SR1.1.1 Add support for showing daily standard deviation on inflammation data

inflammation-analysis.py

@@ -21,7 +21,7 @@ def main(args):
     for filename in InFiles:
         inflammation_data = models.load_csv(filename)
 
-        view_data = {'average': models.daily_mean(inflammation_data), 'max': models.daily_max(inflammation_data), 'min': models.daily_min(inflammation_data)}
+        view_data = {'average': models.daily_mean(inflammation_data), 'max': models.daily_max(inflammation_data), 'min': models.daily_min(inflammation_data), 'daily deviation': models.s_dev(inflammation_data)}
 
         views.visualize(view_data)
 

inflammation/models.py

@@ -32,3 +32,7 @@ def daily_min(data):
     """Calculate the daily min of a 2d inflammation data array."""
     return np.min(data, axis=0)
 
+
+def daily_standard_deviation(data):
+    """Computes and returns standard deviation for data."""
+    return np.std(data)

inflammation/views.py

@@ -1,7 +1,7 @@
 """Module containing code for plotting inflammation data."""
 
 from matplotlib import pyplot as plt
-import numpy as np
+# import numpy as np
 
 
 def visualize(data_dict):

tests/test_models.py

@@ -2,6 +2,7 @@
 
 import numpy as np
 import numpy.testing as npt
+import pytest
 
 
 def test_daily_mean_zeros():
@@ -29,3 +30,16 @@ def test_daily_mean_integers():
     # Need to use Numpy testing functions to compare arrays
     npt.assert_array_equal(daily_mean(test_input), test_result)
 
+
+@pytest.mark.parametrize('data, expected_standard_deviation', [
+    ([0, 0, 0], 0.0),
+    ([1.0, 1.0, 1.0], 0),
+    ([0.0, 2.0], 1.0),
+    ([-1,0,1],0),
+    (np.array(1,2,3),2)
+])
+def test_daily_standard_deviation(data, expected_standard_deviation):
+    """Test standard deviation function works for an array of  integers."""
+    from inflammation.models import daily_standard_deviation
+    result_data = daily_standard_deviation(data)['standard deviation']
+    npt.assert_approx_equal(result_data, expected_standard_deviation)