AttributeError: 'numpy.flatiter' object has no attribute 'get_offsets' in python - python-2.7

Question

In a scatter plot matrix, I would like to draw a region in every subplot and print the points that are included in the region. I found the LassoSelector widget, which does exactly that. I am trying to extend its functionality for more than one subplots. I am getting the following error: self.xys = collection.get_offsets(),
AttributeError: 'numpy.flatiter' object has no attribute 'get_offsets'.
when the line selector = SelectFromCollection(axes, ax.flat) is in the for loop, and I am getting the error: self.canvas = ax.figure.canvas,AttributeError: 'numpy.ndarray' object has no attribute 'figure' when the line selector = SelectFromCollection(ax, ax.flat) is outside of the loop. Why does this happen?
Here is my code:
from __future__ import print_function
import numpy as np
from matplotlib.widgets import LassoSelector
from matplotlib.path import Path
class SelectFromCollection(object):
"""Select indices from a matplotlib collection using `LassoSelector`.
Selected indices are saved in the `ind` attribute. This tool highlights
selected points by fading them out (i.e., reducing their alpha values).
If your collection has alpha < 1, this tool will permanently alter them.
Note that this tool selects collection objects based on their *origins*
(i.e., `offsets`).
Parameters
----------
ax : :class:`~matplotlib.axes.Axes`
Axes to interact with.
collection : :class:`matplotlib.collections.Collection` subclass
Collection you want to select from.
alpha_other : 0 <= float <= 1
To highlight a selection, this tool sets all selected points to an
alpha value of 1 and non-selected points to `alpha_other`.
"""
def __init__(self, ax, collection, alpha_other=0.3):
self.canvas = ax.figure.canvas
self.collection = collection
self.alpha_other = alpha_other
self.xys = collection.get_offsets()
self.Npts = len(self.xys)
# Ensure that we have separate colors for each object
self.fc = collection.get_facecolors()
if len(self.fc) == 0:
raise ValueError('Collection must have a facecolor')
elif len(self.fc) == 1:
self.fc = np.tile(self.fc, self.Npts).reshape(self.Npts, -1)
self.lasso = LassoSelector(ax, onselect=self.onselect)
self.ind = []
def onselect(self, verts):
path = Path(verts)
self.ind = np.nonzero([path.contains_point(xy) for xy in self.xys])[0]
self.fc[:, -1] = self.alpha_other
self.fc[self.ind, -1] = 1
self.collection.set_facecolors(self.fc)
self.canvas.draw_idle()
print(selector.xys[selector.ind])
#selector.disconnect()
def disconnect(self):
self.lasso.disconnect_events()
self.fc[:, -1] = 1
self.collection.set_facecolors(self.fc)
self.canvas.draw_idle()
if __name__ == '__main__':
import matplotlib.pyplot as plt
plt.ion()
data=np.loadtxt(r"data.txt")
x = data[:, 3]
x1 = data[:, 4]
y = data[:,5]
y1 = data[:,6]
fig, ax = plt.subplots(nrows=2, ncols=2, squeeze=True)
for axes, marker in zip(ax.flat, ['o', 'o']):
ax.flat[0].plot(x, y, 'r', ls='', marker=marker)
ax.flat[1].plot(x, x1,'r', ls='', marker=marker)
ax.flat[2].plot(x, y1,'r', ls='', marker=marker)
ax.flat[3].plot(y, x1,'r', ls='', marker=marker)
selector = SelectFromCollection(ax, ax.flat)
plt.show(block=True)
plt.draw()

Answer 1

Ok, I found a few problems that are causing your code not to work properly. There we go:
Firts of all, you modified the SelectFromCollection class that you got from the LassoSelector example to print every selected point, but forgot a detail:
class SelectFromCollection(object):
def __init__(self, ax, collection, alpha_other=0.3):
# ...
# No changes here...
# ...
def onselect(self, verts):
path = Path(verts)
self.ind = np.nonzero([path.contains_point(xy) for xy in self.xys])[0]
self.fc[:, -1] = self.alpha_other
self.fc[self.ind, -1] = 1
self.collection.set_facecolors(self.fc)
self.canvas.draw_idle()
print(self.xys[self.ind]) # <- THIS LINE HAS CHANGED!!!
#selector.disconnect()
def disconnect(self):
# ...
# No changes here...
# ...
Now you can use multiple instances of SelectFromCollection.
Then, you are also creating only one instance of SelectFromCollection (so only one subplot would react). Furthermore, according to the doctsring the second argument the __init__ method expects is a matplotlib.collections.Collection instance.
Instead you are passing it a numpy array (in fact a numpy.Flatiter) that contains two Axes instances. If you look at the example, there it gets a Collection instance returned by the scattercommand (they use scatter instead of plot).
All in all, and restiling the loop, this is my version
if __name__ == '__main__':
import matplotlib.pyplot as plt
data=np.random.rand(3,100)
xdata = data[:-1] # all rows but last
y = data[-1] # last row
fig, axes = plt.subplots(nrows=1, ncols=2, squeeze=True)
markers = ['o','^']
selectors =[]
for i in xrange(xdata.shape[0]):
pts = axes[i].scatter(xdata[i], y, c='r', marker=markers[i])
selectors.append(SelectFromCollection(axes[i], pts))
plt.show()
EDIT
If you want to do more plots, it is not hard. You can try to write more synthetic code with a for loop and so on, but an easier solution is to write directly the repetitions of the code:
if __name__ == '__main__':
import matplotlib.pyplot as plt
data=np.loadtxt(r"data.txt")
x = data[:, 3]
x1 = data[:, 4]
y = data[:,5]
y1 = data[:,6]
fig, axes = plt.subplots(nrows=2, ncols=2)
pts1 = axes[0,0].scatter(x, y, c='r', marker='o')
select1 = SelectFromCollection(axes[0,0], pts1)
pts2 = axes[1,0].scatter(x, x1, c='r', marker='o')
select2 = SelectFromCollection(axes[1,0], pts2)
pts3 = axes[0,1].scatter(x, y1, c='r', marker='o')
select3 = SelectFromCollection(axes[0,1], pts3)
pts4 = axes[1,1].scatter(y, x1, c='r', marker='o')
select4 = SelectFromCollection(axes[1,1], pts4)
plt.show()
Still, it is necessary that you change the definition of the SelectFromCollection class as I said above.