def __init__(self, report_slug, name, keys, values):
super(ClinicReportDisplayRow, self).__init__(name, keys, values)
self.report_slug = report_slug
if "Clinic" in self.keys:
self.clinic_code = self.keys["Clinic"]
self.keys["Clinic"] = clinic_display(self.clinic_code)
else:
self.clinic_code = None
def render_summary_graph(report):
"""
Generate a graph that plots all the pi indicators for each clinic
from the data in the ReportDisplay object
"""
if report is None or len(report.rows) == 0:
return
# Create array of all indicator data by month for each clinic
headings = report.get_display_value_keys()
slugs = report.get_slug_keys()
report_data = []
for row in report.rows:
ordered_values = [row.get_value(key).graph_value if row.get_value(key) else 0 for key in slugs]
# hack - for the CHW PI report just blank this field out. Everything else can work the same
clinic = row.keys['Clinic'] if "Clinic" in row.keys else ""
row_with_clinic = list(itertools.chain([clinic], [row.keys['Month']], [row.keys['Year']], [ordered_values]))
report_data.append(row_with_clinic)
# sort by clinic
sorted_data=sorted(report_data, key=lambda data: data[0])
# create a clinic list, date list for display on plot, combine data for same clinic
clinic_list=[]
date_list=[]
data_by_clinic=[]
for entry in sorted_data:
if entry[0] not in clinic_list:
clinic_list.append(entry[0])
date_list.append([datetime(entry[2], entry[1], 1)])
data_by_clinic.append(entry[3:])
else:
data_by_clinic[-1] = data_by_clinic[-1] + entry[3:]
date_list[-1] = date_list[-1] + [datetime(entry[2], entry[1], 1)]
# go through data for each clinic, add y-axis point for plotting based on
# number of months plotted for each clinic check that data value valid,
# create list with data values that don't exist for plotting
height_per_indicator = 50
num_indicators = len(ordered_values)
plot_height =[]
display_data = []
valid_data = []
for row in data_by_clinic:
display_row = []
valid_row = []
increment_val = len(row) + 1
y_value = 1
indicator_counter = 0
month_counter = 0
for month in row:
display_month = []
valid_value = []
for x_value in month:
if x_value != "N/A":
data_value = x_value
valid = "True"
else:
data_value = 0
valid = "False"
display_month.append([data_value, y_value])
valid_value.append(valid)
if indicator_counter < (num_indicators-1):
y_value += increment_val
indicator_counter += 1
else:
# reset condition
month_counter += 1
y_value = month_counter+1
indicator_counter = 0
display_row.append(display_month)
valid_row.append(valid_value)
display_data.append(display_row)
valid_data.append(valid_row)
plot_height.append(len(row)*num_indicators*height_per_indicator + height_per_indicator)
# add clinic name
clinic_name_list=[]
for clinic in clinic_list:
clinic_name_list.append(clinic_display(clinic))
descriptions = report.get_descriptions()
# sort by date and render for display
display_dates = [[d.strftime("%B %Y") for d in sorted(inner_list)] for inner_list in date_list]
return render_to_string("reports/partials/report_summary_graph.html",
{"headings": json.dumps(headings),
"rows": display_data,
"height": plot_height,
"clinic_names": clinic_name_list,
"dates": display_dates,
"descriptions": descriptions,
"titles": report.get_display_value_keys(),
"valid_data": valid_data
})
