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_dendrogram.py
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# -*- coding: utf-8 -*-
from __future__ import absolute_import
from collections import OrderedDict
from plotly import exceptions, optional_imports
from plotly.graph_objs import graph_objs
# Optional imports, may be None for users that only use our core functionality.
np = optional_imports.get_module('numpy')
scp = optional_imports.get_module('scipy')
sch = optional_imports.get_module('scipy.cluster.hierarchy')
scs = optional_imports.get_module('scipy.spatial')
def create_dendrogram(X, orientation="bottom", labels=None,
colorscale=None, distfun=None,
linkagefun=lambda x: sch.linkage(x, 'complete'),
hovertext=None):
"""
BETA function that returns a dendrogram Plotly figure object.
:param (ndarray) X: Matrix of observations as array of arrays
:param (str) orientation: 'top', 'right', 'bottom', or 'left'
:param (list) labels: List of axis category labels(observation labels)
:param (list) colorscale: Optional colorscale for dendrogram tree
:param (function) distfun: Function to compute the pairwise distance from
the observations
:param (function) linkagefun: Function to compute the linkage matrix from
the pairwise distances
:param (list[list]) hovertext: List of hovertext for constituent traces of dendrogram
clusters
Example 1: Simple bottom oriented dendrogram
```
import plotly.plotly as py
from plotly.figure_factory import create_dendrogram
import numpy as np
X = np.random.rand(10,10)
dendro = create_dendrogram(X)
plot_url = py.plot(dendro, filename='simple-dendrogram')
```
Example 2: Dendrogram to put on the left of the heatmap
```
import plotly.plotly as py
from plotly.figure_factory import create_dendrogram
import numpy as np
X = np.random.rand(5,5)
names = ['Jack', 'Oxana', 'John', 'Chelsea', 'Mark']
dendro = create_dendrogram(X, orientation='right', labels=names)
dendro['layout'].update({'width':700, 'height':500})
py.iplot(dendro, filename='vertical-dendrogram')
```
Example 3: Dendrogram with Pandas
```
import plotly.plotly as py
from plotly.figure_factory import create_dendrogram
import numpy as np
import pandas as pd
Index= ['A','B','C','D','E','F','G','H','I','J']
df = pd.DataFrame(abs(np.random.randn(10, 10)), index=Index)
fig = create_dendrogram(df, labels=Index)
url = py.plot(fig, filename='pandas-dendrogram')
```
"""
if not scp or not scs or not sch:
raise ImportError("FigureFactory.create_dendrogram requires scipy, \
scipy.spatial and scipy.hierarchy")
s = X.shape
if len(s) != 2:
exceptions.PlotlyError("X should be 2-dimensional array.")
if distfun is None:
distfun = scs.distance.pdist
dendrogram = _Dendrogram(X, orientation, labels, colorscale,
distfun=distfun, linkagefun=linkagefun,
hovertext=hovertext)
return graph_objs.Figure(data=dendrogram.data, layout=dendrogram.layout)
class _Dendrogram(object):
"""Refer to FigureFactory.create_dendrogram() for docstring."""
def __init__(self, X, orientation='bottom', labels=None, colorscale=None,
width="100%", height="100%", xaxis='xaxis', yaxis='yaxis',
distfun=None,
linkagefun=lambda x: sch.linkage(x, 'complete'),
hovertext=None):
self.orientation = orientation
self.labels = labels
self.xaxis = xaxis
self.yaxis = yaxis
self.data = []
self.leaves = []
self.sign = {self.xaxis: 1, self.yaxis: 1}
self.layout = {self.xaxis: {}, self.yaxis: {}}
if self.orientation in ['left', 'bottom']:
self.sign[self.xaxis] = 1
else:
self.sign[self.xaxis] = -1
if self.orientation in ['right', 'bottom']:
self.sign[self.yaxis] = 1
else:
self.sign[self.yaxis] = -1
if distfun is None:
distfun = scs.distance.pdist
(dd_traces, xvals, yvals,
ordered_labels, leaves) = self.get_dendrogram_traces(X, colorscale,
distfun,
linkagefun,
hovertext)
self.labels = ordered_labels
self.leaves = leaves
yvals_flat = yvals.flatten()
xvals_flat = xvals.flatten()
self.zero_vals = []
for i in range(len(yvals_flat)):
if yvals_flat[i] == 0.0 and xvals_flat[i] not in self.zero_vals:
self.zero_vals.append(xvals_flat[i])
self.zero_vals.sort()
self.layout = self.set_figure_layout(width, height)
self.data = graph_objs.Data(dd_traces)
def get_color_dict(self, colorscale):
"""
Returns colorscale used for dendrogram tree clusters.
:param (list) colorscale: Colors to use for the plot in rgb format.
:rtype (dict): A dict of default colors mapped to the user colorscale.
"""
# These are the color codes returned for dendrograms
# We're replacing them with nicer colors
d = {'r': 'red',
'g': 'green',
'b': 'blue',
'c': 'cyan',
'm': 'magenta',
'y': 'yellow',
'k': 'black',
'w': 'white'}
default_colors = OrderedDict(sorted(d.items(), key=lambda t: t[0]))
if colorscale is None:
colorscale = [
'rgb(0,116,217)', # blue
'rgb(35,205,205)', # cyan
'rgb(61,153,112)', # green
'rgb(40,35,35)', # black
'rgb(133,20,75)', # magenta
'rgb(255,65,54)', # red
'rgb(255,255,255)', # white
'rgb(255,220,0)'] # yellow
for i in range(len(default_colors.keys())):
k = list(default_colors.keys())[i] # PY3 won't index keys
if i < len(colorscale):
default_colors[k] = colorscale[i]
return default_colors
def set_axis_layout(self, axis_key):
"""
Sets and returns default axis object for dendrogram figure.
:param (str) axis_key: E.g., 'xaxis', 'xaxis1', 'yaxis', yaxis1', etc.
:rtype (dict): An axis_key dictionary with set parameters.
"""
axis_defaults = {
'type': 'linear',
'ticks': 'outside',
'mirror': 'allticks',
'rangemode': 'tozero',
'showticklabels': True,
'zeroline': False,
'showgrid': False,
'showline': True,
}
if len(self.labels) != 0:
axis_key_labels = self.xaxis
if self.orientation in ['left', 'right']:
axis_key_labels = self.yaxis
if axis_key_labels not in self.layout:
self.layout[axis_key_labels] = {}
self.layout[axis_key_labels]['tickvals'] = \
[zv*self.sign[axis_key] for zv in self.zero_vals]
self.layout[axis_key_labels]['ticktext'] = self.labels
self.layout[axis_key_labels]['tickmode'] = 'array'
self.layout[axis_key].update(axis_defaults)
return self.layout[axis_key]
def set_figure_layout(self, width, height):
"""
Sets and returns default layout object for dendrogram figure.
"""
self.layout.update({
'showlegend': False,
'autosize': False,
'hovermode': 'closest',
'width': width,
'height': height
})
self.set_axis_layout(self.xaxis)
self.set_axis_layout(self.yaxis)
return self.layout
def get_dendrogram_traces(self, X, colorscale, distfun, linkagefun, hovertext):
"""
Calculates all the elements needed for plotting a dendrogram.
:param (ndarray) X: Matrix of observations as array of arrays
:param (list) colorscale: Color scale for dendrogram tree clusters
:param (function) distfun: Function to compute the pairwise distance
from the observations
:param (function) linkagefun: Function to compute the linkage matrix
from the pairwise distances
:param (list) hovertext: List of hovertext for constituent traces of dendrogram
:rtype (tuple): Contains all the traces in the following order:
(a) trace_list: List of Plotly trace objects for dendrogram tree
(b) icoord: All X points of the dendrogram tree as array of arrays
with length 4
(c) dcoord: All Y points of the dendrogram tree as array of arrays
with length 4
(d) ordered_labels: leaf labels in the order they are going to
appear on the plot
(e) P['leaves']: left-to-right traversal of the leaves
"""
d = distfun(X)
Z = linkagefun(d)
P = sch.dendrogram(Z, orientation=self.orientation,
labels=self.labels, no_plot=True)
icoord = scp.array(P['icoord'])
dcoord = scp.array(P['dcoord'])
ordered_labels = scp.array(P['ivl'])
color_list = scp.array(P['color_list'])
colors = self.get_color_dict(colorscale)
trace_list = []
for i in range(len(icoord)):
# xs and ys are arrays of 4 points that make up the '∩' shapes
# of the dendrogram tree
if self.orientation in ['top', 'bottom']:
xs = icoord[i]
else:
xs = dcoord[i]
if self.orientation in ['top', 'bottom']:
ys = dcoord[i]
else:
ys = icoord[i]
color_key = color_list[i]
hovertext_label = None
if hovertext:
hovertext_label = hovertext[i]
trace = graph_objs.Scatter(
x=np.multiply(self.sign[self.xaxis], xs),
y=np.multiply(self.sign[self.yaxis], ys),
mode='lines',
marker=graph_objs.Marker(color=colors[color_key]),
text=hovertext_label,
hoverinfo='text'
)
try:
x_index = int(self.xaxis[-1])
except ValueError:
x_index = ''
try:
y_index = int(self.yaxis[-1])
except ValueError:
y_index = ''
trace['xaxis'] = 'x' + x_index
trace['yaxis'] = 'y' + y_index
trace_list.append(trace)
return trace_list, icoord, dcoord, ordered_labels, P['leaves']