def plotter(title,
df,
x_label = None,
y_label = None,
style = 'ggplot',
figsize = (8, 4),
save = False,
legend_pos = 'best',
reverse_legend = 'guess',
num_to_plot = 7,
tex = 'try',
colours = 'Paired',
cumulative = False,
pie_legend = True,
partial_pie = False,
show_totals = False,
transparent = False,
output_format = 'png',
interactive = False,
black_and_white = False,
show_p_val = False,
indices = 'guess',
**kwargs):
"""plot interrogator() or editor() output.
**kwargs are for pandas first, which can then send them through to matplotlib.plot():
http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.plot.html
http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.plot
pie_legend: False to label slices rather than give legend
show_totals: where to show percent/abs frequencies: False, 'plot', 'legend', or 'both'
"""
import corpkit
import os
import matplotlib as mpl
if interactive:
import matplotlib.pyplot as plt, mpld3
else:
import matplotlib.pyplot as plt
from matplotlib import rc
import pandas
import pandas as pd
from pandas import DataFrame
import numpy
from time import localtime, strftime
from corpkit.tests import check_pytex, check_spider, check_t_kinter
if interactive:
import mpld3
import collections
from mpld3 import plugins, utils
from plugins import InteractiveLegendPlugin, HighlightLines
tk = check_t_kinter()
running_python_tex = check_pytex()
# incorrect spelling of spider on purpose
running_spider = check_spider()
def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
"""remove extreme values from colourmap --- no pure white"""
import matplotlib.colors as colors
import numpy as np
new_cmap = colors.LinearSegmentedColormap.from_list(
'trunc({n},{a:.2f},{b:.2f})'.format(n=cmap.name, a=minval, b=maxval),
cmap(np.linspace(minval, maxval, n)))
return new_cmap
def get_savename(imagefolder, save = False, title = False, ext = 'png'):
"""Come up with the savename for the image."""
import os
def urlify(s):
"Turn title into filename"
import re
s = s.lower()
s = re.sub(r"[^\w\s-]", '', s)
s = re.sub(r"\s+", '-', s)
s = re.sub(r"-(textbf|emph|textsc|textit)", '-', s)
return s
# name as
if not ext.startswith('.'):
ext = '.' + ext
if type(save) == str:
savename = os.path.join(imagefolder, (urlify(save) + ext))
#this 'else' is redundant now that title is obligatory
else:
if title:
filename = urlify(title) + ext
savename = os.path.join(imagefolder, filename)
# remove duplicated ext
if savename.endswith('%s%s' % (ext, ext)):
savename = savename.replace('%s%s' % (ext, ext), ext, 1)
return savename
def rename_data_with_total(dataframe, was_series = False, using_tex = False, absolutes = True):
"""adds totals (abs, rel, keyness) to entry name strings"""
if was_series:
where_the_words_are = dataframe.index
else:
where_the_words_are = dataframe.columns
the_labs = []
for w in list(where_the_words_are):
if not absolutes:
if was_series:
perc = dataframe.T[w][0]
else:
the_labs.append(w)
continue
if using_tex:
the_labs.append('%s (%.2f\%%)' % (w, perc))
else:
the_labs.append('%s (%.2f %%)' % (w, perc))
else:
if was_series:
score = dataframe.T[w].sum()
else:
score = dataframe[w].sum()
if using_tex:
the_labs.append('%s (n=%d)' % (w, score))
else:
the_labs.append('%s (n=%d)' % (w, score))
if not was_series:
dataframe.columns = the_labs
else:
vals = list(dataframe[list(dataframe.columns)[0]].values)
dataframe = pd.DataFrame(vals, index = the_labs)
dataframe.columns = ['Total']
return dataframe
def auto_explode(dataframe, input, was_series = False, num_to_plot = 7):
"""give me a list of strings and i'll output explode option"""
output = [0 for s in range(num_to_plot)]
if was_series:
l = list(dataframe.index)
else:
l = list(dataframe.columns)
if type(input) == str or type(input) == int:
input = [input]
if type(input) == list:
for i in input:
if type(i) == str:
index = l.index(i)
else:
index = i
output[index] = 0.1
return output
# are we doing subplots?
sbplt = False
if 'subplots' in kwargs:
if kwargs['subplots'] is True:
sbplt = True
if colours is True:
colours = 'Paired'
styles = ['dark_background', 'bmh', 'grayscale', 'ggplot', 'fivethirtyeight']
if style not in styles:
raise ValueError('Style %s not found. Use %s' % (style, ', '.join(styles)))
if 'savepath' in kwargs.keys():
mpl.rcParams['savefig.directory'] = kwargs['savepath']
del kwargs['savepath']
mpl.rcParams['savefig.bbox'] = 'tight'
# try to use tex
# TO DO:
# make some font kwargs here
using_tex = False
mpl.rcParams['font.family'] = 'sans-serif'
mpl.rcParams['text.latex.unicode'] = True
if tex == 'try' or tex is True:
try:
rc('text', usetex=True)
rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})
using_tex = True
except:
matplotlib.rc('font', family='sans-serif')
matplotlib.rc('font', serif='Helvetica Neue')
matplotlib.rc('text', usetex='false')
rc('text', usetex=False)
else:
rc('text', usetex=False)
if interactive:
using_tex = False
if show_totals is False:
show_totals = 'none'
# find out what kind of plot we're making, and enable
# or disable interactive values if need be
if 'kind' not in kwargs:
kwargs['kind'] = 'line'
if interactive:
if kwargs['kind'].startswith('bar'):
interactive_types = [3]
elif kwargs['kind'] == 'area':
interactive_types = [2, 3]
elif kwargs['kind'] == 'line':
interactive_types = [2, 3]
elif kwargs['kind'] == 'pie':
interactive_types = None
warnings.warn('Interactive plotting not yet available for pie plots.')
else:
interactive_types = [None]
if interactive is False:
interactive_types = [None]
# find out if pie mode, add autopct format
piemode = False
if 'kind' in kwargs:
if kwargs['kind'] == 'pie':
piemode = True
# always the best spot for pie
#if legend_pos == 'best':
#legend_pos = 'lower left'
if show_totals.endswith('plot') or show_totals.endswith('both'):
kwargs['pctdistance'] = 0.6
if using_tex:
kwargs['autopct'] = r'%1.1f\%%'
else:
kwargs['autopct'] = '%1.1f%%'
#if piemode:
#if partial_pie:
#kwargs['startangle'] = 180
kwargs['subplots'] = sbplt
# copy data, make series into df
dataframe = df.copy()
was_series = False
if type(dataframe) == pandas.core.series.Series:
was_series = True
if not cumulative:
dataframe = DataFrame(dataframe)
else:
dataframe = DataFrame(dataframe.cumsum())
else:
# don't know if this is much good.
if cumulative:
dataframe = DataFrame(dataframe.cumsum())
if len(list(dataframe.columns)) == 1:
was_series = True
# attempt to convert x axis to ints:
try:
dataframe.index = [int(i) for i in list(dataframe.index)]
except:
pass
# remove totals and tkinter order
if not was_series:
for name, ax in zip(['Total'] * 2 + ['tkintertable-order'] * 2, [0, 1, 0, 1]):
dataframe = dataframe.drop(name, axis = ax, errors = 'ignore')
else:
dataframe = dataframe.drop('tkintertable-order', errors = 'ignore')
dataframe = dataframe.drop('tkintertable-order', axis = 1, errors = 'ignore')
# look at columns to see if all can be ints, in which case, set up figure
# for depnumming
if not was_series:
if indices == 'guess':
def isint(x):
try:
a = float(x)
b = int(a)
except ValueError or OverflowError:
return False
else:
return a == b
if all([isint(x) is True for x in list(dataframe.columns)]):
indices = True
else:
indices = False
# if depnumming, plot all, transpose, and rename axes
if indices is True:
num_to_plot = 'all'
dataframe = dataframe.T
if y_label is None:
y_label = 'Percentage of all matches'
if x_label is None:
x_label = ''
# set backend?
output_formats = ['svgz', 'ps', 'emf', 'rgba', 'raw', 'pdf', 'svg', 'eps', 'png', 'pgf']
if output_format not in output_formats:
raise ValueError('%s output format not recognised. Must be: %s' % (output_format, ', '.join(output_formats)))
# don't know if these are necessary
if 'pdf' in output_format:
plt.switch_backend(output_format)
if 'pgf' in output_format:
plt.switch_backend(output_format)
if num_to_plot == 'all':
if was_series:
if not piemode:
num_to_plot = len(dataframe)
else:
num_to_plot = len(dataframe)
else:
if not piemode:
num_to_plot = len(list(dataframe.columns))
else:
num_to_plot = len(dataframe.index)
# explode pie, or remove if not piemode
if 'explode' in kwargs:
if not piemode:
del kwargs['explode']
if piemode:
if 'explode' in kwargs:
if not sbplt:
kwargs['explode'] = auto_explode(dataframe,
kwargs['explode'],
was_series = was_series,
num_to_plot = num_to_plot)
if 'legend' in kwargs:
legend = kwargs['legend']
else:
legend = True
#cut data short
plotting_a_totals_column = False
if was_series:
if list(dataframe.columns)[0] != 'Total':
try:
can_be_ints = [int(x) for x in list(dataframe.index)]
num_to_plot = len(dataframe)
except:
dataframe = dataframe[:num_to_plot]
elif list(dataframe.columns)[0] == 'Total':
plotting_a_totals_column = True
if not 'legend' in kwargs:
legend = False
num_to_plot = len(dataframe)
else:
dataframe = dataframe.T.head(num_to_plot).T
# remove stats fields, put p in entry text, etc.
statfields = ['slope', 'intercept', 'r', 'p', 'stderr']
try:
dataframe = dataframe.drop(statfields, axis = 1)
except:
pass
try:
dataframe.ix['p']
there_are_p_vals = True
except:
there_are_p_vals = False
if show_p_val:
if there_are_p_vals:
newnames = []
for col in list(dataframe.columns):
pval = dataframe[col]['p']
newname = '%s (p=%s)' % (col, format(pval, '.5f'))
newnames.append(newname)
dataframe.columns = newnames
dataframe.drop(statfields, axis = 0, inplace = True)
else:
warnings.warn('No p-values calculated to show.\n\nUse sort_by and keep_stats in editor() to generate these values.')
else:
if there_are_p_vals:
dataframe.drop(statfields, axis = 0, inplace = True)
# make and set y label
absolutes = True
if type(dataframe) == pandas.core.frame.DataFrame:
try:
if not all([s.is_integer() for s in dataframe.iloc[0,:].values]):
absolutes = False
except:
pass
else:
if not all([s.is_integer() for s in dataframe.values]):
absolutes = False
# use colormap if need be:
if num_to_plot > 0:
if not was_series:
if 'kind' in kwargs:
if kwargs['kind'] in ['pie', 'line', 'area']:
if colours:
if not plotting_a_totals_column:
if colours == 'Default':
colours = 'Paired'
kwargs['colormap'] = colours
#else:
if colours:
if colours == 'Default':
colours = 'Paired'
kwargs['colormap'] = colours
if piemode:
if num_to_plot > 0:
if colours == 'Default':
colours = 'Paired'
kwargs['colormap'] = colours
else:
if num_to_plot > 0:
if colours == 'Default':
colours = 'Paired'
kwargs['colormap'] = colours
#else:
#if len(dataframe.T.columns) < 8:
#try:
#del kwargs['colormap']
#except:
#pass
# multicoloured bar charts
if 'kind' in kwargs:
if colours:
if kwargs['kind'].startswith('bar'):
if len(list(dataframe.columns)) == 1:
if not black_and_white:
import numpy as np
the_range = np.linspace(0, 1, num_to_plot)
cmap = plt.get_cmap(colours)
kwargs['colors'] = [cmap(n) for n in the_range]
# make a bar width ... ?
#kwargs['width'] = (figsize[0] / float(num_to_plot)) / 1.5
# reversing legend option
if reverse_legend is True:
rev_leg = True
elif reverse_legend is False:
rev_leg = False
# show legend or don't, guess whether to reverse based on kind
if 'kind' in kwargs:
if kwargs['kind'] in ['bar', 'barh', 'area', 'line', 'pie']:
if was_series:
legend = False
if kwargs['kind'] == 'pie':
if pie_legend:
legend = True
else:
legend = False
if kwargs['kind'] in ['barh', 'area']:
if reverse_legend == 'guess':
rev_leg = True
if not 'rev_leg' in locals():
rev_leg = False
# the default legend placement
if legend_pos is True:
legend_pos = 'best'
# cut dataframe if just_totals
try:
tst = dataframe['Combined total']
dataframe = dataframe.head(num_to_plot)
except:
pass
# rotate automatically
if 'rot' not in kwargs:
if not was_series:
xvals = [str(i) for i in list(dataframe.index)[:num_to_plot]]
#if 'kind' in kwargs:
#if kwargs['kind'] in ['barh', 'area']:
#xvals = [str(i) for i in list(dataframe.columns)[:num_to_plot]]
else:
xvals = [str(i) for i in list(dataframe.columns)[:num_to_plot]]
if len(max(xvals, key=len)) > 6:
if not piemode:
kwargs['rot'] = 45
# no title for subplots because ugly,
if sbplt:
if 'title' in kwargs:
del kwargs['title']
else:
kwargs['title'] = title
# no interactive subplots yet:
if sbplt and interactive:
import warnings
interactive = False
warnings.warn('No interactive subplots yet, sorry.')
return
# not using pandas for labels or legend anymore.
#kwargs['labels'] = None
#kwargs['legend'] = False
if legend:
# kwarg options go in leg_options
leg_options = {'framealpha': .8}
if 'shadow' in kwargs:
leg_options['shadow'] = True
if 'ncol' in kwargs:
leg_options['ncol'] = kwargs['ncol']
del kwargs['ncol']
else:
if num_to_plot > 6:
leg_options['ncol'] = num_to_plot / 7
# determine legend position based on this dict
if legend_pos:
possible = {'best': 0, 'upper right': 1, 'upper left': 2, 'lower left': 3, 'lower right': 4,
'right': 5, 'center left': 6, 'center right': 7, 'lower center': 8, 'upper center': 9,
'center': 10, 'o r': 2, 'outside right': 2, 'outside upper right': 2,
'outside center right': 'center left', 'outside lower right': 'lower left'}
if type(legend_pos) == int:
the_loc = legend_pos
elif type(legend_pos) == str:
try:
the_loc = possible[legend_pos]
except KeyError:
raise KeyError('legend_pos value must be one of:\n%s\n or an int between 0-10.' %', '.join(possible.keys()))
leg_options['loc'] = the_loc
#weirdness needed for outside plot
if legend_pos in ['o r', 'outside right', 'outside upper right']:
leg_options['bbox_to_anchor'] = (1.02, 1)
if legend_pos == 'outside center right':
leg_options['bbox_to_anchor'] = (1.02, 0.5)
if legend_pos == 'outside lower right':
leg_options['loc'] == 'upper right'
leg_options['bbox_to_anchor'] = (0.5, 0.5)
# a bit of distance between legend and plot for outside legends
if type(legend_pos) == str:
if legend_pos.startswith('o'):
leg_options['borderaxespad'] = 1
if not piemode:
if show_totals.endswith('both') or show_totals.endswith('legend'):
dataframe = rename_data_with_total(dataframe,
was_series = was_series,
using_tex = using_tex,
absolutes = absolutes)
else:
if pie_legend:
if show_totals.endswith('both') or show_totals.endswith('legend'):
dataframe = rename_data_with_total(dataframe,
was_series = was_series,
using_tex = using_tex,
absolutes = absolutes)
if piemode:
if partial_pie:
dataframe = dataframe / 100.0
# some pie things
if piemode:
if not sbplt:
kwargs['y'] = list(dataframe.columns)[0]
if pie_legend:
kwargs['legend'] = False
if was_series:
leg_options['labels'] = list(dataframe.index)
else:
leg_options['labels'] = list(dataframe.columns)
else:
if pie_legend:
kwargs['legend'] = False
if was_series:
leg_options['labels'] = list(dataframe.index)
else:
leg_options['labels'] = list(dataframe.index)
areamode = False
if 'kind' in kwargs:
if kwargs['kind'] == 'area':
areamode = True
if legend is False:
kwargs['legend'] = False
# cumulative grab first col
if cumulative:
kwargs['y'] = list(dataframe.columns)[0]
# line highlighting option for interactive!
if interactive:
if 2 in interactive_types:
if kwargs['kind'] == 'line':
kwargs['marker'] = ','
if not piemode:
kwargs['alpha'] = 0.1
# convert dates --- works only in my current case!
if plotting_a_totals_column or not was_series:
try:
can_it_be_int = int(list(dataframe.index)[0])
can_be_int = True
except:
can_be_int = False
if can_be_int:
if 1500 < int(list(dataframe.index)[0]):
if 2050 > int(list(dataframe.index)[0]):
n = pd.PeriodIndex([d for d in list(dataframe.index)], freq='A')
dataframe = dataframe.set_index(n)
MARKERSIZE = 4
COLORMAP = {
0: {'marker': None, 'dash': (None,None)},
1: {'marker': None, 'dash': [5,5]},
2: {'marker': "o", 'dash': (None,None)},
3: {'marker': None, 'dash': [1,3]},
4: {'marker': "s", 'dash': [5,2,5,2,5,10]},
5: {'marker': None, 'dash': [5,3,1,2,1,10]},
6: {'marker': 'o', 'dash': (None,None)},
7: {'marker': None, 'dash': [5,3,1,3]},
8: {'marker': "1", 'dash': [1,3]},
9: {'marker': "*", 'dash': [5,5]},
10: {'marker': "2", 'dash': [5,2,5,2,5,10]},
11: {'marker': "s", 'dash': (None,None)}
}
HATCHES = {
0: {'color': '#dfdfdf', 'hatch':"/"},
1: {'color': '#6f6f6f', 'hatch':"\\"},
2: {'color': 'b', 'hatch':"|"},
3: {'color': '#dfdfdf', 'hatch':"-"},
4: {'color': '#6f6f6f', 'hatch':"+"},
5: {'color': 'b', 'hatch':"x"}
}
if black_and_white:
if kwargs['kind'] == 'line':
kwargs['linewidth'] = 1
cmap = plt.get_cmap('Greys')
new_cmap = truncate_colormap(cmap, 0.25, 0.95)
if kwargs['kind'] == 'bar':
# darker if just one entry
if len(dataframe.columns) == 1:
new_cmap = truncate_colormap(cmap, 0.70, 0.90)
kwargs['colormap'] = new_cmap
# use styles and plot
with plt.style.context((style)):
if not sbplt:
# check if negative values, no stacked if so
if areamode:
if dataframe.applymap(lambda x: x < 0.0).any().any():
kwargs['stacked'] = False
rev_leg = False
ax = dataframe.plot(figsize = figsize, **kwargs)
else:
if not piemode and not sbplt:
ax = dataframe.plot(figsize = figsize, **kwargs)
else:
ax = dataframe.plot(figsize = figsize, **kwargs)
handles, labels = plt.gca().get_legend_handles_labels()
plt.legend( handles, labels, loc = leg_options['loc'], bbox_to_anchor = (0,-0.1,1,1),
bbox_transform = plt.gcf().transFigure )
if not tk:
plt.show()
return
if 'rot' in kwargs:
if kwargs['rot'] != 0 and kwargs['rot'] != 90:
labels = [item.get_text() for item in ax.get_xticklabels()]
ax.set_xticklabels(labels, rotation = kwargs['rot'], ha='right')
if transparent:
plt.gcf().patch.set_facecolor('white')
plt.gcf().patch.set_alpha(0)
if black_and_white:
#plt.grid()
plt.gca().set_axis_bgcolor('w')
if kwargs['kind'] == 'line':
# white background
# change everything to black and white with interesting dashes and markers
c = 0
for line in ax.get_lines():
line.set_color('black')
#line.set_width(1)
line.set_dashes(COLORMAP[c]['dash'])
line.set_marker(COLORMAP[c]['marker'])
line.set_markersize(MARKERSIZE)
c += 1
if c == len(COLORMAP.keys()):
c = 0
if legend:
if not piemode and not sbplt:
if 3 not in interactive_types:
if not rev_leg:
lgd = plt.legend(**leg_options)
else:
handles, labels = plt.gca().get_legend_handles_labels()
lgd = plt.legend(handles[::-1], labels[::-1], **leg_options)
#if black_and_white:
#lgd.set_facecolor('w')
#if interactive:
#if legend:
#lgd.set_title("")
#if not sbplt:
#if 'layout' not in kwargs:
#plt.tight_layout()
if interactive:
# 1 = highlight lines
# 2 = line labels
# 3 = legend switches
ax = plt.gca()
# fails for piemode
lines = ax.lines
handles, labels = plt.gca().get_legend_handles_labels()
if 1 in interactive_types:
plugins.connect(plt.gcf(), HighlightLines(lines))
if 3 in interactive_types:
plugins.connect(plt.gcf(), InteractiveLegendPlugin(lines, labels, alpha_unsel=0.0))
for i, l in enumerate(lines):
y_vals = l.get_ydata()
x_vals = l.get_xdata()
x_vals = [str(x) for x in x_vals]
if absolutes:
ls = ['%s (%s: %d)' % (labels[i], x_val, y_val) for x_val, y_val in zip(x_vals, y_vals)]
else:
ls = ['%s (%s: %.2f%%)' % (labels[i], x_val, y_val) for x_val, y_val in zip(x_vals, y_vals)]
if 2 in interactive_types:
#if 'kind' in kwargs and kwargs['kind'] == 'area':
tooltip_line = mpld3.plugins.LineLabelTooltip(lines[i], labels[i])
mpld3.plugins.connect(plt.gcf(), tooltip_line)
#else:
if kwargs['kind'] == 'line':
tooltip_point = mpld3.plugins.PointLabelTooltip(l, labels = ls)
mpld3.plugins.connect(plt.gcf(), tooltip_point)
# works:
#plugins.connect(plt.gcf(), plugins.LineLabelTooltip(l, labels[i]))
#labels = ["Point {0}".format(i) for i in range(num_to_plot)]
#tooltip = plugins.LineLabelTooltip(lines)
#mpld3.plugins.connect(plt.gcf(), mpld3.plugins.PointLabelTooltip(lines))
if piemode:
if not sbplt:
plt.axis('equal')
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
# add x label
# this could be revised now!
# if time series period, it's year for now
if type(dataframe.index) == pandas.tseries.period.PeriodIndex:
x_label = 'Year'
if x_label is not False:
if type(x_label) == str:
plt.xlabel(x_label)
else:
check_x_axis = list(dataframe.index)[0] # get first entry# get second entry of first entry (year, count)
try:
if type(dataframe.index) == pandas.tseries.period.PeriodIndex:
x_label = 'Year'
check_x_axis = int(check_x_axis)
if 1500 < check_x_axis < 2050:
x_label = 'Year'
else:
x_label = 'Group'
except:
x_label = 'Group'
if not sbplt:
if not piemode:
plt.xlabel(x_label)
# no offsets for numerical x and y values
if type(dataframe.index) != pandas.tseries.period.PeriodIndex:
try:
# check if x axis can be an int
check_x_axis = list(dataframe.index)[0]
can_it_be_int = int(check_x_axis)
# if so, set these things
from matplotlib.ticker import ScalarFormatter
plt.gca().xaxis.set_major_formatter(ScalarFormatter())
except:
pass
# same for y axis
try:
# check if x axis can be an int
check_y_axis = list(dataframe.columns)[0]
can_it_be_int = int(check_y_axis)
# if so, set these things
from matplotlib.ticker import ScalarFormatter
plt.gca().yaxis.set_major_formatter(ScalarFormatter())
except:
pass
# y labelling
y_l = False
if not absolutes:
y_l = 'Percentage'
else:
y_l = 'Absolute frequency'
if y_label is not False:
if not sbplt:
if not piemode:
if type(y_label) == str:
plt.ylabel(y_label)
else:
plt.ylabel(y_l)
# hacky: turn legend into subplot titles :)
if sbplt:
# title the big plot
#plt.suptitle(title, fontsize = 16)
# get all axes
if 'layout' not in kwargs:
axes = [l for index, l in enumerate(ax)]
else:
axes = []
cols = [l for index, l in enumerate(ax)]
for col in cols:
for bit in col:
axes.append(bit)
# set subplot titles
for index, a in enumerate(axes):
try:
titletext = list(dataframe.columns)[index]
except:
pass
a.set_title(titletext)
try:
a.legend_.remove()
except:
pass
# remove axis labels for pie plots
if piemode:
a.axes.get_xaxis().set_visible(False)
a.axes.get_yaxis().set_visible(False)
a.axis('equal')
# add sums to bar graphs and pie graphs
# doubled right now, no matter
if not sbplt:
if 'kind' in kwargs:
if kwargs['kind'].startswith('bar'):
width = ax.containers[0][0].get_width()
if was_series:
the_y_limit = plt.ylim()[1]
if show_totals.endswith('plot') or show_totals.endswith('both'):
# make plot a bit higher if putting these totals on it
plt.ylim([0,the_y_limit * 1.05])
for i, label in enumerate(list(dataframe.index)):
if len(dataframe.ix[label]) == 1:
score = dataframe.ix[label][0]
else:
if absolutes:
score = dataframe.ix[label].sum()
else:
#import warnings
#warnings.warn("It's not possible to determine total percentage from individual percentages.")
continue
if not absolutes:
plt.annotate('%.2f' % score, (i, score), ha = 'center', va = 'bottom')
else:
plt.annotate(score, (i, score), ha = 'center', va = 'bottom')
else:
the_y_limit = plt.ylim()[1]
if show_totals.endswith('plot') or show_totals.endswith('both'):
for i, label in enumerate(list(dataframe.columns)):
if len(dataframe[label]) == 1:
score = dataframe[label][0]
else:
if absolutes:
score = dataframe[label].sum()
else:
#import warnings
#warnings.warn("It's not possible to determine total percentage from individual percentages.")
continue
if not absolutes:
plt.annotate('%.2f' % score, (i, score), ha = 'center', va = 'bottom')
else:
plt.annotate(score, (i, score), ha = 'center', va = 'bottom')
#if not running_python_tex:
#plt.gcf().show()
plt.subplots_adjust(left=0.1)
plt.subplots_adjust(bottom=0.18)
#if 'layout' not in kwargs:
#plt.tight_layout()
if save:
import os
if running_python_tex:
imagefolder = '../images'
else:
imagefolder = 'images'
savename = get_savename(imagefolder, save = save, title = title, ext = output_format)
if not os.path.isdir(imagefolder):
os.makedirs(imagefolder)
# save image and get on with our lives
if legend_pos.startswith('o'):
plt.gcf().savefig(savename, dpi=150, bbox_extra_artists=(lgd,), bbox_inches='tight', format = output_format)
else:
plt.gcf().savefig(savename, dpi=150, format = output_format)
time = strftime("%H:%M:%S", localtime())
if os.path.isfile(savename):
print '\n' + time + ": " + savename + " created."
else:
raise ValueError("Error making %s." % savename)
if not interactive and not running_python_tex and not running_spider and not tk:
plt.show()
return
if running_spider or tk or sbplt:
return plt
if interactive:
plt.subplots_adjust(right=.8)
plt.subplots_adjust(left=.1)
try:
ax.legend_.remove()
except:
pass
return mpld3.display()
def plotter(title,
df,
kind = 'line',
x_label = None,
y_label = None,
style = 'ggplot',
figsize = (8, 4),
save = False,
legend_pos = 'best',
reverse_legend = 'guess',
num_to_plot = 7,
tex = 'try',
colours = 'Accent',
cumulative = False,
pie_legend = True,
partial_pie = False,
show_totals = False,
transparent = False,
output_format = 'png',
interactive = False,
black_and_white = False,
show_p_val = False,
indices = False,
**kwargs):
"""Visualise corpus interrogations.
:param title: A title for the plot
:type title: str
:param df: Data to be plotted
:type df: pandas.core.frame.DataFrame
:param x_label: A label for the x axis
:type x_label: str
:param y_label: A label for the y axis
:type y_label: str
:param kind: The kind of chart to make
:type kind: str ('line'/'bar'/'barh'/'pie'/'area')
:param style: Visual theme of plot
:type style: str ('ggplot'/'bmh'/'fivethirtyeight'/'seaborn-talk'/etc)
:param figsize: Size of plot
:type figsize: tuple (int, int)
:param save: If bool, save with *title* as name; if str, use str as name
:type save: bool/str
:param legend_pos: Where to place legend
:type legend_pos: str ('upper right'/'outside right'/etc)
:param reverse_legend: Reverse the order of the legend
:type reverse_legend: bool
:param num_to_plot: How many columns to plot
:type num_to_plot: int/'all'
:param tex: Use TeX to draw plot text
:type tex: bool
:param colours: Colourmap for lines/bars/slices
:type colours: str
:param cumulative: Plot values cumulatively
:type cumulative: bool
:param pie_legend: Show a legend for pie chart
:type pie_legend: bool
:param partial_pie: Allow plotting of pie slices only
:type partial_pie: bool
:param show_totals: Print sums in plot where possible
:type show_totals: str -- 'legend'/'plot'/'both'
:param transparent: Transparent .png background
:type transparent: bool
:param output_format: File format for saved image
:type output_format: str -- 'png'/'pdf'
:param black_and_white: Create black and white line styles
:type black_and_white: bool
:param show_p_val: Attempt to print p values in legend if contained in df
:type show_p_val: bool
:param indices: To use when plotting "distance from root"
:type indices: bool
:param stacked: When making bar chart, stack bars on top of one another
:type stacked: str
:param filled: For area and bar charts, make every column sum to 100
:type filled: str
:param legend: Show a legend
:type legend: bool
:param rot: Rotate x axis ticks by *rot* degrees
:type rot: int
:param subplots: Plot each column separately
:type subplots: bool
:param layout: Grid shape to use when *subplots* is True
:type layout: tuple -- (int, int)
:param interactive: Experimental interactive options
:type interactive: list -- [1, 2, 3]
:returns: matplotlib figure
"""
import corpkit
import os
try:
from IPython.utils.shimmodule import ShimWarning
import warnings
warnings.simplefilter('ignore', ShimWarning)
except:
pass
import matplotlib as mpl
from matplotlib import rc
# prefer seaborn plotting
try:
import seaborn as sns
except:
pass
if interactive:
import matplotlib.pyplot as plt, mpld3
else:
import matplotlib.pyplot as plt
import pandas
from pandas import DataFrame
import numpy
from time import localtime, strftime
from corpkit.tests import check_pytex, check_spider, check_t_kinter
if interactive:
import mpld3
import collections
from mpld3 import plugins, utils
from plugins import InteractiveLegendPlugin, HighlightLines
# check what environment we're in
tk = check_t_kinter()
running_python_tex = check_pytex()
running_spider = check_spider()
def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
"""remove extreme values from colourmap --- no pure white"""
import matplotlib.colors as colors
import numpy as np
new_cmap = colors.LinearSegmentedColormap.from_list(
'trunc({n},{a:.2f},{b:.2f})'.format(n=cmap.name, a=minval, b=maxval),
cmap(np.linspace(minval, maxval, n)))
return new_cmap
def get_savename(imagefolder, save = False, title = False, ext = 'png'):
"""Come up with the savename for the image."""
import os
def urlify(s):
"Turn title into filename"
import re
s = s.lower()
s = re.sub(r"[^\w\s-]", '', s)
s = re.sub(r"\s+", '-', s)
s = re.sub(r"-(textbf|emph|textsc|textit)", '-', s)
return s
# name as
if not ext.startswith('.'):
ext = '.' + ext
if type(save) == str:
savename = os.path.join(imagefolder, (urlify(save) + ext))
#this 'else' is redundant now that title is obligatory
else:
if title:
filename = urlify(title) + ext
savename = os.path.join(imagefolder, filename)
# remove duplicated ext
if savename.endswith('%s%s' % (ext, ext)):
savename = savename.replace('%s%s' % (ext, ext), ext, 1)
return savename
def rename_data_with_total(dataframe, was_series = False, using_tex = False, absolutes = True):
"""adds totals (abs, rel, keyness) to entry name strings"""
if was_series:
where_the_words_are = dataframe.index
else:
where_the_words_are = dataframe.columns
the_labs = []
for w in list(where_the_words_are):
if not absolutes:
if was_series:
perc = dataframe.T[w][0]
else:
the_labs.append(w)
continue
if using_tex:
the_labs.append('%s (%.2f\%%)' % (w, perc))
else:
the_labs.append('%s (%.2f %%)' % (w, perc))
else:
if was_series:
score = dataframe.T[w].sum()
else:
score = dataframe[w].sum()
if using_tex:
the_labs.append('%s (n=%d)' % (w, score))
else:
the_labs.append('%s (n=%d)' % (w, score))
if not was_series:
dataframe.columns = the_labs
else:
vals = list(dataframe[list(dataframe.columns)[0]].values)
dataframe = pandas.DataFrame(vals, index = the_labs)
dataframe.columns = ['Total']
return dataframe
def auto_explode(dataframe, input, was_series = False, num_to_plot = 7):
"""give me a list of strings and i'll output explode option"""
output = [0 for s in range(num_to_plot)]
if was_series:
l = list(dataframe.index)
else:
l = list(dataframe.columns)
if type(input) == str or type(input) == int:
input = [input]
if type(input) == list:
for i in input:
if type(i) == str:
index = l.index(i)
else:
index = i
output[index] = 0.1
return output
# check if we're doing subplots
sbplt = False
if 'subplots' in kwargs:
if kwargs['subplots'] is True:
sbplt = True
kwargs['subplots'] = sbplt
if colours is True:
colours = 'Paired'
# todo: get this dynamically instead.
styles = ['dark_background', 'bmh', 'grayscale', 'ggplot', 'fivethirtyeight', 'matplotlib', False, 'mpl-white']
#if style not in styles:
#raise ValueError('Style %s not found. Use %s' % (str(style), ', '.join(styles)))
if style == 'mpl-white':
try:
sns.set_style("whitegrid")
except:
pass
style = 'matplotlib'
if style is not False and style.startswith('seaborn'):
colours = False
# use 'draggable = True' to make a draggable legend
dragmode = kwargs.get('draggable', False)
kwargs.pop('draggable', None)
if kwargs.get('savepath'):
mpl.rcParams['savefig.directory'] = kwargs.get('savepath')
kwargs.pop('savepath', None)
mpl.rcParams['savefig.bbox'] = 'tight'
mpl.rcParams.update({'figure.autolayout': True})
# try to use tex
# TO DO:
# make some font kwargs here
using_tex = False
mpl.rcParams['font.family'] = 'sans-serif'
mpl.rcParams['text.latex.unicode'] = True
if tex == 'try' or tex is True:
try:
rc('text', usetex=True)
rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})
using_tex = True
except:
matplotlib.rc('font', family='sans-serif')
matplotlib.rc('font', serif='Helvetica Neue')
matplotlib.rc('text', usetex='false')
rc('text', usetex=False)
else:
rc('text', usetex=False)
if interactive:
using_tex = False
if show_totals is False:
show_totals = 'none'
# find out what kind of plot we're making, and enable
# or disable interactive values if need be
kwargs['kind'] = kind.lower()
if interactive:
if kwargs['kind'].startswith('bar'):
interactive_types = [3]
elif kwargs['kind'] == 'area':
interactive_types = [2, 3]
elif kwargs['kind'] == 'line':
interactive_types = [2, 3]
elif kwargs['kind'] == 'pie':
interactive_types = None
warnings.warn('Interactive plotting not yet available for pie plots.')
else:
interactive_types = [None]
if interactive is False:
interactive_types = [None]
# find out if pie mode, add autopct format
piemode = False
if kind == 'pie':
piemode = True
# always the best spot for pie
#if legend_pos == 'best':
#legend_pos = 'lower left'
if show_totals.endswith('plot') or show_totals.endswith('both'):
kwargs['pctdistance'] = 0.6
if using_tex:
kwargs['autopct'] = r'%1.1f\%%'
else:
kwargs['autopct'] = '%1.1f%%'
# copy data, make series into df
dataframe = df.copy()
was_series = False
if type(dataframe) == pandas.core.series.Series:
was_series = True
if not cumulative:
dataframe = DataFrame(dataframe)
else:
dataframe = DataFrame(dataframe.cumsum())
else:
# don't know if this is much good.
if cumulative:
dataframe = DataFrame(dataframe.cumsum())
if len(list(dataframe.columns)) == 1:
was_series = True
# attempt to convert x axis to ints:
try:
dataframe.index = [int(i) for i in list(dataframe.index)]
except:
pass
# remove totals and tkinter order
if not was_series and not all(x.lower() == 'total' for x in list(dataframe.columns)):
for name, ax in zip(['Total'] * 2 + ['tkintertable-order'] * 2, [0, 1, 0, 1]):
try:
dataframe = dataframe.drop(name, axis = ax, errors = 'ignore')
except:
pass
else:
dataframe = dataframe.drop('tkintertable-order', errors = 'ignore')
dataframe = dataframe.drop('tkintertable-order', axis = 1, errors = 'ignore')
# look at columns to see if all can be ints, in which case, set up figure
# for depnumming
if not was_series:
if indices == 'guess':
def isint(x):
try:
a = float(x)
b = int(a)
except ValueError or OverflowError:
return False
else:
return a == b
if all([isint(x) is True for x in list(dataframe.columns)]):
indices = True
else:
indices = False
# if depnumming, plot all, transpose, and rename axes
if indices is True:
num_to_plot = 'all'
dataframe = dataframe.T
if y_label is None:
y_label = 'Percentage of all matches'
if x_label is None:
x_label = ''
# set backend?
output_formats = ['svgz', 'ps', 'emf', 'rgba', 'raw', 'pdf', 'svg', 'eps', 'png', 'pgf']
if output_format not in output_formats:
raise ValueError('%s output format not recognised. Must be: %s' % (output_format, ', '.join(output_formats)))
# don't know if these are necessary
if 'pdf' in output_format:
plt.switch_backend(output_format)
if 'pgf' in output_format:
plt.switch_backend(output_format)
if num_to_plot == 'all':
if was_series:
if not piemode:
num_to_plot = len(dataframe)
else:
num_to_plot = len(dataframe)
else:
if not piemode:
num_to_plot = len(list(dataframe.columns))
else:
num_to_plot = len(dataframe.index)
# explode pie, or remove if not piemode
if piemode and not sbplt and kwargs.get('explode'):
kwargs['explode'] = auto_explode(dataframe,
kwargs['explode'],
was_series = was_series,
num_to_plot = num_to_plot)
else:
kwargs.pop('explode', None)
legend = kwargs.get('legend', False)
#cut data short
plotting_a_totals_column = False
if was_series:
if list(dataframe.columns)[0] != 'Total':
try:
can_be_ints = [int(x) for x in list(dataframe.index)]
num_to_plot = len(dataframe)
except:
dataframe = dataframe[:num_to_plot]
elif list(dataframe.columns)[0] == 'Total':
plotting_a_totals_column = True
if not 'legend' in kwargs:
legend = False
num_to_plot = len(dataframe)
else:
dataframe = dataframe.T.head(num_to_plot).T
# remove stats fields, put p in entry text, etc.
statfields = ['slope', 'intercept', 'r', 'p', 'stderr']
try:
dataframe = dataframe.drop(statfields, axis = 1, errors = 'ignore')
except:
pass
try:
dataframe.ix['p']
there_are_p_vals = True
except:
there_are_p_vals = False
if show_p_val:
if there_are_p_vals:
newnames = []
for col in list(dataframe.columns):
pval = dataframe[col]['p']
def p_string_formatter(val):
if val < 0.001:
if not using_tex:
return 'p < 0.001'
else:
return r'p $<$ 0.001'
else:
return 'p = %s' % format(val, '.3f')
pstr = p_string_formatter(pval)
newname = '%s (%s)' % (col, pstr)
newnames.append(newname)
dataframe.columns = newnames
dataframe.drop(statfields, axis = 0, inplace = True, errors = 'ignore')
else:
warnings.warn('No p-values calculated to show.\n\nUse sort_by and keep_stats in editor() to generate these values.')
else:
if there_are_p_vals:
dataframe.drop(statfields, axis = 0, inplace = True, errors = 'ignore')
# make and set y label
absolutes = True
if type(dataframe) == pandas.core.frame.DataFrame:
try:
if not all([s.is_integer() for s in dataframe.iloc[0,:].values]):
absolutes = False
except:
pass
else:
if not all([s.is_integer() for s in dataframe.values]):
absolutes = False
# use colormap if need be:
if num_to_plot > 0:
if not was_series:
if kind in ['pie', 'line', 'area']:
if colours:
if not plotting_a_totals_column:
if colours == 'Default':
colours = 'Paired'
kwargs['colormap'] = colours
#else:
if colours:
if colours == 'Default':
colours = 'Paired'
kwargs['colormap'] = colours
if piemode:
if num_to_plot > 0:
if colours == 'Default':
colours = 'Paired'
kwargs['colormap'] = colours
else:
if num_to_plot > 0:
if colours == 'Default':
colours = 'Paired'
kwargs['colormap'] = colours
# multicoloured bar charts
if colours:
if kind.startswith('bar'):
if len(list(dataframe.columns)) == 1:
if not black_and_white:
import numpy as np
the_range = np.linspace(0, 1, num_to_plot)
cmap = plt.get_cmap(colours)
kwargs['colors'] = [cmap(n) for n in the_range]
# make a bar width ... ? ...
#kwargs['width'] = (figsize[0] / float(num_to_plot)) / 1.5
# reversing legend option
if reverse_legend is True:
rev_leg = True
elif reverse_legend is False:
rev_leg = False
# show legend or don't, guess whether to reverse based on kind
if kind in ['bar', 'barh', 'area', 'line', 'pie']:
if was_series:
legend = False
if kind == 'pie':
if pie_legend:
legend = True
else:
legend = False
if kind in ['barh', 'area']:
if reverse_legend == 'guess':
rev_leg = True
if not 'rev_leg' in locals():
rev_leg = False
# the default legend placement
if legend_pos is True:
legend_pos = 'best'
# cut dataframe if just_totals
try:
tst = dataframe['Combined total']
dataframe = dataframe.head(num_to_plot)
except:
pass
# rotate automatically
if 'rot' not in kwargs:
if not was_series:
xvals = [str(i) for i in list(dataframe.index)[:num_to_plot]]
#if 'kind' in kwargs:
#if kwargs['kind'] in ['barh', 'area']:
#xvals = [str(i) for i in list(dataframe.columns)[:num_to_plot]]
else:
xvals = [str(i) for i in list(dataframe.columns)[:num_to_plot]]
if len(max(xvals, key=len)) > 6:
if not piemode:
kwargs['rot'] = 45
# no title for subplots because ugly,
if title and not sbplt:
kwargs['title'] = title
# no interactive subplots yet:
if sbplt and interactive:
import warnings
interactive = False
warnings.warn('No interactive subplots yet, sorry.')
return
# not using pandas for labels or legend anymore.
#kwargs['labels'] = None
#kwargs['legend'] = False
if legend:
if num_to_plot > 6:
if not kwargs.get('ncol'):
kwargs['ncol'] = num_to_plot / 7
# kwarg options go in leg_options
leg_options = {'framealpha': .8,
'shadow': kwargs.get('shadow', False),
'ncol': kwargs.pop('ncol', 1)}
# determine legend position based on this dict
if legend_pos:
possible = {'best': 0, 'upper right': 1, 'upper left': 2, 'lower left': 3, 'lower right': 4,
'right': 5, 'center left': 6, 'center right': 7, 'lower center': 8, 'upper center': 9,
'center': 10, 'o r': 2, 'outside right': 2, 'outside upper right': 2,
'outside center right': 'center left', 'outside lower right': 'lower left'}
if type(legend_pos) == int:
the_loc = legend_pos
elif type(legend_pos) == str:
try:
the_loc = possible[legend_pos]
except KeyError:
raise KeyError('legend_pos value must be one of:\n%s\n or an int between 0-10.' %', '.join(possible.keys()))
leg_options['loc'] = the_loc
#weirdness needed for outside plot
if legend_pos in ['o r', 'outside right', 'outside upper right']:
leg_options['bbox_to_anchor'] = (1.02, 1)
if legend_pos == 'outside center right':
leg_options['bbox_to_anchor'] = (1.02, 0.5)
if legend_pos == 'outside lower right':
leg_options['loc'] == 'upper right'
leg_options['bbox_to_anchor'] = (0.5, 0.5)
# a bit of distance between legend and plot for outside legends
if type(legend_pos) == str:
if legend_pos.startswith('o'):
leg_options['borderaxespad'] = 1
if not piemode:
if show_totals.endswith('both') or show_totals.endswith('legend'):
dataframe = rename_data_with_total(dataframe,
was_series = was_series,
using_tex = using_tex,
absolutes = absolutes)
else:
if pie_legend:
if show_totals.endswith('both') or show_totals.endswith('legend'):
dataframe = rename_data_with_total(dataframe,
was_series = was_series,
using_tex = using_tex,
absolutes = absolutes)
if piemode:
if partial_pie:
dataframe = dataframe / 100.0
# some pie things
if piemode:
if not sbplt:
kwargs['y'] = list(dataframe.columns)[0]
if pie_legend:
kwargs['legend'] = False
if was_series:
leg_options['labels'] = list(dataframe.index)
else:
leg_options['labels'] = list(dataframe.columns)
else:
if pie_legend:
kwargs['legend'] = False
if was_series:
leg_options['labels'] = list(dataframe.index)
else:
leg_options['labels'] = list(dataframe.index)
def filler(df):
pby = df.T.copy()
for i in list(pby.columns):
tot = pby[i].sum()
pby[i] = pby[i] * 100.0 / tot
return pby.T
areamode = False
if kind == 'area':
areamode = True
if legend is False:
kwargs['legend'] = False
# line highlighting option for interactive!
if interactive:
if 2 in interactive_types:
if kind == 'line':
kwargs['marker'] = ','
if not piemode:
kwargs['alpha'] = 0.1
# convert dates --- works only in my current case!
if plotting_a_totals_column or not was_series:
try:
can_it_be_int = int(list(dataframe.index)[0])
can_be_int = True
except:
can_be_int = False
if can_be_int:
if 1500 < int(list(dataframe.index)[0]):
if 2050 > int(list(dataframe.index)[0]):
n = pandas.PeriodIndex([d for d in list(dataframe.index)], freq='A')
dataframe = dataframe.set_index(n)
if kwargs.get('filled'):
if areamode or kind.startswith('bar'):
dataframe = filler(dataframe)
kwargs.pop('filled', None)
MARKERSIZE = 4
COLORMAP = {
0: {'marker': None, 'dash': (None,None)},
1: {'marker': None, 'dash': [5,5]},
2: {'marker': "o", 'dash': (None,None)},
3: {'marker': None, 'dash': [1,3]},
4: {'marker': "s", 'dash': [5,2,5,2,5,10]},
5: {'marker': None, 'dash': [5,3,1,2,1,10]},
6: {'marker': 'o', 'dash': (None,None)},
7: {'marker': None, 'dash': [5,3,1,3]},
8: {'marker': "1", 'dash': [1,3]},
9: {'marker': "*", 'dash': [5,5]},
10: {'marker': "2", 'dash': [5,2,5,2,5,10]},
11: {'marker': "s", 'dash': (None,None)}
}
HATCHES = {
0: {'color': '#dfdfdf', 'hatch':"/"},
1: {'color': '#6f6f6f', 'hatch':"\\"},
2: {'color': 'b', 'hatch':"|"},
3: {'color': '#dfdfdf', 'hatch':"-"},
4: {'color': '#6f6f6f', 'hatch':"+"},
5: {'color': 'b', 'hatch':"x"}
}
if black_and_white:
if kind == 'line':
kwargs['linewidth'] = 1
cmap = plt.get_cmap('Greys')
new_cmap = truncate_colormap(cmap, 0.25, 0.95)
if kind == 'bar':
# darker if just one entry
if len(dataframe.columns) == 1:
new_cmap = truncate_colormap(cmap, 0.70, 0.90)
kwargs['colormap'] = new_cmap
class dummy_context_mgr():
"""a fake context for plotting without style
perhaps made obsolete by 'classic' style in new mpl"""
def __enter__(self):
return None
def __exit__(self, one, two, three):
return False
with plt.style.context((style)) if style != 'matplotlib' else dummy_context_mgr():
if not sbplt:
# check if negative values, no stacked if so
if areamode:
kwargs['legend'] = False
if dataframe.applymap(lambda x: x < 0.0).any().any():
kwargs['stacked'] = False
rev_leg = False
ax = dataframe.plot(figsize = figsize, **kwargs)
if areamode:
handles, labels = plt.gca().get_legend_handles_labels()
del handles
del labels
else:
plt.gcf().set_tight_layout(False)
if not piemode:
ax = dataframe.plot(figsize = figsize, **kwargs)
else:
ax = dataframe.plot(figsize = figsize, **kwargs)
handles, labels = plt.gca().get_legend_handles_labels()
plt.legend( handles, labels, loc = leg_options['loc'], bbox_to_anchor = (0,-0.1,1,1),
bbox_transform = plt.gcf().transFigure )
# this line allows layouts with missing plots
# i.e. layout = (5, 2) with only nine plots
plt.gcf().set_tight_layout(False)
if 'rot' in kwargs:
if kwargs['rot'] != 0 and kwargs['rot'] != 90:
labels = [item.get_text() for item in ax.get_xticklabels()]
ax.set_xticklabels(labels, rotation = kwargs['rot'], ha='right')
if transparent:
plt.gcf().patch.set_facecolor('white')
plt.gcf().patch.set_alpha(0)
if black_and_white:
if kind == 'line':
# white background
# change everything to black and white with interesting dashes and markers
c = 0
for line in ax.get_lines():
line.set_color('black')
#line.set_width(1)
line.set_dashes(COLORMAP[c]['dash'])
line.set_marker(COLORMAP[c]['marker'])
line.set_markersize(MARKERSIZE)
c += 1
if c == len(COLORMAP.keys()):
c = 0
# draw legend with proper placement etc
if legend:
if not piemode and not sbplt:
if 3 not in interactive_types:
handles, labels = plt.gca().get_legend_handles_labels()
# area doubles the handles and labels. this removes half:
if areamode:
handles = handles[-len(handles) / 2:]
labels = labels[-len(labels) / 2:]
if rev_leg:
handles = handles[::-1]
labels = labels[::-1]
lgd = plt.legend(handles, labels, **leg_options)
if interactive:
# 1 = highlight lines
# 2 = line labels
# 3 = legend switches
ax = plt.gca()
# fails for piemode
lines = ax.lines
handles, labels = plt.gca().get_legend_handles_labels()
if 1 in interactive_types:
plugins.connect(plt.gcf(), HighlightLines(lines))
if 3 in interactive_types:
plugins.connect(plt.gcf(), InteractiveLegendPlugin(lines, labels, alpha_unsel=0.0))
for i, l in enumerate(lines):
y_vals = l.get_ydata()
x_vals = l.get_xdata()
x_vals = [str(x) for x in x_vals]
if absolutes:
ls = ['%s (%s: %d)' % (labels[i], x_val, y_val) for x_val, y_val in zip(x_vals, y_vals)]
else:
ls = ['%s (%s: %.2f%%)' % (labels[i], x_val, y_val) for x_val, y_val in zip(x_vals, y_vals)]
if 2 in interactive_types:
#if 'kind' in kwargs and kwargs['kind'] == 'area':
tooltip_line = mpld3.plugins.LineLabelTooltip(lines[i], labels[i])
mpld3.plugins.connect(plt.gcf(), tooltip_line)
#else:
if kind == 'line':
tooltip_point = mpld3.plugins.PointLabelTooltip(l, labels = ls)
mpld3.plugins.connect(plt.gcf(), tooltip_point)
if piemode:
if not sbplt:
plt.axis('equal')
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
# add x label
# this could be revised now!
# if time series period, it's year for now
if type(dataframe.index) == pandas.tseries.period.PeriodIndex:
x_label = 'Year'
if x_label is not False:
if type(x_label) == str:
plt.xlabel(x_label)
else:
check_x_axis = list(dataframe.index)[0] # get first entry# get second entry of first entry (year, count)
try:
if type(dataframe.index) == pandas.tseries.period.PeriodIndex:
x_label = 'Year'
check_x_axis = int(check_x_axis)
if 1500 < check_x_axis < 2050:
x_label = 'Year'
else:
x_label = 'Group'
except:
x_label = 'Group'
if not sbplt:
if not piemode:
plt.xlabel(x_label)
def is_number(s):
"""check if str can be can be made into float/int"""
try:
float(s) # for int, long and float
except ValueError:
try:
complex(s) # for complex
except ValueError:
return False
return True
# for now, always turn off sci notation
from matplotlib.ticker import ScalarFormatter
if type(dataframe.index) != pandas.tseries.period.PeriodIndex:
try:
if all(is_number(s) for s in list(dataframe.index)):
plt.gca().xaxis.set_major_formatter(ScalarFormatter())
except:
pass
try:
if all(is_number(s) for s in list(dataframe.columns)):
plt.gca().yaxis.set_major_formatter(ScalarFormatter())
except:
pass
# y labelling
y_l = False
if not absolutes:
y_l = 'Percentage'
else:
y_l = 'Absolute frequency'
def suplabel(axis,label,label_prop=None,
labelpad=5,
ha='center',va='center'):
''' Add super ylabel or xlabel to the figure
Similar to matplotlib.suptitle
axis - string: "x" or "y"
label - string
label_prop - keyword dictionary for Text
labelpad - padding from the axis (default: 5)
ha - horizontal alignment (default: "center")
va - vertical alignment (default: "center")
'''
fig = plt.gcf()
xmin = []
ymin = []
for ax in fig.axes:
xmin.append(ax.get_position().xmin)
ymin.append(ax.get_position().ymin)
xmin,ymin = min(xmin),min(ymin)
dpi = fig.dpi
if axis.lower() == "y":
rotation=90.
x = xmin-float(labelpad)/dpi
y = 0.5
elif axis.lower() == 'x':
rotation = 0.
x = 0.5
y = ymin - float(labelpad)/dpi
else:
raise Exception("Unexpected axis: x or y")
if label_prop is None:
label_prop = dict()
plt.gcf().text(x,y,label,rotation=rotation,
transform=fig.transFigure,
ha=ha,va=va,
**label_prop)
if y_label is not False:
if not sbplt:
if not piemode:
if type(y_label) == str:
plt.ylabel(y_label)
else:
plt.ylabel(y_l)
else:
if type(y_label) == str:
the_y = y_label
else:
the_y = y_l
#suplabel('y', the_y, labelpad = 1.5)
plt.gcf().text(0.04, 0.5, the_y, va='center', rotation='vertical')
#plt.subplots_adjust(left=0.5)
# if not piemode:
# if type(y_label) == str:
# plt.ylabel(y_label)
# else:
# plt.ylabel(y_l)
# hacky: turn legend into subplot titles :)
if sbplt:
# title the big plot
#plt.gca().suptitle(title, fontsize = 16)
#plt.subplots_adjust(top=0.9)
# get all axes
if 'layout' not in kwargs:
axes = [l for index, l in enumerate(ax)]
else:
axes = []
cols = [l for index, l in enumerate(ax)]
for col in cols:
for bit in col:
axes.append(bit)
# set subplot titles
for index, a in enumerate(axes):
try:
titletext = list(dataframe.columns)[index]
except:
pass
a.set_title(titletext)
try:
a.legend_.remove()
except:
pass
# remove axis labels for pie plots
if piemode:
a.axes.get_xaxis().set_visible(False)
a.axes.get_yaxis().set_visible(False)
a.axis('equal')
# show grid
a.grid(b=kwargs.get('grid', False))
kwargs.pop('grid', None)
# add sums to bar graphs and pie graphs
# doubled right now, no matter
if not sbplt:
if kind.startswith('bar'):
width = ax.containers[0][0].get_width()
# show grid
a.grid(b=kwargs.get('grid', False))
kwargs.pop('grid', None)
if was_series:
the_y_limit = plt.ylim()[1]
if show_totals.endswith('plot') or show_totals.endswith('both'):
# make plot a bit higher if putting these totals on it
plt.ylim([0,the_y_limit * 1.05])
for i, label in enumerate(list(dataframe.index)):
if len(dataframe.ix[label]) == 1:
score = dataframe.ix[label][0]
else:
if absolutes:
score = dataframe.ix[label].sum()
else:
#import warnings
#warnings.warn("It's not possible to determine total percentage from individual percentages.")
continue
if not absolutes:
plt.annotate('%.2f' % score, (i, score), ha = 'center', va = 'bottom')
else:
plt.annotate(score, (i, score), ha = 'center', va = 'bottom')
else:
the_y_limit = plt.ylim()[1]
if show_totals.endswith('plot') or show_totals.endswith('both'):
for i, label in enumerate(list(dataframe.columns)):
if len(dataframe[label]) == 1:
score = dataframe[label][0]
else:
if absolutes:
score = dataframe[label].sum()
else:
#import warnings
#warnings.warn("It's not possible to determine total percentage from individual percentages.")
continue
if not absolutes:
plt.annotate('%.2f' % score, (i, score), ha = 'center', va = 'bottom')
else:
plt.annotate(score, (i, score), ha = 'center', va = 'bottom')
plt.subplots_adjust(left=0.1)
plt.subplots_adjust(bottom=0.18)
if 'layout' not in kwargs:
if not sbplt:
plt.tight_layout()
if save:
import os
if running_python_tex:
imagefolder = '../images'
else:
imagefolder = 'images'
savename = get_savename(imagefolder, save = save, title = title, ext = output_format)
if not os.path.isdir(imagefolder):
os.makedirs(imagefolder)
# save image and get on with our lives
if legend_pos.startswith('o'):
plt.gcf().savefig(savename, dpi=150, bbox_extra_artists=(lgd,), bbox_inches='tight', format = output_format)
else:
plt.gcf().savefig(savename, dpi=150, format = output_format)
time = strftime("%H:%M:%S", localtime())
if os.path.isfile(savename):
print '\n' + time + ": " + savename + " created."
else:
raise ValueError("Error making %s." % savename)
if dragmode:
plt.legend().draggable()
if sbplt:
plt.subplots_adjust(right=.8)
plt.subplots_adjust(left=.1)
if not interactive and not running_python_tex and not running_spider \
and not tk:
plt.gcf().show()
return
elif running_spider or tk:
return plt
if interactive:
plt.subplots_adjust(right=.8)
plt.subplots_adjust(left=.1)
try:
ax.legend_.remove()
except:
pass
return mpld3.display()
