Merge branch 'develop' into documentation

tests/integrate_test.py

@@ -0,0 +1,51 @@
+import numpy as np
+import autograd.numpy as anp
+import pyerrors as pe
+
+
+def test_integration():
+    def f(p, x):
+        return p[0] * x + p[1] * x**2 - p[2] / x
+
+    def F(p, x):
+        return p[0] * x**2 / 2. + p[1] * x**3 / 3. - anp.log(x) * p[2]
+
+    def check_ana_vs_int(p, l, u, **kwargs):
+        numint_full = pe.integrate.quad(f, p, l, u, **kwargs)
+        numint = numint_full[0]
+
+        anaint = F(p, u) - F(p, l)
+        diff = (numint - anaint)
+
+        if isinstance(numint, pe.Obs):
+            numint.gm()
+            anaint.gm()
+
+            assert(diff.is_zero())
+        else:
+            assert(np.isclose(0, diff))
+
+    pobs = np.array([pe.cov_Obs(1., .1**2, '0'), pe.cov_Obs(2., .2**2, '1'), pe.cov_Obs(2.2, .17**2, '2')])
+    lobs = pe.cov_Obs(.123, .012**2, 'l')
+    uobs = pe.cov_Obs(1., .05**2, 'u')
+
+    check_ana_vs_int(pobs, lobs, uobs)
+    check_ana_vs_int(pobs, lobs.value, uobs)
+    check_ana_vs_int(pobs, lobs, uobs.value)
+    check_ana_vs_int(pobs, lobs.value, uobs.value)
+    for i in range(len(pobs)):
+        p = [pi for pi in pobs]
+        p[i] = pobs[i].value
+        check_ana_vs_int(p, lobs, uobs)
+
+    check_ana_vs_int([pi.value for pi in pobs], lobs, uobs)
+    check_ana_vs_int([pi.value for pi in pobs], lobs.value, uobs.value)
+
+    check_ana_vs_int(pobs, lobs, uobs, epsabs=1.e-9, epsrel=1.236e-10, limit=100)
+    assert(len(pe.integrate.quad(f, pobs, lobs, uobs, full_output=True)) > 2)
+
+    r1, _ = pe.integrate.quad(F, pobs, 1, 0.1)
+    r2, _ = pe.integrate.quad(F, pobs, 0.1, 1)
+    assert r1 == -r2
+    iamzero, _ = pe.integrate.quad(F, pobs, 1, 1)
+    assert iamzero == 0

tests/linalg_test.py

@@ -14,9 +14,9 @@ def get_real_matrix(dimension):
         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):
@@ -109,7 +109,6 @@ def test_einsum():
         assert np.all([o.imag.is_zero_within_error(0.001) for o in arr])
         assert np.all([o.imag.dvalue < 0.001 for o in arr])
 
-
     tt = [get_real_matrix(4), get_real_matrix(3)]
     q = np.tensordot(tt[0], tt[1], 0)
     c1 = tt[1] @ q
@@ -355,3 +354,4 @@ def test_complex_matrix_real_entries():
     my_mat[0, 1] = 4
     my_mat[2, 0] = pe.Obs([np.random.normal(1.0, 0.1, 100)], ['t'])
     assert np.all((my_mat @ pe.linalg.inv(my_mat) - np.identity(4)) == 0)
+