# plot3d.py
# Walker M. White (wmw2), Steve Marschner (srm2), Lillian Lee (ljl2)
# November 1, 2013
"""Visualization App to verify that k-means works
The visualize can view any clustering on a set of 3D points.
Visualization is limited to 3d points and k-values < 15."""
import matplotlib
import numpy
import math
import traceback
matplotlib.use('TkAgg')
# Modules to embed matplotlib in a custom Tkinter window
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2TkAgg
# implement the default mpl key bindings
from matplotlib.backend_bases import key_press_handler
from matplotlib.figure import Figure
from mpl_toolkits.mplot3d import Axes3D
# File support to load data files
import os
import sys
import Tkinter as Tk
import tkFileDialog
import tkMessageBox
import tkFont
# The k-means implementation
import a6
# Maximum allowable k-means
MAX_K_VAL = 14
def parse_data(data):
"""Return: 3-element list equivalent to file line
Precondition: data is a line from csv file whole first three elements are numbers."""
if data[0] == '#':
return None
return map(float,data[:-1].split(',')[-3:])
class Visualizer(object):
"""Instance is a visualization app.
INSTANCE ATTRIBUTES:
_root: TCL/TK graphics backend [TK object]
_canvas: MatPlotLib canvas [FigureCanvas object]
_axes: MatPlotLib axes [Axes object]
_ds: Data set [Dataset object]
_kmean: Clustering of dataset [Clustering object]
_count: Number of steps executed [int >= 0]
_finish: Whether the computation is done [bool]
There are several other attributes for GUI widgets
(buttons and labels). We do not list all of them here."""
def __init__(self, filename=None):
"""Initializer: Make a visualization app"""
self._root = Tk.Tk()
self._root.wm_title("Clustering Assignment Visualizer")
self._ds = None
self._kmean = None
# Start the application
self._config_canvas()
self._config_control()
self._canvas.show()
# Load data if provided
if filename is not None:
self._load_file(filename)
Tk.mainloop()
def _config_canvas(self):
"""Load the MatPlotLib drawing code"""
# Create the drawing canvas
figure = Figure(figsize=(6,6), dpi=100)
self._canvas = FigureCanvasTkAgg(figure, master=self._root)
self._canvas._tkcanvas.pack(side=Tk.LEFT, expand=True, fill=Tk.BOTH)
# Initialize the scatter plot
self._axes = figure.gca(projection='3d')
self._axes.set_xlim((0.0, 1.0))
self._axes.set_ylim((0.0, 1.0))
self._axes.set_zlim((0.0, 1.0))
self._axes.set_xlabel('X')
self._axes.set_ylabel('Y')
self._axes.set_zlabel('Z')
self._axes.set_xticks(numpy.arange(0.0,1.0,0.1))
self._axes.set_yticks(numpy.arange(0.0,1.0,0.1))
self._axes.set_zticks(numpy.arange(0.0,1.0,0.1))
self._axes.tick_params(labelsize=9)
def _config_control(self):
"""Create the control panel on the right hand side
This method is WAY too long, but GUI layout code is typically
like this. Plus, Tkinter makes this even worse than it should be."""
panel = Tk.Frame(master=self._root)
panel.columnconfigure(0,pad=3)
panel.columnconfigure(1,pad=3)
panel.rowconfigure(0,pad=3)
panel.rowconfigure(1,pad=0)
panel.rowconfigure(2,pad=23)
panel.rowconfigure(3,pad=3)
panel.rowconfigure(4,pad=3)
panel.rowconfigure(5,pad=3)
panel.rowconfigure(6,pad=13)
title = Tk.Label(master=panel,text='K Means Control',height=3)
wfont = tkFont.Font(font=title['font'])
wfont.config(weight='bold',size=20)
title.grid(row=0,columnspan=2, sticky='we')
title.config(font=wfont)
divider = Tk.Frame(master=panel,height=2, bd=1, relief=Tk.SUNKEN)
divider.grid(row=1,columnspan=2, sticky='we')
# Label and button for managing files.
label = Tk.Label(master=panel,text='Data Set: ',height=2)
wfont = tkFont.Font(font=label['font'])
wfont.config(weight='bold')
label.config(font=wfont)
label.grid(row=2,column=0, sticky='e')
self._filebutton = Tk.Button(master=panel, text='<select file>', width=10,command=self._load)
self._filebutton.grid(row=2,column=1, sticky='w',padx=(0,10))
# Label and option menu to select k-value
label = Tk.Label(master=panel,text='K Value: ',height=2,font=wfont)
label.grid(row=3,column=0,sticky='e')
self._kval = Tk.IntVar(master=self._root)
self._kval.set(3)
options = Tk.OptionMenu(panel,self._kval,*range(1,MAX_K_VAL+1),command=self._reset)
options.grid(row=3,column=1,sticky='w')
# Label and step indicator
label = Tk.Label(master=panel,text='At Step: ',height=2,font=wfont)
label.grid(row=4,column=0,sticky='e')
self._count = 0
self._countlabel = Tk.Label(master=panel,text='0')
self._countlabel.grid(row=4,column=1,sticky='w')
# Label and convergence indicator
label = Tk.Label(master=panel,text='Finished: ',height=2,font=wfont)
label.grid(row=5,column=0,sticky='e')
self._finished = False
self._finishlabel = Tk.Label(master=panel,text='False')
self._finishlabel.grid(row=5,column=1,sticky='w')
# Control buttons
button = Tk.Button(master=panel, text='Reset', width=8, command=self._reset)
button.grid(row=6,column=0,padx=(10,0))
button = Tk.Button(master=panel, text='Step', width=8, command=self._step)
button.grid(row=6,column=1)
panel.pack(side=Tk.RIGHT, fill=Tk.Y)
def _plot_clusters(self):
"""Plot the clusters in a completed assignment"""
COLORS = ('r','g','b','k','c','m','y')
for k in range(self._kval.get()):
c = COLORS[k % len(COLORS)]
m = 'x' if k % 2 == 0 else '+'
cluster = self._kmean.getClusters()[k]
rows = numpy.array(cluster.getContents())
cent = cluster.getCentroid()
if (len(rows) > 0):
self._axes.scatter(rows[:,0], rows[:,1], rows[:,2], c=c, marker=m)
self._axes.scatter(cent[0],cent[1],cent[2],c=c,s=30,marker='o')
def _plot_one_cluster(self):
"""Plot one cluster in an assignment that has finished Cluster but not Clustering."""
# Try to show everything in one cluster.
cluster = a6.Cluster(self._ds, self._ds.getPoint(0))
for i in range(self._ds.getSize()):
cluster.addIndex(i)
cluster.updateCentroid()
rows = numpy.array(self._ds.getContents())
cent = cluster.getCentroid()
if (len(rows) > 0):
self._axes.scatter(rows[:,0], rows[:,1], rows[:,2], c='b', marker='+')
self._axes.scatter(cent[0],cent[1],cent[2],c='b',s=30,marker='o')
def _plot_points(self):
"""Plot the clusters in an assignment that has finished Dataset but not much else."""
rows = numpy.array(self._ds.getContents())
self._axes.scatter(rows[:,0], rows[:,1], rows[:,2], c='k', marker='+')
def _plot(self):
"""General plot function
This function replots the data any time that it changes."""
assert not self._ds is None, 'Invariant Violation: Attempted to plot when data set is None'
self._axes.clear()
if self._kmean is not None:
try:
self._plot_clusters()
except BaseException as e:
print 'FAILED KMEANS VISUALIZATION: '
traceback.print_exc()
print ''
print 'Attempting One Cluster Only'
try:
self._plot_one_cluster()
except BaseException as e:
print 'FAILED CLUSTER VISUALIZATION '
traceback.print_exc()
print ''
print 'Attempting Data Set Only'
self._plot_points()
else:
self._plot_points()
# Reset axes information
xb = self._axes.get_xbound()
xb = (numpy.floor(xb[0]*10)/10.0,numpy.ceil(xb[1]*10)/10.0)
self._axes.set_xlim(xb)
self._axes.set_xticks(numpy.arange(xb[0],xb[1],0.1))
yb = self._axes.get_ybound()
yb = (numpy.floor(yb[0]*10)/10.0,numpy.ceil(yb[1]*10)/10.0)
self._axes.set_ylim(yb)
self._axes.set_yticks(numpy.arange(yb[0],yb[1],0.1))
zb = self._axes.get_zbound()
zb = (numpy.floor(zb[0]*10)/10.0,numpy.ceil(zb[1]*10)/10.0)
self._axes.set_zlim(zb)
self._axes.set_zticks(numpy.arange(zb[0],zb[1],0.1))
self._axes.set_xlabel('X')
self._axes.set_ylabel('Y')
self._axes.set_zlabel('Z')
self._canvas.show()
def _load(self):
"""Let the user select a file, and load it."""
filename = tkFileDialog.askopenfilename(initialdir='.',
title='Select a Data File',
filetypes=[('CSV Data Files', '.csv')])
if filename is None:
return
self._load_file(filename)
def _load_file(self, filename):
"""Load a data set file into a Dataset."""
try:
f = open(filename)
contents = []
first = f.readline()
assert first[1:].strip()[:5] == 'kdata'
for x in f:
if x[0] != '#': # Ignore comments
point = parse_data(x)
contents.append(point)
self._ds = a6.Dataset(3,contents)
if not self._ds.getContents():
raise RuntimeError()
shortname = os.path.split(filename)[1]
if (len(shortname) > 10):
shortname = shortname[0:10]+'...'
self._filebutton.configure(text=shortname)
self._kmean = None
self._plot()
except RuntimeError:
tkMessageBox.showwarning('Load','ERROR: You must complete Dataset first.')
except AssertionError:
tkMessageBox.showwarning('Load','ERROR: CSV file must be a kdata file.')
except:
traceback.print_exc()
tkMessageBox.showwarning('Load','ERROR: kdata file is corrupted.')
def _reset(self,k=None):
"""Reset the k-means calculation with the given k value. If k is
None, use the value of self._kval.
Precondition: k > 0 is an int, and a dataset with at least k
points is loaded. If k is None, the current value of self._kval
is used."""
if k is None:
k = self._kval.get()
if self._ds is None:
tkMessageBox.showwarning('Reset','ERROR: No data set loaded.')
self._count = 0
self._countlabel.configure(text='0')
self._finished = False
self._finishlabel.configure(text='False')
# Student may not have implemented this yet.
self._kmean = a6.ClusterGroup(self._ds, k)
self._kmean._partition()
self._plot()
def _step(self):
"""Perform one step in k-means clustering"""
if self._ds is None:
tkMessageBox.showwarning('Step','ERROR: No data set loaded.')
if self._kmean is None:
self._reset()
if self._finished:
return
self._count = self._count+1
self._countlabel.configure(text=str(self._count))
self._finished = self._kmean.step()
self._finishlabel.configure(text=str(self._finished))
self._plot()
# Script code
if __name__ == '__main__':
if len(sys.argv) == 2:
Visualizer(sys.argv[1])
else:
Visualizer()