Python utility tools for research
Project description
See the source for this project on our GitHub page
Install
pip install toolman
Modules
mist_utils.py
miscellaneous utility functions including data I/O and processing
Read/write different formats of files in one function:
import toolman as tm
data = tm.misc_utils.load_file(file_name)
tm.misc_utils.save_file(file_name, data)
Currently support extensions including: .npy, .pkl, .txt, .csv, .json and commonly used image formats.
Argument parser, parse nested argument list:
import sys
import argparse
import toolman as tm
parser = argparse.ArgumentParser()
args, extras = parser.parse_known_args(sys.argv[1:])
cfg_dict = tm.misc_utils.parse_args(extras)
vis_utils.py
Matplotlib utility functions for visualization
Display images in side by side with axis linked
import toolman as tm
fig1 = tm.misc_utils.load_file(img_name_1)
fig2 = tm.misc_utils.load_file(img_name_1)
tm.vis_utils.compare_figures([fig1, fig2], (1, 2), fig_size=(12, 5))
Display barplots
import toolman as tm
data = np.random.random((3, 4))
labels = ['group 1', 'group 2', 'group 3']
xticks = ['cluster 1', 'cluster 2', 'cluster 3', 'cluster 4']
tm.vis_utils.compare_bars(data, labels, xticks)
img_utils
image specific utility functions
pytorch_utils
pytorch specific utility functions
process_block
A processing unit that do certain operations only if it has never done before. This is helpful avoid duplicate executing time consuming jobs.
import toolman as tm
def foo(cnt_len):
cnt = 0
for i in range(cnt_len):
cnt += 1
return cnt
pb = tm.process_block.ProcessBlock(foo, file_dir)
pb.run(force_run=False, cnt_len=100)
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