Merge branch 'main' of github.com:LOAMRI/asltk

Author: acsenrafilho

.github/ISSUE_TEMPLATE/general-improvement.md

@@ -4,7 +4,6 @@ about: Propose an improvement for the repo code (e.g. documentation, a module, a
   testing, etc)
 title: "[Improvement]"
 labels: enhancement
-assignees: acsenrafilho
 
 ---
 

asltk/__init__.py

@@ -0,0 +1,2 @@
+BIDS_IMAGE_FORMATS = ('.nii', '.nii.gz')
+AVAILABLE_IMAGE_FORMATS = ('.nii', '.nii.gz', '.mha', '.nrrd')

asltk/asldata.py

@@ -3,7 +3,7 @@
 import numpy as np
 import SimpleITK as sitk
 
-from asltk.utils import load_image, save_image
+from asltk.utils import load_image
 
 
 class ASLData:
@@ -82,13 +82,21 @@ def __init__(
         if kwargs.get('dw_values'):
             self._parameters['dw'] = kwargs.get('dw_values')
 
-    def set_image(self, full_path: str, spec: str):
+    def set_image(self, image, spec: str):
         """Insert a image necessary to define de ASL data processing.
 
         The `spec` parameters specifies what is the type of image to be used in
         ASL processing step. Choose one of the options: `m0` for the M0 volume,
         `pcasl` for the pCASL data.
 
+        Note:
+            The image can be a full path to the image file or a numpy array.
+            In case the image parameter is a path, then the method will load
+            the image file directly and associate it with the `spec` parameter.
+            However, if the image is a numpy array, then the method will
+            pass it to the ASLData object image data regarding the `spec`
+            parameter as well.
+
         Examples:
             >>> data = ASLData()
             >>> path_m0 = './tests/files/m0.nii.gz' # M0 file with shape (5,35,35)
@@ -97,13 +105,19 @@ def set_image(self, full_path: str, spec: str):
             (5, 35, 35)
 
         Args:
-            full_path (str): The full path with filename to be loaded
+            image (str): The image to be used.
             spec (str): The type of image being used in the ASL processing.
         """
-        if spec == 'm0':
-            self._m0_image = load_image(full_path)
-        elif spec == 'pcasl':
-            self._asl_image = load_image(full_path)
+        if isinstance(image, str) and os.path.exists(image):
+            if spec == 'm0':
+                self._m0_image = load_image(image)
+            elif spec == 'pcasl':
+                self._asl_image = load_image(image)
+        elif isinstance(image, np.ndarray):
+            if spec == 'm0':
+                self._m0_image = image
+            elif spec == 'pcasl':
+                self._asl_image = image
 
     def get_ld(self):
         """Obtain the LD array values"""

asltk/aux_methods.py

@@ -0,0 +1,33 @@
+import warnings
+
+import numpy as np
+
+
+def _check_mask_values(mask, label, ref_shape):
+    # Check wheter mask input is an numpy array
+    if not isinstance(mask, np.ndarray):
+        raise TypeError(f'mask is not an numpy array. Type {type(mask)}')
+
+    # Check whether the mask provided is a binary image
+    unique_values = np.unique(mask)
+    if unique_values.size > 2:
+        warnings.warn(
+            'Mask image is not a binary image. Any value > 0 will be assumed as brain label.',
+            UserWarning,
+        )
+
+    # Check whether the label value is found in the mask image
+    label_ok = False
+    for value in unique_values:
+        if label == value:
+            label_ok = True
+            break
+    if not label_ok:
+        raise ValueError('Label value is not found in the mask provided.')
+
+    # Check whether the dimensions between mask and input volume matches
+    mask_shape = mask.shape
+    if mask_shape != ref_shape:
+        raise TypeError(
+            f'Image mask dimension does not match with input 3D volume. Mask shape {mask_shape} not equal to {ref_shape}'
+        )