Python to generate nice looking SVG graph http://pygal.org/
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#!/usr/bin/env python
from itertools import izip, count, chain
from lxml import etree
from svg.charts.graph import Graph
from util import float_range
def get_pairs(i):
i = iter(i)
while True: yield i.next(), i.next()
class Plot(Graph):
"""=== For creating SVG plots of scalar data
= Synopsis
require 'SVG/Graph/Plot'
# Data sets are x,y pairs
# Note that multiple data sets can differ in length, and that the
# data in the datasets needn't be in order; they will be ordered
# by the plot along the X-axis.
projection = [
6, 11, 0, 5, 18, 7, 1, 11, 13, 9, 1, 2, 19, 0, 3, 13,
7, 9
]
actual = [
0, 18, 8, 15, 9, 4, 18, 14, 10, 2, 11, 6, 14, 12,
15, 6, 4, 17, 2, 12
]
graph = SVG::Graph::Plot.new({
:height => 500,
:width => 300,
:key => true,
:scale_x_integers => true,
:scale_y_integerrs => true,
})
graph.add_data({
:data => projection
:title => 'Projected',
})
graph.add_data({
:data => actual,
:title => 'Actual',
})
print graph.burn()
= Description
Produces a graph of scalar data.
This object aims to allow you to easily create high quality
SVG[http://www.w3c.org/tr/svg] scalar plots. You can either use the
default style sheet or supply your own. Either way there are many options
which can be configured to give you control over how the graph is
generated - with or without a key, data elements at each point, title,
subtitle etc.
= Examples
http://www.germane-software/repositories/public/SVG/test/plot.rb
= Notes
The default stylesheet handles upto 10 data sets, if you
use more you must create your own stylesheet and add the
additional settings for the extra data sets. You will know
if you go over 10 data sets as they will have no style and
be in black.
Unlike the other types of charts, data sets must contain x,y pairs:
[1, 2] # A data set with 1 point: (1,2)
[1,2, 5,6] # A data set with 2 points: (1,2) and (5,6)
= See also
* SVG::Graph::Graph
* SVG::Graph::BarHorizontal
* SVG::Graph::Bar
* SVG::Graph::Line
* SVG::Graph::Pie
* SVG::Graph::TimeSeries
== Author
Sean E. Russell <serATgermaneHYPHENsoftwareDOTcom>
Copyright 2004 Sean E. Russell
This software is available under the Ruby license[LICENSE.txt]"""
top_align = right_align = top_font = right_font = 1
"""Determines the scaling for the Y axis divisions.
graph.scale_y_divisions = 0.5
would cause the graph to attempt to generate labels stepped by 0.5; EG:
0, 0.5, 1, 1.5, 2, ..."""
scale_y_divisions = None
"Make the X axis labels integers"
scale_x_integers = False
"Make the Y axis labels integers"
scale_y_integers = False
"Fill the area under the line"
area_fill = False
"""Show a small circle on the graph where the line
goes from one point to the next."""
show_data_points = True
"Indicate whether the lines should be drawn between points"
draw_lines_between_points = True
"Set the minimum value of the X axis"
min_x_value = None
"Set the minimum value of the Y axis"
min_y_value = None
"Set the maximum value of the X axis"
max_x_value = None
"Set the maximum value of the Y axis"
max_y_value = None
stacked = False
@apply
def scale_x_divisions():
doc = """Determines the scaling for the X axis divisions.
graph.scale_x_divisions = 2
would cause the graph to attempt to generate labels stepped by 2; EG:
0,2,4,6,8..."""
def fget(self):
return getattr(self, '_scale_x_divisions', None)
def fset(self, val):
self._scale_x_divisions = val
return property(**locals())
def validate_data(self, data):
if len(data['data']) % 2 != 0:
raise "Expecting x,y pairs for data points for %s." % self.__class__.__name__
def process_data(self, data):
pairs = list(get_pairs(data['data']))
pairs.sort()
data['data'] = zip(*pairs)
def calculate_left_margin(self):
super(Plot, self).calculate_left_margin()
label_left = len(str(self.get_x_labels()[0])) / 2 * self.font_size * 0.6
self.border_left = max(label_left, self.border_left)
def calculate_right_margin(self):
super(Plot, self).calculate_right_margin()
label_right = len(str(self.get_x_labels()[-1])) / 2 * self.font_size * 0.6
self.border_right = max(label_right, self.border_right)
def data_max(self, axis):
data_index = getattr(self, '%s_data_index' % axis)
max_value = max(chain(*map(lambda set: set['data'][data_index], self.data)))
# above is same as
#max_value = max(map(lambda set: max(set['data'][data_index]), self.data))
spec_max = getattr(self, 'max_%s_value' % axis)
max_value = max(max_value, spec_max)
return max_value
def data_min(self, axis):
data_index = getattr(self, '%s_data_index' % axis)
min_value = min(chain(*map(lambda set: set['data'][data_index], self.data)))
spec_min = getattr(self, 'min_%s_value' % axis)
if spec_min is not None:
min_value = min(min_value, spec_min)
return min_value
x_data_index = 0
y_data_index = 1
def data_range(self, axis):
side = {'x': 'right', 'y': 'top'}[axis]
min_value = self.data_min(axis)
max_value = self.data_max(axis)
range = max_value - min_value
side_pad = range / 20.0 or 10
scale_range = (max_value + side_pad) - min_value
scale_division = getattr(self, 'scale_%s_divisions' % axis) or (scale_range / 10.0)
if getattr(self, 'scale_%s_integers' % axis):
scale_division = round(scale_division) or 1
return min_value, max_value, scale_division
def x_range(self): return self.data_range('x')
def y_range(self): return self.data_range('y')
def get_data_values(self, axis):
min_value, max_value, scale_division = self.data_range(axis)
return tuple(float_range(*self.data_range(axis)))
def get_x_values(self): return self.get_data_values('x')
def get_y_values(self): return self.get_data_values('y')
def get_x_labels(self):
return map(str, self.get_x_values())
def get_y_labels(self):
return map(str, self.get_y_values())
def field_size(self, axis):
size = {'x': 'width', 'y': 'height'}[axis]
side = {'x': 'right', 'y': 'top'}[axis]
values = getattr(self, 'get_%s_values' % axis)()
max_d = self.data_max(axis)
dx = float(max_d - values[-1]) / (values[-1] - values[-2])
graph_size = getattr(self, 'graph_%s' % size)
side_font = getattr(self, '%s_font' % side)
side_align = getattr(self, '%s_align' % side)
result = (float(graph_size) - self.font_size*2*side_font) / \
(len(values) + dx - side_align)
return result
def field_width(self): return self.field_size('x')
def field_height(self): return self.field_size('y')
def draw_data(self):
self.load_transform_parameters()
for line, data in izip(count(1), self.data):
x_start, y_start = self.transform_output_coordinates(
(data['data'][self.x_data_index][0],
data['data'][self.y_data_index][0])
)
data_points = zip(*data['data'])
graph_points = self.get_graph_points(data_points)
lpath = self.get_lpath(graph_points)
if self.area_fill:
graph_height = self.graph_height
path = etree.SubElement(self.graph, 'path', {
'd': 'M%(x_start)f %(graph_height)f %(lpath)s V%(graph_height)f Z' % vars(),
'class': 'fill%(line)d' % vars()})
if self.draw_lines_between_points:
path = etree.SubElement(self.graph, 'path', {
'd': 'M%(x_start)f %(y_start)f %(lpath)s' % vars(),
'class': 'line%(line)d' % vars()})
self.draw_data_points(line, data_points, graph_points)
self._draw_constant_lines()
del self.__transform_parameters
def add_constant_line(self, value, label = None, style = None):
self.constant_lines = getattr(self, 'constant_lines', [])
self.constant_lines.append((value, label, style))
def _draw_constant_lines(self):
if hasattr(self, 'constant_lines'):
map(self.__draw_constant_line, self.constant_lines)
def __draw_constant_line(self, (value, label, style)):
"Draw a constant line on the y-axis with the label"
start = self.transform_output_coordinates((0, value))[1]
stop = self.graph_width
path = etree.SubElement(self.graph, 'path', {
'd': 'M 0 %(start)s h%(stop)s' % vars(),
'class': 'constantLine'})
if style:
path.set('style', style)
text = etree.SubElement(self.graph, 'text', {
'x': str(2),
'y': str(start - 2),
'class': 'constantLine'})
text.text = label
def load_transform_parameters(self):
"Cache the parameters necessary to transform x & y coordinates"
x_min, x_max, x_div = self.x_range()
y_min, y_max, y_div = self.y_range()
x_step = (float(self.graph_width) - self.font_size*2) / \
(x_max - x_min)
y_step = (float(self.graph_height) - self.font_size*2) / \
(y_max - y_min)
self.__transform_parameters = dict(vars())
del self.__transform_parameters['self']
def get_graph_points(self, data_points):
return map(self.transform_output_coordinates, data_points)
def get_lpath(self, points):
points = map(lambda p: "%f %f" % p, points)
return 'L' + ' '.join(points)
def transform_output_coordinates(self, (x,y)):
x_min = self.__transform_parameters['x_min']
x_step = self.__transform_parameters['x_step']
y_min = self.__transform_parameters['y_min']
y_step = self.__transform_parameters['y_step']
#locals().update(self.__transform_parameters)
#vars().update(self.__transform_parameters)
x = (x - x_min) * x_step
y = self.graph_height - (y - y_min) * y_step
return x,y
def draw_data_points(self, line, data_points, graph_points):
if not self.show_data_points \
and not self.show_data_values: return
for ((dx,dy),(gx,gy)) in izip(data_points, graph_points):
if self.show_data_points:
etree.SubElement(self.graph, 'circle', {
'cx': str(gx),
'cy': str(gy),
'r': '2.5',
'class': 'dataPoint%(line)s' % vars()})
if self.show_data_values:
self.add_popup(gx, gy, self.format(dx, dy))
self.make_datapoint_text(gx, gy-6, dy)
def format(self, x, y):
return '(%0.2f, %0.2f)' % (x,y)