Merge pull request #47 from UoMResearchIT/earlier-scripts

Earlier scripts

code/02-arrays.m

@@ -5,7 +5,7 @@
 % ## Initializing an Array
   Z = zeros(3,5)
   Z = zeros(3)
-  Z = zeros(1x5)
+  Z = zeros(1,5)
   R = rand(8);
   O = ones(10,10);
 

code/03-loading_data.m

@@ -68,6 +68,11 @@
 % ## Most inflamed patients
 % !! Solution:
   find(per_patient_max == global_max)
+% !! Solution:
+% ## Alternative solution
+  find(patient_data == global_max)
+  [r,c]=ind2sub(size(patient_data),find(patient_data == global_max))
+
 
 
 

code/04-plotting.m

@@ -8,23 +8,29 @@
 
 
 
-  title('Daily average inflammation')
-  xlabel('Day of trial')
-  ylabel('Inflammation')
+  title("Daily average inflammation")
+  xlabel("Day of trial")
+  ylabel("Inflammation")
   plot(per_day_max)
-  title('Maximum inflammation per day')
-  ylabel('Inflammation')
-  xlabel('Day of trial')
+  title("Maximum inflammation per day")
+  ylabel("Inflammation")
+  xlabel("Day of trial")
+
+% ## Scripts
+  edit src/single_plot.m
+  addpath("src")
+
   plot(per_day_min)
-  title('Minimum inflammation per day')
-  ylabel('Inflammation')
-  xlabel('Day of trial')
+  title("Minimum inflammation per day")
+  ylabel("Inflammation")
+  xlabel("Day of trial")
 % ## Multiple lines in a plot
+  copyfile("src/single_plot.m","src/multiline_plot.m")
   plot(per_day_mean,DisplayName="Mean")
   legend
-  title('Daily average inflammation')
-  xlabel('Day of trial')
-  ylabel('Inflammation')
+  title("Daily average inflammation")
+  xlabel("Day of trial")
+  ylabel("Inflammation")
   hold on
   plot(patient_5,DisplayName="Patient 5")
   hold off
@@ -34,37 +40,38 @@
 % !! Solution:
   plot(per_day_mean,DisplayName="Mean")
   legend
-  title('Daily average inflammation')
-  xlabel('Day of trial')
-  ylabel('Inflammation')
+  title("Daily average inflammation")
+  xlabel("Day of trial")
+  ylabel("Inflammation")
   hold on
   plot(patient_data(3,:),DisplayName="Patient 3")
   plot(patient_data(4,:),DisplayName="Patient 4")
   hold off
 
 
 % ## Multiple plots in a figure
+  edit src/tiled_plot.m
   tiledlayout(1, 2)
   nexttile
   plot(per_day_max)
-  title('Max')
-  xlabel('Day of trial')
-  ylabel('Inflamation')
+  title("Max")
+  xlabel("Day of trial")
+  ylabel("Inflamation")
   nexttile
   plot(per_day_min)
-  title('Min')
-  xlabel('Day of trial')
-  ylabel('Inflamation')
-  tlo=tiledlayout(1, 2)
-  title(tlo,'Per day data')
-  xlabel(tlo,'Day of trial')
-  ylabel(tlo,'Inflamation')
+  title("Min")
+  xlabel("Day of trial")
+  ylabel("Inflamation")
+  tlo=tiledlayout(1, 2);
+  title(tlo,"Per day data")
+  xlabel(tlo,"Day of trial")
+  ylabel(tlo,"Inflamation")
   nexttile
   plot(per_day_max)
-  title('Max')
+  title("Max")
   nexttile
   plot(per_day_min)
-  title('Min')
+  title("Min")
 
 % ## Where is the `nexttile`?
   tiledlayout(3,5)
@@ -78,15 +85,16 @@
 
 
 % ## Clearing a figure
+  clf
 
 % ## Heatmaps
   heatmap(patient_data)
-  title('Inflammation')
-  xlabel('Day of trial')
-  ylabel('Patient number')
+  title("Inflammation")
+  xlabel("Day of trial")
+  ylabel("Patient number")
   imagesc(patient_data)
-  title('Inflammation')
-  xlabel('Day of trial')
-  ylabel('Patient number')
+  title("Inflammation")
+  xlabel("Day of trial")
+  ylabel("Patient number")
 
 

code/05-scripts.m

@@ -7,7 +7,7 @@
 % ## The MATLAB path
 
   % Load patient data
-  patient_data = readmatrix('data/base/inflammation-01.csv');
+  patient_data = readmatrix("data/base/inflammation-01.csv");
 
   % Compute global statistics
   g_mean = mean(patient_data(:));
@@ -20,12 +20,12 @@
   p_min = min(patient_data(5,:));
 
   % Compare patient vs global
-  disp('Patient 5:')
-  disp('High mean?')
+  disp("Patient 5:")
+  disp("High mean?")
   disp(p_mean > g_mean)
-  disp('Highest max?')
+  disp("Highest max?")
   disp(p_max == g_max)
-  disp('Lowest min?')
+  disp("Lowest min?")
   disp(p_min == g_min)
 
 % ## Comments
@@ -34,28 +34,27 @@
   clc
   patient_analysis
   % Load patient data
-  patient_data = readmatrix('data/base/inflammation-01.csv');
+  patient_data = readmatrix("data/base/inflammation-01.csv");
 
   % Compute global statistics
   g_mean = mean(patient_data(:));
   g_max = max(patient_data(:));
   g_min = min(patient_data(:));
 
-  patient_number = 8;
-
   % Compute patient statistics
+  patient_number = 8;
   p_mean = mean(patient_data(patient_number,:));
   p_max = max(patient_data(patient_number,:));
   p_min = min(patient_data(patient_number,:));
 
   % Compare patient vs global
-  disp('Patient:')
+  disp("Patient:")
   disp(patient_number)
-  disp('High mean?')
+  disp("High mean?")
   disp(p_mean > g_mean)
-  disp('Highest max?')
+  disp("Highest max?")
   disp(p_max == g_max)
-  disp('Lowest min?')
+  disp("Lowest min?")
   disp(p_min == g_min)
   patient_analysis
 
@@ -65,83 +64,74 @@
   help patient_analysis
 % ## Script for plotting
   edit src/plot_daily_average.m
-  % PLOT_DAILY_AVERAGE   Plots daily average inflammation accross patients.
-
-  % Load patient data
-  patient_data = readmatrix('data/base/inflammation-01.csv');
-
-  figure
-
-  % Plot average inflammation per day
-  plot(mean(patient_data, 1))
-  title('Daily average inflammation')
-  xlabel('Day of trial')
-  ylabel('Inflammation')
-  figure
-  plot_daily_average
-% ### Modified script for sub-plots
   % PLOT_DAILY_AVERAGE   Plots daily average, max and min inflammation accross patients.
 
   % Load patient data
-  patient_data = readmatrix('data/base/inflammation-01.csv');
+  patient_data = readmatrix("data/base/inflammation-01.csv");
 
-  figure
+  fig = figure;
 
   % Define tiled layout and labels
   tlo = tiledlayout(1,3);
-  xlabel(tlo,'Day of trial')
-  ylabel(tlo,'Inflammation')
+  xlabel(tlo,"Day of trial")
+  ylabel(tlo,"Inflammation")
 
   % Plot average inflammation per day
   nexttile
   plot(mean(patient_data, 1))
-  title('Average')
+  title("Average")
 
   % Plot max inflammation per day
   nexttile
   plot(max(patient_data, [], 1))
-  title('Max')
+  title("Max")
 
   % Plot min inflammation per day
   nexttile
   plot(min(patient_data, [], 1))
-  title('Min')
-  % Save plot in 'results' folder as png image:
-  print('results/daily_average_01','-dpng')
+  title("Min")
+  figure
+  plot_daily_average
+% ### Saving figures
+  % Save plot in "results" folder as png image:
+  saveas(fig,"results/daily_average_01.png")
 
-  % Save plot in 'results' folder as png image:
-  saveas(gcf,'results/daily_average_01.png')
+% ## Getting the current figure
+  % Save plot in "results" folder as png image:
+  saveas(gcf,"results/daily_average_01.png")
+  gcf == fig
 
+% ### Hiding figures
   % PLOT_DAILY_AVERAGE   Saves plot of daily average, max and min inflammation accross patients.
 
   % Load patient data
-  patient_data = readmatrix('data/base/inflammation-01.csv');
+  patient_data = readmatrix("data/base/inflammation-01.csv");
 
-  figure(visible='off')
+  fig = figure(Visible='off');
 
   % Define tiled layout and labels
   tlo = tiledlayout(1,3);
-  xlabel(tlo,'Day of trial')
-  ylabel(tlo,'Inflammation')
+  xlabel(tlo,"Day of trial")
+  ylabel(tlo,"Inflammation")
 
   % Plot average inflammation per day
   nexttile
   plot(mean(patient_data, 1))
-  title('Average')
+  title("Average")
 
   % Plot max inflammation per day
   nexttile
   plot(max(patient_data, [], 1))
-  title('Max')
+  title("Max")
 
   % Plot min inflammation per day
   nexttile
   plot(min(patient_data, [], 1))
-  title('Min')
+  title("Min")
 
-  % Save plot in 'results' folder as png image:
-  saveas(gcf,'results/daily_average_01.png')
+  % Save plot in "results" folder as png image:
+  saveas(fig,"results/daily_average_01.png")
 
-  close()
+  close(fig)
 
 

episodes/02-arrays.md

@@ -1,7 +1,7 @@
 ---
 title: Arrays
 teaching: 30
-exercises: 30
+exercises: 10
 ---
 
 ::::::::::::::::::::::::::::::::::::::: objectives
@@ -47,7 +47,7 @@ Z =
 yields a 3×3 array.
 If we want a single row and 5 columns, we need to remember that MATLAB reads `rows`×`columns`, so
 ```matlab
->> Z = zeros(1x5)
+>> Z = zeros(1,5)
 ```
 ```output
 Z =

episodes/03-loading_data.md

@@ -1,6 +1,6 @@
 ---
 title: Loading data
-teaching: 35
+teaching: 25
 exercises: 15
 ---
 
@@ -453,6 +453,42 @@ ans =
 ```
 So patient 31 has the maximum inflamation level.
 
+<br>
+
+::::::::::::  solution
+
+## Alternative solution
+
+We can only do this because we had already calculated `per_patient_max`.
+However, there is another way of doing this.
+Just as we used `find` to locate the patients that had a maximum inflammation value equal to the global maximum,
+we can find the value from the whole data set:
+```matlab
+>> find(patient_data == global_max)
+```
+```
+ans =
+     391
+```
+However, this resulted in a rather odd number.
+This number represents the linear index of the global maximum.
+Linear indices result from counting through the elements in the first column, then continue the count on the second column and so on.
+Luckily, there is a function to convert this linear index into a row and number column, `ind2sub`.
+We need to provide the size of our array, and the linear index, i.e. `ind2sub([60,40],391)`.
+We also need to provide space for both outputs (the row and column numbers), so we call it as `[r,c]=ind2sub([60,40],391)`.
+ternatively, we can get the size and index inside the call:
+```matlab
+>> [r,c]=ind2sub(size(patient_data),find(patient_data == global_max))
+```
+```
+r =
+    31
+c =
+     7
+```
+
+::::::::::::
+
 :::::::::::::::::::::::::
 
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