15th Sep 2021
University of Sheffield RSE Team
3 x ~10min talks followed by Q&A
Speakers:
venv
conda
poetry
Questions via: https://app.sli.do/event/hcmaidrc
We’ll revisit questions after all of the talks.
import glob
import numpy
import matplotlib.pyplot
filenames = sorted(glob.glob('inflammation*.csv'))
filenames = filenames[0:3]
for filename in filenames:
print(filename)
data = numpy.loadtxt(fname=filename, delimiter=',')
fig = matplotlib.pyplot.figure(figsize=(10.0, 3.0))
axes1 = fig.add_subplot(1, 3, 1)
axes2 = fig.add_subplot(1, 3, 2)
axes3 = fig.add_subplot(1, 3, 3)
axes1.set_ylabel('average')
axes1.plot(numpy.mean(data, axis=0))
axes2.set_ylabel('max')
axes2.plot(numpy.max(data, axis=0))
axes3.set_ylabel('min')
axes3.plot(numpy.min(data, axis=0))
fig.tight_layout()
matplotlib.pyplot.show()
We’re looking for:
Details at: rse.shef.ac.uk/community/lunch-bytes/