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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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4
chapter.mk
View File

@ -8,8 +8,8 @@ PYPDFFILES=$(PYFILES:.py=.pdf)
pythonplots : $(PYPDFFILES)
$(PYPDFFILES) : %.pdf: %.py
python3 $<
$(PYPDFFILES) : %.pdf: %.py ../../plotstyle.py
PYTHONPATH="../../" python3 $<
cleanpythonplots :
rm -f $(PYPDFFILES)

86
plotstyle.py Normal file
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@ -0,0 +1,86 @@
import matplotlib as mpl
import matplotlib.pyplot as plt
# colors:
colors = {
'red': '#CC0000',
'orange': '#FF9900',
'lightorange': '#FFCC00',
'yellow': '#FFFF66',
'green': '#99FF00',
'blue': '#0000FF'
}
def show_spines(ax, spines):
""" Show and hide spines.
Parameters
----------
ax: matplotlib figure, matplotlib axis, or list of matplotlib axes
Axis whose spines and ticks are manipulated.
If figure, then apply manipulations on all axes of the figure.
If list of axes, apply manipulations on each of the given axes.
spines: string
Specify which spines and ticks should be shown. All other ones or hidden.
'l' is the left spine, 'r' the right spine, 't' the top one and 'b' the bottom one.
E.g. 'lb' shows the left and bottom spine, and hides the top and and right spines,
as well as their tick marks and labels.
'' shows no spines at all.
'lrtb' shows all spines and tick marks.
"""
# collect spine visibility:
xspines = []
if 't' in spines:
xspines.append('top')
if 'b' in spines:
xspines.append('bottom')
yspines = []
if 'l' in spines:
yspines.append('left')
if 'r' in spines:
yspines.append('right')
# collect axes:
if isinstance(ax, (list, tuple)):
axs = ax
else:
axs = ax.get_axes()
if not isinstance(axs, (list, tuple)):
axs = [axs]
for ax in axs:
# hide spines:
if not 'top' in xspines:
ax.spines['top'].set_visible(False)
if not 'bottom' in xspines:
ax.spines['bottom'].set_visible(False)
if not 'left' in yspines:
ax.spines['left'].set_visible(False)
if not 'right' in yspines:
ax.spines['right'].set_visible(False)
# ticks:
if len(xspines) == 0:
ax.xaxis.set_ticks_position('none')
ax.set_xticks([])
elif len(xspines) == 1:
ax.xaxis.set_ticks_position(xspines[0])
else:
ax.xaxis.set_ticks_position('both')
if len(yspines) == 0:
ax.yaxis.set_ticks_position('none')
ax.set_yticks([])
elif len(yspines) == 1:
ax.yaxis.set_ticks_position(yspines[0])
else:
ax.yaxis.set_ticks_position('both')
# initialization:
plt.xkcd()
mpl.rcParams['figure.facecolor'] = 'white'
mpl.rcParams['xtick.direction'] = 'out'
mpl.rcParams['ytick.direction'] = 'out'
mpl.rcParams['xtick.major.size'] = 6
mpl.rcParams['ytick.major.size'] = 6
mpl.rcParams['xtick.major.width'] = 1.25
mpl.rcParams['ytick.major.width'] = 1.25

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()