feat: alternative matrix multiplication routine jack_matmul implemented

tests/linalg_test.py

@@ -7,6 +7,27 @@ import pytest
 np.random.seed(0)
 
 
+def get_real_matrix(dimension):
+    base_matrix = np.empty((dimension, dimension), dtype=object)
+    for (n, m), entry in np.ndenumerate(base_matrix):
+        exponent_real = np.random.normal(0, 1)
+        exponent_imag = np.random.normal(0, 1)
+        base_matrix[n, m] = pe.Obs([np.random.normal(1.0, 0.1, 100)], ['t'])
+
+
+    return base_matrix
+
+def get_complex_matrix(dimension):
+    base_matrix = np.empty((dimension, dimension), dtype=object)
+    for (n, m), entry in np.ndenumerate(base_matrix):
+        exponent_real = np.random.normal(0, 1)
+        exponent_imag = np.random.normal(0, 1)
+        base_matrix[n, m] = pe.CObs(pe.Obs([np.random.normal(1.0, 0.1, 100)], ['t']),
+                                    pe.Obs([np.random.normal(1.0, 0.1, 100)], ['t']))
+
+    return base_matrix
+
+
 def test_matmul():
     for dim in [4, 8]:
         my_list = []
@@ -29,6 +50,26 @@ def test_matmul():
             assert e.is_zero(), t
 
 
+def test_jack_matmul():
+    tt = get_real_matrix(8)
+    check1 = pe.linalg.jack_matmul(tt, tt) - pe.linalg.matmul(tt, tt)
+    [o.gamma_method() for o in check1.ravel()]
+    assert np.all([o.is_zero_within_error(0.1) for o in check1.ravel()])
+    trace1 = np.trace(check1)
+    trace1.gamma_method()
+    assert trace1.dvalue < 0.001
+
+    tt2 = get_complex_matrix(8)
+    check2 = pe.linalg.jack_matmul(tt2, tt2) - pe.linalg.matmul(tt2, tt2)
+    [o.gamma_method() for o in check2.ravel()]
+    assert np.all([o.real.is_zero_within_error(0.1) for o in check2.ravel()])
+    assert np.all([o.imag.is_zero_within_error(0.1) for o in check2.ravel()])
+    trace2 = np.trace(check2)
+    trace2.gamma_method()
+    assert trace2.real.dvalue < 0.001
+    assert trace2.imag.dvalue < 0.001
+
+
 def test_multi_dot():
     for dim in [4, 8]:
         my_list = []