From 4936347d646910f5014b58b0ac6ffd5655721751 Mon Sep 17 00:00:00 2001
From: sharoncy <s.c.yates@medisin.uio.no>
Date: Thu, 8 Jun 2023 16:27:40 +0200
Subject: [PATCH] def flat_to_dataframe
---
PyNutil/coordinate_extraction.py | 2 +-
PyNutil/counting_and_load.py | 6 +++---
PyNutil/load_workflow.py | 12 ++++++------
3 files changed, 10 insertions(+), 10 deletions(-)
diff --git a/PyNutil/coordinate_extraction.py b/PyNutil/coordinate_extraction.py
index 5df3143..b6740dd 100644
--- a/PyNutil/coordinate_extraction.py
+++ b/PyNutil/coordinate_extraction.py
@@ -93,7 +93,7 @@ def folder_to_atlas_space(
object_cutoff=0,
):
"""Apply Segmentation to atlas space to all segmentations in a folder."""
-
+ """Return pixel_points, centroids, points_len, centroids_len, segmentation_filenames, """
# This should be loaded above and passed as an argument
slices = load_visualign_json(quint_alignment)
diff --git a/PyNutil/counting_and_load.py b/PyNutil/counting_and_load.py
index 7f62012..b5faaca 100644
--- a/PyNutil/counting_and_load.py
+++ b/PyNutil/counting_and_load.py
@@ -117,7 +117,7 @@ def pixel_count_per_region(
"""Read flat file and write into an np array"""
"""Read flat file, write into an np array, assign label file values, return array"""
-def flat_to_array(flat_file, labelfile):
+def flat_to_dataframe(flat_file, labelfile):
with open(flat_file, "rb") as f:
# I don't know what b is, w and h are the width and height that we get from the
# flat file header
@@ -145,9 +145,9 @@ def flat_to_array(flat_file, labelfile):
values = image_arr[coordsx, coordsy] # assign x,y coords from image_array into values
lbidx = labelfile["idx"].values
allen_id_image = lbidx[values.astype(int)]
- return allen_id_image
+ #return allen_id_image
-#def count_per_uniqueidx()
+ #def count_per_uniqueidx()
"""count pixels for unique idx"""
unique_ids, counts = np.unique(allen_id_image, return_counts=True)
diff --git a/PyNutil/load_workflow.py b/PyNutil/load_workflow.py
index ca271c9..c99fd13 100644
--- a/PyNutil/load_workflow.py
+++ b/PyNutil/load_workflow.py
@@ -6,27 +6,27 @@ import pandas as pd
import numpy as np
#from read_and_write import flat_to_array, label_to_array
-from counting_and_load import flat_to_array
+from counting_and_load import flat_to_dataframe
base = r"../test_data/tTA_2877_NOP_s037_atlasmap/2877_NOP_tTA_lacZ_Xgal_s037_nl.flat"
label = r"../annotation_volumes\allen2017_colours.csv"
#image_arr = flat_to_array(base, label)
-plt.imshow(flat_to_array(base, label))
+#plt.imshow(flat_to_array(base, label))
+df_area_per_label = flat_to_dataframe(base, label)
"""count pixels in np array for unique idx, return pd df"""
-unique_ids, counts = np.unique(allen_id_image, return_counts=True)
+#unique_ids, counts = np.unique(allen_id_image, return_counts=True)
-area_per_label = list(zip(unique_ids, counts))
+#area_per_label = list(zip(unique_ids, counts))
# create a list of unique regions and pixel counts per region
-df_area_per_label = pd.DataFrame(area_per_label, columns=["idx", "area_count"])
+#df_area_per_label = pd.DataFrame(area_per_label, columns=["idx", "area_count"])
# create a pandas df with regions and pixel counts
-
"""add region name and colours corresponding to each idx into dataframe.
This could be a separate function"""
--
GitLab