using for loop to install conda package

.CondaPkg/env/Lib/site-packages/scipy/sparse/tests/test_extract.py

@@ -0,0 +1,42 @@
+"""test sparse matrix construction functions"""
+
+from numpy.testing import assert_equal
+from scipy.sparse import csr_matrix
+
+import numpy as np
+from scipy.sparse import _extract
+
+
+class TestExtract:
+    def setup_method(self):
+        self.cases = [
+            csr_matrix([[1,2]]),
+            csr_matrix([[1,0]]),
+            csr_matrix([[0,0]]),
+            csr_matrix([[1],[2]]),
+            csr_matrix([[1],[0]]),
+            csr_matrix([[0],[0]]),
+            csr_matrix([[1,2],[3,4]]),
+            csr_matrix([[0,1],[0,0]]),
+            csr_matrix([[0,0],[1,0]]),
+            csr_matrix([[0,0],[0,0]]),
+            csr_matrix([[1,2,0,0,3],[4,5,0,6,7],[0,0,8,9,0]]),
+            csr_matrix([[1,2,0,0,3],[4,5,0,6,7],[0,0,8,9,0]]).T,
+        ]
+
+    def find(self):
+        for A in self.cases:
+            I,J,V = _extract.find(A)
+            assert_equal(A.toarray(), csr_matrix(((I,J),V), shape=A.shape))
+
+    def test_tril(self):
+        for A in self.cases:
+            B = A.toarray()
+            for k in [-3,-2,-1,0,1,2,3]:
+                assert_equal(_extract.tril(A,k=k).toarray(), np.tril(B,k=k))
+
+    def test_triu(self):
+        for A in self.cases:
+            B = A.toarray()
+            for k in [-3,-2,-1,0,1,2,3]:
+                assert_equal(_extract.triu(A,k=k).toarray(), np.triu(B,k=k))