Source code for honeybee_radiance.postprocess.en17037

"""Functions for post-processing EN 17037 daylight outputs."""
import json
import os

from .annual import filter_schedule_by_hours, _process_input_folder


def _daylight_autonomy(values, occ_pattern, threshold, total_hours):
    """Calculate annual daylight autonomy for a sensor.

    Args:
        values: Hourly illuminance values as numbers.
        occ_pattern: A list of 0 and 1 values for hours of occupancy.
        threshold: Threshold value for daylight autonomy.
        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:
        daylight autonomy
    """
    da = 0
    for is_occ, value in zip(occ_pattern, values):
        if is_occ == 0:
            continue
        if value > threshold:
            da += 1

    return round(100.0 * da / total_hours, 2)


[docs] def en17037_metrics_to_files( ill_file, occ_pattern, output_folder, grid_name=None, total_hours=None ): """Compute annual EN 17037 metrics for an ill file and write the results to a folder. This function generates 6 different files for daylight autonomy based on the varying level of recommendation in EN 17037. Args: ill_file: Path to an ill file generated by Radiance. The ill 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 illuminance 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. 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. """ if not os.path.isdir(output_folder): os.makedirs(output_folder) recommendations = { 'minimum_illuminance': { 'minimum': 100, 'medium': 300, 'high': 500 }, 'target_illuminance': { 'minimum': 300, 'medium': 500, 'high': 750 } } grid_name = grid_name or os.path.split(ill_file)[-1][-4:] da_folders = [] for target_type, thresholds in recommendations.items(): type_folder = os.path.join(output_folder, target_type) if not os.path.isdir(type_folder): os.makedirs(type_folder) for level, threshold in thresholds.items(): level_folder = os.path.join(type_folder, level) if not os.path.isdir(level_folder): os.makedirs(level_folder) da_file = os.path.join( level_folder, 'da', '%s.da' % grid_name).replace('\\', '/') folder = os.path.dirname(da_file) if not os.path.isdir(folder): os.makedirs(folder) sda_file = os.path.join( level_folder, 'sda', '%s.sda' % grid_name).replace('\\', '/') folder = os.path.dirname(sda_file) if not os.path.isdir(folder): os.makedirs(folder) da = [] with open(ill_file) as results, open(da_file, 'w') as daf: for pt_res in results: values = (float(res) for res in pt_res.split()) dar = _daylight_autonomy(values, occ_pattern, threshold, total_hours) daf.write(str(dar) + '\n') da.append(dar) space_target = 50 if target_type == 'target_illuminance' else 95 pass_fail = [int(val > space_target) for val in da] sda = sum(pass_fail) / len(pass_fail) with open(sda_file, 'w') as sdaf: sdaf.write(str(sda)) da_folders.append(os.path.join(level_folder, 'da')) return da_folders
# TODO - support a list of schedules/schedule folder to match the input grids
[docs] def en17037_to_folder( results_folder, schedule, grids_filter='*', sub_folder='metrics' ): """Compute annual EN 17037 metrics in a folder and write them in a subfolder. This folder is an output folder of annual daylight 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. This should be a daylight hours schedule. 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) if total_occ != 4380: raise ValueError( 'There are %s occupied hours in the schedule. According to EN 17037 the ' 'schedule must consist of the daylight hours which is defined ' 'as the half of the year with the largest quantity of daylight' % total_occ) metrics_folder = os.path.join(results_folder, sub_folder) if not os.path.isdir(metrics_folder): os.makedirs(metrics_folder) for grid in grids: ill_file = os.path.join(results_folder, '%s.ill' % grid['full_id']) da_folders = en17037_metrics_to_files( ill_file, occ_pattern, metrics_folder, grid['full_id'], total_occ ) # copy info.json to all results folders for folder_name in da_folders: grid_info = os.path.join(metrics_folder, folder_name, 'grids_info.json') with open(grid_info, 'w') as outf: json.dump(grids, outf, indent=2) # create info for available results. This file will be used by honeybee-vtk for # results visualization config_file = os.path.join(metrics_folder, 'config.json') cfg = _annual_daylight_en17037_config() with open(config_file, 'w') as outf: json.dump(cfg, outf) return metrics_folder
def _annual_daylight_en17037_config(): """Return vtk-config for annual daylight EN 17037. """ cfg = { "data": [ { "identifier": "Daylight Autonomy - target 300 lux", "object_type": "grid", "unit": "Percentage", "path": "target_illuminance/minimum/da", "hide": False, "legend_parameters": { "hide_legend": False, "min": 0, "max": 100, "color_set": "nuanced", }, }, { "identifier": "Daylight Autonomy - target 500 lux", "object_type": "grid", "unit": "Percentage", "path": "target_illuminance/medium/da", "hide": False, "legend_parameters": { "hide_legend": False, "min": 0, "max": 100, "color_set": "nuanced", }, }, { "identifier": "Daylight Autonomy - target 750 lux", "object_type": "grid", "unit": "Percentage", "path": "target_illuminance/high/da", "hide": False, "legend_parameters": { "hide_legend": False, "min": 0, "max": 100, "color_set": "nuanced", }, }, { "identifier": "Daylight Autonomy - minimum 100 lux", "object_type": "grid", "unit": "Percentage", "path": "minimum_illuminance/minimum/da", "hide": False, "legend_parameters": { "hide_legend": False, "min": 0, "max": 100, "color_set": "nuanced", }, }, { "identifier": "Daylight Autonomy - minimum 300 lux", "object_type": "grid", "unit": "Percentage", "path": "minimum_illuminance/medium/da", "hide": False, "legend_parameters": { "hide_legend": False, "min": 0, "max": 100, "color_set": "nuanced", }, }, { "identifier": "Daylight Autonomy - minimum 500 lux", "object_type": "grid", "unit": "Percentage", "path": "minimum_illuminance/high/da", "hide": False, "legend_parameters": { "hide_legend": False, "min": 0, "max": 100, "color_set": "nuanced", }, }, ] } return cfg