Added some logging/mapping notes

main.py

@@ -43,8 +43,9 @@ job_df = job_df.progress_apply(flight_filtering.filter_flights, axis=1)
 """
 TRANSFORMATION
 """
-print('Running CDA/thresholding')
+print('Running CDA')
 job_df = job_df.progress_apply(transformation.cda_preprocess, axis=1)
+print('Running thresholding')
 job_df = job_df.progress_apply(transformation.threshold, axis=1)
 
 """

stages/mapping.py

@@ -8,3 +8,33 @@ def scale_coord_to_arr_dim(lat_lon, h_w, input_points):
     # y must be reversed because the orientation of the image in the matplotlib.
     # image - (0, 0) in upper left corner; coordinate system - (0, 0) in lower left corner
     return int(x), h_w[1] - int(y)
+
+
+def scale_arr_points_to_coord(lat_lon, h_w, input_points):
+    new = (input_points[2], input_points[0])
+    old = (0, h_w[1])
+    y = ((lat_lon[0] - old[0]) * (new[1] - new[0]) / (old[1] - old[0])) + new[0]
+    new = (input_points[1], input_points[3])
+    old = (0, h_w[0])
+    x = ((lat_lon[1] - old[0]) * (new[1] - new[0]) / (old[1] - old[0])) + new[0]
+    # y must be reversed because the orientation of the image in the matplotlib.
+    # image - (0, 0) in upper left corner; coordinate system - (0, 0) in lower left corner
+    return int(x), h_w[1] - int(y)
+
+"""
+NOTES
+
+# use ndi for mapping coordinates
+# importing numpy package for
+# creating arrays
+import numpy as np
+  
+# importing scipy
+from scipy import ndimage
+  
+# creating an array from 0 to 15 values
+a = np.arange(16.).reshape((4, 4))
+  
+# finding coordinates
+ndimage.map_coordinates(a, [[0.3, 1], [0.5, 1]], order=1)
+"""