I want to create a scatter plot matrix that will consist of some subplots. I extracted my data from the TXT file and created an array of the form (x,y,z,p1,p2,p3,p4). The first three columns of the array represent the x, y, z coordinates from the original image from which this data comes from, and the last four columns (p1, p2, p3, p4) are some other parameters. Therefore, in each row of the array, the parameters p1, p2, p3, p4 have the same coordinates (x, y, z). In the scatter plot, I want to visualize each parameter p_i (e.g. p1) with respect to another p_i (e.g. p2, p3, p4).
I want to draw an area of interest (ROI) in each subtitle, highlight the points that are included in the ROI in each subtitle. In each subheading, various parameters are visualized (for example, p1 vs p2), but for one point in each subheading there is another point with the same coordinates x, y, z in the remaining subsets. I implemented a ROI drawing using the Lassomatplotlib example . An example of how this code is implemented is shown in the following figure.
There is a malfunction in my implementation. I can draw a lasso in each subtitle, but the dots are highlighted only when lasso is drawn in a specific subtitle, which corresponds to the first function call LassoManagerin my code (in my code selector1). As you can see in the following figure, the initial value is assigned to lassos, which can be drawn in different subheadings, but only the identifier that matches in selector 1 is used, which causes a code malfunction, regardless of which subheading I drew the ROI.
Here is my code:
"""
Show how to use a lasso to select a set of points and get the indices
of the selected points. A callback is used to change the color of the
selected points
This is currently a proof-of-concept implementation (though it is
usable as is). There will be some refinement of the API.
"""
from matplotlib.widgets import Lasso
from matplotlib.colors import colorConverter
from matplotlib.collections import RegularPolyCollection
from matplotlib import path
import matplotlib.pyplot as plt
import numpy as np
class Datum(object):
colorin = colorConverter.to_rgba('red')
colorout = colorConverter.to_rgba('blue')
def __init__(self, x, y, include=False):
self.x = x
self.y = y
if include: self.color = self.colorin
else: self.color = self.colorout
class LassoManager(object):
#class for highlighting region of points within a Lasso
def __init__(self, ax, data):
self.axes = ax
self.canvas = ax.figure.canvas
self.data = data
self.Nxy = len(data)
facecolors = [d.color for d in data]
self.xys = [(d.x, d.y) for d in data]
fig = ax.figure
self.collection = RegularPolyCollection(
fig.dpi, 6, sizes=(1,),
facecolors=facecolors,
offsets = self.xys,
transOffset = ax.transData)
ax.add_collection(self.collection)
self.cid = self.canvas.mpl_connect('button_press_event', self.onpress)
def callback(self, verts):
facecolors = self.collection.get_facecolors()
print "The id of this lasso is", id(self)
p = path.Path(verts)
ind = p.contains_points(self.xys)
#ind prints boolean array of points in subplot where true means that the point is included
for i in range(len(self.xys)):
if ind[i]:
# facecolors[i] = Datum.colorin
axes[0][0].plot(x[i], y[i], 'ro', ls='', picker=3)
axes[2][0].plot(x[i], y1[i], 'ro', ls='', picker=3)
axes[1][0].plot(x[i], x1[i], 'ro', ls='', picker=3)
axes[1][4].plot(y[i], x1[i], 'ro', ls='', picker=3)
axes[2][5].plot(x1[i], y1[i], 'ro', ls='', picker=3)
axes[2][6].plot(y[i], y1[i], 'ro', ls='', picker=3)
# print ind[i], x[i], y[i], x1[i], y1[i]
else:
# facecolors[i] = Datum.colorout
axes[0][0].plot(x[i], y[i], 'bo', ls='', picker=3)
axes[2][0].plot(x[i], y1[i], 'bo', ls='', picker=3)
axes[1][0].plot(x[i], x1[i], 'bo', ls='', picker=3)
axes[1][7].plot(y[i], x1[i], 'bo', ls='', picker=3)
axes[2][8].plot(x1[i], y1[i], 'bo', ls='', picker=3)
axes[2][9].plot(y[i], y1[i], 'bo', ls='', picker=3)
plt.draw()
self.canvas.draw_idle()
self.canvas.widgetlock.release(self.lasso)
del self.lasso
# noinspection PyArgumentList
def onpress(self, event):
if self.canvas.widgetlock.locked(): return
if event.inaxes is None: return
self.lasso = Lasso(event.inaxes, (event.xdata, event.ydata), self.callback)
# acquire a lock on the widget drawing
self.canvas.widgetlock(self.lasso)
if __name__ == '__main__':
dat = np.loadtxt(r"parameters.txt")
x, y = dat[:, 3], dat[:, 4] #p1,p2
x1, y1 = dat[:, 5], dat[:, 6] #p3,p4
a = np.array([x,y]) #p1,p2
a = a.transpose()
b = np.array([x,y1]) #p1,p4
b = b.transpose()
c = np.array([x,x1]) #p1,p3
c = c.transpose()
d = np.array([y,x1]) #p3,p2
d = d.transpose()
e = np.array([x1,y1]) #p3,p4
e = e.transpose()
f = np.array([y,y1]) ##p2, p4
f = f.transpose()
data = []
data0 = [Datum(*xy) for xy in a] #p1,p2
data.append(data0)
data1 = [Datum(*xy) for xy in b] #p1,p4
data.append(data1)
data2 = [Datum(*xy) for xy in c] #p1,p3
data.append(data2)
data3 = [Datum(*xy) for xy in d] #p3,p2
data.append(data3)
data4 = [Datum(*xy) for xy in e] #p3,p4
data.append(data4)
data5 = [Datum(*xy) for xy in f] #p2, p4
data.append(data5)
#print data
#print len(data)
fig, axes = plt.subplots(ncols=3, nrows=3)
axes[0][0].plot(x, y, 'bo', ls='', picker=3)
axes[0][0].set_xlabel('p1')
axes[0][0].set_ylabel('p2')
axes[0][0].set_xlim((min(x)-50, max(x)+50))
axes[0][0].set_ylim((min(y)-50, max(y)+50))
selector1 = LassoManager(axes[0][0], data[0])
print "selector1 is", id(selector1) #lman.append(l1)
#p1 vs p4
axes[2][0].plot(x, y1, 'bo', ls='', picker=3)
axes[2][0].set_xlabel('p1')
axes[2][0].set_ylabel('p4')
axes[2][0].set_xlim((min(x)-50, max(x)+50))
axes[2][0].set_ylim((min(y1)-40, max(y1)+50))
selector2 = LassoManager(axes[2][0], data[1])
print "selector2 is", id(selector2)
#p1 vs p3
axes[1][0].plot(x, x1, 'bo', ls='', picker=3)
axes[1][0].set_xlabel('p1')
axes[1][0].set_ylabel('p3')
axes[1][0].set_xlim((min(x)-50, max(x)+50))
axes[1][0].set_ylim((min(x1)-40, max(x1)+50))
selector3 = LassoManager(axes[1][0], data[2])
print "selector3 is", id(selector3)
#p2 vs p3
axes[1][10].plot(y, x1, 'bo', ls='', picker=3)
axes[1][11].set_xlabel('p2')
axes[1][12].set_ylabel('p3')
axes[1][13].set_xlim((min(y)-50, max(y)+50))
axes[1][14].set_ylim((min(x1)-40, max(x1)+50))
selector4 = LassoManager(axes[1][15], data[3])
print "selector4 is", id(selector4)
#p2 vs p4
axes[2][16].plot(y, y1, 'bo', ls='', picker=3)
axes[2][17].set_xlabel('p2')
axes[2][18].set_ylabel('p4')
axes[2][19].set_xlim((min(y)-50, max(y)+50))
axes[2][20].set_ylim((min(y1)-40, max(y1)+50))
selector5 = LassoManager(axes[2][21], data[5])
print "selector5 is", id(selector5)
#p3 vs p4
axes[2][22].plot(x1, y1, 'bo', ls='', picker=3)
axes[2][23].set_xlabel('p3')
axes[2][24].set_ylabel('p4')
axes[2][25].set_xlim((min(x1)-50, max(x1)+50))
axes[2][26].set_ylim((min(y1)-40, max(y1)+50))
selector6 = LassoManager(axes[2][27], data[4])
print "selector6 is", id(selector6)
#non-visible subplots
axes[0][28].plot(x,x)
axes[0][29].set_visible(False)
axes[0][30].plot(y,y)
axes[0][31].set_visible(False)
axes[1][32].plot(x1,x1)
axes[1][33].set_visible(False)
plt.subplots_adjust(left=0.1, right=0.95, wspace=0.6, hspace=0.7)
plt.show()
Why is this happening in my code? There is no error in the code, but it does not work correctly. Any help would be appreciated!