Split off reading of ROI table

Currently does exactly the same as before, but should help us
introduce more flexibility, particularly to customise for
different versions of the LabView setup.

Author: ageorgou

src/silverlabnwb/nwb_file.py

@@ -19,6 +19,7 @@
 from . import metadata
 from .header import LabViewHeader, LabViewVersions
 from .imaging import Modes
+from .rois import RoiReader
 from .timings import LabViewTimings231, LabViewTimingsPre2018
 
 try:
@@ -969,28 +970,11 @@ def add_rois(self, roi_path):
         organised by ROI number and channel name, so we can iterate there. Issue #16.
         """
         self.log('Loading ROI locations from {}', roi_path)
-        assert os.path.isfile(roi_path)
-        roi_data = pd.read_csv(
-            roi_path, sep='\t', header=0, index_col=False, dtype=np.float16,
-            converters={'Z start': np.float64, 'Z stop': np.float64}, memory_map=True)
-        # Rename the columns so that we can use them as identifiers later on
-        column_mapping = {
-            'ROI index': 'roi_index', 'Pixels in ROI': 'num_pixels',
-            'X start': 'x_start', 'Y start': 'y_start', 'Z start': 'z_start',
-            'X stop': 'x_stop', 'Y stop': 'y_stop', 'Z stop': 'z_stop',
-            'Laser Power (%)': 'laser_power', 'ROI Time (ns)': 'roi_time_ns',
-            'Angle (deg)': 'angle_deg', 'Composite ID': 'composite_id',
-            'Number of lines': 'num_lines', 'Frame Size': 'frame_size',
-            'Zoom': 'zoom', 'ROI group ID': 'roi_group_id'
-        }
-        roi_data.rename(columns=column_mapping, inplace=True)
+        reader = RoiReader()
+        roi_data = reader.read_roi_table(roi_path)
         module = self.nwb_file.create_processing_module(
             'Acquired_ROIs',
             'ROI locations and acquired fluorescence readings made directly by the AOL microscope.')
-        # Convert some columns to int
-        roi_data = roi_data.astype(
-            {'x_start': np.uint16, 'x_stop': np.uint16, 'y_start': np.uint16, 'y_stop': np.uint16,
-             'num_pixels': int})
         seg_iface = ImageSegmentation()
         module.add(seg_iface)
         self._write()
@@ -1015,9 +999,8 @@ def add_rois(self, roi_path):
             )
             # Specify the non-standard data we will be storing for each ROI,
             # which includes all the raw data fields from the original file
-            plane.add_column('dimensions', 'Dimensions of the ROI')
-            for old_name, new_name in column_mapping.items():
-                plane.add_column(new_name, old_name)
+            for column_name, column_description in reader.columns.items():
+                plane.add_column(column_name, column_description)
             index = 0  # index of the row as it will be stored in the ROI table
             self.roi_mapping[plane_name] = {}
             for row in roi_group.itertuples():
@@ -1044,7 +1027,7 @@ def add_rois(self, roi_path):
                     pixels[i, 2] = 1  # weight for this pixel
                 plane.add_roi(id=roi_id, pixel_mask=[tuple(r) for r in pixels.tolist()],
                               dimensions=dimensions,
-                              **{field: getattr(row, field) for field in column_mapping.values()})
+                              **reader.get_row_attributes(row))
                 self.roi_mapping[plane_name][roi_id] = index
                 index += 1
         self._write()

src/silverlabnwb/rois.py

@@ -0,0 +1,61 @@
+"""Functionality for handling Regions of Interest in different versions."""
+
+import os
+
+import numpy as np
+import pandas as pd
+
+
+class RoiReader:
+    """A class for reading ROI information."""
+    def __init__(self):
+        self.column_mapping = {
+            'ROI index': 'roi_index', 'Pixels in ROI': 'num_pixels',
+            'X start': 'x_start', 'Y start': 'y_start', 'Z start': 'z_start',
+            'X stop': 'x_stop', 'Y stop': 'y_stop', 'Z stop': 'z_stop',
+            'Laser Power (%)': 'laser_power', 'ROI Time (ns)': 'roi_time_ns',
+            'Angle (deg)': 'angle_deg', 'Composite ID': 'composite_id',
+            'Number of lines': 'num_lines', 'Frame Size': 'frame_size',
+            'Zoom': 'zoom', 'ROI group ID': 'roi_group_id'
+        }
+
+    @property
+    def columns(self):
+        column_descriptions = {
+            'dimensions': 'Dimensions of the ROI'
+        }
+        # for old_name, new_name in self.column_mapping.items():
+        #     column_descriptions[new_name] = old_name
+        column_descriptions.update({
+            new_name: old_name
+            for old_name, new_name in self.column_mapping.items()
+        })
+        return column_descriptions
+
+    def read_roi_table(self, roi_path):
+        assert os.path.isfile(roi_path)
+        roi_data = pd.read_csv(
+            roi_path, sep='\t', header=0, index_col=False, dtype=np.float16,
+            converters={'Z start': np.float64, 'Z stop': np.float64}, memory_map=True)
+        # Rename the columns so that we can use them as identifiers later on
+        column_mapping = {
+            'ROI index': 'roi_index', 'Pixels in ROI': 'num_pixels',
+            'X start': 'x_start', 'Y start': 'y_start', 'Z start': 'z_start',
+            'X stop': 'x_stop', 'Y stop': 'y_stop', 'Z stop': 'z_stop',
+            'Laser Power (%)': 'laser_power', 'ROI Time (ns)': 'roi_time_ns',
+            'Angle (deg)': 'angle_deg', 'Composite ID': 'composite_id',
+            'Number of lines': 'num_lines', 'Frame Size': 'frame_size',
+            'Zoom': 'zoom', 'ROI group ID': 'roi_group_id'
+        }
+        roi_data.rename(columns=column_mapping, inplace=True)
+        # Convert some columns to int
+        roi_data = roi_data.astype(
+            {'x_start': np.uint16, 'x_stop': np.uint16, 'y_start': np.uint16, 'y_stop': np.uint16,
+             'num_pixels': int})
+        return roi_data
+
+    def get_row_attributes(self, roi_row):
+        return {
+            field: getattr(roi_row, field)
+            for field in self.column_mapping.values()
+        }