I have followed this example (Drawing lines between two plots in Matplotlib) but am running into problems. I believe it has something to do with the fact that I essentially have two different y points, but am not sure how to amend the code to fix it. I would like the line to start at one point and end at the other point directly below it, as well as plotting for all lines.
fig=plt.figure(figsize=(22,10), dpi=150)
ax1 = fig.add_subplot(1, 1, 1)
ax2 = ax1.twinx()
n = 10
y1 = np.random.random(n)
y2 = np.random.random(n) + 1
x1 = np.arange(n)
ax1.scatter(x1, y1)
ax2.scatter(x1, y2)
i = 1
xy = (x1[i],y1[i])
con = ConnectionPatch(xyA=xy, xyB=xy, coordsA="data", coordsB="data",
axesA=ax1, axesB=ax2, color="red")
ax2.add_artist(con)
ax1.plot(x1[i],y1[i],'g+',markersize=12)
ax2.plot(x1[i],y1[i],'g+',markersize=12)
Just iterate over zipped (x, y1, y2):
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import ConnectionPatch
fig = plt.figure(figsize=(10, 5), dpi=100)
ax1 = fig.add_subplot(1, 1, 1)
ax2 = ax1.twinx()
n = 10
y1 = np.random.random(n)
y2 = np.random.random(n) + 1
x1 = np.arange(n)
# I add some colors blue for left y-axis, red for right y-axis
ax1.scatter(x1, y1, c='b')
ax2.scatter(x1, y2, c='r')
# Now iterate over paired x, and 2 y values:
for xi, y1i, y2i in zip(x1, y1, y2):
con = ConnectionPatch(
xyA=(xi, y1i),
xyB=(xi, y2i),
coordsA="data",
coordsB="data",
axesA=ax1,
axesB=ax2,
color='g',
)
ax1.add_artist(con)
plt.show()
Out:
Related
Recently I have managed to do the animation. But now I can't make the tangent line went as I want (not even displayed yet). The formula of the tangent line is y=(2/r)(sqrt(1-((r^2)/4))-1)x +r. The formula is obtained from 2 circles equation (C1 and C2). C1(blue) : x^2+y^2=r^2, and C2(green) : (x-1)^2+y^2=1. My goal is to obtain this kind of animation as and my current animation goes like this .
How should the code looks like when the animation looks like the reference one (the first one)? Any comments and answers would be very helpful for me as a beginner, I appreciate it, Thank you.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots(1)
line, = ax.plot([], [], lw=2)
line2, = ax.plot([], [], lw=2)
ax.set_xlim(-5,5)
ax.set_ylim(-5,5)
# theta goes from 0 to 2pi
theta = np.linspace(0, 2*np.pi, 100)
# the radius of the circle
r = np.sqrt(1)
r2 = np.sqrt(4)
# compute x1 and x2
x1 = 1+r*np.cos(theta)
y1 = r*np.sin(theta)
x2 = r2*np.cos(theta)
y2 = r2*np.sin(theta)
# Move left y-axis and bottim x-axis to centre, passing through (0,0)
ax.spines['left'].set_position('center')
ax.spines['bottom'].set_position('center')
# Eliminate upper and right axes
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
# Show ticks in the left and lower axes only
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
def init():
line.set_data([], [])
return line,
def init2():
line.set_data([], [])
return line2,
def animate(i):
x2 = np.sqrt(i)*np.cos(theta)
y2 = np.sqrt(i)*np.sin(theta)
line.set_data(x2, y2)
return line,
def animate2(i):
x3 = np.linspace(0,r2**2,100)
y3 = ((2/r2)*(np.sqrt(1-(r2**2)/4)-1)*x3)+r2
line.set_data(x3, y3)
return line,
# create the figure
ax.plot(x1,y1)
ax.set_aspect(1)
plt.grid()
anim = animation.FuncAnimation(fig, animate, init_func=init,
interval=1000, blit=False,\
frames=np.hstack([range(0),
range(4)[::-1]]))
anim2 = animation.FuncAnimation(fig, animate2, init_func=init2,
interval=1000, blit=False)
plt.show()
f = r"D:/UNPAR/Semester 2/Pemrograman Komputer/Project/SK.gif"
writergif = animation.PillowWriter(fps=30)
anim.save(f, writer=writergif)
The animation functions need to be combined into one. We will combine them into an initialization function and an animation function.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots(1)
line, = ax.plot([], [], lw=2, color='green')
line2, = ax.plot([], [], lw=2, color='red')
ax.set_xlim(-5,5)
ax.set_ylim(-5,5)
# theta goes from 0 to 2pi
theta = np.linspace(0, 2*np.pi, 100)
# the radius of the circle
r = np.sqrt(1)
r2 = np.sqrt(4)
# compute x1 and x2
x1 = 1+r*np.cos(theta)
y1 = r*np.sin(theta)
x2 = r2*np.cos(theta)
y2 = r2*np.sin(theta)
# create the figure
ax.plot(x1,y1)
ax.set_aspect(1)
plt.grid()
def init():
line.set_data([], [])
line2.set_data([], [])
return line,line2
def animate(i):
x2 = np.sqrt(i)*np.cos(theta)
y2 = np.sqrt(i)*np.sin(theta)
print(max(y2))
line.set_data(x2, y2)
x3 = [0, 4-(0.1*i)]
y3 = [max(y2), 0]
line2.set_data(x3, y3)
return line,line2
anim = animation.FuncAnimation(fig, animate, init_func=init, interval=1000, blit=False,frames=np.arange(10,0,-1))
plt.show()
I want to fill between 3 lines in the following problem. Here's the code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
# Construct lines
# x > 0
x = np.linspace(0, 20, 2000)
# C1
y1 = (36-2*x)/6
# C2
y2 = (30-5*x)/3
# C3
y3 = (40-8*x)/2
# C4
# y4 = 0*x
# Make plot
plt.plot(x, y1, label=r'$2 x_{1} + 6 x_{2}\leq 36$')
plt.plot(x, y2, label=r'$x_{1} + 3 x_{2}\leq 30$')
plt.plot(x, y3, label=r'$x_{1} + 2 x_{2}\leq 40$')
# plt.plot(x, y4, label=r'$x_{1}, x_{2}\geq 0$')
plt.xlim((0, 16))
plt.ylim((0, 11))
plt.xlabel(r'$x_1$')
plt.ylabel(r'$x_2$')
# Fill feasible region
y5 = np.minimum(0, 0)
y6 = np.maximum(y2, y3)
plt.fill_between(x, y1, y2, color='grey', alpha=0.5,
interpolate=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
I'd like to fill what is hatched in red in the image below (between y1, y2, y3, and zero)
You could fill between zero and the minimum of the three curves:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 20, 2000)
y1 = (36 - 2 * x) / 6
y2 = (30 - 5 * x) / 3
y3 = (40 - 8 * x) / 2
plt.plot(x, y1, label=r'$2 x_{1} + 6 x_{2}\leq 36$')
plt.plot(x, y2, label=r'$x_{1} + 3 x_{2}\leq 30$')
plt.plot(x, y3, label=r'$x_{1} + 2 x_{2}\leq 40$')
plt.xlim((0, 16))
plt.ylim((0, 11))
plt.xlabel(r'$x_1$')
plt.ylabel(r'$x_2$')
plt.fill_between(x, y1, y2, color='grey', alpha=0.5,
interpolate=True)
plt.fill_between(x, 0, np.min([y1, y2, y3], axis=0), color='red', alpha=0.5, hatch='//',
interpolate=True, label='$intersection$')
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
plt.tight_layout()
plt.show()
Note that:
np.vstack([y1, y2, y3]) creates a 3-row array from your 3 "y" arrays.
….min(0) computes minimum along each column, so it is actually
a minimum of your 3 source arrays (also with negative values for higher x).
….clip(min=0) transforms the above negative elements to 0.
So add to your code:
plt.fill_between(x, 0, np.vstack([y1, y2, y3]).min(0).clip(min=0),
color='yellow', alpha=0.5, interpolate=True)
e.g. after your first fill_between.
For your data, and code with the above instruction added, I got:
If you want, change the filling color to whatever suits your needs.
The goal is to fill the space between two arrays y1 and y2, similar to matplotlib's fill_between. But I don't want to fill the space with a polygon (for example with hatch='|'), but rather I want to draw the vertical lines only between the data points of the two arrays.
import matplotlib.pyplot as plt
import numpy as np
n = 10
y1 = np.random.random(n)
y2 = np.random.random(n) + 1
x1 = np.arange(n)
ax.fill_between(x1, y1, y2, facecolor='w', hatch='|')
Using a LineCollection could be handy if there are lots of lines in the game. Similar to the other answer, but less expensive:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
def draw_lines_between(*, x1=None, x2=None, y1, y2, ax=None, **kwargs):
ax = ax or plt.gca()
x1 = x1 if x1 is not None else np.arange(len(y1))
x2 = x2 if x2 is not None else x1
cl = LineCollection(np.stack((np.c_[x1, x2], np.c_[y1, y2]), axis=2), **kwargs)
ax.add_collection(cl)
return cl
n = 10
y1 = np.random.random(n)
y2 = np.random.random(n) + 1
x = np.arange(n)
color_list = [str(x) for x in np.round(np.linspace(0., 0.8, n), 2)]
fig, ax = plt.subplots()
ax.plot(x, y1, 'r')
ax.plot(x, y2, 'b')
draw_lines_between(ax=ax, x1=x, y1=y1, y2=y2, colors=color_list)
plt.show()
I wrote a little function which takes two arrays y1, y2 (x1, x2 are optional)
and connects their data points vertically.
def draw_lines_between(*, ax, x1=None, x2=None, y1, y2, color_list=None, **kwargs):
assert len(y1) == len(y2)
assert isinstance(color_list, list)
n = len(y1)
if x1 is None:
x1 = np.arange(n)
if x2 is None:
x2 = x1
if color_list is None:
color_list = [None for i in range(n)]
elif len(color_list) < n:
color_list = [color_list] * n
h = np.zeros(n, dtype=object)
for i in range(n):
h[i] = ax.plot((x1[i], x2[i]), (y1[i], y2[i]), color=color_list[i], **kwargs)[0]
return h
import matplotlib.pyplot as plt
import numpy as np
n = 10
y1 = np.random.random(n)
y2 = np.random.random(n) + 1
x1 = np.arange(n)
color_list = [str(x) for x in np.round(np.linspace(0., 0.8, n), 2)]
fig, ax = plt.subplots()
ax.plot(x1, y1, 'r')
ax.plot(x1, y2, 'b')
draw_lines_between(ax=ax, x1=x1, y1=y1, y2=y2, color_list=color_list)
Is it at all possible for me to make one set of subplots (with 2 plots) in a for loop that runs three times, and then fit the three sets of subplots into one main figure. The whole point of this is to be able to have 6 plots on one figure, but have a space between every other plot. I know how to have 6 plots in one figure, but I can only put space between every plot instead of every other plot. I hope my question makes sense. As for the data that I'm using, it is a pretty basic data set I'm using for practice right now. Each pair of plot share the same x-axis, which is why I don't want a space between them.
import matplotlib.pyplot as plt
x1 = [0,1,2,3,4,5]
y1 = [i*2 for i in x1]
y2 = [i*3 for i in x1]
x2 = [4,8,12,16,20]
y3 = [i*5 for i in x2]
y4 = [i*3 for i in x2]
x3 = [0,1,2,3,4,5]
y5 = [i*4 for i in x3]
y6 = [i*7 for i in x3]
fig = plt.figure(1,figsize=(5,5))
ax1 = plt.subplot(611)
ax1.plot(x1,y1)
ax2 = plt.subplot(612)
ax2.plot(x1,y2)
ax3 = plt.subplot(613)
ax3.plot(x2,y3)
ax4 = plt.subplot(614)
ax4.plot(x2,y4)
ax5 = plt.subplot(615)
ax5.plot(x3,y5)
ax6 = plt.subplot(616)
ax6.plot(x3,y6)
fig.subplots_adjust(hspace=0.5)
plt.show()
This is what I get:
Your code makes a graph with six sub-plots. If you make eight subplots and leave two of them empty, you get your added space. Here is the code I used, slightly modified from your code.
import matplotlib.pyplot as plt
x1 = [0,1,2,3,4,5]
y1 = [i*2 for i in x1]
y2 = [i*3 for i in x1]
x2 = [4,8,12,16,20]
y3 = [i*5 for i in x2]
y4 = [i*3 for i in x2]
x3 = [0,1,2,3,4,5]
y5 = [i*4 for i in x3]
y6 = [i*7 for i in x3]
fig = plt.figure(1,figsize=(5,7))
ax1 = plt.subplot(811)
ax1.plot(x1,y1)
ax2 = plt.subplot(812)
ax2.plot(x1,y2)
ax3 = plt.subplot(814)
ax3.plot(x2,y3)
ax4 = plt.subplot(815)
ax4.plot(x2,y4)
ax5 = plt.subplot(817)
ax5.plot(x3,y5)
ax6 = plt.subplot(818)
ax6.plot(x3,y6)
fig.subplots_adjust(hspace=0.5)
plt.show()
I get this result:
I had to increase the figure size height to 7 inches to accommodate the extra space. Is that what you want?
While I can get multiple lines on a chart and multiple bars on a chart - I cannot get a line and bar on the same chart using the same PeriodIndex.
Faux code follows ...
# play data
n = 100
x = pd.period_range('2001-01-01', periods=n, freq='M')
y1 = (Series(np.random.randn(n)).diff() + 5).tolist()
y2 = (Series(np.random.randn(n)).diff()).tolist()
df = pd.DataFrame({'bar':y2, 'line':y1}, index=x)
# let's plot
plt.figure()
ax = df['bar'].plot(kind='bar', label='bar')
df['line'].plot(kind='line', ax=ax, label='line')
plt.savefig('fred.png', dpi=200)
plt.close()
Any help will be greatly appreciated ...
The problem is: bar plots don't use index values as x axis, but use range(0, n). You can use twiny() to create a second axes that share yaxis with the bar axes, and draw line curve in this second axes.
The most difficult thing is how to align x-axis ticks. Here we define the align function, which will align ax2.get_xlim()[0] with x1 in ax1 and ax2.get_xlim()[1] with x2 in ax1:
def align_xaxis(ax2, ax1, x1, x2):
"maps xlim of ax2 to x1 and x2 in ax1"
(x1, _), (x2, _) = ax2.transData.inverted().transform(ax1.transData.transform([[x1, 0], [x2, 0]]))
xs, xe = ax2.get_xlim()
k, b = np.polyfit([x1, x2], [xs, xe], 1)
ax2.set_xlim(xs*k+b, xe*k+b)
Here is the full code:
from matplotlib import pyplot as plt
import pandas as pd
from pandas import Series
import numpy as np
n = 50
x = pd.period_range('2001-01-01', periods=n, freq='M')
y1 = (Series(np.random.randn(n)) + 5).tolist()
y2 = (Series(np.random.randn(n))).tolist()
df = pd.DataFrame({'bar':y2, 'line':y1}, index=x)
# let's plot
plt.figure(figsize=(20, 4))
ax1 = df['bar'].plot(kind='bar', label='bar')
ax2 = ax1.twiny()
df['line'].plot(kind='line', label='line', ax=ax2)
ax2.grid(color="red", axis="x")
def align_xaxis(ax2, ax1, x1, x2):
"maps xlim of ax2 to x1 and x2 in ax1"
(x1, _), (x2, _) = ax2.transData.inverted().transform(ax1.transData.transform([[x1, 0], [x2, 0]]))
xs, xe = ax2.get_xlim()
k, b = np.polyfit([x1, x2], [xs, xe], 1)
ax2.set_xlim(xs*k+b, xe*k+b)
align_xaxis(ax2, ax1, 0, n-1)
and the output: