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added global plotstyle.py providing common formatting and colors

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This commit is contained in:
Jan Benda
2019-12-20 23:08:51 +01:00
parent ebff6cf5ad
commit 6d05e5277c
5 changed files with 113 additions and 60 deletions
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42
regression/lecture/cubicerrors.py
View File

@@ -1,5 +1,6 @@
import matplotlib.pyplot as plt
import numpy as np
from plotstyle import colors, show_spines
def create_data():
# wikipedia:
@@ -15,18 +16,13 @@ def create_data():
def plot_data(ax, x, y, c):
ax.scatter(x, y, marker='o', color='b', s=40, zorder=10)
ax.scatter(x, y, marker='o', color=colors['blue'], s=40, zorder=10)
xx = np.linspace(2.1, 3.9, 100)
ax.plot(xx, c*xx**3.0, color='#CC0000', lw=2, zorder=5)
ax.plot(xx, c*xx**3.0, color=colors['red'], lw=2, zorder=5)
for cc in [0.25*c, 0.5*c, 2.0*c, 4.0*c]:
ax.plot(xx, cc*xx**3.0, color='#FF9900', lw=1.5, zorder=5)
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(direction="out", width=1.25)
ax.tick_params(direction="out", width=1.25)
ax.plot(xx, cc*xx**3.0, color=colors['orange'], lw=1.5, zorder=5)
show_spines(ax, 'lb')
ax.set_xlabel('Size x / m')
ax.set_ylabel('Weight y / kg')
ax.set_xlim(2, 4)
@@ -36,12 +32,7 @@ def plot_data(ax, x, y, c):
def plot_data_errors(ax, x, y, c):
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(direction="out", width=1.25)
ax.tick_params(direction="out", width=1.25)
show_spines(ax, 'lb')
ax.set_xlabel('Size x / m')
#ax.set_ylabel('Weight y / kg')
ax.set_xlim(2, 4)
@@ -54,23 +45,18 @@ def plot_data_errors(ax, x, y, c):
xytext=(3.4, 70), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(0.9,1.0),
connectionstyle="angle3,angleA=50,angleB=-30") )
ax.scatter(x[:40], y[:40], color='b', s=10, zorder=0)
ax.scatter(x[:40], y[:40], color=colors['blue'], s=10, zorder=0)
inxs = [3, 10, 11, 17, 18, 21, 28, 30, 33]
ax.scatter(x[inxs], y[inxs], color='b', s=40, zorder=10)
ax.scatter(x[inxs], y[inxs], color=colors['blue'], s=40, zorder=10)
xx = np.linspace(2.1, 3.9, 100)
ax.plot(xx, c*xx**3.0, color='#CC0000', lw=2)
ax.plot(xx, c*xx**3.0, color=colors['red'], lw=2)
for i in inxs :
xx = [x[i], x[i]]
yy = [c*x[i]**3.0, y[i]]
ax.plot(xx, yy, color='#FF9900', lw=2, zorder=5)
ax.plot(xx, yy, color=colors['orange'], lw=2, zorder=5)
def plot_error_hist(ax, x, y, c):
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(direction="out", width=1.25)
ax.tick_params(direction="out", width=1.25)
show_spines(ax, 'lb')
ax.set_xlabel('Squared error')
ax.set_ylabel('Frequency')
bins = np.arange(0.0, 1250.0, 100)
@@ -85,18 +71,16 @@ def plot_error_hist(ax, x, y, c):
xytext=(800, 3), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(0.0,0.2),
connectionstyle="angle3,angleA=10,angleB=90") )
ax.hist(errors, bins, color='#FF9900')
ax.hist(errors, bins, color=colors['orange'])
if __name__ == "__main__":
x, y, c = create_data()
plt.xkcd()
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(7., 2.6))
plot_data(ax1, x, y, c)
plot_data_errors(ax2, x, y, c)
#plot_error_hist(ax2, x, y, c)
fig.set_facecolor("white")
fig.tight_layout()
fig.savefig("cubicerrors.pdf")
plt.close()

16
regression/lecture/cubicfunc.py
View File

@@ -1,5 +1,6 @@
import matplotlib.pyplot as plt
import numpy as np
from plotstyle import colors, show_spines
if __name__ == "__main__":
# wikipedia:
@@ -12,21 +13,15 @@ if __name__ == "__main__":
noise = rng.randn(len(x))*50
y += noise
plt.xkcd()
fig, ax = plt.subplots(figsize=(7., 3.6))
ax.scatter(x, y, marker='o', color='b', s=40, zorder=10)
ax.scatter(x, y, marker='o', color=colors['blue'], s=40, zorder=10)
xx = np.linspace(2.1, 3.9, 100)
ax.plot(xx, c*xx**3.0, color='#CC0000', lw=3, zorder=5)
ax.plot(xx, c*xx**3.0, color=colors['red'], lw=3, zorder=5)
for cc in [0.25*c, 0.5*c, 2.0*c, 4.0*c]:
ax.plot(xx, cc*xx**3.0, color='#FF9900', lw=2, zorder=5)
ax.plot(xx, cc*xx**3.0, color=colors['orange'], lw=2, zorder=5)
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(direction="out", width=1.25)
ax.tick_params(direction="out", width=1.25)
show_spines(ax, 'lb')
ax.set_xlabel('Size x / m')
ax.set_ylabel('Weight y / kg')
ax.set_xlim(2, 4)
@@ -34,7 +29,6 @@ if __name__ == "__main__":
ax.set_xticks(np.arange(2.0, 4.1, 0.5))
ax.set_yticks(np.arange(0, 401, 100))
fig.set_facecolor("white")
fig.subplots_adjust(0.11, 0.16, 0.98, 0.97)
fig.savefig("cubicfunc.pdf")
plt.close()

25
regression/lecture/cubicmse.py
View File

@@ -1,5 +1,6 @@
import matplotlib.pyplot as plt
import numpy as np
from plotstyle import colors, show_spines
def create_data():
# wikipedia:
@@ -38,9 +39,9 @@ def plot_mse(ax, x, y, c, cs):
for i, cc in enumerate(ccs):
mses[i] = np.mean((y-(cc*x**3.0))**2.0)
ax.plot(ccs, mses, 'b', lw=2, zorder=10)
ax.scatter(cs, ms, color='#cc0000', s=40, zorder=20)
ax.scatter(cs[-1], ms[-1], color='#FF9900', s=60, zorder=30)
ax.plot(ccs, mses, colors['blue'], lw=2, zorder=10)
ax.scatter(cs, ms, color=colors['red'], s=40, zorder=20)
ax.scatter(cs[-1], ms[-1], color=colors['orange'], s=60, zorder=30)
for i in range(4):
ax.annotate('',
xy=(cs[i+1]+0.2, ms[i+1]), xycoords='data',
@@ -49,12 +50,7 @@ def plot_mse(ax, x, y, c, cs):
connectionstyle="angle3,angleA=10,angleB=70") )
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(direction="out", width=1.25)
ax.tick_params(direction="out", width=1.25)
show_spines(ax, 'lb')
ax.set_xlabel('c')
ax.set_ylabel('mean squared error')
ax.set_xlim(0, 10)
@@ -63,14 +59,9 @@ def plot_mse(ax, x, y, c, cs):
ax.set_yticks(np.arange(0, 30001, 10000))
def plot_descent(ax, cs, mses):
ax.plot(np.arange(len(mses))+1, mses, '-o', c='#cc0000', mew=0, ms=8)
ax.plot(np.arange(len(mses))+1, mses, '-o', c=colors['red'], mew=0, ms=8)
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(direction="out", width=1.25)
ax.tick_params(direction="out", width=1.25)
show_spines(ax, 'lb')
ax.set_xlabel('iteration')
#ax.set_ylabel('mean squared error')
ax.set_xlim(0, 10.5)
@@ -83,11 +74,9 @@ def plot_descent(ax, cs, mses):
if __name__ == "__main__":
x, y, c = create_data()
cs, mses = gradient_descent(x, y)
plt.xkcd()
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(7., 2.6))
plot_mse(ax1, x, y, c, cs)
plot_descent(ax2, cs, mses)
fig.set_facecolor("white")
fig.tight_layout()
fig.savefig("cubicmse.pdf")
plt.close()