use pytest

.travis.yml

@@ -2,11 +2,9 @@ language: python
 python:
   - "2.6"
   - "2.7"
-  - "3.2"
-  - "3.3"
   - "3.4"
   - "3.5"
-  - "3.5-dev" # 3.5 development branch
-  - "nightly" # currently points to 3.6-dev
-install: "pip install nose numpy"
-script: nosetests
+  - "3.6"
+  - "nightly"
+install: "pip install pytest numpy"
+script: pytest

test_irr.py

@@ -0,0 +1,74 @@
+import pytest, random, math, numpy, time, functools
+import irr
+
+
+def run_many(case):
+    @functools.wraps(case)
+    def wrapped():
+        for test in range(1000):
+            d, r = case()
+            assert irr.irr(d) == pytest.approx(r)
+    return wrapped
+
+
+@run_many
+def test_simple_bond():
+    r = math.exp(random.gauss(0, 1)) - 1
+    x = random.gauss(0, 1)
+    d = [x / (1 + r), -x]
+    return d, r
+
+
+@run_many
+def test_slightly_longer_bond(n=10):
+    r = math.exp(random.gauss(0, 1)) - 1
+    x = random.gauss(0, 1)
+    d = [x] + [0.0] * (n-2) + [-x * (1+r)**(n-1)]
+    return d, r
+
+
+@run_many
+def test_more_nonzero(n=10):
+    r = math.exp(random.gauss(0, 1)) - 1
+    d = [random.random() for i in range(n-1)]
+    d.append(-sum([x * (1+r)**(n-i-1) for i, x in enumerate(d)]))
+    return d, r
+
+
+def test_performance():
+    us_times = []
+    np_times = []
+    ns = [10, 20, 50, 100]
+    for n in ns:
+        k = 100
+        sums = [0.0, 0.0]
+        for j in range(k):
+            r = math.exp(random.gauss(0, 1.0 / n)) - 1
+            x = random.gauss(0, 1)
+            d = [x] + [0.0] * (n-2) + [-x * (1+r)**(n-1)]
+
+            results = []
+            for i, f in enumerate([irr.irr, numpy.irr]):
+                t0 = time.time()
+                results.append(f(d))
+                sums[i] += time.time() - t0
+
+            if not numpy.isnan(results[1]):
+                assert results[0] == pytest.approx(results[1])
+        for times, sum in zip([us_times, np_times], sums):
+            times.append(sum/k)
+
+    try:
+        from matplotlib import pyplot
+        import seaborn
+    except ImportError:
+        return
+
+    pyplot.plot(ns, us_times, label='Our library')
+    pyplot.plot(ns, np_times, label='Numpy')
+    pyplot.xlabel('n')
+    pyplot.ylabel('time(s)')
+    pyplot.yscale('log')
+    pyplot.savefig('plot.png')
+
+