This Python 3 module helps you speedup generation of subplots in pseudo-parallel mode using matplotlib and multiprocessing. This can be useful if you are dealing with expensive preprocessing or plotting tasks such as violin plots per subplot.
License: MIT License
Describe the bug
Any row or col label will not wrap, but overlap if it is too long.
Minimal Code To Reproduce
from parallelplot import parallel_plot
import matplotlib.pyplot as plt
import numpy as np
def violin(data, fig, axes):
axes.violinplot(data)
X = np.random.uniform(low=-1, high=1, size=(45, 512, 512))
# _parallel_plot_worker((0, X[0]), violin, figsize=(3, 6))
labels = ["this is a very long label blah blah blah" for _ in enumerate(X)]
parallel_plot(plot_fn=violin, data=X, grid_shape=(3, 15), cleanup=False,
col_labels=labels, row_labels=labels)
plt.show()Expected behavior
Labels should wrap.
Describe the bug
TypeError: parallel_plot() got an unexpected keyword argument 'figsize'
I saw your blog post(https://towardsdatascience.com/plotting-in-parallel-with-matplotlib-and-python-f7efb3d944de)
and try scatter example has figsize option.
parallel_plot(plot_fn=scatter, data=X, grid_shape=(1, 5), figsize=(25, 5))
but it doesn't work.
Minimal Code To Reproduce
parallel_plot(plot_fn=scatter, data=X, grid_shape=(1, 5), figsize=(25, 5))
Expected behavior
figsize option accepted
Environment (please complete the following information):
Additional context
Add any other context about the problem here.
In WSL(Windows Subsystem Linux. it is just linux), this package works well.
But in Just normal windows, the simple code below is not run well but wait forever.
and terminal shows lot of errors about multiprocessing.
what i tried
import numpy as np
from parallelplot import parallel_plot
def scatter(data, fig, axes):
axes.scatter(data[:, 0], data[:, 1])
X = np.random.uniform(low=-1, high=1, size=(5, 50, 50))
parallel_plot(plot_fn=scatter, data=X, grid_shape=(1, 5), show_progress=False )
result in terminal is
Process SpawnPoolWorker-3:
Traceback (most recent call last):
File "\Python310\lib\multiprocessing\process.py", line 315, in _bootstrap
self.run()
File "\Python310\lib\multiprocessing\process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "\Python310\lib\multiprocessing\pool.py", line 114, in worker
task = get()
File "\Python310\lib\multiprocessing\queues.py", line 367, in get
return _ForkingPickler.loads(res)
AttributeError: Can't get attribute 'scatter' on <module '__main__' (built-in)>
Process SpawnPoolWorker-1:
Traceback (most recent call last):
File "\Python310\lib\multiprocessing\process.py", line 315, in _bootstrap
self.run()
File "\Python310\lib\multiprocessing\process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "\Python310\lib\multiprocessing\pool.py", line 114, in worker
task = get()
File "\Python310\lib\multiprocessing\queues.py", line 367, in get
return _ForkingPickler.loads(res)
AttributeError: Can't get attribute 'scatter' on <module '__main__' (built-in)>
Process SpawnPoolWorker-2:
Process SpawnPoolWorker-4:
Process SpawnPoolWorker-5:
Traceback (most recent call last):
File "\Python310\lib\multiprocessing\process.py", line 315, in _bootstrap
self.run()
File "\Python310\lib\multiprocessing\process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "\Python310\lib\multiprocessing\pool.py", line 114, in worker
task = get()
Traceback (most recent call last):
File "\Python310\lib\multiprocessing\queues.py", line 367, in get
return _ForkingPickler.loads(res)
File "\Python310\lib\multiprocessing\process.py", line 315, in _bootstrap
self.run()
AttributeError: Can't get attribute 'scatter' on <module '__main__' (built-in)>
File "\Python310\lib\multiprocessing\process.py", line 108, in run
self._target(*self._args, **self._kwargs)
Traceback (most recent call last):
File "\Python310\lib\multiprocessing\pool.py", line 114, in worker
task = get()
File "\Python310\lib\multiprocessing\process.py", line 315, in _bootstrap
self.run()
File "\Python310\lib\multiprocessing\queues.py", line 367, in get
return _ForkingPickler.loads(res)
AttributeError: Can't get attribute 'scatter' on <module '__main__' (built-in)>
File "\Python310\lib\multiprocessing\process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "\Python310\lib\multiprocessing\pool.py", line 114, in worker
task = get()
File "\Python310\lib\multiprocessing\queues.py", line 367, in get
return _ForkingPickler.loads(res)
AttributeError: Can't get attribute 'scatter' on <module '__main__' (built-in)>
Describe the solution you'd like
not sure, but...... probably multiprocessing is the key point.
Describe the bug
The Top / Right Axis of subplots not always visible. EDIT: This seems to be applicable to everything close to the edges.
Minimal Code To Reproduce
from parallelplot import parallel_plot
import matplotlib.pyplot as plt
import numpy as np
def violin(data, fig, axes):
axes.violinplot(data)
# Gen some fake data
X = np.random.uniform(low=-1, high=1, size=(30, 512, 512))
parallel_plot(plot_fn=violin, data=X, grid_shape=(3, 10))
plt.show()Expected behavior
All axis should be visible
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