"""Functions for post-processing imageless annual glare outputs.
Note: These functions will most likely be moved to a separate package in the near future.
"""
import json
import os
from .annual import filter_schedule_by_hours, _process_input_folder
[docs]def glare_autonomy_to_file(dgp_file, occ_pattern, output_folder, glare_threshold=0.4,
grid_name=None, total_hours=None):
"""Compute glare autonomy for an dgp file and write the results to a folder.
This function generates 1 file for glare autonomy.
Args:
dgp_file: Path to an dgp file generated by Radiance. The dgp file should be
tab separated and shot NOT have a header. The results for each sensor point
should be available in a row and and each column should be the daylight
glare probability value for a sun_up_hour. The number of columns should
match the number of sun up hours.
occ_pattern: A list of 0 and 1 values for hours of occupancy.
output_folder: An output folder where the results will be written to. The folder
will be created if not exist.
glare_threshold: A fractional number for the threshold of DGP above which
conditions are considered to induce glare. Default: 0.4.
grid_name: An optional name for grid name which will be used to name the output
files. If None the name of the input file will be used.
total_hours: An integer for the total number of occupied hours in the
occupancy schedule. If None, it will be assumed that all of the
occupied hours are sun-up hours and are already accounted for
in the the occ_pattern.
Returns:
file.ga
"""
if not os.path.isdir(output_folder):
os.makedirs(output_folder)
grid_name = grid_name or os.path.split(dgp_file)[-1][-4:]
ga = os.path.join(output_folder, 'ga', '%s.ga' % grid_name).replace('\\', '/')
folder = os.path.dirname(ga)
if not os.path.isdir(folder):
os.makedirs(folder)
with open(dgp_file) as results, open(ga, 'w') as gaf:
for pt_res in results:
values = (float(res) for res in pt_res.split())
gar = _glare_autonomy(values, occ_pattern, glare_threshold, total_hours)
gaf.write(str(gar) + '\n')
return ga
[docs]def glare_autonomy(dgp_file, occ_pattern, glare_threshold=0.4, total_hours=None):
"""Compute glare autonomy for a given result file.
Args:
dgp_file: Path to a dgp file generated by Radiance. The dgp file should be
tab separated and shot NOT have a header. The results for each sensor point
should be available in a row and and each column should be the DGP value for
a sun_up_hour. The number of columns should match the number of sun up hours.
occ_pattern: A list of 0 and 1 values for hours of occupancy.
glare_threshold: Threshold DGP level for glare autonomy. Default: 0.4.
total_hours: An integer for the total number of occupied hours in the
occupancy schedule. If None, it will be assumed that all of the
occupied hours are sun-up hours and are already accounted for
in the the occ_pattern.
Returns:
A list of glare autonomy values. Number of results in each list matches the
number of lines in dgp input file.
"""
ga = []
total_occupied_hours = sum(occ_pattern) if total_hours is None else total_hours
with open(dgp_file) as results:
for pt_res in results:
values = (float(res) for res in pt_res.split())
ga_v = _glare_autonomy(
values, occ_pattern, glare_threshold, total_occupied_hours
)
ga.append(ga_v)
return ga
# TODO - support a list of schedules/schedule folder to match the input grids
[docs]def glare_autonomy_from_folder(results_folder, schedule=None, glare_threshold=0.4,
grids_filter='*'):
"""Compute glare autonomy for a folder.
This folder is an output folder of imageless annual glare recipe. Folder should
include grids_info.json and sun-up-hours.txt - the script uses the list in
grids_info.json to find the result files for each sensor grid.
Args:
results_folder: Results folder.
schedule: An annual schedule for 8760 hours of the year as a list of values.
glare_threshold: Threshold DGP level for glare autonomy. Default: 0.4.
grids_filter: A pattern to filter the grids. By default all the grids will be
processed.
Returns:
Tuple[List] - There will be a list for each input sensor grid. Number of results
in each list matches the number of lines in ill input file.
"""
ga = []
grids, sun_up_hours = _process_input_folder(results_folder, grids_filter)
occ_pattern, total_occ, sun_down_occ_hours = \
filter_schedule_by_hours(sun_up_hours=sun_up_hours, schedule=schedule)
for grid in grids:
dgp_file = os.path.join(results_folder, '%s.dgp' % grid['full_id'])
ga_r = glare_autonomy(dgp_file, occ_pattern, glare_threshold, total_occ)
ga.append(ga_r)
return ga
[docs]def glare_autonomy_to_folder(
results_folder, schedule=None, glare_threshold=0.4, grids_filter='*',
sub_folder='metrics'
):
"""Compute annual glare autonomy in a folder and write them in a subfolder.
This folder is an output folder of imageless annual glare recipe. Folder should
include grids_info.json and sun-up-hours.txt - the script uses the list in
grids_info.json to find the result files for each sensor grid.
Args:
results_folder: Results folder.
schedule: An annual schedule for 8760 hours of the year as a list of values.
glare_threshold: A fractional number for the threshold of DGP above which
conditions are considered to induce glare. Default: 0.4.
grids_filter: A pattern to filter the grids. By default all the grids will be
processed.
sub_folder: An optional relative path for subfolder to copy results files.
Default: metrics
Returns:
str -- Path to results folder.
"""
grids, sun_up_hours = _process_input_folder(results_folder, grids_filter)
occ_pattern, total_occ, sun_down_occ_hours = \
filter_schedule_by_hours(sun_up_hours=sun_up_hours, schedule=schedule)
metrics_folder = os.path.join(results_folder, sub_folder)
if not os.path.isdir(metrics_folder):
os.makedirs(metrics_folder)
for grid in grids:
dgp_file = os.path.join(results_folder, '%s.dgp' % grid['full_id'])
glare_autonomy_to_file(
dgp_file, occ_pattern, metrics_folder, glare_threshold,
grid['full_id'], total_occ
)
# copy info.json to all results folders
grid_info = os.path.join(metrics_folder, 'ga', 'grids_info.json')
with open(grid_info, 'w') as outf:
json.dump(grids, outf)
return metrics_folder
def _glare_autonomy(values, occ_pattern, glare_threshold, total_hours):
"""Calculate annual glare autonomy for a sensor.
Args:
values: Hourly illuminance values as numbers.
occ_pattern: A list of 0 and 1 values for hours of occupancy.
glare_threshold: A fractional number for the threshold of DGP above which
conditions are considered to induce glare. Default: 0.4.
total_hours: An integer for the total number of occupied hours, which can be used
to avoid having to sum occ pattern each time.
Returns:
glare autonomy
"""
def _percentage(in_v, occ_hours):
return round(100.0 * in_v / occ_hours, 2)
ga_above = 0
# count hours above glare threshold
for is_occ, value in zip(occ_pattern, values):
if is_occ == 0:
continue
if value > glare_threshold:
ga_above += 1
# get the number of glare free hours
ga = total_hours - ga_above
return _percentage(ga, total_hours)