updates to inflamm and test scripts

Author: nocs-darfar

inflammation-analysis.py

@@ -13,12 +13,12 @@ def main(args):
     - selecting the necessary models and views for the current task
     - passing data between models and views
     """
-    InFiles = args.infiles
-    if not isinstance(InFiles, list):
-        InFiles = [args.infiles]
+    infiles = args.infiles
+    if not isinstance(infiles, list):
+        infiles = [args.infiles]
 
 
-    for filename in InFiles:
+    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)}

inflammation/models.py

@@ -32,3 +32,30 @@ def daily_min(data):
     """Calculate the daily min of a 2d inflammation data array."""
     return np.min(data, axis=0)
 
+def patient_normalise(data):
+    """Normalise patient data from a 2D inflammation data array."""
+    max = np.max(data, axis=0)
+    return data / max[:, np.newaxis]
+
+def patient_normalise(data):
+    """
+    Normalise patient data between 0 and 1 of a 2D inflammation data array.
+
+    Any NaN values are ignored, and normalised to 0
+
+    :param data: 2D array of inflammation data
+    :type data: ndarray
+
+    """
+    if not isinstance(data, np.ndarray):
+        raise TypeError('data input should be ndarray')
+    if len(data.shape) != 2:
+        raise ValueError('inflammation array should be 2-dimensional')
+    if np.any(data < 0):
+        raise ValueError('inflammation values should be non-negative')
+    max = np.nanmax(data, axis=1)
+    with np.errstate(invalid='ignore', divide='ignore'):
+        normalised = data / max[:, np.newaxis]
+    normalised[np.isnan(normalised)] = 0
+    return normalised
+...

tests/test_models.py

@@ -3,6 +3,7 @@
 import numpy as np
 import pytest
 import numpy.testing as npt
+import pytest_cov
 
 from inflammation.models import daily_mean
 
@@ -63,4 +64,26 @@ def test_daily_min():
     ])
 def test_daily_mean(test, expected):
     """Test mean function works for array of zeroes and positive integers."""
-    npt.assert_array_equal(daily_mean(np.array(test)), np.array(expected))
+    npt.assert_array_equal(daily_mean(np.array(test)), np.array(expected))
+
+    def patient_normalise(data):
+        """
+        Normalise patient data between 0 and 1 of a 2D inflammation data array.
+
+        Any NaN values are ignored, and normalised to 0
+
+        :param data: 2D array of inflammation data
+        :type data: ndarray
+
+        """
+        if not isinstance(data, np.ndarray):
+            raise TypeError('data input should be ndarray')
+        if len(data.shape) != 2:
+            raise ValueError('inflammation array should be 2-dimensional')
+        if np.any(data < 0):
+            raise ValueError('inflammation values should be non-negative')
+        max = np.nanmax(data, axis=1)
+        with np.errstate(invalid='ignore', divide='ignore'):
+            normalised = data / max[:, np.newaxis]
+        normalised[np.isnan(normalised)] = 0
+        return normalised