Correct spelling

CHANGELOG.md

@@ -1,5 +1,9 @@
 This document contains the nifti_mrs_tools release history in reverse chronological order.
 
+1.1.0 (WIP)
+-----------------------------
+- Code spelling changes.
+
 1.0.2 (Friday 28th July 2023)
 -----------------------------
 - Bugfix release for NIfTI-MRS header extension validator.
@@ -19,7 +23,7 @@ This document contains the nifti_mrs_tools release history in reverse chronologi
 
 0.1.7 (Friday 31st March 2023)
 --------------------------------
-- Added `--newaxis` option to `mrs_tools merge` allowing the user to merge files along a previously non-existant dimension (without using `reorder` first).
+- Added `--newaxis` option to `mrs_tools merge` allowing the user to merge files along a previously non-existent dimension (without using `reorder` first).
 
 0.1.6 (Thursday 30th March 2023)
 --------------------------------

setup.cfg

@@ -39,7 +39,7 @@ versionfile_build = nifti_mrs/_version.py
 
 [tool:pytest]
 markers =
-    with_fsl_mrs: marks tests as requring fsl-mrs installation (deselect with '-m "with_fsl_mrs"')
+    with_fsl_mrs: marks tests as requiring fsl-mrs installation (deselect with '-m "with_fsl_mrs"')
 
 [flake8]
 ignore =

src/nifti_mrs/nifti_mrs.py

@@ -444,7 +444,7 @@ def copy(self, remove_dim=None):
     def save(self, filepath):
         """Save NIfTI-MRS to file
 
-        :param filepath: Name and path of save loaction
+        :param filepath: Name and path of save location
         :type filepath: str or pathlib.Path
         """
         # Ensure final copy of header extension is loaded into Image object
@@ -469,7 +469,7 @@ def iterate_over_dims(self, dim=None, iterate_over_space=False, reduce_dim_index
         :type reduce_dim_index: bool, optional
         :param voxel_index: slice or tuple of first three spatial dimensions., defaults to None
         :type voxel_index: slice or tuple, optional
-        :return: yeildsarray of sliced data
+        :return: yeilds array of sliced data
         :rtype: np.array
         :return: data location slice object.
         :rtype: slice
@@ -478,7 +478,7 @@ def iterate_over_dims(self, dim=None, iterate_over_space=False, reduce_dim_index
         data = self[:]
         dim = self._dim_tag_to_index(dim)
 
-        # Convert indicies to slices to preserve singleton dimensions
+        # Convert indices to slices to preserve singleton dimensions
         if voxel_index is not None:
             tmp = []
             for vi in voxel_index:

src/nifti_mrs/tools/reorder.py

@@ -37,23 +37,23 @@ def reorder(nmrs, dim_tag_list):
     dims_to_add = tuple(range(original_dims, new_dim + 1))
     data_with_singleton = np.expand_dims(nmrs[:], dims_to_add)
 
-    # Create list of source indicies
-    # Create list of destination indicies
+    # Create list of source indices
+    # Create list of destination indices
     # Keep track of singleton tags
-    source_indicies = []
-    dest_indicies = []
+    source_indices = []
+    dest_indices = []
     singleton_tags = {}
     counter = 0
     for idx, tag in enumerate(dim_tag_list):
         if tag is not None:
             if tag in nmrs.dim_tags:
-                source_indicies.append(nmrs.dim_tags.index(tag) + 4)
+                source_indices.append(nmrs.dim_tags.index(tag) + 4)
             else:
-                source_indicies.append(nmrs.ndim + counter)
+                source_indices.append(nmrs.ndim + counter)
                 counter += 1
                 singleton_tags.update({(idx + 5): tag})
 
-            dest_indicies.append(idx + 4)
+            dest_indices.append(idx + 4)
 
     # Sort header extension dim_tags
     dim_n = re.compile(r'^dim_[567]$')
@@ -70,7 +70,7 @@ def reorder(nmrs, dim_tag_list):
             else:
                 tmp_header = None
 
-            new_index = dest_indicies[source_indicies.index(int(key[4]) - 1)] + 1
+            new_index = dest_indices[source_indices.index(int(key[4]) - 1)] + 1
             new_ind_str = f'{new_index}th'
             new_hdr_ext.set_dim_info(
                 new_ind_str,
@@ -87,7 +87,7 @@ def reorder(nmrs, dim_tag_list):
         nmrs.header)
 
     new_nmrs = NIFTI_MRS(
-        np.moveaxis(data_with_singleton, source_indicies, dest_indicies),
+        np.moveaxis(data_with_singleton, source_indices, dest_indices),
         header=new_header)
 
     return new_nmrs

src/nifti_mrs/tools/split_merge.py

@@ -11,7 +11,7 @@
 from nifti_mrs import utils
 
 
-def split(nmrs, dimension, index_or_indicies):
+def split(nmrs, dimension, index_or_indices):
     """Splits, or extracts indices from, a specified dimension of a
     NIFTI_MRS object. Output is two NIFTI_MRS objects. Header information preserved.
 
@@ -20,13 +20,13 @@ def split(nmrs, dimension, index_or_indicies):
     :param dimension: Dimension along which to split.
         Dimension tag or one of 4, 5, 6 (for 0-indexed 5th, 6th, and 7th)
     :type dimension: str or int
-    :param index_or_indicies: Single integer index to split after,
-        or list of interger indices to insert into second array.
+    :param index_or_indices: Single integer index to split after,
+        or list of integer indices to insert into second array.
         E.g. '0' will place the first index into the first output
         and 1 -> N in the second.
         '[1, 5, 10]' will place 1, 5 and 10 into the second output
         and all other will remain in the first.
-    :type index_or_indicies: int or [int]
+    :type index_or_indices: int or [int]
     :return: Two NIFTI_MRS object containing the split files
     :rtype: fsl_mrs.core.nifti_mrs.NIFTI_MRS
     """
@@ -46,28 +46,28 @@ def split(nmrs, dimension, index_or_indicies):
         raise TypeError('Dimension must be an int (4, 5, or 6) or string (DIM_TAG string).')
 
     # Construct indexing
-    if isinstance(index_or_indicies, int):
-        if index_or_indicies < 0\
-                or (index_or_indicies + 1) >= nmrs.shape[dim_index]:
-            raise ValueError('index_or_indicies must be between 0 and N-1,'
+    if isinstance(index_or_indices, int):
+        if index_or_indices < 0\
+                or (index_or_indices + 1) >= nmrs.shape[dim_index]:
+            raise ValueError('index_or_indices must be between 0 and N-1,'
                              f' where N is the size of the specified dimension ({nmrs.shape[dim_index]}).')
-        index = np.arange(index_or_indicies + 1, nmrs.shape[dim_index])
+        index = np.arange(index_or_indices + 1, nmrs.shape[dim_index])
 
-    elif isinstance(index_or_indicies, list):
-        if not np.logical_and(np.asarray(index_or_indicies) >= 0,
-                              np.asarray(index_or_indicies) <= nmrs.shape[dim_index]).all():
-            raise ValueError('index_or_indicies must have elements between 0 and N,'
+    elif isinstance(index_or_indices, list):
+        if not np.logical_and(np.asarray(index_or_indices) >= 0,
+                              np.asarray(index_or_indices) <= nmrs.shape[dim_index]).all():
+            raise ValueError('index_or_indices must have elements between 0 and N,'
                              f' where N is the size of the specified dimension ({nmrs.shape[dim_index]}).')
-        index = index_or_indicies
+        index = index_or_indices
 
     else:
-        raise TypeError('index_or_indicies must be single index or list of indicies')
+        raise TypeError('index_or_indices must be single index or list of indices')
 
     # Split header down
     split_hdr_ext_1, split_hdr_ext_2 = _split_dim_header(nmrs.hdr_ext,
                                                          dim_index + 1,
                                                          nmrs.shape[dim_index],
-                                                         index_or_indicies)
+                                                         index_or_indices)
     out_hdr_1 = utils.modify_hdr_ext(split_hdr_ext_1, nmrs.header)
     out_hdr_2 = utils.modify_hdr_ext(split_hdr_ext_2, nmrs.header)
 
@@ -86,7 +86,7 @@ def _split_dim_header(hdr, dimension, dim_length, index):
     :type dimension: int
     :param dim_length: Length of dimension
     :type index: int
-    :param index: Index to split after or indicies to extract
+    :param index: Index to split after or indices to extract
     :type index: int or list of ints
     :return: Split header eextension dicts
     :rtype: dict

src/nifti_mrs/utils.py

@@ -103,7 +103,7 @@ def _list_to_dict(list_desc):
 
     If conversion is not possible return the passed list.
 
-    :param list_desc: List of header indicies
+    :param list_desc: List of header indices
     :type list_desc: list
     :return: Dict representation or unmodified list
     :rtype: Dict or list

tests/test_nifti_mrs_tools_split_merge.py

@@ -373,39 +373,39 @@ def test_split():
         nmrs_tools.split(nmrs, 'DIM_DYN', -1)
 
     assert exc_info.type is ValueError
-    assert exc_info.value.args[0] == "index_or_indicies must be between 0 and N-1,"\
+    assert exc_info.value.args[0] == "index_or_indices must be between 0 and N-1,"\
                                      " where N is the size of the specified dimension (16)."
 
     # Single index - out of range high
     with pytest.raises(ValueError) as exc_info:
         nmrs_tools.split(nmrs, 'DIM_DYN', 64)
 
     assert exc_info.type is ValueError
-    assert exc_info.value.args[0] == "index_or_indicies must be between 0 and N-1,"\
+    assert exc_info.value.args[0] == "index_or_indices must be between 0 and N-1,"\
                                      " where N is the size of the specified dimension (16)."
 
-    # List of indicies - out of range low
+    # List of indices - out of range low
     with pytest.raises(ValueError) as exc_info:
         nmrs_tools.split(nmrs, 'DIM_DYN', [-1, 0, 1])
 
     assert exc_info.type is ValueError
-    assert exc_info.value.args[0] == "index_or_indicies must have elements between 0 and N,"\
+    assert exc_info.value.args[0] == "index_or_indices must have elements between 0 and N,"\
                                      " where N is the size of the specified dimension (16)."
 
-    # List of indicies - out of range high
+    # List of indices - out of range high
     with pytest.raises(ValueError) as exc_info:
         nmrs_tools.split(nmrs, 'DIM_DYN', [0, 65])
 
     assert exc_info.type is ValueError
-    assert exc_info.value.args[0] == "index_or_indicies must have elements between 0 and N,"\
+    assert exc_info.value.args[0] == "index_or_indices must have elements between 0 and N,"\
                                      " where N is the size of the specified dimension (16)."
 
-    # List of indicies - wrong type
+    # List of indices - wrong type
     with pytest.raises(TypeError) as exc_info:
         nmrs_tools.split(nmrs, 'DIM_DYN', '1')
 
     assert exc_info.type is TypeError
-    assert exc_info.value.args[0] == "index_or_indicies must be single index or list of indicies"
+    assert exc_info.value.args[0] == "index_or_indices must be single index or list of indices"
 
     # Functionality testing
 

tests/test_script_mrs_tools.py

@@ -183,14 +183,14 @@ def test_split(tmp_path):
     subprocess.check_call(['mrs_tools', 'split',
                            '--dim', 'DIM_DYN',
                            '--indices', '1', '4', '15',
-                           '--filename', 'indicies_select',
+                           '--filename', 'indices_select',
                            '--output', str(tmp_path),
                            '--file', str(test_data_split)])
 
-    assert (tmp_path / 'indicies_select_others.nii.gz').exists()
-    assert (tmp_path / 'indicies_select_selected.nii.gz').exists()
-    f1 = nib.load(tmp_path / 'indicies_select_others.nii.gz')
-    f2 = nib.load(tmp_path / 'indicies_select_selected.nii.gz')
+    assert (tmp_path / 'indices_select_others.nii.gz').exists()
+    assert (tmp_path / 'indices_select_selected.nii.gz').exists()
+    f1 = nib.load(tmp_path / 'indices_select_others.nii.gz')
+    f2 = nib.load(tmp_path / 'indices_select_selected.nii.gz')
     assert f1.shape[5] == 13
     assert f2.shape[5] == 3