I have a problem dealing with 3rd dimension plot for three variables.
I have three matrices: X, Y and Z with parameters in this type:
(x_1, y_1, z_1)
(x_2, y_2, z_2)
.
(x_n, y_n, z_n)
and I can show them in separate points by scatter3D plot. blow is my code that objective[0] is x, objective[1] is y and objective[2] indicates z:
from mpl_toolkits import mplot3d
import matplotlib.pyplot as plt
fig = plt.figure()
ax = plt.axes(projection='3d')
ax.scatter3D([s.objectives[0] for s in algorithm.result],
[s.objectives[1] for s in algorithm.result],
[s.objectives[2] for s in algorithm.result])
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
But, my problem is when I want to show a line between points. I want to have a line between points in direction of changing in one of the matrices, for example x.
I mean, if my goal is based on x and suppose that x is continuously increasing, i want to have a line between the point that has x_1 and the point that has x_2, then between point that has x_2 to point that has x_3 and ....
Actually this line shows, how my three parameters are changing when x is changing (when x is increased).
To do it, I used plot3D, blow is my code:
ax.plot3D([s.objectives[0] for s in algorithm.result],
[s.objectives[1] for s in algorithm.result],
[s.objectives[2] for s in algorithm.result])
But in the figure I have line between each point to all other points. I mean ((n*n-1)/2) lines instead of n-1 lines.
How can i achieve my goal with mplot3d? or other ways.
Related
I am programming in Python 3 and I have data structured like this:
coordinates = [(0.15,0.25),(0.35,0.25),(0.55,0.45),(0.65,0.10),(0.15,0.25)]
These are coordinates. Within each pair, the first number is the x coordinate and the second one the y coordinate. Some of the coordinates repeat themselves. I want to plot these data like this:
The coordinates that are most frequently found should appear either as higher intensity (i.e., brighter) points or as points with a different color (for example, red for very frequent coordinates and blue for very infrequent coordinates). Don't worry about the circle and semicircle. That's irrelevant. Is there a matplotlib plot that can do this? Scatter plots do not work because they do not report on the frequency with which each coordinate is found. They just create a cloud.
The answer is:
import matplotlib.pyplot as plt
from scipy.stats import kde
import numpy as np
xvalues = np.random.normal(loc=0.5,scale=0.01,size=50000)
yvalues = np.random.normal(loc=0.25,scale=0.1,size=50000)
nbins=300
k = kde.gaussian_kde([xvalues,yvalues])
xi, yi = np.mgrid[0:1:nbins*1j,0:1:nbins*1j]
zi = k(np.vstack([xi.flatten(),yi.flatten()]))
fig, ax = plt.subplots()
ax.pcolormesh(xi, yi, zi.reshape(xi.shape), shading='auto', cmap=plt.cm.hot)
x = np.arange(0.0,1.01,0.01,dtype=np.float64)
y = np.sqrt((0.5*0.5)-((x-0.5)*(x-0.5)))
ax.axis([0,1,0,0.55])
ax.set_ylabel('S', fontsize=16)
ax.set_xlabel('G', fontsize=16)
ax.tick_params(labelsize=12, width=3)
ax.plot(x,y,'w--')
plt.show()
I have a plot that looks as follows:
I want to put labels for both the lineplot and the markers in red. However the legend is not appearning because its the plot is taking out its space.
Update
it turns out I cannot put several strings in plt.legend()
I made the figure bigger by using the following:
fig = plt.gcf()
fig.set_size_inches(18.5, 10.5)
However now I have only one label in the legend, with the marker appearing on the lineplot while I rather want two: one for the marker alone and another for the line alone:
Updated code:
plt.plot(range(len(y)), y, '-bD', c='blue', markerfacecolor='red', markeredgecolor='k', markevery=rare_cases, label='%s' % target_var_name)
fig = plt.gcf()
fig.set_size_inches(18.5, 10.5)
# changed this over here
plt.legend()
plt.savefig(output_folder + fig_name)
plt.close()
What you want to do (have two labels for a single object) is not completely impossible but it's MUCH easier to plot separately the line and the rare values, e.g.
# boilerplate
import numpy as np
import matplotlib.pyplot as plt
# synthesize some data
N = 501
t = np.linspace(0, 10, N)
s = np.sin(np.pi*t)
rare = np.zeros(N, dtype=bool); rare[:20]=True; np.random.shuffle(rare)
plt.plot(t, s, label='Curve')
plt.scatter(t[rare], s[rare], label='rare')
plt.legend()
plt.show()
Update
[...] it turns out I cannot put several strings in plt.legend()
Well, you can, as long as ① the several strings are in an iterable (a tuple or a list) and ② the number of strings (i.e., labels) equals the number of artists (i.e., thingies) in the plot.
plt.legend(('a', 'b', 'c'))
I am trying to modify the legend of a figure that contains two overlayed scatter plots. More specifically, I want two legend handles and labels: the first handle will contain multiple points (each colored differently), while the other handle consists of a single point.
As per this related question, I can modify the legend handle to show multiple points, each one being a different color.
As per this similar question, I am aware that I can change the number of points shown by a specified handle. However, this applies the change to all handles in the legend. Can it be applied to one handle only?
My goal is to combine both approaches. Is there a way to do this?
In case it isn't clear, I would like to modify the embedded figure (see below) such that Z vs X handle shows only one-point next to the corresponding legend label, while leaving the Y vs X handle unchanged.
My failed attempt at producing such a figure is below:
To replicate this figure, one can run the code below:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.legend_handler import HandlerTuple, HandlerRegularPolyCollection
class ScatterHandler(HandlerRegularPolyCollection):
def update_prop(self, legend_handle, orig_handle, legend):
""" """
legend._set_artist_props(legend_handle)
legend_handle.set_clip_box(None)
legend_handle.set_clip_path(None)
def create_collection(self, orig_handle, sizes, offsets, transOffset):
""" """
p = type(orig_handle)([orig_handle.get_paths()[0]], sizes=sizes, offsets=offsets, transOffset=transOffset, cmap=orig_handle.get_cmap(), norm=orig_handle.norm)
a = orig_handle.get_array()
if type(a) != type(None):
p.set_array(np.linspace(a.min(), a.max(), len(offsets)))
else:
self._update_prop(p, orig_handle)
return p
x = np.arange(10)
y = np.sin(x)
z = np.cos(x)
fig, ax = plt.subplots()
hy = ax.scatter(x, y, cmap='plasma', c=y, label='Y vs X')
hz = ax.scatter(x, z, color='k', label='Z vs X')
ax.grid(color='k', linestyle=':', alpha=0.3)
fig.subplots_adjust(bottom=0.2)
handler_map = {type(hz) : ScatterHandler()}
fig.legend(mode='expand', ncol=2, loc='lower center', handler_map=handler_map, scatterpoints=5)
plt.show()
plt.close(fig)
One solution that I do not like is to create two legends - one for Z vs X and one for Y vs X. But, my actual use case involves an optional number of handles (which can exceed two) and I would prefer not having to calculate the optimal width/height of each legend box. How else can this problem be approached?
This is a dirty trick and not an elegant solution, but you can set the sizes of other points for Z-X legend to 0. Just change your last two lines to the following.
leg = fig.legend(mode='expand', ncol=2, loc='lower center', handler_map=handler_map, scatterpoints=5)
# The third dot of the second legend stays the same size, others are set to 0
leg.legendHandles[1].set_sizes([0,0,leg.legendHandles[1].get_sizes()[2],0,0])
The result is as shown.
I have a figure with many different plots (contour plots and lots of other stuff). I want to extract the contour plot to another single figure to see more details. But I fail how to do so.
Have a look on this code:
import numpy as np
from matplotlib import gridspec as gs, pyplot as plt
# Figure 1 with many different plots.
fig1 = plt.figure()
gridSpec = gs.GridSpec(2, 3)
for i in range(6):
fig1.add_subplot(gridSpec[i])
# Create contour plot
x = np.arange(-3.0, 3.0, 0.02)
y = np.arange(-2.0, 2.0, 0.01)
X, Y = np.meshgrid(x, y)
Z1 = np.exp(-X**2 - Y**2)
Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
Z = (Z1 - Z2) ** 4
# Plot it to a particular axes.
ax1 = fig1.axes[2]
contour = ax1.contour(X, Y, Z)
# Try to copy the contour plot to another figure (with only 1 subplot).
fig2, ax2 = plt.subplots()
# How to copy the content of ax1 to ax2?
plt.show()
This will give me the following:
I want to create a second figure with only 1 subplot and its content should be the same as you can see in top right corner of the first figure with 6 subplots.
First thing I tried was
ax2.add_collection(contour.collections[1])
but I got the error message
RuntimeError: Can not put single artist in more than one figure
This is because the content is already plottet to figure 1, so it is not possible to plot it to figure 2 as well. So I tried to make a copy of the contour plot:
from copy import deepcopy
ax2.add_collection(deepcopy(contour.collections[1]))
But this will get me a new error that copiing is not possible ...
NotImplementedError: TransformNode instances can not be copied. Consider using frozen() instead.
So .. what can I do? Any ideas for that problem? :)
Thanks a lot!
(Python 3.7.4, Matplotlib 3.1.1)
I have a subplot with a single legend entry. I am placing the legend at the bottom of the figure and using mode='expand'; however, the single legend entry is placed to the very left of the legend box. To my understanding, changing kwargs such as bbox_to_anchor changes the legend box parameters but not the parameters of the symbols/text within. Below is an example to reproduce my issue.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-10, 10, 21)
y = np.exp(x)
z = x **2
fig, axes = plt.subplots(nrows=1, ncols=2)
axes[0].plot(x, y, color='r', label='exponential')
axes[1].plot(x, z, color='b')
# handles, labels = axes[0].get_legend_handles_labels()
plt.subplots_adjust(bottom=0.125)
fig.legend(mode='expand', loc='lower center')
plt.show()
plt.close(fig)
This code produces . How can I change the position of the symbol and text such that they are centered in the legend box?
PS: I am aware that exponential is a bad label for this subplot since it only describes the first subfigure. But, this is just for examples-sake so that I can apply it to my actual use-case.
The legend entries are placed using a HPacker object. This does not allow to be centered. The behaviour is rather that those HPackers are "justified" (similar to the "justify" option in common word processing software).
A workaround would be to create three (or any odd number of) legend entries, such that the desired entry is in the middle. This would be accomplished via the ncol argument and the use of "dummy" entries (which might be transparent and have no associated label).
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-10, 10, 21)
y = np.exp(x)
z = x **2
fig, axes = plt.subplots(nrows=1, ncols=2)
fig.subplots_adjust(bottom=0.125)
l1, = axes[0].plot(x, y, color='r', label='exponential')
axes[1].plot(x, z, color='b')
dummy = plt.Line2D([],[], alpha=0)
fig.legend(handles=[dummy, l1, dummy],
mode='expand', loc='lower center', ncol=3)
plt.show()