85 lines
2.5 KiB
Python
85 lines
2.5 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib.transforms import Bbox
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def create_data():
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m = 0.75
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n= -40
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x = np.arange(10.,110., 2.5)
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y = m * x + n;
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rng = np.random.RandomState(37281)
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noise = rng.randn(len(x))*15
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y += noise
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return x, y, m, n
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def plot_data(ax, x, y):
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ax.scatter(x, y, marker='o', color='b', s=40)
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ax.spines["right"].set_visible(False)
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ax.spines["top"].set_visible(False)
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ax.yaxis.set_ticks_position('left')
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ax.xaxis.set_ticks_position('bottom')
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ax.tick_params(direction="out", width=1.25)
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ax.tick_params(direction="out", width=1.25)
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ax.set_xlabel('Input x')
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ax.set_ylabel('Output y')
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ax.set_xlim(0, 120)
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ax.set_ylim(-80, 80)
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ax.set_xticks(np.arange(0,121, 40))
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ax.set_yticks(np.arange(-80,81, 40))
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def plot_data_slopes(ax, x, y, m, n):
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ax.scatter(x, y, marker='o', color='b', s=40)
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xx = np.asarray([2, 118])
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for i in np.linspace(0.3*m, 2.0*m, 5):
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ax.plot(xx, i*xx+n, color="r", lw=2)
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ax.spines["right"].set_visible(False)
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ax.spines["top"].set_visible(False)
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ax.yaxis.set_ticks_position('left')
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ax.xaxis.set_ticks_position('bottom')
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ax.tick_params(direction="out", width=1.25)
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ax.tick_params(direction="out", width=1.25)
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ax.set_xlabel('Input x')
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#ax.set_ylabel('Output y')
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ax.set_xlim(0, 120)
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ax.set_ylim(-80, 80)
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ax.set_xticks(np.arange(0,121, 40))
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ax.set_yticks(np.arange(-80,81, 40))
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def plot_data_intercepts(ax, x, y, m, n):
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ax.scatter(x, y, marker='o', color='b', s=40)
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xx = np.asarray([2, 118])
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for i in np.linspace(n-1*n, n+1*n, 5):
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ax.plot(xx, m*xx + i, color="r", lw=2)
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ax.spines["right"].set_visible(False)
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ax.spines["top"].set_visible(False)
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ax.yaxis.set_ticks_position('left')
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ax.xaxis.set_ticks_position('bottom')
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ax.tick_params(direction="out", width=1.25)
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ax.tick_params(direction="out", width=1.25)
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ax.set_xlabel('Input x')
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#ax.set_ylabel('Output y')
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ax.set_xlim(0, 120)
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ax.set_ylim(-80, 80)
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ax.set_xticks(np.arange(0,121, 40))
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ax.set_yticks(np.arange(-80,81, 40))
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if __name__ == "__main__":
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x, y, m, n = create_data()
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plt.xkcd()
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fig = plt.figure()
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ax = fig.add_subplot(1, 3, 1)
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plot_data(ax, x, y)
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ax = fig.add_subplot(1, 3, 2)
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plot_data_slopes(ax, x, y, m, n)
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ax = fig.add_subplot(1, 3, 3)
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plot_data_intercepts(ax, x, y, m, n)
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fig.set_facecolor("white")
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fig.set_size_inches(7., 2.6)
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fig.tight_layout()
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fig.savefig("lin_regress.pdf")
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plt.close()
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