Python/matplotlib
From Christoph's Personal Wiki
matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy.
Examples
import matplotlib.pyplot as plt import numpy as np
- Simple plot
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 10, 10) # start, end, num points in-between
y = np.sin(x)
plt.plot(x, y)
plt.show()
# Add labels
plt.plot(x, y)
plt.xlabel("Time")
plt.ylabel("Some function of time")
plt.title("Example plot")
plt.show()
# Increase number of points in-between
x = np.linspace(0, 10, 100)
y = np.sin(x)
plt.plot(x,y)
plt.show() # => much smoother line
- Scatter plots
import os
os.chdir('../linear_regression_class/')
import pandas as pd
A = pd.read_csv('data_1d.csv', header=None).as_matrix()
A.head()
A.info
A.shape
x = A[:,0]
y = A[:,1]
plt.scatter(x, y)
plt.show()
x_line = np.linspace(0, 100, 100)
y_line = 2*x_line + 1
plt.scatter(x, y)
plt.plot(x_line, y_line)
plt.show()
- Histograms
# Using same data from above plt.hist(x) R = np.random.random(10000) plt.hist(R) plt.show() plt.hist(R, bins=20) plt.show() # normally distributed y_actual = 2*x + 1 residuals = y - y_actual plt.hist(residuals) plt.show() # more-or-less a bell curve (with so few data points)
- Plotting images
- An image is just a matrix of numbers
- A(i,j) represents the pixel intensity at coordinate (i,j)
- JPG or PNG are not matrices because they are compressed
- Decompress them to get back a matrix
- In this example, we will use the MNIST dataset (handwritten digits, 0-9)
- Digit Recognizer via Kaggle
- Download the "train.csv" file
- 28x28 = 784 pixels => 784 columns in CSV file
import pandas as pd
df = pd.read_csv("train.csv")
df.shape # => (42000, 785)
M = df.as_matrix()
M[0,0] # => digit "1"
im = M[0, 1:] # get 0th row and all columns except column 0
im.shape
im = im.reshape(28, 28)
im.shape
plt.imshow(im)
plt.show()
plt.imshow(im, cmap='gray')
plt.show()
plt.imshow(255 - im, cmap='gray')
plt.show()
M[20,0] # => digit "8"
im = M[20, 1:]
im.shape
im = im.reshape(28, 28)
plt.imshow(255 - im, cmap='gray')
plt.show()
