Hi @chris
Can i double check with you please - does the HB UTCI component now include emissivity and a normalising factor when calculating the longwave MRT as you’re discussing in the above convo?
I ask because i cant see this in the source code (from here: ladybug_comfort.map.mrt — ladybug comfort documentation)
this bit specifically?
load the EPW and outdoor surface temperatures if they are needed
if enclosure_dict['has_outdoor']:
if sql_obj is not None:
out_srf_outp = 'Surface Outside Face Temperature'
out_srf_dict = {d.header.metadata['Surface']: d for d in
sql_obj.data_collections_by_output_name(out_srf_outp)}
out_srf = [out_srf_dict[s] for s in srf_order[:-3]]
if out_srf[0].header.analysis_period != a_per:
out_srf = [d.filter_by_analysis_period(a_per) for d in out_srf]
else:
out_srf = []
epw_obj = EPW(epw)
out_avg = epw_obj.dry_bulb_temperature
out_sky = epw_obj.sky_temperature
if not a_per.is_annual:
out_avg = out_avg.filter_by_analysis_period(a_per)
out_sky = out_sky.filter_by_analysis_period(a_per)
out_data = out_srf + [out_avg, out_sky, out_avg]
out_data = tuple(zip(*out_data))
# load the view factors and perform the matrix multiplication with temperature
with open(view_factors) as csv_data_file:
vf_data = tuple(
tuple(float(val) for val in row.split(',')) for row in csv_data_file)
mrt_data = []
for sen_enc, view_facs in zip(enclosure_dict['sensor_indices'], vf_data):
if sen_enc == -1: # outdoor sensor
temp_data = out_data
else: # indoor sensor
temp_data = in_data[sen_enc]
sensor_vals = []
for t_step in temp_data:
sensor_vals.append(sum(vf * t for vf, t in zip(view_facs, t_step)))
mrt_data.append(sensor_vals)
return mrt_data
But maybe im not looking at the right document?