fix(foreground.poisson): fix cumulative_trapezoid call (#60)

* fix(foreground.poisson): fix cumulative_trapezoid call

The first parameter is y (the values to intregrate), the
second, optional, parameter is x, the axis of integration.

Also use the `initial` parameter to prepend a zero the result,
removing the need to pre-initialise the output array.

* tests

.gitignore

@@ -37,3 +37,7 @@ nosetests.xml
 .mr.developer.cfg
 .project
 .pydevproject
+
+#Editor rubble
+*~
+.*.sw*

cora/foreground/poisson.py

@@ -196,8 +196,7 @@ def inhomogeneous_process_approx(t, rate):
     ts = np.linspace(0.0, t, 10000)
     rs = rate(ts)
 
-    cumr = np.zeros_like(ts)
-    cumr[1:] = cumulative_trapezoid(ts, rs)
+    cumr = cumulative_trapezoid(rs, ts, initial=0)
     cumr /= cumr[-1]
 
     # Interpolate to generate the inverse CDF and use this to generate

tests/test_maps.py

@@ -54,6 +54,6 @@ def test_pointsource():
     pstd = pol.std(axis=-1)
     assert (pstd[:, 0] > 3.0).all()
     assert (pstd[:, 0] < 15.0).all()
-    assert (pol.std(axis=-1)[:, 1:3] > 0.01).all()
-    assert (pol.std(axis=-1)[:, 1:3] < 0.05).all()
-    assert (pol.std(axis=-1)[:, 3] == 0.0).all()
+    assert (pstd[:, 1:3] > 0.005).all()
+    assert (pstd[:, 1:3] < 0.015).all()
+    assert (pstd[:, 3] == 0.0).all()

tests/test_poisson.py

@@ -0,0 +1,24 @@
+"""Test caput.foreground.poisson"""
+
+import numpy as np
+
+from cora.foreground.poisson import inhomogeneous_process_approx
+
+
+def test_inhomogeneous_process_approx():
+    """Test inhomogeneous_process_approx"""
+
+    # the most boringest rate function
+    rate = lambda s: 1000 * (5 - s)
+
+    result = inhomogeneous_process_approx(5, rate)
+
+    # Mean should be approximately 1.666
+    mean = result.mean()
+    assert mean > 1.6
+    assert mean < 1.75
+
+    # stdev should be approximately 1.2
+    stdev = result.std()
+    assert stdev > 1.1
+    assert stdev < 1.3