This is a self-correcting activity generated by nbgrader. Fill in any place that says YOUR CODE HERE or YOUR ANSWER HERE. Run subsequent cells to check your code.

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NumPy

Environment setup

import platform

print(f"Python version: {platform.python_version()}")
assert platform.python_version_tuple() >= ("3", "6")

import numpy as np
import matplotlib.pyplot as plt

print(f"NumPy version: {np.__version__}")

# Setup plots
%matplotlib inline
plt.rcParams["figure.figsize"] = 10, 8
%config InlineBackend.figure_format = "retina"

# Import ML packages
import sklearn

print(f"scikit-learn version: {sklearn.__version__}")

from sklearn.datasets import load_sample_images

Part 1: Tensor Basics

Question

Create a 2D tensor (a matrix) with dimensions (3,4) containing integer values of your choice. Store this tensor in a variable named x.

# YOUR CODE HERE

print(x)

# Assert dimensions
assert x.ndim == 2
assert x.shape == (3, 4)

# Assert data type 
assert issubclass(x.dtype.type, np.integer)

Question

Update the shape of the previous tensor so that it has dimensions (6,2).

# YOUR CODE HERE

print(x)

# Assert tensor dimensions
assert x.ndim == 2
assert x.shape == (6, 2)

Question

Change the type of the previous tensor values to float32.

# YOUR CODE HERE

print(x)

# Assert data type
assert issubclass(x.dtype.type, np.floating)

Part 2: Image Management

# Load samples images
images = np.asarray(load_sample_images().images)
print(f"Number of images: {len(images)}. Images tensor: {images.shape}")

first_image = images[0]
# Display first image
plt.imshow(first_image)

# Print details about first image
print(f"First image: {first_image.shape}")

Question

Store in variables respectively named rgb_values_topleft and rgb_values_bottomright the RGB values of the top-left and bottom-right pixels of the first image.

# YOUR CODE HERE

print(f"Top-left pixel: {rgb_values_topleft}")
assert rgb_values_topleft.shape == (3,)

print(f"Bottom-right pixel: {rgb_values_bottomright}")
assert rgb_values_bottomright.shape == (3,)

Question

Reshape the previous images tensor into a 2D tensor.

# YOUR CODE HERE

# Assert new tensor dimensions
assert images.shape == (2, 819840)

# Assert RGB values of top-left in first image
assert np.array_equal(rgb_values_topleft, images[0,:3])

# Assert RGB values of bottom-right pixel in first image
assert np.array_equal(rgb_values_bottomright, images[0,819837:])