def get_balance_statistics_var_names(user_map):
means = get_balance_statistics_means(user_map)
ordered_unique = OrderedDict.fromkeys([mean.name for mean in means])
return [
layer_services.legible_covariate_names(var)
for var in list(ordered_unique)
]
def get_display_name(self, obj):
return legible_covariate_names(obj.name)
def create_report(request, bbox, width, height):
"""
Create PDF that displays the results of the previous job that was run by the user
:param request:
:return:
"""
user_map = Map.objects.get(pk=request.session['mid'])
job = user_map.job_set.most_recent(user_map)
if job:
job = job[0]
job_stats = job.jobstats_set.get()
report_generated_time = DateFormat(now()).format('jS F Y H:i e')
response = HttpResponse(content_type='application/pdf')
report_filename = 'FCET_{region}_{report_generated_time}'.format(
region=job_stats.state,
report_generated_time=report_generated_time.replace(' ', '_'))
response[
'Content-Disposition'] = 'attachment; filename={filename}.pdf'.format(
filename=report_filename)
results_chart = table_services.get_results_chart_as_dict(user_map)
results_data = table_services.get_results_table_as_list(user_map)
fields = {
'country':
job_stats.country.encode('utf8'),
'region_type':
job_stats.region_type,
'state':
job_stats.state,
'start_year':
job.low_outcome_year,
'end_year':
job.high_outcome_year,
'min_forest_cover':
job_stats.min_forest_cover,
'max_forest_cover':
job_stats.max_forest_cover,
'agroforest':
job_stats.agroforest,
'agriculture':
job_stats.agriculture,
'forest':
job_stats.forest,
'treatment_area_option':
job_stats.treatment_area_option,
'control_area_option':
job_stats.control_area_option,
'matching_method':
job.matching_method,
'matching_estimator':
job.matching_estimator,
'covariates': [
layer_services.legible_covariate_names(cov)
for cov in job.covariate_variables.split(',')
],
'caliper':
job.caliper_distance,
'common_support':
job.common_support,
'standard_errors':
job.standard_error_type,
'control_mean':
results_chart['Unmatched Control'],
'match_mean':
results_chart['Matched Control'],
'treated_mean':
results_chart['Treatment'],
'att':
results_chart['ATT'],
'results_data':
results_data,
'summary_statistics_data':
table_services.get_summary_statistics_table(user_map),
'balance_statistics_data':
table_services.get_balance_statistics_table(user_map),
'balance_statistics_means_unmatched':
table_services.get_balance_statistics_means_unmatched(user_map),
'balance_statistics_means_matched':
table_services.get_balance_statistics_means_matched(user_map),
'balance_statistics_var_names':
table_services.get_balance_statistics_var_names(user_map),
'session_start_time':
DateFormat(job_stats.session_start).format('jS F Y H:i e'),
'report_generated_time':
report_generated_time,
'map_url':
geoserver_map(bbox, width, height, user_map)
}
generate_results_report(response, fields)
pdf_location = os.path.join(
BASE_DIR, 'reports', report_filename + '_' + str(job.id) + '.pdf')
# with open(pdf_location, 'w+') as out_file:
# out_file.write(response.content)
# out_file.close()
return response
else:
return HttpResponse(
'Please run a match before attempting to generate a report',
status=400)
def get_balance_statistics_table(user_map):
cbs_means = CBSmeans.objects.get_table(user_map)
return [[
layer_services.legible_covariate_names(row.name), row.sample,
row.treated, row.control, row.bias, row.biasr, row.t, row.pt
] for row in cbs_means]