Enhance data visualization examples with 1D, 2D, and 3D plotting; add…

… image manipulation techniques and examples

learn/learn-python/module-3/4-displaying-data.qmd

@@ -36,6 +36,25 @@ import matplotlib.pyplot as plot
 array_1x7 = np.array([1, 2, 2, 4, 1, 1, 7])
 
 plot.plot(array_1x7)
+
+
+
+plot.show()
+```
+
+## Let's plot some 1D data
+
+![](/media/1d-plot-pyplot-basic.png){.centre-full-image .top-55}
+
+
+## Let's plot some 1D data
+
+```{.python filename="pyplot_1d.py" code-line-numbers="6-8"}
+import matplotlib.pyplot as plot
+
+array_1x7 = np.array([1, 2, 2, 4, 1, 1, 7])
+
+plot.plot(array_1x7)
 plot.title("1x7 Array Visualization")
 plot.xlabel("Index")
 plot.ylabel("Value")
@@ -62,6 +81,28 @@ plot.show()
 array_2x7 = np.array([[1, 2, 3, 4, 5, 6, 7],
                       [8, 9, 10, 11, 12, 13, 13]])
 
+plot.imshow(array_2x7)
+
+
+
+
+
+plot.show()
+```
+
+## Plotting 2D data
+
+![](/media/2d-heatmap-pyplot-basic.png){.centre-full-image .top-55}
+
+
+## Plotting 2D data
+
+* Heatmaps are useful
+
+```{.python filename="pyplot_2d.py" code-line-numbers="4-9"}
+array_2x7 = np.array([[1, 2, 3, 4, 5, 6, 7],
+                      [8, 9, 10, 11, 12, 13, 13]])
+
 plot.imshow(array_2x7, cmap='viridis', aspect='auto')
 plot.colorbar()
 plot.title("2x7 Array Heatmap")
@@ -71,16 +112,64 @@ plot.ylabel("Rows")
 plot.show()
 ```
 
+
 ## Plotting 2D data
 
 ![](/media/2d-heatmap-pyplot.png){.centre-full-image .top-55}
 
 
+## Plotting 3D data
+
+* Here is some 3-dimensional data to plot.
+
+```{.python filename="pyplot_3d.py"}
+array_3D = np.array([[[0, 80, 2, 3, 4, 5, 6],
+                      [7, 8, 9, 10, 111, 12, 13]],
+                     [[1, 2, 3, 4, 5, 6, 7],
+                      [8, 9, 10, 11, 122, 13, 14]],
+                     [[15, 16, 17, 18, 19, 20, 21],
+                      [22, 23, 24, 25, 26, 27, 28]]])
+```
+
+
 ## Plotting 3D data {.smaller}
 
 * 3D scatter plots are useful
 
-```{.python filename="pyplot_3d.py"}
+```{.python filename="pyplot_3d.py" code-line-numbers="1-7,20"}
+fig = plot.figure()
+ax = fig.add_subplot(111, projection='3d')
+
+x, y, z = np.indices(array_3D.shape)
+values = array_3D.flatten()
+
+sc = ax.scatter(x.flatten(), y.flatten(), z.flatten(), c=values, cmap='viridis', s=100)
+
+
+
+
+
+
+
+
+
+
+
+
+plot.show()
+```
+
+
+## Plotting 3D data
+
+![](/media/3d-scatterplot-pyplot-basic.png){.centre-full-image .top-55}
+
+
+## Plotting 3D data {.smaller}
+
+* 3D scatter plots are useful
+
+```{.python filename="pyplot_3d.py" code-line-numbers="8-19"}
 fig = plot.figure()
 ax = fig.add_subplot(111, projection='3d')
 
@@ -108,7 +197,6 @@ plot.show()
 
 ![](/media/3d-scatterplot-pyplot.png){.centre-full-image .top-55}
 
-
 ## Now try it yourself!
 
 * Go to the Lesson 3 folder.

learn/learn-python/module-3/5-manipulating-images.qmd

@@ -5,19 +5,159 @@ format: revealjs
 logo: /media/ldd-logo.png
 css: /slides.css
 title-slide-attributes:
-    data-background-image: /media/jupyter-notebook-logo.png
-    data-background-opacity: "0.1"
+    data-background-image: /media/women-at-beach-sunset.jpg
+    data-background-opacity: "0.5"
 ---
 
 
+## Python image library
+
+* Image
+
+
+## Introduction to Image Manipulation
+
+* Image manipulation involves altering or transforming images using various techniques and tools. 
+* This can include resizing, cropping, rotating, adjusting colours, and applying filters.
+
+
+## Loading Images
+
+* To manipulate images, we first need to load them into our environment. 
+* In Python, we can use the `PIL` (also called Pillow) module from `Image`.
+
+
+```{.python filename="images.py" code-line-numbers="1-2"}
+from PIL import Image
+
+import matplotlib.pyplot as plt
+
+img_1 = Image.open('hand-x-ray.jpg')
+
+plt.imshow(img_1)
+
+plt.show()
+```
+
+## Loading Images
+
+* You will also need to use the pyplot module.
+
+
+```{.python filename="images.py" code-line-numbers="3"}
+from PIL import Image
+
+import matplotlib.pyplot as plt
+
+img_1 = Image.open('hand-x-ray.jpg')
+
+plt.imshow(img_1)
+
+plt.show()
+```
+
+
+## Loading Images
+
+* And then open the image file.
+
+
+```{.python filename="images.py" code-line-numbers="5"}
+from PIL import Image
+
+import matplotlib.pyplot as plt
+
+img_1 = Image.open('hand-x-ray.jpg')
+
+plt.imshow(img_1)
+
+plt.show()
+```
+
+## Loading Images {background-image="/media/two-spotlights.jpg" background-opacity="0.4"}
+
+* And then prepare to show the image and then actually show it.
+
+```{.python filename="images.py" code-line-numbers="7-9"}
+from PIL import Image
+
+import matplotlib.pyplot as plt
+
+img_1 = Image.open('hand-x-ray.jpg')
+
+plt.imshow(img_1)
+
+plt.show()
+```
+
+
+## Resizing Images {background-image="/media/two-tape-measures.jpg" background-opacity="0.4"}
+
+* To resize an image, you can use the `resize` method from the `PIL` library.
+* `img_1.resize((width, height))` needs a tuple with the new width and height.
+
+```{.python filename="resize.py"}
+resized_img_1 = img_1.resize((50, 300))
+
+plt.imshow(resized_img_1)
+plt.show()
+```
+
+
+## Cropping Images {background-image="/media/yin-yang-hands.jpg" background-opacity="0.4"}
+
+
+* Define the top-left and bottom-right coordinates of the area you want to crop.
+* Then use the `crop` method from the `PIL` library.
+
+```{.python filename="crop.py"}
+box = (3900, 2900, 6000, 5500)
+
+cropped_img_1 = img_1.crop(box)
+```
+
+
+## Rotate Images {background-image="/media/spirit-level.jpg" background-opacity="0.4"}
+
+* Use the `rotate` method from the `PIL` library to rotate an image.
+* Just provide an angle in degrees.
+
+```{.python filename="rotate.py"}
+rotated_img_2 = img_2.rotate(10)
+```
+
+
+## Inverting Images {background-image="/media/inverted-landscape-glass-sphere.jpg" background-opacity="0.4"}
+
+
+* Invert with the PIL library using the `invert` method.
+
+```{.python filename="rotate.py"}
+from PIL import ImageOps
+
+inverted_img_3 = ImageOps.invert(img_3)
+```
+
+
+## Change file type {background-image="/media/file-cabinets-old.jpg" background-opacity="0.4"}
+
+* Use the `save` method from the `PIL` library to save the image in a different format.
+
+```{.python filename="rotate.py"}
+bmp_filename = 'converted_image_3.bmp'
+
+inverted_img_3.save(bmp_filename)
+```
+
+
 ## Now try it yourself!
 
 * Go to the Lesson 4 folder.
 * Open `lesson_4.ipynb`.
 * Don't forget to ask your tutor if you need help.
 * See you in 40 minutes.
 
-If you finish lesson 4, you can try your hand at lesson 5.
+If you finish lesson 4 (but no need to rush), you can try your hand at lesson 5.
 
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