diff --git a/PyNutil/coordinate_extraction.py b/PyNutil/coordinate_extraction.py
index ff51c5e9ab3e91136ba30b90a1a7547c07f13077..232d4f3c698f12f4c3a41fba360a675e1d7c12d3 100644
--- a/PyNutil/coordinate_extraction.py
+++ b/PyNutil/coordinate_extraction.py
@@ -79,72 +79,8 @@ def transformToAtlasSpace(anchoring, Y, X, RegHeight, RegWidth):
return (O + XYZU + XYZV).T
-# related to coordinate extraction
-def SegmentationToAtlasSpace(slice, SegmentationPath, pixelID="auto", nonLinear=True):
- """combines many functions to convert a segmentation to atlas space. It takes care
- of deformations"""
- Segmentation = cv2.imread(SegmentationPath)
-
- if pixelID == "auto":
- # remove the background from the segmentation
- SegmentationNoBackGround = Segmentation[~np.all(Segmentation == 255, axis=2)]
- pixelID = np.vstack(
- {tuple(r) for r in SegmentationNoBackGround.reshape(-1, 3)}
- ) # remove background
- # currently only works for a single label
- pixelID = pixelID[0]
- ID_pixels = findMatchingPixels(Segmentation, pixelID)
- # transform pixels to registration space (the registered image and segmentation have different dimensions)
- SegHeight = Segmentation.shape[0]
- SegWidth = Segmentation.shape[1]
- RegHeight = slice["height"]
- RegWidth = slice["width"]
- # this calculates reg/seg
- Yscale, Xscale = transformToRegistration(SegHeight, SegWidth, RegHeight, RegWidth)
- scaledY, scaledX = scalePositions(ID_pixels[0], ID_pixels[1], Yscale, Xscale)
- if nonLinear:
- if "markers" in slice:
- # this creates a triangulation using the reg width
- triangulation = triangulate(RegWidth, RegHeight, slice["markers"])
- newX, newY = transform_vec(triangulation, scaledX, scaledY)
- else:
- print(f"no markers found for {slice['filename']}, result for section will be linear")
- newX, newY = scaledX, scaledY
- else:
- newX, newY = scaledX, scaledY
-
- # scale U by Uxyz/RegWidth and V by Vxyz/RegHeight
- points = transformToAtlasSpace(slice["anchoring"], newY, newX, RegHeight, RegWidth)
- # points = points.reshape(-1)
- return np.array(points)
-# related to coordinate extraction
-def FolderToAtlasSpace(folder, QUINT_alignment, pixelID=[0, 0, 0], nonLinear=True):
- "apply Segmentation to atlas space to all segmentations in a folder"
- slices = loadVisuAlignJson(QUINT_alignment)
- points = []
- segmentationFileTypes = [".png", ".tif", ".tiff", ".jpg", ".jpeg"]
- Segmentations = [
- file
- for file in glob(folder + "/*")
- if any([file.endswith(type) for type in segmentationFileTypes])
- ]
- SectionNumbers = number_sections(Segmentations)
- # order segmentations and sectionNumbers
- # Segmentations = [x for _,x in sorted(zip(SectionNumbers,Segmentations))]
- # SectionNumbers.sort()
- for SegmentationPath in Segmentations:
- seg_nr = int(number_sections([SegmentationPath])[0])
- current_slice_index = np.where([s["nr"] == seg_nr for s in slices])
- current_slice = slices[current_slice_index[0][0]]
- ##this converts the segmentation to a point cloud
- points.extend(
- SegmentationToAtlasSpace(
- current_slice, SegmentationPath, pixelID, nonLinear
- )
- )
- return np.array(points)
# points.append would make list of lists, keeping sections separate.
@@ -152,7 +88,7 @@ def FolderToAtlasSpace(folder, QUINT_alignment, pixelID=[0, 0, 0], nonLinear=Tru
# related to coordinate extraction
# this function returns an array of points
-def FolderToAtlasSpaceMultiThreaded(
+def FolderToAtlasSpace(
folder, QUINT_alignment, pixelID=[0, 0, 0], nonLinear=True
):
"apply Segmentation to atlas space to all segmentations in a folder"
@@ -175,7 +111,7 @@ def FolderToAtlasSpaceMultiThreaded(
current_slice_index = np.where([s["nr"] == seg_nr for s in slices])
current_slice = slices[current_slice_index[0][0]]
x = threading.Thread(
- target=SegmentationToAtlasSpaceMultiThreaded,
+ target=SegmentationToAtlasSpace,
args=(
current_slice,
SegmentationPath,
@@ -198,7 +134,7 @@ def FolderToAtlasSpaceMultiThreaded(
# related to coordinate extraction
# this function returns an array of points
-def SegmentationToAtlasSpaceMultiThreaded(
+def SegmentationToAtlasSpace(
slice, SegmentationPath, pixelID="auto", nonLinear=True, pointsList=None, index=None
):
"""combines many functions to convert a segmentation to atlas space. It takes care
diff --git a/PyNutil/counting_and_load.py b/PyNutil/counting_and_load.py
index d0775e64fbaaddcf8301139845374173ca600826..d33bc04a599a4645210018a6f1f7bd5220d6bbcb 100644
--- a/PyNutil/counting_and_load.py
+++ b/PyNutil/counting_and_load.py
@@ -23,7 +23,7 @@ def labelPoints(points, label_volume, scale_factor=1):
# related to counting_and_load
-def PixelCountPerRegion(labelsDict, label_colours):
+def PixelCountPerRegion(labelsDict, df_label_colours):
"""Function for counting no. of pixels per region and writing to CSV based on
a dictionary with the region as the key and the points as the value,"""
counted_labels, label_counts = np.unique(labelsDict, return_counts=True)
@@ -34,7 +34,7 @@ def PixelCountPerRegion(labelsDict, label_colours):
df_counts_per_label = pd.DataFrame(counts_per_label, columns=["idx", "pixel_count"])
# create a pandas df with regions and pixel counts
- df_label_colours = pd.read_csv(label_colours, sep=",")
+ # df_label_colours = pd.read_csv(label_colours, sep=",")
# find colours corresponding to each region ID and add to the pandas dataframe
# look up name, r, g, b in df_allen_colours in df_counts_per_label based on "idx"
diff --git a/PyNutil/main.py b/PyNutil/main.py
index f87b63395f8578c63fcc9b533b43d8ff2993e0e1..31b2af65dea9338225ebc9f5ae85cdc377d7259e 100644
--- a/PyNutil/main.py
+++ b/PyNutil/main.py
@@ -1,7 +1,10 @@
from .metadata import metadata_loader
-from .read_and_write import readAtlasVolume
-from .coordinate_extraction import FolderToAtlasSpaceMultiThreaded
+from .read_and_write import readAtlasVolume, WritePointsToMeshview
+from .coordinate_extraction import FolderToAtlasSpace
+from .counting_and_load import labelPoints, PixelCountPerRegion
import json
+import pandas as pd
+from datetime import datetime
class PyNutil:
def __init__(
@@ -46,8 +49,15 @@ class PyNutil:
atlas_root_path = self.config["annotation_volume_directory"]
current_atlas_path = self.config["annotation_volumes"][self.atlas]["volume"]
print("loading atlas volume")
+ startTime = datetime.now()
self.atlas_volume = readAtlasVolume(atlas_root_path + current_atlas_path)
- print("atlas volume loaded")
+ time_taken = datetime.now() - startTime
+ print(f"atlas volume loaded in: {time_taken}")
+ atlas_label_path = self.config["annotation_volumes"][self.atlas]["labels"]
+ print("loading atlas labels")
+ self.atlas_labels = pd.read_csv(atlas_root_path + atlas_label_path)
+ print("atlas labels loaded")
+
def get_coordinates(self, nonLinear=True, method="all"):
if not hasattr(self, "atlas_volume"):
@@ -64,4 +74,31 @@ class PyNutil:
self.points = points
+ def quantify_coordinates(self):
+ if not hasattr(self, "points"):
+ raise ValueError("Please run get_coordinates before running quantify_coordinates")
+ print("quantifying coordinates")
+ labeled_points = labelPoints(self.points, self.atlas_volume, scale_factor=2.5)
+ self.label_df = PixelCountPerRegion(labeled_points, self.atlas_labels)
+ self.labeled_points = labeled_points
+
+ print("quantification complete")
+
+ def save_analysis(self, output_folder):
+ if not hasattr(self, "points"):
+ raise ValueError("Please run get_coordinates before running save_analysis")
+ if not hasattr(self, "label_df"):
+ print("no quantification found so we will only save the coordinates")
+ print("if you want to save the quantification please run quantify_coordinates")
+ self.label_df.to_csv(output_folder + '/counts.csv', sep=";", na_rep="", index=False)
+ else:
+ self.label_df.to_csv(output_folder + '/counts.csv', sep=";", na_rep="", index=False)
+ WritePointsToMeshview(
+ self.points,
+ self.labeled_points,
+ output_folder + '/pixels_meshview.json',
+ self.atlas_labels
+ )
+
+
diff --git a/PyNutil/read_and_write.py b/PyNutil/read_and_write.py
index 5689fa151ab8d99778781fa9b5d6399d3b64d2ed..bbb67301ee23c759395ad04dca302fa25bec979c 100644
--- a/PyNutil/read_and_write.py
+++ b/PyNutil/read_and_write.py
@@ -53,7 +53,7 @@ def WritePointsToMeshview(points, pointNames, filename, infoFile):
regionDict = createRegionDict(points, pointNames)
WritePoints(regionDict, filename, infoFile)
-
+# I think this might not need to be its own function :)
def SaveDataframeasCSV(df_to_save, output_csv):
"""Function for saving a df as a CSV file"""
df_to_save.to_csv(output_csv, sep=";", na_rep="", index=False)
@@ -111,4 +111,4 @@ def FilesinDirectory(directory):
def readAtlasVolume(atlas_volume_path):
data, header = nrrd.read(atlas_volume_path)
- return data, header
+ return data
diff --git a/testOOP.py b/testOOP.py
index 92ee5f3e95348aa7346527f631f2a3796c332a1e..9c19e0055f031685e8d599cf5af8c4dd5b32d6d0 100644
--- a/testOOP.py
+++ b/testOOP.py
@@ -7,3 +7,6 @@ pnt.build_quantifier()
pnt.get_coordinates()
+pnt.quantify_coordinates()
+
+pnt.save_analysis('outputs/test4_2017')
\ No newline at end of file