Interactive scatter plot with colorbar legend

Question

I have a 3D array (3,10).

I have a 2D scatter plot, where the color and size of the markers is dependent on the 3rd column. I get stuck on two things: trying to have the legend show the color and/or size, and trying to make the labels interactive so that I can move them (so that they do not overlap). It is tricky to explain; I hope my code below will bring some clarity.

The code

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

aha = [0.1872, 0.0101, 0.0166, 0.0164, 0.0164, 0.0170, 0.0187, 0.0188, 0.0652, 0.0102]
ahaa = [0.2872, 0.0301, 0.0466, 0.0364, 0.0564, 0.0670, 0.0287, 0.0888, 0.0852, 0.0502]
dist = [0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2]
mod = ['One', 'Another', 'Other', 'That', 'This', 'Two', 'Three', 'Four', 'Five', 'Six']
N = 10
data = np.vstack((aha, ahaa, dist))
data = np.transpose(data)
labels = [mod[i].format(i) for i in range (N)]
plt.subplots_adjust(bottom = 0.1)
plt.scatter(
    data[:, 0], data[:, 1], marker = 'o', c = data[:, 0], s = data[:, 2]*1500,
    cmap = plt.get_cmap('Spectral'))
for label, x, y in zip(labels, data[:, 0], data[:, 1]):
    plt.annotate(
        label, 
        xy = (x, y), xytext = (-20, 20),
        textcoords = 'offset points', ha = 'right', va = 'bottom',
        bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5),
        arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))


plt.show()

I am new to Python, and would be utterly grateful for any help.

Regards Joel

*EDIT

Based on the feedback I have also this code now,

import numpy as np
import matplotlib.pyplot as plt
from numpy.random import *

def get_text_positions(x_data, y_data, txt_width, txt_height):
    a = zip(y_data, x_data)
    text_positions = y_data.copy()
    for index, (y, x) in enumerate(a):
        local_text_positions = [i for i in a if i[0] > (y - txt_height) 
                            and (abs(i[1] - x) < txt_width * 2) and i != (y,x)]
        if local_text_positions:
            sorted_ltp = sorted(local_text_positions)
            if abs(sorted_ltp[0][0] - y) < txt_height: #True == collision
                differ = np.diff(sorted_ltp, axis=0)
                a[index] = (sorted_ltp[-1][0] + txt_height, a[index][1])
                text_positions[index] = sorted_ltp[-1][0] + txt_height
                for k, (j, m) in enumerate(differ):
                    #j is the vertical distance between words
                    if j > txt_height * 2: #if True then room to fit a word in
                        a[index] = (sorted_ltp[k][0] + txt_height, a[index][1])
                        text_positions[index] = sorted_ltp[k][0] + txt_height
                        break
    return text_positions

def text_plotter(x_data, y_data, text_positions, axis,txt_width,txt_height):
    for x,y,t in zip(x_data, y_data, text_positions):
        axis.text(x - txt_width, 1.01*t, '%d'%int(y),rotation=0, color='blue')
        if y != t:
            axis.arrow(x, t,0,y-t, color='red',alpha=0.3, width=txt_width*0.1, 
                       head_width=txt_width, head_length=txt_height*0.5, 
                       zorder=0,length_includes_head=True)

#test data:
aha = [0.1872, 0.0101, 0.0166, 0.0164, 0.0164, 0.0170, 0.0187, 0.0188, 0.0652, 0.0102]
ahaa = [0.2872, 0.0301, 0.0466, 0.0364, 0.0564, 0.0670, 0.0287, 0.0888, 0.0852, 0.0502]
dist = [0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2]
mod = ['One', 'Another', 'Other', 'That', 'This', 'Two', 'Three', 'Four', 'Five', 'Six']
N = 10
data = np.vstack((aha, ahaa, dist))
data = np.transpose(data)
x_data = data[:,0]
y_data = data[:,1]

#GOOD PLOT:
fig2 = plt.figure()
ax2 = fig2.add_subplot(111)
#ax2.plt.scatter(x_data, y_data)
labels = [mod[i].format(i) for i in range (N)]
#ax2 = plt.subplots_adjust(bottom = 0.1)
#################################
for i in range (10):
    plt.scatter(
        data[:, 0], data[:, 1], marker = 'o', c = data[:, 0], s = data[:, 2]*1500, alpha=0.7,
        cmap = plt.get_cmap('Spectral'))
#set the bbox for the text. Increase txt_width for wider text.
txt_height = 0.04*(plt.ylim()[1] - plt.ylim()[0])
txt_width = 0.02*(plt.xlim()[1] - plt.xlim()[0])
#Get the corrected text positions, then write the text.
text_positions = get_text_positions(x_data, y_data, txt_width, txt_height)
text_plotter(x_data, y_data, text_positions, ax2, txt_width, txt_height)

plt.ylim(0,max(text_positions)+2*txt_height)
plt.xlim(-0.1,1.1)


for x,y,z in zip(x_data, y_data, mod):
    ax2.text(x - txt_width, 1.01*y, '%s'%z,rotation=0)
plt.ylim(0,max(text_positions)+2*txt_height)
plt.xlim(-0.1,1.1)

plt.show()

The placement of the label bounding boxes looks good, but the issue I am having is that the labels themselves are not in the bounding boxes. The label is just above each point, while the arrow and bounding box is in a different place.

Again, would really appreciate any help.

Try the answer to [this](http://stackoverflow.com/questions/8850142/matplotlib-overlapping-annotations) question for overlapping annotations. — DavidG, Oct 25 '16 at 14:31
Thanks for the comment! I have to admit I struggle to implement that solution. Copy and paste works fine, but when I try to use my labels instead of the values used in that example I get stuck. If you would be able to advice, I would be very grateful! The example did inspire me to achieve _something_ though. I implemented a very ugly temporary fix which adjusts each label by calling two arrays with offsets I defined (1 for the x offset, 1 for the y offset). Thank you again. If you would be able to advice regarding adjusting the answer you linked to, I would be really appreciate it. — Minary, Oct 25 '16 at 16:32

score 0 · Accepted Answer · answered Oct 26 '16 at 10:27

Thanks to @DavidG I have been able to solve this.

I will post my code in case it can assist someone in the future;

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from numpy.random import *
from matplotlib.colors import ListedColormap

def get_text_positions(x_data, y_data, txt_width, txt_height):
    a = zip(y_data, x_data)
    text_positions = y_data.copy()
    for index, (y, x) in enumerate(a):
        local_text_positions = [i for i in a if i[0] > (x - txt_height) 
                            and (abs(i[1] - x) < txt_width * 2) and i != (y,x)]
        if local_text_positions:
            sorted_ltp = sorted(local_text_positions)
            if abs(sorted_ltp[0][0] - y) < txt_height: #True == collision
                differ = np.diff(sorted_ltp, axis=0)
                a[index] = (sorted_ltp[-1][0] + txt_height, a[index][1])
                text_positions[index] = sorted_ltp[-1][0] + txt_height
                for k, (j, m) in enumerate(differ):
                    #j is the vertical distance between words
                    if j > txt_height * 2: #if True then room to fit a word in
                        a[index] = (sorted_ltp[k][0] + txt_height, a[index][1])
                        text_positions[index] = sorted_ltp[k][0] + txt_height
                        break
    return text_positions

def text_plotter(x_data, y_data, z_data, text_positions, axis,txt_width,txt_height):
    for x,y,z,t in zip(x_data, y_data, z_data, text_positions):
        axis.text(x - txt_width, 1.03*t, '%s'%z,rotation=0, color='blue')
        if y != t:
            axis.arrow(x, t,0,y-t, color='red',alpha=0.5, width=txt_width*0.1, 
                       head_width=txt_width, head_length=txt_height*0.5, 
                       zorder=0,length_includes_head=True)




aha = [0.1872, 0.0101, 0.0166, 0.0164, 0.0164, 0.0170, 0.0187, 0.0188, 0.0652, 0.0102]
ahaa = [0.2872, 0.0301, 0.0466, 0.0364, 0.0564, 0.0670, 0.0287, 0.0888, 0.0852, 0.0502]
dist = [0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2]
mod = ['One', 'Another', 'Other', 'That', 'This', 'Two', 'Three', 'Four', 'Five', 'Six']
N = 10
data = np.vstack((aha, ahaa, dist))
data = np.transpose(data)

fig1 = plt.figure()
ax2 = fig1.add_subplot(111)
labels = [mod[i].format(i) for i in range (N)]
plt.subplots_adjust(bottom = 0.1)
CS = ax2.scatter(
    data[:, 0], data[:, 1], marker = 'o', c = data[:, 0], s = data[:, 2]*1500, alpha = 0.5,
    cmap = plt.cm.Spectral)



##################################
x_data = data[:,0]
y_data = data[:,1]
z_data = mod
#set the bbox for the text. Increase txt_width for wider text.
txt_height = 0.03*(plt.ylim()[1] - plt.ylim()[0])
txt_width = 0.02*(plt.xlim()[1] - plt.xlim()[0])
#Get the corrected text positions, then write the text.
text_positions = get_text_positions(x_data, y_data, txt_width, txt_height)
text_plotter(x_data, y_data, z_data, text_positions, ax2, txt_width, txt_height)

print text_positions

cbar = plt.colorbar(CS)
cbar.ax.set_ylabel('Legend Label')


plt.show()

Interactive scatter plot with colorbar legend

1 Answers1