[July 24-25] Software Carpentry at UCL: Bash, Git, and Python Workshop

Staff

DAY 1:

Instructors: Will Graham, Krishnakumar Gopalakrishnan
Helpers: David Wong, Nik Khadijah Nik Aznan

DAY 2:

Instructors: Will Graham, Paddy Roddy
Helpers: Katic Buntic

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Notes

If you missed setting the Git options:

git config --global user.name "YOUR NAME"
git config --global user.email "YOUR EMAIL"
git config --global core.autocrlf input # only run if you're on MAC or Linux
git config --global core.autocrlf true # only run if you're on Windows
git config --global core.editor "nano -w"
git config --global init.defaultBranch main

# We are now going to make a plot of the average inflammation on each day

# First, we need to compute the average inflammation on each day, and save it
avg_inflammation_each_day = np.mean(data, axis=0)

# Create the plot and graph!
fig = plt.figure() # This gives us a "figure box" to draw things in!
ax = fig.add_subplot(1, 1, 1) # Add an x/y axis for us to draw on. The 1, 1, 1 is a positioning thing for the figure box

# Populate our axes with our data!
ax.plot(avg_inflammation_each_day, ".r")
ax.set_xlabel("Day of trial")
ax.set_ylabel("Avg. Inflammation")

# Display our graph!
plt.show()

Longer, plotting on 3 different axes:

# Actually, I want to make 3 plots in the same figure, for the max, min, and average

# First, we need to compute the average, max, and min inflammation on each day, and save it
avg_inflammation_each_day = np.mean(data, axis=0)
max_inflammation_each_day = np.max(data, axis=0)
min_inflammation_each_day = np.min(data, axis=0)

# I still need a figure window
fig = plt.figure(figsize=(10., 3.)) # Keep the figure a certain size

# I need 3 x-y axes side-by-side, rather than just one for each plot.
min_axes = fig.add_subplot(1, 3, 1) # 1st of 3 sets of axes
max_axes = fig.add_subplot(1, 3, 2) # 2nd of 3 sets of axes
avg_axes = fig.add_subplot(1, 3, 3) # 3rd of 3 sets of axes

# Plot the relevant data on its corresponding axis
min_axes.plot(min_inflammation_each_day, "green")
max_axes.plot(max_inflammation_each_day, "red")
avg_axes.plot(avg_inflammation_each_day, "blue")

# Add axis labels to each set of axes
min_axes.set_ylabel("Min")
max_axes.set_ylabel("Max")
avg_axes.set_ylabel("Avg")

# Get rid of the lable clipping into other plots
fig.tight_layout()

# Display the plot!
plt.show()

On lists:

odds = [1, 3, 5, 7] # Make a list
print(odds)

# Get items from the list
print(odds[0], odds[1], odds[2], odds[3])

odds.reverse() # reverse a list
print(odds)

odds.pop(1) # Remove the item at INDEX 1 in the list (removes 3)
print(odds)

odds.pop(1) # Remove the item at INDEX 1 in the list (removes 5)
print(odds)

Combining Lists, Loops, and Plotting

import numpy as np
import matplotlib.pyplot as plt
import glob

filenames = sorted(glob.glob("data/inflammation-??.csv"))

for filename in filenames[:3]: # Only loop over the first 3 files
    print(filename)
    
    # Load data for the current file we're looking at
    data = np.loadtxt(fname=filename, delimiter=",")
    
    # Make the plot window and the x-y axes we need
    fig = plt.figure()
    
    ax1 = fig.add_subplot(1, 3, 1)
    ax2 = fig.add_subplot(1, 3, 2)
    ax3 = fig.add_subplot(1, 3, 3)
    
    # Now, setup each axes with a plot
    # ax1 plots the average
    ax1.set_ylabel("Average")
    ax1.plot(data.mean(axis=0))
    
    # ax2 plots the max
    ax2.set_ylabel("Max")
    ax2.plot(data.max(axis=0))
    
    # ax3 plots the min
    ax2.set_ylabel("Min")
    ax2.plot(data.min(axis=0))
    
    # Fixes captions being in the wrong place
    fig.tight_layout()
    
    # Show the figure
    plt.show()