mirror of https://github.com/Kozea/pygal.git
Python to generate nice looking SVG graph
http://pygal.org/
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256 lines
6.4 KiB
256 lines
6.4 KiB
#!python |
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from SVG import Graph |
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from itertools import chain |
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__all__ = ( 'VerticalBar', 'HorizontalBar' ) |
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class Bar( Graph ): |
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"A superclass for bar-style graphs. Do not instantiate directly." |
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# gap between bars |
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bar_gap = True |
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# how to stack adjacent dataset series |
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# overlap - overlap bars with transparent colors |
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# top - stack bars on top of one another |
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# side - stack bars side-by-side |
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stack = 'overlap' |
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scale_divisions = None |
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def __init__( self, fields, *args, **kargs ): |
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self.fields = fields |
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super( Bar, self ).__init__( *args, **kargs ) |
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def data_max( self ): |
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return max( chain( *map( lambda set: set['data'], self.data ) ) ) |
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# above is same as |
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# return max( map( lambda set: max( set['data'] ), self.data ) ) |
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def data_min( self ): |
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if not getattr(self, 'min_scale_value') is None: return self.min_scale_value |
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min_value = min( chain( *map( lambda set: set['data'], self.data ) ) ) |
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min_value = min( min_value, 0 ) |
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return min_value |
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def get_css( self ): |
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return """\ |
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/* default fill styles for multiple datasets (probably only use a single dataset on this graph though) */ |
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.key1,.fill1{ |
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fill: #ff0000; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 0.5px; |
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} |
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.key2,.fill2{ |
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fill: #0000ff; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key3,.fill3{ |
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fill: #00ff00; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key4,.fill4{ |
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fill: #ffcc00; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key5,.fill5{ |
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fill: #00ccff; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key6,.fill6{ |
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fill: #ff00ff; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key7,.fill7{ |
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fill: #00ffff; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key8,.fill8{ |
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fill: #ffff00; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key9,.fill9{ |
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fill: #cc6666; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key10,.fill10{ |
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fill: #663399; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key11,.fill11{ |
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fill: #339900; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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.key12,.fill12{ |
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fill: #9966FF; |
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fill-opacity: 0.5; |
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stroke: none; |
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stroke-width: 1px; |
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} |
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""" |
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def float_range( start = 0, stop = None, step = 1 ): |
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"Much like the built-in function range, but accepts floats" |
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while start < stop: |
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yield float( start ) |
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start += step |
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class VerticalBar( Bar ): |
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""" # === Create presentation quality SVG bar graphs easily |
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# |
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# = Synopsis |
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# |
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# require 'SVG/Graph/Bar' |
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# |
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# fields = %w(Jan Feb Mar); |
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# data_sales_02 = [12, 45, 21] |
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# |
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# graph = SVG::Graph::Bar.new( |
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# :height => 500, |
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# :width => 300, |
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# :fields => fields |
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# ) |
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# |
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# graph.add_data( |
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# :data => data_sales_02, |
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# :title => 'Sales 2002' |
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# ) |
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# |
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# print "Content-type: image/svg+xml\r\n\r\n" |
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# print graph.burn |
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# |
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# = Description |
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# |
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# This object aims to allow you to easily create high quality |
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# SVG[http://www.w3c.org/tr/svg bar graphs. You can either use the default |
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# style sheet or supply your own. Either way there are many options which |
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# can be configured to give you control over how the graph is generated - |
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# with or without a key, data elements at each point, title, subtitle etc. |
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# |
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# = Notes |
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# |
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# The default stylesheet handles upto 12 data sets, if you |
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# use more you must create your own stylesheet and add the |
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# additional settings for the extra data sets. You will know |
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# if you go over 12 data sets as they will have no style and |
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# be in black. |
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# |
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# = Examples |
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# |
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# * http://germane-software.com/repositories/public/SVG/test/test.rb |
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# |
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# = See also |
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# |
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# * SVG::Graph::Graph |
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# * SVG::Graph::BarHorizontal |
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# * SVG::Graph::Line |
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# * SVG::Graph::Pie |
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# * SVG::Graph::Plot |
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# * SVG::Graph::TimeSeries |
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""" |
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top_align = top_font = 1 |
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def get_x_labels( self ): |
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return self.fields |
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# adapted from plot (very much like calling data_range('y')) |
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def data_range( self ): |
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min_value = self.data_min( ) |
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max_value = self.data_max( ) |
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range = max_value - min_value |
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top_pad = range / 20.0 or 10 |
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scale_range = ( max_value + top_pad ) - min_value |
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scale_division = self.scale_divisions or ( scale_range / 10.0 ) |
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if self.scale_integers: |
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scale_division = round(scale_division) or 1 |
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return min_value, max_value, scale_division |
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# adapted from Plot |
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def get_data_values( self ): |
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min_value, max_value, scale_division = self.data_range() |
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result = tuple( float_range( min_value, max_value + scale_division, scale_division ) ) |
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if self.scale_integers: |
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result = map(int, result) |
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return result |
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# adapted from Plot |
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def get_y_labels( self ): |
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return map( str, self.get_data_values() ) |
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def x_label_offset( self, width ): |
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return width / 2.0 |
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def draw_data( self ): |
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min_value = self.data_min() |
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unit_size = (float(self.graph_height) - self.font_size*2*self.top_font) |
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unit_size /= (max(self.get_data_values()) - min(self.get_data_values()) ) |
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bar_gap = 0 |
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if self.bar_gap: |
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bar_gap = 10 |
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if self.get_field_width() < 10: |
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bar_gap = self.get_field_width() / 2 |
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bar_width = self.get_field_width() - bar_gap |
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if self.stack == 'side': |
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bar_width /= len( self.data ) |
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x_mod = ( self.graph_width - bar_gap )/2 |
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if self.stack == 'side': |
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x_mod -= bar_width/2 |
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bottom = self.graph_height |
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for field_count, field in enumerate( self.fields ): |
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for dataset_count, dataset in enumerate( self.data ): |
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# cases (assume 0 = +ve): |
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# value min length |
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# +ve +ve value - min |
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# +ve -ve value - 0 |
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# -ve -ve value.abs - 0 |
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value = dataset['data'][field_count] |
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left = self.get_field_width() * field_count |
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length = ( abs(value) - max( min_value, 0 ) ) * unit_size |
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# top is 0 if value is negative |
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top = bottom - (( max(value,0) - min_value ) * unit_size ) |
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if self.stack == 'side': |
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left += bar_width * dataset_count |
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rect = self._create_element( 'rect', { |
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'x': str(left), |
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'y': str(top), |
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'width': str(bar_width), |
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'height': str(length), |
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'class': 'fill%s' % (dataset_count+1), |
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} ) |
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self.graph.appendChild( rect ) |
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self.make_datapoint_text( left + bar_width/2.0, top-6, value )
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