Notebook to teach for loops in python

_includes/script_for_loop/script_for_loop_python.py

@@ -0,0 +1,164 @@
+# %%
+# Create a bunch of example images to simulate a typical analysis problem
+# np.random.randint(lower,upper,size): generates random integers from lower to upper
+# .reshape: reshapes a np.array to new dimensions
+import numpy as np
+image1 = np.random.randint(0,255,100).reshape((10,10))
+image2 = np.random.randint(0,255,100).reshape((10,10))
+image3 = np.random.randint(0,255,100).reshape((10,10))
+image4 = np.random.randint(0,255,100).reshape((10,10))
+image5 = np.random.randint(0,255,100).reshape((10,10))
+image6 = np.random.randint(0,255,100).reshape((10,10))
+image7 = np.random.randint(0,255,100).reshape((10,10))
+image8 = np.random.randint(0,255,100).reshape((10,10))
+image9 = np.random.randint(0,255,100).reshape((10,10))
+image10 = np.random.randint(0,255,100).reshape((10,10))
+
+# Calculate the mean of every image
+# Oberserve that it is very tedious and error prone
+print(f'Image {1} has an avg intensity of {image1.mean()}.')
+print(f'Image {2} has an avg intensity of {image2.mean()}.')
+print(f'Image {3} has an avg intensity of {image3.mean()}.')
+print(f'Image {4} has an avg intensity of {image4.mean()}.')
+print(f'Image {5} has an avg intensity of {image5.mean()}.')
+print(f'Image {6} has an avg intensity of {image6.mean()}.')
+print(f'Image {7} has an avg intensity of {image7.mean()}.')
+print(f'Image {8} has an avg intensity of {image8.mean()}.')
+print(f'Image {9} has an avg intensity of {image9.mean()}.')
+print(f'Image {10} has an avg intensity of {image10.mean()}.')
+
+# %%
+# Create a for loop
+# Typical notation in C-style: for i=0, i<10, i++ {do something}
+# For loop in python
+# Observe the difference in notation
+for i in [0,1,2,3,4,5,6,7,8,9]:
+    print(i)
+
+# use range
+# Observe that range is actually a generator producing values on the fly
+print(range(10))
+print(type(range(10)))
+for i in range(10):
+    print(i)
+
+# %%
+# Anything iterable can be iterated over with a for loop
+# Observe that:
+# - list content don't matter
+# - that the iterator will always be overwritten by the next item
+for i in ['a','b','c',1,2,3,[1,2,3],1.5,2.7]:
+    print(f'"i" has the value "{i}" and type "{type(i)}"')
+
+# %%
+# Use a for loop for the example in the beginning
+# First pack images into a list for looping over
+image_list = [image1,image2,image3,image4,image5,image6,image7,image8,image9,image10]
+
+# Loop over images and calculate the mean
+for image in image_list:
+    print(f'Avg intensity: {image.mean()}')
+
+# Excersize: Modify the loop to calculate the standard deviation
+for image in image_list:
+    print(f'Intensity standard deviation: {image.std()}')
+
+#%%
+# Iterate with an index
+number_of_images = len(image_list)
+print(number_of_images)
+for i in range(number_of_images):
+    print(f'Image {i} has an avg intensity of {image_list[i].mean()}.')
+
+# Iterate over two or more list (with the same length)
+for i,image in zip(range(number_of_images),image_list):
+    print(f'Image {i} has an avg intensity of {image.mean()}.')
+
+# Iterate with additional index
+for i,image in enumerate(image_list):
+    print(f'Image {i} has an avg intensity of {image.mean()}.')
+
+# %%
+# For loops but advanced
+
+# %%
+# list comprehension
+squares = []
+for i in range(10):
+    squares.append(i**2)
+print(squares)
+# use list comprehension
+squares = [i**2 for i in range(10)]
+print(squares)
+
+# usefull for creating an filepath iterable
+from pathlib import Path
+[file for file in Path().cwd().iterdir()]
+
+# %%
+# for loop with if
+for x in range(10):
+    if x != 0:
+        print(f'X: {x}, 1/X: {1/x}')
+
+# for loop with if and else
+for x in range(10):
+    if x == 0:
+        print(f'X: {x}, 1/X: Division by {x} not defined.')
+    else:
+        print(f'X: {x}, 1/X: {1/x}')
+
+# %%
+# for loop with continue and break
+# Usage:
+# - skip files/data for processing
+# - debugging
+# continue
+for x in range(10):
+    if x==0:
+        continue
+    print(f'X: {x}, 1/X: {1/x}')
+
+# break
+for x in range(10):
+    if x==3:
+        break
+    print(x)
+
+# %%
+# Nested loops
+for x in range(1,4):
+    for y in range(1,4):
+        print(f'X: {x}, Y: {y}, X*Y: {x*y}')
+
+# Nested lists
+for sublist in [[1,2,3],[4,5,6],[7,8,9]]:
+    for i in sublist:
+        print(i)
+
+# np.array
+# Observe that you iterate only over the first dimension when using simple loop
+array = np.random.randint(0,10,100).reshape(10,10)
+print(array.shape)
+for i in array:
+    print(i)
+
+for row in array:
+    for i in row:
+        print(i)
+
+# %%
+# Looping over pandas DataFrame
+# Observe that
+# - looping with iterrows always gives an index
+# - the second variable will always be a pandas Series object
+import pandas as pd
+df = pd.DataFrame({
+    'a':[1,2,3],
+    'b':[4,5,6]})
+print(df)
+for i,row in df.iterrows():
+    print(type(row))
+    value_a = row['a']
+    value_b = row['b']
+    print(f'Row index {i}\nColumn value "a": {value_a} and Column value "b": {value_b}')

_modules/script_for_loop.md

@@ -36,6 +36,7 @@ activities:
  - ["ImageJ Macro, loop structure", "script_for_loop/activities/script_for_loop_loopstructure.ijm"]
  - ["ImageJ Macro, example no loop", "script_for_loop/activities/script_for_loop_measure_distances_noloop.ijm"]
  - ["ImageJ Macro, example with loop", "script_for_loop/activities/script_for_loop_measure_distances_withloop.ijm"]
+ - ["Python, for loop", "script_for_loop/script_for_loop_python.py"]
 
 exercise_preface: |
  ### Multiple erosion