Merge pull request #118 from friskluft/POL3116_bugfix_issue_115

POL 3116 bugfix in README.md example and typecheck in featurize()

Author: hsidky

README.md

@@ -76,27 +76,23 @@ or a pair of 3D arrays containing 2D intensity and mask images. There is also tw
 ```python 
 from nyxus import Nyxus
 import numpy as np
+
 nyx = Nyxus(["*ALL*"])
-intens = [
+
+intens = np.array([
     [[1, 4, 4, 1, 1],
      [1, 4, 6, 1, 1],
      [4, 1, 6, 4, 1],
      [4, 4, 6, 4, 1]],
-    [[1, 4, 4, 1, 1],
-     [1, 1, 6, 1, 1],
-     [1, 1, 3, 1, 1],
-     [4, 4, 6, 1, 1]]
-]
-seg = [
-    [[1, 1, 1, 1, 1],
-     [1, 1, 1, 1, 1],
-     [1, 1, 1, 1, 1],
-     [1, 1, 1, 1, 1]],
+])
+
+seg = np.array([
     [[1, 1, 1, 1, 1],
      [1, 1, 1, 1, 1],
      [0, 1, 1, 1, 1],
      [1, 1, 1, 1, 1]]
-]
+])
+
 features = nyx.featurize(intens, seg)
 ```
 

src/nyx/python/nyxus/nyxus.py

@@ -203,8 +203,8 @@ def featurize_directory(
 
     def featurize(
         self,
-        intensity_images: np.array,
-        label_images: np.array,
+        intensity_images: np.ndarray,
+        label_images: np.ndarray,
         intensity_names: list = [],
         label_names: list = []
     ):
@@ -218,9 +218,9 @@ def featurize(
 
         Parameters
         ----------
-        intensity_dir : np.array
+        intensity_images : np.ndarray
             2D image or 3D collection of intensity images.
-        label_images : np.array
+        label_images : np.ndarray
             2D image or 3D collection of label images.
         intensity_names (optional): list
             names for the images in for the DataFrame output. 
@@ -234,6 +234,13 @@ def featurize(
             per image.
         """
 
+        # verify argument types
+        if not isinstance(intensity_images, np.ndarray):
+            raise ValueError("intensity_images parameter must be numpy.ndarray")
+
+        if not isinstance(label_images, np.ndarray):
+            raise ValueError("label_images parameter must be numpy.ndarray")
+        
         # verify dimensions of images are the same
         if(intensity_images.ndim == 2):
             if(label_images.ndim != 2):