def gchart(context, nodelist, type, dataset, **kwargs): G = GChart(type, dataset, encoding=kwargs.pop('encoding', 'text')) for node in nodelist: if isinstance(node, TextNode): for part in node.render(context).splitlines(): cmd, value = parse_cmd(part) if cmd is None: continue if cmd.startswith('axes'): cmd = getattr(G.axes, cmd[5:]) else: cmd = getattr(G, cmd) cmd(*value.split()) if 'instance' in kwargs: return G return G.img(**kwargs)
def gchart(context, nodelist, type, dataset, **kwargs): G = GChart(type, dataset, encoding=kwargs.pop('encoding','text')) for node in nodelist: if isinstance(node, TextNode): for part in node.render(context).splitlines(): cmd,value = parse_cmd(part) if cmd is None: continue if cmd.startswith('axes'): cmd = getattr(G.axes, cmd[5:]) else: cmd = getattr(G, cmd) cmd(*value.split()) if 'instance' in kwargs: return G return G.img(**kwargs)
def render_macro(self, req, name, content): # XXX: This is a big security hole. Need to replace this with something that # only accepts simple key/value pairs. options = eval("dict(%s)" % content) query = options.get('query', None) ctype = options.get('type', None) columns = options.get('columns', None) if query is None or ctype is None: raise ValueError("Chart 'type' and 'query' parameters are required") for key in NON_API_KEYS: if key in options: del options[key] datasets = {} scales = {} labels = {} if columns is not None: for idx, val in enumerate(columns): if len(val) >= 2: if val[1] == 'labels': labels[idx] = [] elif val[1] in ('percentage', 'scaled'): datasets[idx] = [] scales[idx] = (0,0) db = self.env.get_db_cnx() cursor = db.cursor() cursor.execute(query) col_count = 0 if columns is not None: col_count = len(columns) # Collect label, scale and dataset data for row in cursor: if not col_count: col_count = len(row) if columns is None: columns = [] for idx in range(col_count): columns.append((None, 'percentage')) datasets[idx] = [] scales[idx] = (0,0) elif len(columns) != col_count: raise KeyError("Table has %d columns, but 'columns' parameter has %d items" % \ (col_count, len(columns),)) for idx, col in enumerate(row): if idx in labels: labels[idx].append(col) elif idx in datasets: try: col_value = float(col) except (TypeError, ValueError): continue datasets[idx].append(col_value) scales[idx] = (min(scales[idx][0], col_value), max(scales[idx][1], col_value),) dense_dataset = [] dataset_to_idx = {} idx_to_axis = {} axis_to_idx = {} axis_types = [] # x, x, y - in order scaled_axes = {} # idx -> min/max for that scale current_dataset = 0 current_axis = 0 for idx, col in enumerate(columns): if len(col) >= 1 and col[0]: idx_to_axis[idx] = current_axis axis_to_idx[current_axis] = idx axis_types.append(col[0]) current_axis += 1 if len(col) >= 2 and col[1] == 'scaled': scale_min = len(col) >= 3 and col[2] or scales[idx][0] scale_max = len(col) >= 4 and col[3] or scales[idx][1] scaled_axes[idx] = (scale_min, scale_max,) if idx in datasets: dataset_to_idx[current_dataset] = idx dense_dataset.append(datasets[idx]) current_dataset += 1 # Add axes if 'chxt' not in options: if axis_types: options['chxt'] = ','.join(axis_types) # Add axis labels if 'chxl' not in options: label_data = [] for idx, values in sorted(labels.items()): if idx not in idx_to_axis: continue label_data.append('%d:|%s' % (idx_to_axis[idx], '|'.join(values),)) if label_data: options['chxl'] = '|'.join(label_data) # Add scale range axes if 'chxr' not in options: range_triples = [] for idx, (scale_min, scale_max) in sorted(scaled_axes.items()): if idx not in idx_to_axis: continue range_triples.append('%d,%.1f,%.1f' % (idx_to_axis[idx], scale_min, scale_max,)) if range_triples: options['chxr'] = '|'.join(range_triples) # Add data scaling if 'chds' not in options and scaled_axes: scale_data = [] for cnt in range(len(dense_dataset)): idx = dataset_to_idx[cnt] scale_item = ',' if idx in scaled_axes: scale_min, scale_max = scaled_axes[idx] scale_item = '%.1f,%.1f' % (scale_min, scale_max) scale_data.append(scale_item) if scale_data: options['chds'] = ','.join(scale_data) chart = GoogleChart(ctype=ctype, dataset=dense_dataset, **options) return Markup(chart.img())
def tarp_subsidies(request): estimated_subsidies = [] subsidy_rates = [] amounts_received = [] names = [] colors = [] for r in SubsidyRecord.objects.all(): estimated_subsidies.append(r.estimated_subsidy) subsidy_rates.append(r.subsidy_rate) amounts_received.append(r.amount_received) names.append(r.name) colors.append(r.color) # reverse names (API wrapper bug?) names.reverse() # estimated subsidies chart estimates_subsidies_normalized = _normalize_chart_range( estimated_subsidies) estimated_subsidies_chart = GChart('bhs', estimates_subsidies_normalized.values()) estimated_subsidies_chart.size((500, 250)) estimated_subsidies_chart.color('|'.join(colors)) estimated_subsidies_chart.bar(18, 2, 0) estimated_subsidies_chart.axes.type('xy') estimated_subsidies_chart_xlabels = range( 0, (_get_scale_bound(estimated_subsidies) + 1), 5) estimated_subsidies_chart_xlabels = map((lambda x: str(x)), estimated_subsidies_chart_xlabels) estimated_subsidies_chart.axes.label( str('|'.join(estimated_subsidies_chart_xlabels))) estimated_subsidies_chart.axes.label('|'.join(names)) estimated_subsidies_chart.axes.style('000000') estimated_subsidies_chart.axes.style('000000') i = 0 for x in estimated_subsidies: marker_text = 't $%.1f' % x estimated_subsidies_chart.marker(marker_text, '000000', 0, i, 10, -1) i = i + 1 # subsidy rates chart subsidy_rates_normalized = _normalize_chart_range(subsidy_rates) subsidy_rate_chart = GChart('bhs', subsidy_rates_normalized.values()) subsidy_rate_chart.size((500, 250)) subsidy_rate_chart.color('|'.join(colors)) subsidy_rate_chart.bar(18, 2, 0) subsidy_rate_chart.axes.type('xy') subsidy_rate_chart_xlabels = range(0, (_get_scale_bound(subsidy_rates) + 1), 10) subsidy_rate_chart_xlabels = map((lambda x: str(x)), subsidy_rate_chart_xlabels) subsidy_rate_chart.axes.label(str('|'.join(subsidy_rate_chart_xlabels))) subsidy_rate_chart.axes.label('|'.join(names)) subsidy_rate_chart.axes.style('000000') subsidy_rate_chart.axes.style('000000') i = 0 for x in subsidy_rates: marker_text = 't %d%%' % x subsidy_rate_chart.marker(marker_text, '000000', 0, i, 10, -1) i = i + 1 # amounts received chart amounts_received_normalized = _normalize_chart_range(amounts_received) amounts_received_chart = GChart('bhs', amounts_received_normalized.values()) amounts_received_chart.size((500, 250)) amounts_received_chart.color('|'.join(colors)) amounts_received_chart.bar(18, 2, 0) amounts_received_chart.axes.type('xy') amounts_received_chart_xlabels = range( 0, (_get_scale_bound(amounts_received) + 1), 10) amounts_received_chart_xlabels = map((lambda x: str(x)), amounts_received_chart_xlabels) amounts_received_chart.axes.label( str('|'.join(amounts_received_chart_xlabels))) amounts_received_chart.axes.label('|'.join(names)) amounts_received_chart.axes.style('000000') amounts_received_chart.axes.style('000000') i = 0 for x in amounts_received: marker_text = 't $%.1f' % x amounts_received_chart.marker(marker_text, '000000', 0, i, 10, -1) i = i + 1 return render_to_response( 'bailout/tarp_subsidy_table.html', { 'estimated_subsidies_chart': estimated_subsidies_chart.img(), 'subsidy_rate_chart': subsidy_rate_chart.img(), 'amounts_received_chart': amounts_received_chart.img(), 'estimated_subsidies': estimated_subsidies, 'subsidy_rates': subsidy_rates, 'amounts_received': amounts_received, 'names': ' '.join(names), 'colors': '|'.join(colors) }, context_instance=RequestContext(request))