From baae40684b0173367bd3b13e578b10c31c8acc90 Mon Sep 17 00:00:00 2001
From: monadal <morgane.nadal@inria.fr>
Date: Tue, 10 Mar 2020 11:12:55 +0100
Subject: [PATCH] wrote fct for relative intensity image normalization +
refractoring
---
brick/general/feedback.py | 8 ++++----
brick/processing/input.py | 32 ++++++++++++++++++++++----------
nutrimorph.py | 4 ++--
3 files changed, 28 insertions(+), 16 deletions(-)
diff --git a/brick/general/feedback.py b/brick/general/feedback.py
index a0973cc..814a05e 100644
--- a/brick/general/feedback.py
+++ b/brick/general/feedback.py
@@ -57,10 +57,10 @@ def PlotSomas(somas: Sequence[soma_t], som_nfo: dict, axes: dict) -> None:
for soma in somas:
axes[soma.uid] = ot_.PlotLMap(som_nfo["lmp"], labels=soma.uid)
pl_.title(f"Soma.{soma.uid}")
- pl_.matshow(som_nfo["influence_map"].max(axis=0)), pl_.title("Soma Influencess")
- pl_.show(block=True)
- pl_.matshow(som_nfo["dist_to_closest"].max(axis=0)), pl_.title("Soma Distances")
- pl_.show(block=True)
+ # pl_.matshow(som_nfo["influence_map"].max(axis=0)), pl_.title("Soma Influencess")
+ # pl_.show(block=True)
+ # pl_.matshow(som_nfo["dist_to_closest"].max(axis=0)), pl_.title("Soma Distances")
+ # pl_.show(block=True)
def PlotExtensions(
diff --git a/brick/processing/input.py b/brick/processing/input.py
index b0bb8f1..a9a1a11 100644
--- a/brick/processing/input.py
+++ b/brick/processing/input.py
@@ -68,21 +68,33 @@ def ImageVerification(image, channel):
# print('WARNING. The 3 RGB color channels were selected in the parameters but the image has only one channel.')
-def NormalizedImage(image: array_t) -> array_t:
+def IntensityNormalizedImage(image: array_t) -> array_t:
#
- print(
- "This normalization does not bring anything; left as is for now to avoid the need for changing prms"
- )
- nonextreme_values = image[np_.logical_and(image > 0.0, image < image.max())]
+ print('Relative Intensity Normalization between 0 and 1 (Not a standardization). Need to reevaluate the parameters !!!')
- if nonextreme_values.size > 0:
- nonextreme_avg = nonextreme_values.mean()
- result = image.astype(np_.float32) / nonextreme_avg
- else:
- result = image.astype(np_.float32)
+ value_max = image.astype(np_.float32).max()
+ value_min = image.astype(np_.float32).min()
+
+ result = (image.astype(np_.float32) - value_min)/(value_max - value_min)
return result
+ # print(
+ # "This normalization does not bring anything; left as is for now to avoid the need for changing prms"
+ # )
+ # nonextreme_values = image[np_.logical_and(image > 0.0, image < image.max())]
+ #
+ # if nonextreme_values.size > 0:
+ # nonextreme_avg = nonextreme_values.mean()
+ # result = image.astype(np_.float32) / nonextreme_avg
+ # else:
+ # result = image.astype(np_.float32)
+ #
+ # return result
+
+def MetricNormalizedImage(image: array_t) -> array_t: # TODO
+ #
+ print('Image metric in converted to micrometers.')
def DijkstraCosts(image: array_t, som_map: array_t, ext_map: array_t) -> array_t:
#
diff --git a/nutrimorph.py b/nutrimorph.py
index 3df86f9..ca15e44 100644
--- a/nutrimorph.py
+++ b/nutrimorph.py
@@ -106,8 +106,8 @@ img_shape = image.shape
#
print(f"IMAGE: s.{img_shape} t.{image.dtype} m.{image.min()} M.{image.max()}")
-image_for_soma = in_.NormalizedImage(image)
-image_for_ext = in_.NormalizedImage(image)
+image_for_soma = in_.IntensityNormalizedImage(image)
+image_for_ext = in_.IntensityNormalizedImage(image)
print(f"NRM-IMG: t.{image_for_soma.dtype} m.{image_for_soma.min():.2f} M.{image_for_soma.max():.2f}")
# --- Initialization
--
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