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Heatmap.py
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Created
Sat, Sep 21, 13:52
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4 KB
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text/x-python
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Mon, Sep 23, 13:52 (2 d)
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blob
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Handle
20967187
Attached To
R11778 LPBF Transfer Learning
Heatmap.py
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# -*- coding: utf-8 -*-
"""
Created on Sat Feb 8 22:10:18 2020
@author: srpv
"""
import
numpy
as
np
import
matplotlib
import
matplotlib.pyplot
as
plt
def
heatmap
(
data
,
row_labels
,
col_labels
,
ax
=
None
,
cbar_kw
=
{},
cbarlabel
=
""
,
**
kwargs
):
"""
Create a heatmap from a numpy array and two lists of labels.
Parameters
----------
data
A 2D numpy array of shape (N, M).
row_labels
A list or array of length N with the labels for the rows.
col_labels
A list or array of length M with the labels for the columns.
ax
A `matplotlib.axes.Axes` instance to which the heatmap is plotted. If
not provided, use current axes or create a new one. Optional.
cbar_kw
A dictionary with arguments to `matplotlib.Figure.colorbar`. Optional.
cbarlabel
The label for the colorbar. Optional.
**kwargs
All other arguments are forwarded to `imshow`.
"""
if
not
ax
:
ax
=
plt
.
gca
()
# Plot the heatmap
im
=
ax
.
imshow
(
data
,
**
kwargs
)
# Create colorbar
cbar
=
ax
.
figure
.
colorbar
(
im
,
ax
=
ax
,
**
cbar_kw
)
cbar
.
ax
.
set_ylabel
(
cbarlabel
,
rotation
=-
90
,
va
=
"bottom"
)
# We want to show all ticks...
ax
.
set_xticks
(
np
.
arange
(
data
.
shape
[
1
]))
ax
.
set_yticks
(
np
.
arange
(
data
.
shape
[
0
]))
# ... and label them with the respective list entries.
ax
.
set_xticklabels
(
col_labels
)
ax
.
set_yticklabels
(
row_labels
)
# Let the horizontal axes labeling appear on top.
ax
.
tick_params
(
top
=
False
,
bottom
=
True
,
labeltop
=
False
,
labelbottom
=
True
)
# Rotate the tick labels and set their alignment.
plt
.
setp
(
ax
.
get_xticklabels
(),
rotation
=
90
,
ha
=
"right"
,
rotation_mode
=
"anchor"
)
# Turn spines off and create white grid.
for
edge
,
spine
in
ax
.
spines
.
items
():
spine
.
set_visible
(
False
)
ax
.
set_xticks
(
np
.
arange
(
data
.
shape
[
1
]
+
1
)
-.
5
,
minor
=
True
)
ax
.
set_yticks
(
np
.
arange
(
data
.
shape
[
0
]
+
1
)
-.
5
,
minor
=
True
)
ax
.
grid
(
which
=
"minor"
,
color
=
"w"
,
linestyle
=
'-'
,
linewidth
=
1
)
ax
.
tick_params
(
which
=
"minor"
,
bottom
=
False
,
left
=
False
)
return
im
,
cbar
def
annotate_heatmap
(
im
,
data
=
None
,
valfmt
=
"{x:.2f}"
,
textcolors
=
[
"black"
,
"white"
],
threshold
=
None
,
**
textkw
):
"""
A function to annotate a heatmap.
Parameters
----------
im
The AxesImage to be labeled.
data
Data used to annotate. If None, the image's data is used. Optional.
valfmt
The format of the annotations inside the heatmap. This should either
use the string format method, e.g. "$ {x:.2f}", or be a
`matplotlib.ticker.Formatter`. Optional.
textcolors
A list or array of two color specifications. The first is used for
values below a threshold, the second for those above. Optional.
threshold
Value in data units according to which the colors from textcolors are
applied. If None (the default) uses the middle of the colormap as
separation. Optional.
**kwargs
All other arguments are forwarded to each call to `text` used to create
the text labels.
"""
if
not
isinstance
(
data
,
(
list
,
np
.
ndarray
)):
data
=
im
.
get_array
()
# Normalize the threshold to the images color range.
if
threshold
is
not
None
:
threshold
=
im
.
norm
(
threshold
)
else
:
threshold
=
im
.
norm
(
data
.
max
())
/
2.
# Set default alignment to center, but allow it to be
# overwritten by textkw.
kw
=
dict
(
horizontalalignment
=
"center"
,
verticalalignment
=
"center"
)
kw
.
update
(
textkw
)
# Get the formatter in case a string is supplied
if
isinstance
(
valfmt
,
str
):
valfmt
=
matplotlib
.
ticker
.
StrMethodFormatter
(
valfmt
)
# Loop over the data and create a `Text` for each "pixel".
# Change the text's color depending on the data.
texts
=
[]
for
i
in
range
(
data
.
shape
[
0
]):
for
j
in
range
(
data
.
shape
[
1
]):
kw
.
update
(
color
=
textcolors
[
int
(
im
.
norm
(
data
[
i
,
j
])
>
threshold
)])
text
=
im
.
axes
.
text
(
j
,
i
,
valfmt
(
data
[
i
,
j
],
None
),
**
kw
)
texts
.
append
(
text
)
return
texts
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