# filter the radiation by _hoys if they are input
if len(_hoys_) != 0:
_direct_rad = _direct_rad.filter_by_hoys(_hoys_)
_diffuse_rad = _diffuse_rad.filter_by_hoys(_hoys_)
# create the wea and write it to the default_epw_folder
wea = Wea(_location, _direct_rad, _diffuse_rad)
wea_duration = len(wea) / wea.timestep
wea_folder = _folder_ if _folder_ is not None else \
os.path.join(lb_folders.default_epw_folder, 'sky_matrices')
metd = _direct_rad.header.metadata
wea_basename = metd['city'].replace(' ',
'_') if 'city' in metd else 'unnamed'
wea_path = os.path.join(wea_folder, wea_basename)
wea_file = wea.write(wea_path)
# execute the Radiance gendaymtx command
use_shell = True if os.name == 'nt' else False
# command for direct patches
cmds = [gendaymtx_exe, '-m', str(density), '-d', '-O1', '-A', wea_file]
process = subprocess.Popen(cmds, stdout=subprocess.PIPE, shell=use_shell)
stdout = process.communicate()
dir_data_str = stdout[0]
# command for diffuse patches
cmds = [gendaymtx_exe, '-m', str(density), '-s', '-O1', '-A', wea_file]
process = subprocess.Popen(cmds, stdout=subprocess.PIPE, shell=use_shell)
stdout = process.communicate()
diff_data_str = stdout[0]
# parse the data into a single matrix
density = 2 if high_density_ else 1
# filter the radiation by _hoys if they are input
if len(_hoys_) != 0:
_direct_rad = _direct_rad.filter_by_hoys(_hoys_)
_diffuse_rad = _diffuse_rad.filter_by_hoys(_hoys_)
# create the wea and write it to the default_epw_folder
wea = Wea(_location, _direct_rad, _diffuse_rad)
wea_duration = len(wea) / wea.timestep
wea_folder = _folder_ if _folder_ is not None else \
os.path.join(lb_folders.default_epw_folder, 'sky_matrices')
metd = _direct_rad.header.metadata
wea_basename = os.path.join(wea_folder, metd['city'].replace(' ', '_')) \
if 'city' in metd else 'unnamed'
wea_file = wea.write(wea_basename)
# execute the Radiance gendaymtx command
use_shell = True if os.name == 'nt' else False
# command for direct patches
cmds = [gendaymtx_exe, '-m', str(density), '-d', '-O1', '-A', wea_file]
process = subprocess.Popen(cmds, stdout=subprocess.PIPE, shell=use_shell)
stdout = process.communicate()
dir_data_str = stdout[0]
# command for diffuse patches
cmds = [gendaymtx_exe, '-m', str(density), '-s', '-O1', '-A', wea_file]
process = subprocess.Popen(cmds, stdout=subprocess.PIPE, shell=use_shell)
stdout = process.communicate()
diff_data_str = stdout[0]
# parse the data into a single matrix