # create InterSystemRecurrenceNetwork for both
+    isrn1 = InterSystemRecurrenceNetwork(
+            x1, y1, threshold=thresh, recurrence_rate=rr, metric=met)
+    isrn2 = InterSystemRecurrenceNetwork(
+            x2, y2, threshold=thresh, recurrence_rate=rr, metric=met)
+    # get respective adjacency matrices
+    A1 = isrn1.adjacency
+    A2 = isrn2.adjacency
+
+    assert np.array_equal(A1, A2)
+    assert A1.shape == A2.shape
+    assert A1.shape == (len(x1)*2, len(y1)*2)
+    assert A1.dtype == A2.dtype 
+    assert A1.dtype == np.int16
 
 
 # -----------------------------------------------------------------------------