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Tighten up psf/black and flake8 (#2024)

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* Tighten up psf/black and flake8

* Fix some tests

* Fix some E741

* Fix some E741

* updating DIRECTORY.md

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
This commit is contained in:
Christian Clauss
2020-05-22 08:10:11 +02:00
committed by GitHub
parent 21ed8968c0
commit 1f8a21d727
124 changed files with 583 additions and 495 deletions
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6
digital_image_processing/dithering/burkes.py
View File

@@ -54,9 +54,9 @@ class Burkes:
current_error = greyscale + self.error_table[x][y] - 255
"""
Burkes error propagation (`*` is current pixel):
* 8/32 4/32
2/32 4/32 8/32 4/32 2/32
* 8/32 4/32
2/32 4/32 8/32 4/32 2/32
"""
self.error_table[y][x + 1] += int(8 / 32 * current_error)
self.error_table[y][x + 2] += int(4 / 32 * current_error)

4
digital_image_processing/edge_detection/canny.py
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@@ -29,8 +29,8 @@ def canny(image, threshold_low=15, threshold_high=30, weak=128, strong=255):
dst = np.zeros((image_row, image_col))
"""
Non-maximum suppression. If the edge strength of the current pixel is the largest compared to the other pixels
in the mask with the same direction, the value will be preserved. Otherwise, the value will be suppressed.
Non-maximum suppression. If the edge strength of the current pixel is the largest compared to the other pixels
in the mask with the same direction, the value will be preserved. Otherwise, the value will be suppressed.
"""
for row in range(1, image_row - 1):
for col in range(1, image_col - 1):

72
digital_image_processing/index_calculation.py
View File

@@ -6,26 +6,28 @@
# Imports
import numpy as np
# Class implemented to calculus the index
class IndexCalculation:
"""
# Class Summary
This algorithm consists in calculating vegetation indices, these indices
can be used for precision agriculture for example (or remote sensing). There are
functions to define the data and to calculate the implemented indices.
This algorithm consists in calculating vegetation indices, these
indices can be used for precision agriculture for example (or remote
sensing). There are functions to define the data and to calculate the
implemented indices.
# Vegetation index
https://en.wikipedia.org/wiki/Vegetation_Index
A Vegetation Index (VI) is a spectral transformation of two or more bands designed
to enhance the contribution of vegetation properties and allow reliable spatial and
temporal inter-comparisons of terrestrial photosynthetic activity and canopy
structural variations
A Vegetation Index (VI) is a spectral transformation of two or more bands
designed to enhance the contribution of vegetation properties and allow
reliable spatial and temporal inter-comparisons of terrestrial
photosynthetic activity and canopy structural variations
# Information about channels (Wavelength range for each)
* nir - near-infrared
https://www.malvernpanalytical.com/br/products/technology/near-infrared-spectroscopy
Wavelength Range 700 nm to 2500 nm
* Red Edge
* Red Edge
https://en.wikipedia.org/wiki/Red_edge
Wavelength Range 680 nm to 730 nm
* red
@@ -38,7 +40,7 @@ class IndexCalculation:
https://en.wikipedia.org/wiki/Color
Wavelength Range 520 nm to 560 nm
# Implemented index list
#"abbreviationOfIndexName" -- list of channels used
@@ -84,17 +86,19 @@ class IndexCalculation:
#"NDRE" -- redEdge, nir
#list of all index implemented
#allIndex = ["ARVI2", "CCCI", "CVI", "GLI", "NDVI", "BNDVI", "redEdgeNDVI", "GNDVI",
"GBNDVI", "GRNDVI", "RBNDVI", "PNDVI", "ATSAVI", "BWDRVI", "CIgreen",
"CIrededge", "CI", "CTVI", "GDVI", "EVI", "GEMI", "GOSAVI", "GSAVI",
"Hue", "IVI", "IPVI", "I", "RVI", "MRVI", "MSAVI", "NormG", "NormNIR",
"NormR", "NGRDI", "RI", "S", "IF", "DVI", "TVI", "NDRE"]
#allIndex = ["ARVI2", "CCCI", "CVI", "GLI", "NDVI", "BNDVI", "redEdgeNDVI",
"GNDVI", "GBNDVI", "GRNDVI", "RBNDVI", "PNDVI", "ATSAVI",
"BWDRVI", "CIgreen", "CIrededge", "CI", "CTVI", "GDVI", "EVI",
"GEMI", "GOSAVI", "GSAVI", "Hue", "IVI", "IPVI", "I", "RVI",
"MRVI", "MSAVI", "NormG", "NormNIR", "NormR", "NGRDI", "RI",
"S", "IF", "DVI", "TVI", "NDRE"]
#list of index with not blue channel
#notBlueIndex = ["ARVI2", "CCCI", "CVI", "NDVI", "redEdgeNDVI", "GNDVI", "GRNDVI",
"ATSAVI", "CIgreen", "CIrededge", "CTVI", "GDVI", "GEMI", "GOSAVI",
"GSAVI", "IVI", "IPVI", "RVI", "MRVI", "MSAVI", "NormG", "NormNIR",
"NormR", "NGRDI", "RI", "DVI", "TVI", "NDRE"]
#notBlueIndex = ["ARVI2", "CCCI", "CVI", "NDVI", "redEdgeNDVI", "GNDVI",
"GRNDVI", "ATSAVI", "CIgreen", "CIrededge", "CTVI", "GDVI",
"GEMI", "GOSAVI", "GSAVI", "IVI", "IPVI", "RVI", "MRVI",
"MSAVI", "NormG", "NormNIR", "NormR", "NGRDI", "RI", "DVI",
"TVI", "NDRE"]
#list of index just with RGB channels
#RGBIndex = ["GLI", "CI", "Hue", "I", "NGRDI", "RI", "S", "IF"]
@@ -121,8 +125,8 @@ class IndexCalculation:
self, index="", red=None, green=None, blue=None, redEdge=None, nir=None
):
"""
performs the calculation of the index with the values instantiated in the class
:str index: abbreviation of index name to perform
performs the calculation of the index with the values instantiated in the class
:str index: abbreviation of index name to perform
"""
self.setMatrices(red=red, green=green, blue=blue, redEdge=redEdge, nir=nir)
funcs = {
@@ -213,8 +217,8 @@ class IndexCalculation:
def NDVI(self):
"""
Normalized Difference self.nir/self.red Normalized Difference Vegetation Index,
Calibrated NDVI - CDVI
Normalized Difference self.nir/self.red Normalized Difference Vegetation
Index, Calibrated NDVI - CDVI
https://www.indexdatabase.de/db/i-single.php?id=58
:return: index
"""
@@ -222,7 +226,7 @@ class IndexCalculation:
def BNDVI(self):
"""
Normalized Difference self.nir/self.blue self.blue-normalized difference
Normalized Difference self.nir/self.blue self.blue-normalized difference
vegetation index
https://www.indexdatabase.de/db/i-single.php?id=135
:return: index
@@ -410,7 +414,7 @@ class IndexCalculation:
"""
return (self.nir / ((self.nir + self.red) / 2)) * (self.NDVI() + 1)
def I(self):
def I(self): # noqa: E741,E743
"""
Intensity
https://www.indexdatabase.de/db/i-single.php?id=36
@@ -471,8 +475,9 @@ class IndexCalculation:
def NGRDI(self):
"""
Normalized Difference self.green/self.red Normalized self.green self.red
difference index, Visible Atmospherically Resistant Indices self.green (VIself.green)
Normalized Difference self.green/self.red Normalized self.green self.red
difference index, Visible Atmospherically Resistant Indices self.green
(VIself.green)
https://www.indexdatabase.de/db/i-single.php?id=390
:return: index
"""
@@ -506,7 +511,7 @@ class IndexCalculation:
def DVI(self):
"""
Simple Ratio self.nir/self.red Difference Vegetation Index, Vegetation Index
Simple Ratio self.nir/self.red Difference Vegetation Index, Vegetation Index
Number (VIN)
https://www.indexdatabase.de/db/i-single.php?id=12
:return: index
@@ -535,7 +540,7 @@ nir = np.ones((1000,1000, 1),dtype="float64") * 52200
# Examples of how to use the class
# instantiating the class
# instantiating the class
cl = IndexCalculation()
# instantiating the class with the values
@@ -556,9 +561,12 @@ indexValue_form2 = cl.CCCI()
indexValue_form3 = cl.calculation("CCCI", red=red, green=green, blue=blue,
redEdge=redEdge, nir=nir).astype(np.float64)
print("Form 1: "+np.array2string(indexValue_form1, precision=20, separator=', ', floatmode='maxprec_equal'))
print("Form 2: "+np.array2string(indexValue_form2, precision=20, separator=', ', floatmode='maxprec_equal'))
print("Form 3: "+np.array2string(indexValue_form3, precision=20, separator=', ', floatmode='maxprec_equal'))
print("Form 1: "+np.array2string(indexValue_form1, precision=20, separator=', ',
floatmode='maxprec_equal'))
print("Form 2: "+np.array2string(indexValue_form2, precision=20, separator=', ',
floatmode='maxprec_equal'))
print("Form 3: "+np.array2string(indexValue_form3, precision=20, separator=', ',
floatmode='maxprec_equal'))
# A list of examples results for different type of data at NDVI
# float16 -> 0.31567383 #NDVI (red = 50, nir = 100)