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Feature add tukey kramer circles #9

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merged 3 commits into from
Feb 3, 2018
Merged

Feature add tukey kramer circles #9

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55c8323
Added Tukey circles
cmmorrow Feb 3, 2018
15b0083
Fixed a bug causing grand median to always be displayed.
cmmorrow Feb 3, 2018
a8642da
Removed un-needed unit tests
cmmorrow Feb 3, 2018
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86 changes: 67 additions & 19 deletions sci_analysis/graphs/vector.py
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Original file line number Diff line number Diff line change
@@ -1,16 +1,19 @@
import warnings
import six
from math import sqrt, fabs

# matplotlib imports
from matplotlib.pyplot import (show, subplot, yticks, xlabel, ylabel, figure, setp, savefig, close, xticks,
subplots_adjust)
from matplotlib.gridspec import GridSpec
from matplotlib.patches import Circle
from matplotlib.collections import PatchCollection

# Numpy imports
from numpy import polyfit, polyval, sort, arange, array, linspace, mgrid, vstack, reshape
from numpy import polyfit, polyval, sort, arange, array, linspace, mgrid, vstack, reshape, std, sum, mean, median

# Scipy imports
from scipy.stats import probplot, gaussian_kde
from scipy.stats import probplot, gaussian_kde, t

# local imports
from .base import Graph
Expand Down Expand Up @@ -575,9 +578,10 @@ class GraphBoxplot(VectorGraph):
"""

_nrows = 1
_ncols = 2
_ncols = 1
_xsize = 7.5
_ysize = 6
_default_alpha = 0.05

def __init__(self, *args, **kwargs):
"""GraphBoxplot constructor. NOTE: If vectors is a dict, the boxplots are
Expand All @@ -596,8 +600,10 @@ def __init__(self, *args, **kwargs):
self._title = kwargs['title'] if 'title' in kwargs else 'Oneway'
self._nqp = kwargs['nqp'] if 'nqp' in kwargs else True
self._save_to = kwargs['save_to'] if 'save_to' in kwargs else None
self._gmean = kwargs['gmean'] if 'gmean' in kwargs else None
self._gmedian = kwargs['gmedian'] if 'gmedian' in kwargs else None
self._gmean = kwargs['gmean'] if 'gmean' in kwargs else True
self._gmedian = kwargs['gmedian'] if 'gmedian' in kwargs else True
self._circles = kwargs['circles'] if 'circles' in kwargs else True
self._alpha = kwargs['alpha'] if 'alpha' in kwargs else self._default_alpha
if 'title' in kwargs:
self._title = kwargs['title']
elif self._nqp:
Expand Down Expand Up @@ -633,6 +639,31 @@ def __init__(self, *args, **kwargs):
data = Vector(args[0])
super(GraphBoxplot, self).__init__(data, xname=xname, yname=yname, save_to=self._save_to)

@staticmethod
def grand_mean(data):
return mean([mean(sample) for sample in data])

@staticmethod
def grand_median(data):
return median([median(sample) for sample in data])

def tukey_circles(self, data):
num = []
den = []
crit = []
radii = []
xbar = []
for sample in data:
df = len(sample) - 1
num.append(std(sample, ddof=1) ** 2 * df)
den.append(df)
crit.append(t.ppf(1 - self._alpha, df))
mse = sum(num) / sum(den)
for i, sample in enumerate(data):
radii.append(fabs(crit[i]) * sqrt(mse / len(sample)))
xbar.append(mean(sample))
return tuple(zip(xbar, radii))

def draw(self):
"""
Draws the boxplots based on the set parameters.
Expand All @@ -642,6 +673,14 @@ def draw(self):
pass
"""

# Setup the grid variables
w_ratio = [1]
if self._circles:
w_ratio = [4, 1]
self._ncols += 1
if self._nqp:
w_ratio.append(4 if self._circles else 1)
self._ncols += 1
groups, data = zip(*[(g, v['ind']) for g, v in self._data.values.groupby('grp')])

# Create the quantile plot arrays
Expand All @@ -650,11 +689,9 @@ def draw(self):
# Create the figure and gridspec
if self._nqp and len(prob) > 0:
self._xsize *= 2
else:
self._ncols = 1
f = figure(figsize=(self._xsize, self._ysize))
f.suptitle(self._title, fontsize=14)
gs = GridSpec(self._nrows, self._ncols, wspace=0)
gs = GridSpec(self._nrows, self._ncols, width_ratios=w_ratio, wspace=0)

# Draw the boxplots
ax1 = subplot(gs[0])
Expand All @@ -665,31 +702,42 @@ def draw(self):
for i in range(len(groups)):
setp(vp['bodies'][i], facecolors=self.get_color(i))
ax1.yaxis.grid(True, linestyle='-', which='major', color='grey', alpha=0.75)
if is_number(self._gmean):
ax1.axhline(float(self._gmean), c='red', linestyle='--', alpha=0.8)
if is_number(self._gmedian):
ax1.axhline(float(self._gmedian), c='blue', linestyle=':', alpha=0.8)
if self._gmean:
ax1.axhline(float(self.grand_mean(data)), c='k', linestyle='--', alpha=0.4)
if self._gmedian:
ax1.axhline(float(self.grand_median(data)), c='k', linestyle=':', alpha=0.4)
if any([True if len(str(g)) > 10 else False for g in groups]) or len(groups) > 5:
xticks(rotation=60)
subplots_adjust(bottom=0.2)
ylabel(self._yname)
xlabel(self._xname)

# Draw the Tukey-Kramer circles
if self._circles:
ax2 = subplot(gs[1], sharey=ax1)
for i, (center, radius) in enumerate(self.tukey_circles(data)):
c = Circle((0.5, center), radius=radius, facecolor='none', edgecolor=self.get_color(i))
ax2.add_patch(c)
ax2.set_aspect('equal')
setp(ax2.get_xticklabels(), visible=False)
setp(ax2.get_yticklabels(), visible=False)
xticks([])

# Draw the normal quantile plot
if self._nqp and len(prob) > 0:
ax2 = subplot(gs[1], sharey=ax1)
ax3 = subplot(gs[2], sharey=ax1) if self._circles else subplot(gs[1], sharey=ax1)
for i, g in enumerate(prob):
osm = g[0][0]
osr = g[0][1]
slope = g[1][0]
intercept = g[1][1]
ax2.plot(osm, osr, marker='^', color=self.get_color(i), label=groups[i])
ax2.plot(osm, slope * osm + intercept, linestyle='--', linewidth=2, color=self.get_color(i))
ax2.xaxis.grid(True, linestyle='-', which='major', color='grey', alpha=0.75)
ax2.yaxis.grid(True, linestyle='-', which='major', color='grey', alpha=0.75)
ax2.legend(loc='best')
ax3.plot(osm, osr, marker='^', color=self.get_color(i), label=groups[i])
ax3.plot(osm, slope * osm + intercept, linestyle='--', linewidth=2, color=self.get_color(i))
ax3.xaxis.grid(True, linestyle='-', which='major', color='grey', alpha=0.75)
ax3.yaxis.grid(True, linestyle='-', which='major', color='grey', alpha=0.75)
ax3.legend(loc='best')
xlabel("Quantiles")
setp(ax2.get_yticklabels(), visible=False)
setp(ax3.get_yticklabels(), visible=False)

# Save the figure to disk or display
if self._save_to:
Expand Down
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