Read and return all values from an array - matplotlib

Question

Elaborated question:
Let me clarify my question. I want to plot a list of array output as a 2D scatter plot with polarity along x axis subjectivity along y axis and modality values that ranges between -1 and 1 determines the type of marker( o,x, ^, v)
output
polarities: [ 0. 0. 0. 0.]
subjectivity: [ 0.1 0. 0. 0. ]
modalities: [ 1. -0.25 1. 1. ]
The modified code with limited marker value for 2 range.
print "polarities: ", a[:,0]
print "subjectivity: ", a[:,1]
print "modalities: ", a[:,2]
def markers(r):
markers = np.array(r, dtype=np.object)
markers[(r>=0)] = 'o'
markers[r<0] = 'x'
return markers.tolist()
def colors(s):
colors = np.array(s, dtype=np.object)
colors[(s>=0)] = 'g'
colors[s<0] = 'r'
return colors.tolist()
fig=plt.figure()
ax=fig.add_subplot(111)
ax.scatter(a[:,0], a[:,1], marker = markers(a[:,2]), color= colors(a[:,0]), s=100, picker=5)
My intent is to check the modality value and return one of the four markers.
if I hardcore 'o' it returns the plot.
ax.scatter(a[:,0], a[:,1], marker = markers('o'), color= colors(a[:,0]), s=100, picker=5)
As a trial i tried to mimic the color function and pass it as a[:,2] but hit a shell output error
ValueError: Unrecognized marker style ['o', 'x', 'o', 'o']
The question is: Is my approach wrong? or how to make it recognize the marker style?
Edit1
Trying to get the m value between 0 and .5
with this code
ax.scatter (p[0<m<=.5], s[0<m<=.5], marker = "v", color= colors(a[:,0]), s=100, picker=5)
yields this error
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
How to range m value between 0 and .5 in the example given in answer 2.

Answer 1

It's not clear from your question, but I assume your array a is of shape (N,3) and so your arrays s and r are actual arrays and not scalars.
First off, you cannot have several markers with one call of scatter(). If you want your plot to have several markers, you'll have to slice your array correctly and do several scatter() for each of your markers.
Regarding the colors, your problem is that your function colors(r) only return one color where it should return an array of colors (with the same number of elements as a[:,0]). Like such:
def colors(s):
colors = np.array(s, dtype=np.object)
colors[(s>0.25)&(s<0.75)] = 'g'
colors[s>=0.75] = 'b'
colors[s<=0.25] = 'r'
return colors.tolist()
a = np.random.random((100,))
b = np.random.random((100,))
plt.scatter(a,b,color=colors(b))
ANSWER TO YOUR EDIT 1:
You seem to be on the right track, you'll have to do as many scatter() calls as you have markers.
Your error comes from the slicing index [0<m<=.5] which you cannot use like that. You have to use the full notation [(m>0.)&(m<=.5)]

Answer 2

As Diziet pointed out, plt.scatter() cannot handle several markers. You therefore need to make one scatter plot per marker-category. This can be done my conditioning on the property which should be reflected by the marker. In this case:
import numpy as np
import matplotlib.pyplot as plt
p = np.array( [ 0. , 0.2 , -0.3 , 0.2] )
s = np.array( [ 0.1, 0., 0., 0.3 ] )
m = np.array( [ 1., -0.25, 1. , -0.6 ] )
colors = np.array([(0.8*(1-x), 0.7*x, 0) for x in np.ceil(p)])
fig=plt.figure()
ax=fig.add_subplot(111)
ax.scatter(p[m>=0], s[m>=0], marker = "o", color= colors[m>=0], s=100)
ax.scatter(p[m<0], s[m<0], marker = "s", color= colors[m<0], s=100)
ax.set_xlabel("polarity")
ax.set_ylabel("subjectivity")
plt.show()