示例#1
0
def simulate_idf(idf_file, epw_file, folder, log_file):
    """Simulate an IDF file in EnergyPlus.

    \b
    Args:
        idf_file: Full path to a simulate-able .idf file.
        epw_file: Full path to an .epw file.
    """
    try:
        # set the default folder to the default if it's not specified and copy the IDF
        if folder is None:
            proj_name = os.path.basename(idf_file).replace('.idf', '')
            folder = os.path.join(folders.default_simulation_folder, proj_name)
        preparedir(folder, remove_content=False)
        idf = os.path.join(folder, 'in.idf')
        shutil.copy(idf_file, idf)

        # run the file through EnergyPlus
        gen_files = [idf]
        sql, eio, rdd, html, err = run_idf(idf, epw_file)
        if err is not None and os.path.isfile(err):
            gen_files.extend([sql, eio, rdd, html, err])
            err_obj = Err(err)
            for error in err_obj.fatal_errors:
                log_file.write(
                    err_obj.file_contents)  # log before raising the error
                raise Exception(error)
        else:
            raise Exception('Running EnergyPlus failed.')
        log_file.write(json.dumps(gen_files))
    except Exception as e:
        _logger.exception('IDF simulation failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
示例#2
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def mirror_grid(grid_file, vector, name, suffix, folder, log_file):
    """Mirror a honeybee Model's SensorGrids and format them for thermal mapping.

    This involves setting the direction of every sensor to point up (0, 0, 1) and
    then adding a mirrored sensor grid with the same sensor positions that all
    point downward. In thermal mapping workflows, the upward-pointing grids can
    be used to account for direct and diffuse shortwave irradiance while the
    downard pointing grids account for ground-reflected shortwave irradiance.

    \b
    Args:
        model_json: Full path to a Model JSON file.
    """
    try:
        # create the directory if it's not there and set up output paths
        if not os.path.isdir(folder):
            preparedir(folder)
        base_file = os.path.join(folder, '{}.pts'.format(name))
        rev_file = os.path.join(folder, '{}_{}.pts'.format(name, suffix))

        # loop through the lines of the grid_file and mirror the sensors
        if vector is not None and vector != '':
            # process the vector if it exists
            vec = [float(v) for v in vector.split()]
            assert len(vec) == 3, \
                'Vector "{}" must have 3 values. Got {}.'.format(vector, len(vec))
            vec_str = ' {} {} {}\n'.format(*vec)
            rev_vec = [-v for v in vec]
            rev_vec_str = ' {} {} {}\n'.format(*rev_vec)
            # get the lines from the grid file
            with open(grid_file) as sg_file:
                with open(base_file, 'w') as b_file, open(rev_file,
                                                          'w') as r_file:
                    for line in sg_file:
                        origin_str = ' '.join(line.split()[:3])
                        b_file.write(origin_str + vec_str)
                        r_file.write(origin_str + rev_vec_str)
        else:
            # loop through each sensor and reverse the vector
            with open(grid_file) as sg_file:
                with open(rev_file, 'w') as r_file:
                    for line in sg_file:
                        ray_vals = line.strip().split()
                        origin_str = ' '.join(ray_vals[:3])
                        vec_vals = (-float(v) for v in ray_vals[3:])
                        rev_vec_str = ' {} {} {}\n'.format(*vec_vals)
                        r_file.write(origin_str + rev_vec_str)
            # copy the input grid file to the base file location
            shutil.copyfile(grid_file, base_file)

        # write the resulting file paths to the log file
        log_file.write(json.dumps([base_file, rev_file], indent=4))
    except Exception as e:
        _logger.exception('Sensor grid mirroring failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
示例#3
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def orientation_sim_pars(ddy_file, north_angles, output_name, run_period,
                         start_north, filter_des_days, folder, log_file):
    """Get SimulationParameter JSONs with different north angles for orientation studies.

    \b
    Args:
        ddy_file: Full path to a DDY file that will be used to specify design days
            within the simulation parameter.
        north_angles: Any number of values between -360 and 360 for the counterclockwise
            difference between the North and the positive Y-axis in degrees. 90 is
            West and 270 is East.
    """
    try:
        # get a default folder if none was specified
        if folder is None:
            folder = os.path.join(folders.default_simulation_folder,
                                  'orientation_study')
        preparedir(folder, remove_content=False)

        # create a base set of simulation parameters to be edited parametrically
        sim_par = SimulationParameter()
        for out_name in output_name:
            sim_par.output.add_output(out_name)
        _apply_run_period(run_period, sim_par)
        _apply_design_days(ddy_file, filter_des_days, sim_par)

        # shift all of the north angles by the start_north if specified
        if start_north != 0:
            north_angles = [angle + start_north for angle in north_angles]
            for i, angle in enumerate(north_angles):
                angle = angle - 360 if angle > 360 else angle
                angle = angle + 360 if angle < -360 else angle
                north_angles[i] = angle

        # loop through the north angles and write a simulation parameter for each
        json_files = []
        for angle in north_angles:
            sim_par.north_angle = angle
            base_name = 'sim_par_north_{}'.format(int(angle))
            file_name = '{}.json'.format(base_name)
            file_path = os.path.join(folder, file_name)
            with open(file_path, 'w') as fp:
                json.dump(sim_par.to_dict(), fp)
            sp_info = {
                'id': base_name,
                'path': file_name,
                'full_path': os.path.abspath(file_path)
            }
            json_files.append(sp_info)
        log_file.write(json.dumps(json_files))
    except Exception as e:
        _logger.exception(
            'Failed to generate simulation parameters.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
示例#4
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def measure_compatible_model_json(model_json_path, destination_directory=None):
    """Convert a Model JSON to one that is compatible with the honeybee_openstudio_gem.

    This includes the re-serialization of the Model to Python, which will
    automatically ensure that all Apertures and Doors point in the same direction
    as their parent Face. If the Model tolerance is non-zero and Rooms are closed
    solids, this will also ensure that all Room Faces point outwards from their
    parent's volume. If the Model units are not Meters, the model will be scaled
    to be in Meters. Lastly, apertures and doors with more than 4 vertices will
    be triangulated to ensure EnergyPlus accepts them.

    Args:
        model_json_path: File path to the Model JSON.
        destination_directory: The directory into which the Model JSON that is
            compatible with the honeybee_openstudio_gem should be written. If None,
            this will be the same location as the input model_json_path. Default: None.

    Returns:
        The full file path to the new Model JSON written out by this method.
    """
    # check that the file is there
    assert os.path.isfile(model_json_path), \
        'No JSON file found at {}.'.format(model_json_path)

    # get the directory and the file path for the new Model JSON
    directory, _ = os.path.split(model_json_path)
    dest_dir = directory if destination_directory is None else destination_directory
    dest_file_path = os.path.join(dest_dir, 'in.hbjson')

    # serialize the Model to Python
    with open(model_json_path) as json_file:
        data = json.load(json_file)
    parsed_model = Model.from_dict(data)

    # remove colinear vertices to avoid E+ tolerance issues and convert Model to Meters
    if parsed_model.tolerance != 0:
        for room in parsed_model.rooms:
            room.remove_colinear_vertices_envelope(parsed_model.tolerance)
    parsed_model.convert_to_units('Meters')

    # get the dictionary representation of the Model
    model_dict = parsed_model.to_dict(triangulate_sub_faces=True)

    # write the dictionary into a file
    preparedir(dest_dir,
               remove_content=False)  # create the directory if it's not there
    with open(dest_file_path, 'w') as fp:
        json.dump(model_dict, fp)

    return os.path.abspath(dest_file_path)
示例#5
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    def to_geojson(self,
                   location,
                   point=Point2D(0, 0),
                   folder=None,
                   tolerance=0.01):
        """Convert Dragonfly Model to a geoJSON of buildings footprints.

        This geoJSON will be in a format that is compatible with the URBANopt SDK,
        including properties for floor_area, footprint_area, and detailed_model_filename,
        which will align with the paths to OpenStudio model (.osm) files output
        from honeybee Models translated to OSM.

        Args:
            location: A ladybug Location object possessing longitude and latitude data.
            point: A ladybug_geometry Point2D for where the location object exists
                within the space of a scene. The coordinates of this point are
                expected to be in the units of this Model. (Default: (0, 0)).
            folder: Text for the full path to the folder where the OpenStudio
                model files for each building are written. This is also the location
                where the geojson will be written. If None, the honeybee default
                simulation folder will be used (Default: None).
            tolerance: The minimum distance between points at which they are
                not considered touching. Default: 0.01, suitable for objects
                in meters.

        Returns:
            The path to a geoJSON file that contains polygons for all of the
            Buildings within the dragonfly model along with their properties
            (floor area, number of stories, etc.). The polygons will also possess
            detailed_model_filename keys that align with where OpenStudio models
            would be written, assuming the input folder matches that used to
            export OpenStudio models.
        """
        # set the default simulation folder
        if folder is None:
            folder = folders.default_simulation_folder
        else:
            preparedir(folder, remove_content=False)

        # get the geojson dictionary
        geojson_dict = self.to_geojson_dict(location, point, tolerance)

        # write out the dictionary to a geojson file
        project_folder = os.path.join(folder, self.identifier)
        preparedir(project_folder, remove_content=False)
        file_path = os.path.join(project_folder,
                                 '{}.geojson'.format(self.identifier))
        with open(file_path, 'w') as fp:
            json.dump(geojson_dict, fp, indent=4)
        return file_path
示例#6
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def run_uwg(model,
            epw_file_path,
            simulation_parameter=None,
            directory=None,
            silent=False):
    """Run a UWG dictionary file through the UWG on any operating system.

    Args:
        model: A Dragonfly Model to be used to morph the EPW for the urban area.
        epw_file_path: The full path to an EPW file.
        simulation_parameter: A UWGSimulationParameter object that dictates various
            settings about the UWG simulation. If None, default parameters will
            be generated. (Default: None).
        directory: Text for the directory into which the the uwg JSON and morphed
            urban EPW will be written. If None, it will be written into the
            ladybug default_epw_folder within a subfolder bearing the name
            of the dragonfly Model. (Default: None).
        silent: Boolean to note whether the simulation should be run silently.
            This only has an effect on Windows simulations since Unix-based
            simulations always use shell and are always silent (Default: False).

    Returns:
        The following files output from the UWG CLI run

        -   uwg_json -- Path to a .json file derived from the input uwg_dict.

        -   epw -- File path to the morphed EPW. Will be None if the UWG
            failed to run.
    """
    # get the name of the EPW and the directory into which the urban epw will be written
    epw_file_path = os.path.abspath(epw_file_path)
    epw_name = '{}.epw'.format(model.identifier)
    if directory is None:
        directory = os.path.join(lb_folders.default_epw_folder,
                                 model.identifier)
    preparedir(directory, remove_content=False)

    # write the model to a UWG dictionary
    uwg_dict = model.to.uwg(model, epw_file_path, simulation_parameter)
    uwg_json = os.path.join(directory, '{}_uwg.json'.format(model.identifier))
    with open(uwg_json, 'w') as fp:
        json.dump(uwg_dict, fp, indent=4)

    # run the simulation
    if os.name == 'nt':  # we are on Windows
        epw = _run_uwg_windows(uwg_json, epw_file_path, epw_name, silent)
    else:  # we are on Mac, Linux, or some other unix-based system
        epw = _run_uwg_unix(uwg_json, epw_file_path, epw_name)
    return uwg_json, epw
示例#7
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def _thermal_map_csv(folder, result_sql, temperature, condition,
                     condition_intensity):
    """Write out the thermal mapping CSV files associated with every comfort map."""
    if folder is None:
        folder = os.path.join(os.path.dirname(result_sql), 'thermal_map')
    preparedir(folder, remove_content=False)
    result_file_dict = {
        'temperature': os.path.join(folder, 'temperature.csv'),
        'condition': os.path.join(folder, 'condition.csv'),
        'condition_intensity': os.path.join(folder, 'condition_intensity.csv')
    }
    _data_to_csv(temperature, result_file_dict['temperature'])
    _data_to_csv(condition, result_file_dict['condition'])
    _data_to_csv(condition_intensity, result_file_dict['condition_intensity'])
    return result_file_dict
示例#8
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    def write_inputs_json(self, project_folder=None, indent=4, cpu_count=None):
        """Write the inputs.json file that gets passed to queenbee luigi.

        Note that running this method will automatically handle all of the inputs.

        Args:
            project_folder: The full path to where the inputs json file will be
                written. If None, the default_project_folder on this recipe
                will be used.
            indent: The indent at which the JSON will be written (Default: 4).
            cpu_count: An optional integer to override any inputs that are
                named "cpu-count". This can be used to coordinate such recipe
                inputs with the number of workers specified in recipe settings.
                If None, no overriding will happen. (Default: None).
        """
        # create setup the project folder in which the inputs json will be written
        p_fold = project_folder if project_folder else self.default_project_folder
        if not os.path.isdir(p_fold):
            preparedir(p_fold)
        file_path = os.path.join(p_fold,
                                 '{}_inputs.json'.format(self.simulation_id))
        # create the inputs dictionary, ensuring all inputs are handled in the process
        inp_dict = {}
        for inp in self.inputs:
            inp.handle_value()
            if inp.is_path and inp.value is not None and inp.value != '':
                # copy artifact to project folder
                path_basename = os.path.basename(inp.value)
                dest = os.path.join(p_fold, path_basename)
                if os.path.isfile(inp.value):
                    try:
                        shutil.copyfile(inp.value, dest)
                    except shutil.SameFileError:
                        pass  # the file is already in the right place; no need to copy
                elif os.path.isdir(inp.value):
                    copy_file_tree(inp.value, dest, overwrite=True)
                inp_dict[inp.name] = path_basename
            elif inp.is_path and (inp.value is None or inp.value == ''):
                # conditional artifact; ignore it
                pass
            elif inp.name == 'cpu-count' and cpu_count is not None:
                inp_dict[inp.name] = cpu_count
            else:
                inp_dict[inp.name] = inp.value
        # write the inputs dictionary to a file
        with open(file_path, 'w') as fp:
            json.dump(inp_dict, fp, indent=indent)
        return file_path
示例#9
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def model_radiant_enclosure_info(model_json, folder, log_file):
    """Translate a Model JSON file to a list of JSONs with radiant enclosure information.

    There will be one radiant enclosure JSON for each Model SensorGrid written to
    the output folder and each JSON will contain a list of values about which room
    (or radiant enclosure) each sensor is located. JSONs will also include a mapper
    that links the integers of each sensor with the identifier(s) of a room.

    \b
    Args:
        model_json: Full path to a Model JSON file (HBJSON) or a Model pkl (HBpkl) file.
    """
    try:
        # re-serialize the Model
        model = Model.from_file(model_json)

        # set the default folder if it's not specified
        if folder is None:
            folder = os.path.dirname(os.path.abspath(model_json))
            folder = os.path.join(folder, 'enclosure')
        if not os.path.isdir(folder):
            preparedir(folder)  # create the directory if it's not there

        # loop through sensor grids and build up the radiant enclosure dicts
        grids_info = []
        for grid in model.properties.radiance.sensor_grids:
            # write an enclosure JSON for each grid
            enc_dict = grid.enclosure_info_dict(model)
            enclosure_file = os.path.join(folder,
                                          '{}.json'.format(grid.identifier))
            with open(enclosure_file, 'w') as fp:
                json.dump(enc_dict, fp)
            g_info = {
                'id': grid.identifier,
                'enclosure_path': enclosure_file,
                'enclosure_full_path': os.path.abspath(enclosure_file),
                'count': grid.count
            }
            grids_info.append(g_info)

        # write out the list of radiant enclosure JSON info
        log_file.write(json.dumps(grids_info, indent=4))
    except Exception as e:
        _logger.exception(
            'Model translation to radiant enclosure failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
示例#10
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def simulate_osm(osm_file, epw_file, folder, log_file):
    """Simulate an OSM file in EnergyPlus.

    \b
    Args:
        osm_file: Full path to a simulate-able .osm file.
        epw_file: Full path to an .epw file.
    """
    try:
        # set the default folder to the default if it's not specified and copy the IDF
        if folder is None:
            proj_name = os.path.basename(osm_file).replace('.osm', '')
            folder = os.path.join(folders.default_simulation_folder, proj_name)
        preparedir(folder, remove_content=False)
        base_osm = os.path.join(folder, 'in.osm')
        shutil.copy(osm_file, base_osm)

        # create a blank osw for the translation
        osw_dict = {'seed_file': osm_file, 'weather_file': epw_file}
        osw = os.path.join(folder, 'workflow.osw')
        with open(osw, 'w') as fp:
            json.dump(osw_dict, fp, indent=4)

        # run the OSW through OpenStudio CLI
        osm, idf = run_osw(osw)

        # run the file through EnergyPlus
        if idf is not None and os.path.isfile(idf):
            gen_files = [osw, osm, idf]
            sql, eio, rdd, html, err = run_idf(idf, epw_file)
            if err is not None and os.path.isfile(err):
                gen_files.extend([sql, eio, rdd, html, err])
                err_obj = Err(err)
                for error in err_obj.fatal_errors:
                    log_file.write(
                        err_obj.file_contents)  # log before raising the error
                    raise Exception(error)
            else:
                raise Exception('Running EnergyPlus failed.')
        else:
            raise Exception('Running OpenStudio CLI failed.')
        log_file.write(json.dumps(gen_files))
    except Exception as e:
        _logger.exception('OSM simulation failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
示例#11
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def model_to_osm(model_json, sim_par_json, folder, check_model, log_file):
    """Translate a Model JSON file into an OpenStudio Model and corresponding IDF.

    \b
    Args:
        model_json: Full path to a Model JSON file.
    """
    try:
        # set the default folder if it's not specified
        if folder is None:
            folder = os.path.dirname(os.path.abspath(model_json))
        preparedir(folder, remove_content=False)

        # generate default simulation parameters
        if sim_par_json is None:
            sim_par = SimulationParameter()
            sim_par.output.add_zone_energy_use()
            sim_par.output.add_hvac_energy_use()
            sim_par_dict = sim_par.to_dict()
            sp_json = os.path.abspath(
                os.path.join(folder, 'simulation_parameter.json'))
            with open(sp_json, 'w') as fp:
                json.dump(sim_par_dict, fp)

        # run the Model re-serialization and check if specified
        if check_model:
            model_json = measure_compatible_model_json(model_json, folder)

        # Write the osw file to translate the model to osm
        osw = to_openstudio_osw(folder, model_json, sim_par_json)

        # run the measure to translate the model JSON to an openstudio measure
        if osw is not None and os.path.isfile(osw):
            osm, idf = run_osw(osw)
            # run the resulting idf through EnergyPlus
            if idf is not None and os.path.isfile(idf):
                log_file.write(json.dumps([osm, idf]))
            else:
                raise Exception('Running OpenStudio CLI failed.')
        else:
            raise Exception('Writing OSW file failed.')
    except Exception as e:
        _logger.exception('Model translation failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
示例#12
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def test_three_phase_rmtxop():
    runner = CliRunner()
    sky_vector = "./tests/assets/sky/sky.mtx"
    view_matrix = "./tests/assets/multi_phase/matrices/view.vmx"
    t_matrix = "./tests/assets/clear.xml"
    daylight_matrix = "./tests/assets/multi_phase/matrices/daylight.dmx"
    output_folder = "./tests/assets/temp"
    preparedir(output_folder)
    output_matrix = "./tests/assets/temp/three_phase.res"
    cmd_args = [
        view_matrix, t_matrix, daylight_matrix, sky_vector, output_matrix
    ]

    result = runner.invoke(three_phase_rmtxop, cmd_args)
    assert result.exit_code == 0
    assert os.path.isfile("./tests/assets/temp/three_phase.res")
    nukedir(output_folder)
示例#13
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def _write_views(folder, model, views_filter, full_match=False):
    """Write out the view files.

    Args:
        folder: The views folder.
        model: A Honeybee model.
        views_filter: A list of view names to filter the views in the model. Use this
            argument to indicate specific views that should be included. By default,
            all the views will be exported. You can use wildcard symbols in names.
            Use relative path from inside views folder.
        full_match: A boolean to filter views by their identifiers as full matches.
            (Default: False).

    Returns:
        The path to _info.json, which includes the information for the views that
        are written to the folder.
    """
    model_views = model.properties.radiance.views
    filtered_views = _filter_by_pattern(model_views, views_filter, full_match=full_match)
    if len(filtered_views) != 0:
        preparedir(folder)
        # group_by_identifier
        views_info = []
        for view in filtered_views:
            view.to_file(folder)
            info_file = os.path.join(folder, '{}.json'.format(view.identifier))
            with open(info_file, 'w') as fp:
                json.dump(view.info_dict(model), fp, indent=4)

            view_info = {
                'name': view.identifier,
                'identifier': view.identifier,
                'group': view.group_identifier or '',
                'full_id': view.full_identifier
            }
            views_info.append(view_info)

        # write information file for all the views.
        views_info_file = os.path.join(folder, '_info.json')
        with open(views_info_file, 'w') as fp:
            json.dump(views_info, fp, indent=2)

        return views_info_file
    elif len(model_views) != 0:
        raise ValueError('All views were filtered out of the model folder!')
示例#14
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def setup_resource_folders(overwrite=False):
    """Set up user resource folders in their respective locations.

    Args:
        overwrite: Boolean to note whether the user resources should only be set
            up if they do not exist, in which case existing resources will be
            preserved, or should they be overwritten.
    """
    # first check if there's an environment variable available for APPDATA
    app_folder = os.getenv('APPDATA')
    if app_folder is not None:
        resource_folder = os.path.join(app_folder, 'ladybug_tools')
        # set up user standards
        lib_folder = os.path.join(resource_folder, 'standards')
        for sub_f in STANDARDS_SUBFOLDERS:
            sub_lib_folder = os.path.join(lib_folder, sub_f)
            if not os.path.isdir(sub_lib_folder) or overwrite:
                preparedir(sub_lib_folder)
        # set up the user weather
        epw_folder = os.path.join(resource_folder, 'weather')
        if not os.path.isdir(epw_folder) or overwrite:
            if os.path.isdir(epw_folder):
                nukedir(epw_folder, rmdir=True)  # delete all sub-folders
            preparedir(epw_folder)
        # set up the user measures folder
        measure_folder = os.path.join(resource_folder, 'measures')
        if not os.path.isdir(measure_folder) or overwrite:
            if os.path.isdir(measure_folder):
                nukedir(measure_folder, rmdir=True)  # delete all sub-folders
            preparedir(measure_folder)
        return resource_folder
 def write_inputs_json(self, simulation_folder=None, indent=4):
     """Write the inputs.json file that gets passed to queenbee luigi.
     
     Args:
         simulation_folder: The full path to where the inputs.json file
             will be written and where the simulation will be run. If None
             the default_simulation_path on this Wirkflow will be used.
         indent: The indent at which the JSON will be written (Default: 4).
     """
     sim_fold = simulation_folder if simulation_folder else self.default_simulation_path
     inputs = self._info['inputs'].copy(
     )  # avoid editing the base dictionary
     process_inputs(inputs, sim_fold)
     if self.simulation_id:
         inputs['simulation-id'] = self.simulation_id
     # write the inputs dictionary into a file
     if not os.path.isdir(sim_fold):
         preparedir(sim_fold)
     file_path = os.path.join(sim_fold, '{}-inputs.json'.format(self.name))
     with open(file_path, 'w') as fp:
         json.dump(inputs, fp, indent=indent)
     return file_path
示例#16
0
def download_file_by_name(url, target_folder, file_name, mkdir=False):
    """Download a file to a directory.

    Args:
        url: A string to a valid URL.
        target_folder: Target folder for download (e.g. c:/ladybug)
        file_name: File name (e.g. testPts.zip).
        mkdir: Set to True to create the directory if doesn't exist (Default: False)
    """
    # create the target directory.
    if not os.path.isdir(target_folder):
        if mkdir:
            preparedir(target_folder)
        else:
            created = preparedir(target_folder, False)
            if not created:
                raise ValueError("Failed to find %s." % target_folder)
    file_path = os.path.join(target_folder, file_name)

    # set the security protocol to the most recent version
    try:
        # TLS 1.2 is needed to download over https
        System.Net.ServicePointManager.SecurityProtocol = \
            System.Net.SecurityProtocolType.Tls12
    except AttributeError:
        # TLS 1.2 is not provided by MacOS .NET in Rhino 5
        if url.lower().startswith('https'):
            print('This system lacks the necessary security'
                  ' libraries to download over https.')

    # attempt to download the file
    client = System.Net.WebClient()
    try:
        client.DownloadFile(url, file_path)
    except Exception as e:
        raise Exception(' Download failed with the error:\n{}'.format(e))
示例#17
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def _write_sensor_grids(folder, model, grids_filter):
    """Write out the sensor grid files.

    Args:
        folder: The sensor grids folder.
        model: A Honeybee model.
        grids_filter: A list of sensor grid names to filter the sensor grids in the
            model. Use this argument to indicate specific sensor grids that should
            be included. By default all the sensor grids will be exported. You can use
            wildcard symbols in names. Use relative path from inside grids folder.

    Returns:
        A tuple for path to _info.json and _model_grids_info.json. The first file
        includes the information for the sensor grids that are written to the folder and
        the second one is the information for the input sensor grids from the model.

        Use ``_info.json`` for access the sensor grid information for running the
        commands and ``_model_grids_info`` file for loading the results back to match
        with the model. Model_grids_info has an extra key for `start_ln` which provides
        the start line for where the sensors for this grid starts in a pts file. Unless
        there are grids with same identifier this value will be set to 0.

    """
    sensor_grids = model.properties.radiance.sensor_grids
    filtered_grids = _filter_by_pattern(sensor_grids, grids_filter)
    if len(filtered_grids) != 0:
        grids_info = []
        preparedir(folder)
        # group_by_identifier
        grouped_grids = _group_by_identifier(filtered_grids)
        for grid in grouped_grids:
            fp = grid.to_file(folder)
            info_dir = os.path.dirname(fp)
            info_file = os.path.join(info_dir, '{}.json'.format(grid.identifier))
            with open(info_file, 'w') as fp:
                json.dump(grid.info_dict(model), fp, indent=4)

            grid_info = {
                'name': grid.identifier,
                'identifier': grid.identifier,
                'count': grid.count,
                'group': grid.group_identifier or '',
                'full_id': grid.full_identifier
            }

            grids_info.append(grid_info)

        # write information file for all the grids.
        grids_info_file = os.path.join(folder, '_info.json')
        with open(grids_info_file, 'w') as fp:
            json.dump(grids_info, fp, indent=2)

        # write input grids info
        model_grids_info = []
        start_line = defaultdict(lambda: 0)
        for grid in filtered_grids:
            identifier = grid.identifier
            grid_info = {
                'name': identifier,
                'identifier': identifier,
                'count': grid.count,
                'group': grid.group_identifier or '',
                'full_id': grid.full_identifier,
                'start_ln': start_line[identifier]
            }

            start_line[identifier] += grid.count

            model_grids_info.append(grid_info)

        model_grids_info_file = os.path.join(folder, '_model_grids_info.json')
        with open(model_grids_info_file, 'w') as fp:
            json.dump(model_grids_info, fp, indent=2)

        return grids_info_file, model_grids_info_file
    # duplicate model to avoid mutating it as we edit it for energy simulation
    _model = _model.duplicate()
    # remove colinear vertices using the Model tolerance to avoid E+ tolerance issues
    for room in _model.rooms:
        room.remove_colinear_vertices_envelope(_model.tolerance)
    # auto-assign stories if there are none since most OpenStudio measures need these
    if len(_model.stories) == 0:
        _model.assign_stories_by_floor_height()
    # scale the model if the units are not meters
    if _model.units != 'Meters':
        _model.convert_to_units('Meters')

    # delete any existing files in the directory and prepare it for simulation
    nukedir(directory, True)
    preparedir(directory)
    sch_directory = os.path.join(directory, 'schedules')
    preparedir(sch_directory)

    # write the model parameter JSONs
    model_dict = _model.to_dict(triangulate_sub_faces=True)
    model_json = os.path.join(directory, '{}.hbjson'.format(_model.identifier))
    with open(model_json, 'w') as fp:
        json.dump(model_dict, fp)

    # write the simulation parameter JSONs
    sim_par_dict = _sim_par_.to_dict()
    sim_par_json = os.path.join(directory, 'simulation_parameter.json')
    with open(sim_par_json, 'w') as fp:
        json.dump(sim_par_dict, fp)
示例#19
0
def create_view_factor_modifiers(model_file, exclude_sky, exclude_ground,
                                 individual_shades, triangulate, folder, name):
    """Translate a Model into an Octree and corresponding modifier list for view factors.

    \b
    Args:
        model_file: Full path to a Model JSON file (HBJSON) or a Model pkl (HBpkl) file.
    """
    try:
        # create the directory if it's not there
        if not os.path.isdir(folder):
            preparedir(folder)

        # load the model and ensure the properties align with the energy model
        model = Model.from_file(model_file)
        original_units = None
        if model.units != 'Meters':
            original_units = model.units
            model.convert_to_units('Meters')
        for room in model.rooms:
            room.remove_colinear_vertices_envelope(tolerance=0.01,
                                                   delete_degenerate=True)
        if original_units is not None:
            model.convert_to_units(original_units)

        # triangulate the sub-faces if requested
        if triangulate:
            apertures, parents_to_edit = model.triangulated_apertures()
            for tri_aps, edit_infos in zip(apertures, parents_to_edit):
                if len(edit_infos) == 3:
                    for room in model._rooms:
                        if room.identifier == edit_infos[2]:
                            break
                    for face in room._faces:
                        if face.identifier == edit_infos[1]:
                            break
                    for i, ap in enumerate(face._apertures):
                        if ap.identifier == edit_infos[0]:
                            break
                    face._apertures.pop(i)  # remove the aperture to replace
                    face._apertures.extend(tri_aps)
            doors, parents_to_edit = model.triangulated_doors()
            for tri_drs, edit_infos in zip(doors, parents_to_edit):
                if len(edit_infos) == 3:
                    for room in model._rooms:
                        if room.identifier == edit_infos[2]:
                            break
                    for face in room._faces:
                        if face.identifier == edit_infos[1]:
                            break
                    for i, dr in enumerate(face._doors):
                        if dr.identifier == edit_infos[0]:
                            break
                    face._doors.pop(i)  # remove the doors to replace
                    face._doors.extend(tri_drs)

        # set values to be used throughout the modifier assignment
        offset = model.tolerance * -1
        white_plastic = Plastic('white_plastic', 1, 1, 1)
        geo_strs, mod_strs, mod_names = [], [], []

        def _add_geo_and_modifier(hb_obj):
            """Add a honeybee object to the geometry and modifier strings."""
            mod_name = '%s_mod' % hb_obj.identifier
            mod_names.append(mod_name)
            white_plastic.identifier = mod_name
            rad_poly = Polygon(hb_obj.identifier, hb_obj.vertices,
                               white_plastic)
            geo_strs.append(rad_poly.to_radiance(False, False, False))
            mod_strs.append(white_plastic.to_radiance(True, False, False))

        # loop through all geometry in the model and get radiance strings
        for room in model.rooms:
            for face in room.faces:
                if not isinstance(face.type, AirBoundary):
                    if isinstance(face.boundary_condition, Surface):
                        face.move(face.normal * offset)
                    _add_geo_and_modifier(face)
                for ap in face.apertures:
                    _add_geo_and_modifier(ap)
                for dr in face.doors:
                    _add_geo_and_modifier(dr)
        all_shades = model.shades + model._orphaned_faces + \
            model._orphaned_apertures + model._orphaned_doors
        if individual_shades:
            for shade in all_shades:
                _add_geo_and_modifier(shade)
        else:
            white_plastic.identifier = 'shade_plastic_mod'
            mod_names.append(white_plastic.identifier)
            mod_strs.append(white_plastic.to_radiance(True, False, False))
            for shade in all_shades:
                rad_poly = Polygon(shade.identifier, shade.vertices,
                                   white_plastic)
                geo_strs.append(rad_poly.to_radiance(False, False, False))

        # add the ground and sky domes if requested
        if not exclude_sky:
            mod_names.append('sky_glow_mod')
            mod_strs.append('void glow sky_glow_mod 0 0 4 1 1 1 0')
            geo_strs.append('sky_glow_mod source sky_dome 0 0 4 0 0 1 180')
        if not exclude_ground:
            mod_names.append('ground_glow_mod')
            mod_strs.append('void glow ground_glow_mod 0 0 4 1 1 1 0')
            geo_strs.append(
                'ground_glow_mod source ground_dome 0 0 4 0 0 -1 180')

        # write the radiance strings to the output folder
        geo_file = os.path.join(folder, '{}.rad'.format(name))
        mod_file = os.path.join(folder, '{}.mod'.format(name))
        oct_file = os.path.join(folder, '{}.oct'.format(name))
        with open(geo_file, 'w') as gf:
            gf.write('\n\n'.join(mod_strs + geo_strs))
        with open(mod_file, 'w') as mf:
            mf.write('\n'.join(mod_names))

        # use the radiance files to create an octree
        cmd = Oconv(output=oct_file, inputs=[geo_file])
        cmd.options.f = True
        run_command(cmd.to_radiance(), env=folders.env)
    except Exception as e:
        _logger.exception('Model translation failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
def simulate_model(model_json, epw_file, sim_par_json, base_osw, folder,
                   check_model, log_file):
    """Simulate a Model JSON file in EnergyPlus.
    \n
    Args:
        model_json: Full path to a Model JSON file.\n
        epw_file: Full path to an .epw file.
    """
    try:
        # check that the model JSON and the EPW file is there
        assert os.path.isfile(model_json), \
            'No Model JSON file found at {}.'.format(model_json)
        assert os.path.isfile(epw_file), \
            'No EPW file found at {}.'.format(epw_file)
        # ddy variable that might get used later
        epw_folder, epw_file_name = os.path.split(epw_file)
        ddy_file = os.path.join(epw_folder,
                                epw_file_name.replace('.epw', '.ddy'))

        # set the default folder to the default if it's not specified
        if folder is None:
            proj_name = os.path.basename(model_json).replace('.json', '')
            folder = os.path.join(folders.default_simulation_folder, proj_name,
                                  'OpenStudio')
            preparedir(folder, remove_content=False)

        # process the simulation parameters and write new ones if necessary
        def write_sim_par(sim_par):
            """Write simulation parameter object to a JSON."""
            sim_par_dict = sim_par.to_dict()
            sp_json = os.path.abspath(
                os.path.join(folder, 'simulation_parameter.json'))
            with open(sp_json, 'w') as fp:
                json.dump(sim_par_dict, fp)
            return sp_json

        if sim_par_json is None:  # generate some default simulation parameters
            sim_par = SimulationParameter()
            sim_par.output.add_zone_energy_use()
            sim_par.output.add_hvac_energy_use()
            if os.path.isfile(ddy_file):
                sim_par.sizing_parameter.add_from_ddy_996_004(ddy_file)
            else:
                raise ValueError(
                    'No sim-par-json was input and there is no .ddy file next to '
                    'the .epw.\nAt least one of these two cirtieria must be satisfied '
                    'for a successful simulation.')
            sim_par_json = write_sim_par(sim_par)
        else:
            assert os.path.isfile(sim_par_json), \
                'No simulation parameter file found at {}.'.format(sim_par_json)
            with open(sim_par_json) as json_file:
                data = json.load(json_file)
            sim_par = SimulationParameter.from_dict(data)
            if len(sim_par.sizing_parameter.design_days
                   ) == 0 and os.path.isfile(ddy_file):
                sim_par.sizing_parameter.add_from_ddy_996_004(ddy_file)
                sim_par_json = write_sim_par(sim_par)
            elif len(sim_par.sizing_parameter.design_days) == 0:
                raise ValueError(
                    'No design days were found in the input sim-par-json and there is '
                    'no .ddy file next to the .epw.\nAt least one of these two cirtieria '
                    'must be satisfied for a successful simulation.')

        # run the Model re-serialization and check if specified
        if check_model:
            model_json = measure_compatible_model_json(model_json, folder)

        # Write the osw file to translate the model to osm
        osw = to_openstudio_osw(folder,
                                model_json,
                                sim_par_json,
                                base_osw=base_osw,
                                epw_file=epw_file)

        # run the measure to translate the model JSON to an openstudio measure
        if osw is not None and os.path.isfile(osw):
            gen_files = [osw]
            if base_osw is None:  # separate the OS CLI run from the E+ run
                osm, idf = run_osw(osw)
                # run the resulting idf through EnergyPlus
                if idf is not None and os.path.isfile(idf):
                    gen_files.extend([osm, idf])
                    sql, eio, rdd, html, err = run_idf(idf, epw_file)
                    if err is not None and os.path.isfile(err):
                        gen_files.extend([sql, eio, rdd, html, err])
                    else:
                        raise Exception('Running EnergyPlus failed.')
                else:
                    raise Exception('Running OpenStudio CLI failed.')
            else:  # run the whole simulation with the OpenStudio CLI
                osm, idf = run_osw(osw, measures_only=False)
                if idf is not None and os.path.isfile(idf):
                    gen_files.extend([osm, idf])
                else:
                    raise Exception('Running OpenStudio CLI failed.')
                sql, eio, rdd, html, err = output_energyplus_files(
                    os.path.dirname(idf))
                if os.path.isfile(err):
                    gen_files.extend([sql, eio, rdd, html, err])
                else:
                    raise Exception('Running EnergyPlus failed.')
            log_file.write(json.dumps(gen_files))
        else:
            raise Exception('Writing OSW file failed.')
    except Exception as e:
        _logger.exception('Model simulation failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
示例#21
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def simulate_model(model_json, epw_file, sim_par_json, obj_per_model,
                   multiplier, no_plenum, no_cap, shade_dist, base_osw, folder,
                   log_file):
    """Simulate a Dragonfly Model JSON file in EnergyPlus.

    \b
    Args:
        model_json: Full path to a Dragonfly Model JSON file.
        epw_file: Full path to an .epw file.
    """
    try:
        # get a ddy variable that might get used later
        epw_folder, epw_file_name = os.path.split(epw_file)
        ddy_file = os.path.join(epw_folder,
                                epw_file_name.replace('.epw', '.ddy'))

        # set the default folder to the default if it's not specified
        if folder is None:
            proj_name = \
                os.path.basename(model_json).replace('.json', '').replace('.dfjson', '')
            folder = os.path.join(folders.default_simulation_folder, proj_name,
                                  'OpenStudio')
        preparedir(folder, remove_content=False)

        # process the simulation parameters and write new ones if necessary
        def ddy_from_epw(epw_file, sim_par):
            """Produce a DDY from an EPW file."""
            epw_obj = EPW(epw_file)
            des_days = [
                epw_obj.approximate_design_day('WinterDesignDay'),
                epw_obj.approximate_design_day('SummerDesignDay')
            ]
            sim_par.sizing_parameter.design_days = des_days

        def write_sim_par(sim_par):
            """Write simulation parameter object to a JSON."""
            sim_par_dict = sim_par.to_dict()
            sp_json = os.path.abspath(
                os.path.join(folder, 'simulation_parameter.json'))
            with open(sp_json, 'w') as fp:
                json.dump(sim_par_dict, fp)
            return sp_json

        if sim_par_json is None:  # generate some default simulation parameters
            sim_par = SimulationParameter()
            sim_par.output.add_zone_energy_use()
            sim_par.output.add_hvac_energy_use()
        else:
            with open(sim_par_json) as json_file:
                data = json.load(json_file)
            sim_par = SimulationParameter.from_dict(data)
        if len(sim_par.sizing_parameter.design_days) == 0 and os.path.isfile(
                ddy_file):
            try:
                sim_par.sizing_parameter.add_from_ddy_996_004(ddy_file)
            except AssertionError:  # no design days within the DDY file
                ddy_from_epw(epw_file, sim_par)
        elif len(sim_par.sizing_parameter.design_days) == 0:
            ddy_from_epw(epw_file, sim_par)
        sim_par_json = write_sim_par(sim_par)

        # re-serialize the Dragonfly Model
        with open(model_json) as json_file:
            data = json.load(json_file)
        model = Model.from_dict(data)
        model.convert_to_units('Meters')

        # convert Dragonfly Model to Honeybee
        add_plenum = not no_plenum
        cap = not no_cap
        hb_models = model.to_honeybee(obj_per_model, shade_dist, multiplier,
                                      add_plenum, cap)

        # write out the honeybee JSONs
        osms = []
        idfs = []
        sqls = []
        for hb_model in hb_models:
            model_dict = hb_model.to_dict(triangulate_sub_faces=True)
            directory = os.path.join(folder, hb_model.identifier)
            file_path = os.path.join(directory,
                                     '{}.json'.format(hb_model.identifier))
            preparedir(directory, remove_content=False)  # create the directory
            with open(file_path, 'w') as fp:
                json.dump(model_dict, fp, indent=4)

            # Write the osw file to translate the model to osm
            osw = to_openstudio_osw(directory,
                                    file_path,
                                    sim_par_json,
                                    base_osw=base_osw,
                                    epw_file=epw_file)

            # run the measure to translate the model JSON to an openstudio measure
            if osw is not None and os.path.isfile(osw):
                if base_osw is None:  # separate the OS CLI run from the E+ run
                    osm, idf = run_osw(osw)
                    if idf is not None and os.path.isfile(idf):
                        sql, eio, rdd, html, err = run_idf(idf, epw_file)
                        osms.append(osm)
                        idfs.append(idf)
                        sqls.append(sql)
                        if err is None or not os.path.isfile(err):
                            raise Exception('Running EnergyPlus failed.')
                    else:
                        raise Exception('Running OpenStudio CLI failed.')
                else:  # run the whole simulation with the OpenStudio CLI
                    osm, idf = run_osw(osw, measures_only=False)
                    if idf is None or not os.path.isfile(idf):
                        raise Exception('Running OpenStudio CLI failed.')
                    sql, eio, rdd, html, err = \
                        output_energyplus_files(os.path.dirname(idf))
                    if err is None or not os.path.isfile(err):
                        raise Exception('Running EnergyPlus failed.')
                    osms.append(osm)
                    idfs.append(idf)
                    sqls.append(sql)
            else:
                raise Exception('Writing OSW file failed.')
        log_file.write(json.dumps({'osm': osms, 'idf': idfs, 'sql': sqls}))
    except Exception as e:
        _logger.exception('Model translation failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
示例#22
0
    html.append(html_i)
    err.append(err_i)


if all_required_inputs(ghenv.Component) and _run:
    # global lists of outputs to be filled
    sql, zsz, rdd, html, err, err_objs = [], [], [], [], [], []

    # copy the IDFs into a sub-directory if they are not already labeled as in.idf
    idfs = []
    for idf_file_path in _idf:
        idf_dir, idf_file_name = os.path.split(idf_file_path)
        if idf_file_name != 'in.idf':  # copy the IDF file into a sub-directory
            sub_dir = os.path.join(idf_dir, 'run')
            target = os.path.join(sub_dir, 'in.idf')
            preparedir(sub_dir)
            shutil.copy(idf_file_path, target)
            idfs.append(target)
        else:
            idfs.append(idf_file_path)

    # run the IDF files through E+
    silent = True if _run == 2 else False
    if parallel_:
        tasks.Parallel.ForEach(range(len(idfs)), run_idf_and_report_errors)
    else:
        for i in range(len(idfs)):
            run_idf_and_report_errors(i)

    # print out error report if it's only one
    # otherwise it's too much data to be read-able
示例#23
0
def simulate_model(model_json, epw_file, sim_par_json, base_osw, folder,
                   check_model, log_file):
    """Simulate a Model JSON file in EnergyPlus.

    \b
    Args:
        model_json: Full path to a Model JSON file.
        epw_file: Full path to an .epw file.
    """
    try:
        # get a ddy variable that might get used later
        epw_folder, epw_file_name = os.path.split(epw_file)
        ddy_file = os.path.join(epw_folder,
                                epw_file_name.replace('.epw', '.ddy'))

        # set the default folder to the default if it's not specified
        if folder is None:
            proj_name = \
                os.path.basename(model_json).replace('.json', '').replace('.hbjson', '')
            folder = os.path.join(folders.default_simulation_folder, proj_name,
                                  'OpenStudio')
        preparedir(folder, remove_content=False)

        # process the simulation parameters and write new ones if necessary
        def ddy_from_epw(epw_file, sim_par):
            """Produce a DDY from an EPW file."""
            epw_obj = EPW(epw_file)
            des_days = [
                epw_obj.approximate_design_day('WinterDesignDay'),
                epw_obj.approximate_design_day('SummerDesignDay')
            ]
            sim_par.sizing_parameter.design_days = des_days

        def write_sim_par(sim_par):
            """Write simulation parameter object to a JSON."""
            sim_par_dict = sim_par.to_dict()
            sp_json = os.path.abspath(
                os.path.join(folder, 'simulation_parameter.json'))
            with open(sp_json, 'w') as fp:
                json.dump(sim_par_dict, fp)
            return sp_json

        if sim_par_json is None:  # generate some default simulation parameters
            sim_par = SimulationParameter()
            sim_par.output.add_zone_energy_use()
            sim_par.output.add_hvac_energy_use()
        else:
            with open(sim_par_json) as json_file:
                data = json.load(json_file)
            sim_par = SimulationParameter.from_dict(data)
        if len(sim_par.sizing_parameter.design_days) == 0 and os.path.isfile(
                ddy_file):
            try:
                sim_par.sizing_parameter.add_from_ddy_996_004(ddy_file)
            except AssertionError:  # no design days within the DDY file
                ddy_from_epw(epw_file, sim_par)
        elif len(sim_par.sizing_parameter.design_days) == 0:
            ddy_from_epw(epw_file, sim_par)
        sim_par_json = write_sim_par(sim_par)

        # run the Model re-serialization and check if specified
        if check_model:
            model_json = measure_compatible_model_json(model_json, folder)

        # Write the osw file to translate the model to osm
        osw = to_openstudio_osw(folder,
                                model_json,
                                sim_par_json,
                                base_osw=base_osw,
                                epw_file=epw_file)

        # run the measure to translate the model JSON to an openstudio measure
        if osw is not None and os.path.isfile(osw):
            gen_files = [osw]
            if base_osw is None:  # separate the OS CLI run from the E+ run
                osm, idf = run_osw(osw)
                # run the resulting idf through EnergyPlus
                if idf is not None and os.path.isfile(idf):
                    gen_files.extend([osm, idf])
                    sql, eio, rdd, html, err = run_idf(idf, epw_file)
                    if err is not None and os.path.isfile(err):
                        gen_files.extend([sql, eio, rdd, html, err])
                    else:
                        raise Exception('Running EnergyPlus failed.')
                else:
                    raise Exception('Running OpenStudio CLI failed.')
            else:  # run the whole simulation with the OpenStudio CLI
                osm, idf = run_osw(osw, measures_only=False)
                if idf is not None and os.path.isfile(idf):
                    gen_files.extend([osm, idf])
                else:
                    raise Exception('Running OpenStudio CLI failed.')
                sql, eio, rdd, html, err = output_energyplus_files(
                    os.path.dirname(idf))
                if os.path.isfile(err):
                    gen_files.extend([sql, eio, rdd, html, err])
                else:
                    raise Exception('Running EnergyPlus failed.')
            log_file.write(json.dumps(gen_files))
        else:
            raise Exception('Writing OSW file failed.')
    except Exception as e:
        _logger.exception('Model simulation failed.\n{}'.format(e))
        sys.exit(1)
    else:
        sys.exit(0)
    from ladybug_rhino.grasshopper import all_required_inputs, give_warning
except ImportError as e:
    raise ImportError('\nFailed to import ladybug_rhino:\n\t{}'.format(e))


if all_required_inputs(ghenv.Component) and _write:
    # create the UWGSimulationParameter or use the input
    if _sim_par_ is not None:
        assert isinstance(_sim_par_, UWGSimulationParameter), \
        'Expected UWG Simulation Parameters. Got {}.'.format(type(_sim_par_))
    else:
        _sim_par_ = UWGSimulationParameter()

    if run_ is not None and run_ > 0:  # write and simulate the UWG JSON
        silent = True if run_ > 1 else False
        uwg_json, urban_epw = run_uwg(_model, _epw_file, _sim_par_, _folder_, silent)
        if urban_epw is None:
            msg = 'The Urban Weather Generator Failed to run.'
            print(msg)
            give_warning(ghenv.Component, msg)
    else:  # only write the UWG JSON but don't run it
        # get the directory into which the urban epw will be written
        if _folder_ is None:
            _folder_ = os.path.join(lb_folders.default_epw_folder, _model.identifier)
        preparedir(_folder_, remove_content=False)
        # write the model to a UWG dictionary
        uwg_dict = _model.to.uwg(_model, _epw_file, _sim_par_)
        uwg_json = os.path.join(_folder_, '{}_uwg.json'.format(_model.identifier))
        with open(uwg_json, 'w') as fp:
            json.dump(uwg_dict, fp, indent=4)
示例#25
0
def model_to_rad_folder(model, folder=None, config_file=None, minimal=False):
    r"""Write a honeybee model to a rad folder.

    The rad files in the resulting folders will include all geometry (Rooms, Faces,
    Shades, Apertures, Doors), all modifiers, and all states of dynamic objects.
    It also includes any SensorGrids and Views that are assigned to the model's
    radiance properties.

    Args:
        model: A honeybee Model for which radiance folder will be written.
        folder: An optional folder to be used as the root of the model's
            Radiance folder. If None, the files will be written into a sub-directory
            of the honeybee-core default_simulation_folder. This sub-directory
            is specifically: default_simulation_folder/[MODEL IDENTIFIER]/Radiance
        config_file: An optional config file path to modify the default folder
            names. If None, ``folder.cfg`` in ``honeybee-radiance-folder``
            will be used. (Default: None).
        minimal: Boolean to note whether the radiance strings should be written
            in a minimal format (with spaces instead of line breaks). Default: False.
    """
    # prepare the folder for simulation
    model_id = model.identifier
    if folder is None:
        folder = os.path.join(folders.default_simulation_folder, model_id,
                              'Radiance')
    if not os.path.isdir(folder):
        preparedir(folder)  # create the directory if it's not there
    model_folder = ModelFolder(folder, 'model', config_file)
    model_folder.write(folder_type=-1,
                       cfg=folder_config.minimal,
                       overwrite=True)

    # gather and write static apertures to the folder
    aps, aps_blk = model.properties.radiance.subfaces_by_blk()
    mods, mods_blk, mod_combs, mod_names = _collect_modifiers(
        aps, aps_blk, True)
    _write_static_files(folder, model_folder.aperture_folder(full=True),
                        'aperture', aps, aps_blk, mods, mods_blk, mod_combs,
                        mod_names, False, minimal)

    # gather and write static faces
    faces, faces_blk = model.properties.radiance.faces_by_blk()
    f_mods, f_mods_blk, mod_combs, mod_names = _collect_modifiers(
        faces, faces_blk)
    _write_static_files(folder, model_folder.scene_folder(full=True),
                        'envelope', faces, faces_blk, f_mods, f_mods_blk,
                        mod_combs, mod_names, True, minimal)

    # gather and write static shades
    shades, shades_blk = model.properties.radiance.shades_by_blk()
    s_mods, s_mods_blk, mod_combs, mod_names = _collect_modifiers(
        shades, shades_blk)
    _write_static_files(folder, model_folder.scene_folder(full=True), 'shades',
                        shades, shades_blk, s_mods, s_mods_blk, mod_combs,
                        mod_names, False, minimal)

    # write dynamic sub-face groups (apertures and doors)
    ext_dict = {}
    out_subfolder = model_folder.aperture_group_folder(full=True)
    dyn_subface = model.properties.radiance.dynamic_subface_groups
    if len(dyn_subface) != 0:
        preparedir(out_subfolder)
        for group in dyn_subface:
            if group.is_indoor:
                # TODO: Implement dynamic interior apertures once the radiance folder
                # structure is clear about how the "light path" should be input
                raise NotImplementedError(
                    'Dynamic interior apertures are not currently'
                    ' supported by Model.to.rad_folder.')
            else:
                st_d = _write_dynamic_subface_files(folder, out_subfolder,
                                                    group, minimal)
                _write_mtx_files(folder, out_subfolder, group, st_d, minimal)
                ext_dict[group.identifier] = st_d
        _write_dynamic_json(folder, out_subfolder, ext_dict)

    # write dynamic shade groups
    out_dict = {}
    in_dict = {}
    out_subfolder = model_folder.dynamic_scene_folder(full=True, indoor=False)
    in_subfolder = model_folder.dynamic_scene_folder(full=True, indoor=True)
    dyn_shade = model.properties.radiance.dynamic_shade_groups
    if len(dyn_shade) != 0:
        preparedir(out_subfolder)
        indoor_created = False
        for group in dyn_shade:
            if group.is_indoor:
                if not indoor_created:
                    preparedir(in_subfolder)
                    indoor_created = True
                st_d = _write_dynamic_shade_files(folder, in_subfolder, group,
                                                  minimal)
                in_dict[group.identifier] = st_d
            else:
                st_d = _write_dynamic_shade_files(folder, out_subfolder, group,
                                                  minimal)
                out_dict[group.identifier] = st_d
        _write_dynamic_json(folder, out_subfolder, out_dict)
        if indoor_created:
            _write_dynamic_json(folder, in_subfolder, in_dict)

    # copy all bsdfs into the bsdf folder
    bsdf_folder = model_folder.bsdf_folder(full=True)
    bsdf_mods = model.properties.radiance.bsdf_modifiers
    if len(bsdf_mods) != 0:
        preparedir(bsdf_folder)
        for bdf_mod in bsdf_mods:
            bsdf_name = os.path.split(bdf_mod.bsdf_file)[-1]
            new_bsdf_path = os.path.join(bsdf_folder, bsdf_name)
            shutil.copy(bdf_mod.bsdf_file, new_bsdf_path)

    # write the assigned sensor grids and views into the correct folder
    grid_dir = model_folder.grid_folder(full=True)
    grids = model.properties.radiance.sensor_grids
    if len(grids) != 0:
        grids_info = []
        preparedir(grid_dir)
        model.properties.radiance.check_duplicate_sensor_grid_display_names()
        for grid in grids:
            grid.to_file(grid_dir)
            info_file = os.path.join(grid_dir,
                                     '{}.json'.format(grid.display_name))
            with open(info_file, 'w') as fp:
                json.dump(grid.info_dict(model), fp, indent=4)

            grid_info = {'name': grid.display_name, 'count': grid.count}
            grids_info.append(grid_info)

        # write information file for all the grids.
        grids_info_file = os.path.join(grid_dir, '_info.json')
        with open(grids_info_file, 'w') as fp:
            json.dump(grids_info, fp, indent=2)

    view_dir = model_folder.view_folder(full=True)
    views = model.properties.radiance.views
    if len(views) != 0:
        views_info = []
        preparedir(view_dir)
        model.properties.radiance.check_duplicate_view_display_names()
        for view in views:
            view.to_file(view_dir)
            info_file = os.path.join(view_dir,
                                     '{}.json'.format(view.display_name))
            with open(info_file, 'w') as fp:
                json.dump(view.info_dict(model), fp, indent=4)

            # TODO: see if it make sense to use to_dict here instead of only taking the
            # name
            view_info = {'name': view.display_name}
            views_info.append(view_info)

        # write information file for all the views.
        views_info_file = os.path.join(view_dir, '_info.json')
        with open(views_info_file, 'w') as fp:
            json.dump(views_info, fp, indent=2)

    return folder
示例#26
0
def base_honeybee_osw(project_directory,
                      sim_par_json=None,
                      additional_measures=None,
                      additional_mapper_measures=None,
                      base_osw=None,
                      epw_file=None,
                      skip_report=True):
    """Create a honeybee_workflow.osw to be used as a base in URBANopt simulations.

    This method will also copy the Honeybee.rb mapper to this folder if it is
    available in the config of this library.

    Args:
        project_directory: Full path to a folder out of which the URBANopt simulation
            will be run. This is the folder that contains the feature geoJSON.
        sim_par_json: Optional file path to the SimulationParameter JSON.
            If None, the OpenStudio models generated in the URBANopt run will
            not have everything they need to be simulate-able unless such
            parameters are supplied from one of the additional_measures or the
            base_osw. (Default: None).
        additional_measures: An optional array of honeybee-energy Measure objects
            to be included in the output osw. These Measure objects must have
            values for all required input arguments or an exception will be
            raised while running this function. (Default: None).
        additional_mapper_measures: An optional array of dragonfly-energy MapperMeasure
            objects to be included in the output osw. These MapperMeasure objects
            must have values for all required input arguments or an exception will
            be raised while running this function. (Default: None).
        base_osw: Optional file path to an existing OSW JSON be used as the base
            for the honeybee_workflow.osw. This is another way that outside measures
            can be incorporated into the workflow. (Default: None).
        epw_file: Optional file path to an EPW that should be associated with the
            output energy model. (Default: None).
        skip_report: Set to True to have the URBANopt default feature reporting
            measure skipped as part of the workflow. If False, the measure will
            be run after all simulations are complete. Note that this input
            has no effect if the default_feature_reports measure is already
            in the base_osw or additional_measures (Default: True)

    Returns:
        The file path to the honeybee_workflow.osw written out by this method.
        This is used as the base for translating all features in the geoJSON.
    """
    # create a dictionary representation of the .osw with steps to run
    # the model measure and the simulation parameter measure
    if base_osw is None:
        osw_dict = {'steps': [], 'name': None, 'description': None}
    else:
        assert os.path.isfile(
            base_osw), 'No base OSW file found at {}.'.format(base_osw)
        with open(base_osw, 'r') as base_file:
            osw_dict = json.load(base_file)

    # add a simulation parameter step if it is specified
    if sim_par_json is not None:
        sim_par_dict = {
            'arguments': {
                'simulation_parameter_json': sim_par_json
            },
            'measure_dir_name': 'from_honeybee_simulation_parameter'
        }
        osw_dict['steps'].insert(0, sim_par_dict)

    # addd the model json serialization into the steps
    model_measure_dict = {
        'arguments': {
            'model_json': 'model_json_to_be_mapped.json'
        },
        'measure_dir_name': 'from_honeybee_model'
    }
    osw_dict['steps'].insert(0, model_measure_dict)

    # assign the measure_paths to the osw_dict
    if 'measure_paths' not in osw_dict:
        osw_dict['measure_paths'] = []
    if hb_energy_folders.honeybee_openstudio_gem_path:  # add honeybee-openstudio measure
        m_dir = os.path.join(hb_energy_folders.honeybee_openstudio_gem_path,
                             'measures')
        osw_dict['measure_paths'].append(m_dir)

    # add any additional measures to the osw_dict
    if additional_measures or additional_mapper_measures:
        measures = []
        if additional_measures is not None:
            measures.extend(additional_measures)
        if additional_mapper_measures is not None:
            measures.extend(additional_mapper_measures)
        measure_paths = set()  # set of all unique measure paths
        # ensure measures are correctly ordered
        m_dict = {
            'ModelMeasure': [],
            'EnergyPlusMeasure': [],
            'ReportingMeasure': []
        }
        for measure in measures:
            m_dict[measure.type].append(measure)
        sorted_measures = m_dict['ModelMeasure'] + m_dict['EnergyPlusMeasure'] + \
            m_dict['ReportingMeasure']
        for measure in sorted_measures:
            measure.validate(
            )  # ensure that all required arguments have values
            measure_paths.add(os.path.dirname(measure.folder))
            osw_dict['steps'].append(
                measure.to_osw_dict())  # add measure to workflow
            if isinstance(measure, MapperMeasure):
                _add_mapper_measure(project_directory, measure)
        for m_path in measure_paths:  # add outside measure paths
            osw_dict['measure_paths'].append(m_path)

    # add default feature reports if they aren't already in the steps
    all_measures = [step['measure_dir_name'] for step in osw_dict['steps']]
    if 'default_feature_reports' not in all_measures:
        report_measure_dict = {
            'arguments': {
                'feature_id': None,
                'feature_name': None,
                'feature_type': None,
                'feature_location': None
            },
            'measure_dir_name': 'default_feature_reports'
        }
        if skip_report:
            report_measure_dict['arguments']['__SKIP__'] = True
        osw_dict['steps'].append(report_measure_dict)

    # assign the epw_file to the osw if it is input
    if epw_file is not None:
        osw_dict['weather_file'] = epw_file

    # write the dictionary to a honeybee_workflow.osw
    mappers_dir = os.path.join(project_directory, 'mappers')
    if not os.path.isdir(mappers_dir):
        preparedir(mappers_dir)
    osw_json = os.path.join(mappers_dir, 'honeybee_workflow.osw')
    with open(osw_json, 'w') as fp:
        json.dump(osw_dict, fp, indent=4)

    # copy the Honeybee.rb mapper if it exists in the config
    if folders.mapper_path:
        shutil.copy(folders.mapper_path,
                    os.path.join(mappers_dir, 'Honeybee.rb'))

    return os.path.abspath(osw_json)
示例#27
0
def model_to_urbanopt(model, location, point=Point2D(0, 0), shade_distance=None,
                      use_multiplier=True, add_plenum=False, electrical_network=None,
                      folder=None, tolerance=0.01):
    r"""Generate an URBANopt feature geoJSON and honeybee JSONs from a dragonfly Model.

    Args:
        model: A dragonfly Model for which an URBANopt feature geoJSON and
            corresponding honeybee Model JSONs will be returned.
        location: A ladybug Location object possessing longitude and latitude data.
        point: A ladybug_geometry Point2D for where the location object exists
            within the space of a scene. The coordinates of this point are
            expected to be in the units of this Model. (Default: (0, 0)).
        shade_distance: An optional number to note the distance beyond which other
            objects' shade should not be exported into a given honeybee Model. This
            is helpful for reducing the simulation run time of each Model when other
            connected buildings are too far away to have a meaningful impact on
            the results. If None, all other buildings will be included as context
            shade in each and every Model. Set to 0 to exclude all neighboring
            buildings from the resulting models. (Default: None).
        use_multiplier: If True, the multipliers on the Model's Stories will be
            passed along to the generated Honeybee Room objects, indicating the
            simulation will be run once for each unique room and then results
            will be multiplied. If False, full geometry objects will be written
            for each and every floor in the building that are represented through
            multipliers and all resulting multipliers will be 1. (Default: True).
        add_plenum: Boolean to indicate whether ceiling/floor plenums should
            be auto-generated for the Rooms. (Default: False).
        electrical_network: An optional OpenDSS ElectricalNetwork that's associated
            with the dragonfly Model. (Default: None).
        folder: An optional folder to be used as the root of the model's
            URBANopt folder. If None, the files will be written into a sub-directory
            of the honeybee-core default_simulation_folder. This sub-directory
            is specifically: default_simulation_folder/[MODEL IDENTIFIER]
        tolerance: The minimum distance between points at which they are
            not considered touching. (Default: 0.01, suitable for objects
            in meters).

    Returns:
        A tuple with three values.

        feature_geojson -- The path to an URBANopt feature geoJSON that has
            been written by this method.

        hb_model_jsons -- An array of file paths to honeybee Model JSONS that
            correspond to the detailed_model_filename keys in the feature_geojson.

        hb_models -- An array of honeybee Model objects that were generated in
            process of writing the URBANopt files.
    """
    # make sure the model is in meters and, if it's not, duplicate and scale it
    if model.units != 'Meters':
        conversion_factor = hb_model.conversion_factor_to_meters(model.units)
        point = point.scale(conversion_factor)
        if shade_distance is not None:
            shade_distance = shade_distance * conversion_factor
        tolerance = tolerance * conversion_factor
        model = model.duplicate()  # duplicate the model to avoid mutating the input
        model.convert_to_units('Meters')
        if electrical_network is not None:
            electrical_network = electrical_network.scale(conversion_factor)

    # prepare the folder for simulation
    if folder is None:  # use the default simulation folder
        folder = os.path.join(folders.default_simulation_folder, model.identifier)
    nukedir(folder, True)  # get rid of anything that exists in the folder already
    preparedir(folder)  # create the directory if it's not there

    # prepare the folder into which honeybee Model JSONs will be written
    hb_model_folder = os.path.join(folder, 'hb_json')  # folder for honeybee JSONs
    preparedir(hb_model_folder)

    # create geoJSON dictionary
    geojson_dict = model.to_geojson_dict(location, point, tolerance=tolerance)
    for feature_dict in geojson_dict['features']:  # add the detailed model filename
        if feature_dict['properties']['type'] == 'Building':
            bldg_id = feature_dict['properties']['id']
            feature_dict['properties']['detailed_model_filename'] = \
                os.path.join(hb_model_folder, '{}.json'.format(bldg_id))
    
    # add the electrical network to the geoJSOn dictionary
    if electrical_network is not None:
        electric_features = electrical_network.to_geojson_dict(
            model.buildings, location, point, tolerance=tolerance)
        geojson_dict['features'].extend(electric_features)
        electric_json = os.path.join(folder, 'electrical_database.json')
        with open(electric_json, 'w') as fp:
            json.dump(electrical_network.to_electrical_database_dict(), fp, indent=4)

    # write out the geoJSON file
    feature_geojson = os.path.join(folder, '{}.geojson'.format(model.identifier))
    with open(feature_geojson, 'w') as fp:
        json.dump(geojson_dict, fp, indent=4)

    # write out the honeybee Model JSONS from the model
    hb_model_jsons = []
    hb_models = model.to_honeybee(
        'Building', shade_distance, use_multiplier, add_plenum, tolerance=tolerance)
    for bldg_model in hb_models:
        bld_path = os.path.join(hb_model_folder, '{}.json'.format(bldg_model.identifier))
        model_dict = bldg_model.to_dict(triangulate_sub_faces=True)
        with open(bld_path, 'w') as fp:
            json.dump(model_dict, fp)
        hb_model_jsons.append(bld_path)

    return feature_geojson, hb_model_jsons, hb_models
示例#28
0
def rcontrib_command_with_view_postprocess(octree, sensor_grid, modifiers,
                                           ray_count, rad_params,
                                           rad_params_locked, folder, name):
    """Run rcontrib to get spherical view factors from a sensor grid.

    \b
    Args:
        octree: Path to octree file.
        sensor-grid: Path to sensor grid file.
        modifiers: Path to modifiers file.
    """
    try:
        # create the directory if it's not there
        if not os.path.isdir(folder):
            preparedir(folder)

        # generate the ray vectors to be used in the view factor calculation
        if ray_count == 6:
            rays = ((1, 0, 0), (0, 1, 0), (0, 0, 1), (-1, 0, 0), (0, -1, 0),
                    (0, 0, -1))
        else:
            rays = _fibonacci_spiral(ray_count)
        ray_str = [' {} {} {}\n'.format(*ray) for ray in rays]

        # create a new .pts file with the view vectors
        ray_file = os.path.abspath(os.path.join(folder, '{}.pts'.format(name)))
        total_rays = 0
        with open(sensor_grid) as sg_file:
            with open(ray_file, 'w') as r_file:
                for line in sg_file:
                    for ray in ray_str:
                        try:
                            r_file.write(' '.join(line.split()[:3]) + ray)
                            total_rays += 1
                        except Exception:
                            pass  # we are at the end of the file

        # set up the Rcontrib options
        options = RcontribOptions()
        if rad_params:  # parse input radiance parameters
            options.update_from_string(rad_params.strip())
        if rad_params_locked:  # overwrite input values with protected ones
            options.update_from_string(rad_params_locked.strip())
        # overwrite specific options that would otherwise break the command
        options.M = modifiers
        options.update_from_string('-I -V- -y {}'.format(total_rays))

        # create the rcontrib command and run it
        mtx_file = os.path.abspath(os.path.join(folder, '{}.mtx'.format(name)))
        rcontrib = Rcontrib(options=options, octree=octree, sensors=ray_file)
        cmd = rcontrib.to_radiance().replace('\\', '/')
        cmd = '{} | rmtxop -fa - -c .333 .333 .334'.format(cmd)
        cmd = '{}  | getinfo - > {}'.format(cmd, mtx_file.replace('\\', '/'))
        run_command(cmd, env=folders.env)

        # load the resulting matrix and process the results into view factors
        view_fac_mtx = []
        with open(mtx_file) as mtx_data:
            while True:
                sens_lines = list(islice(mtx_data, ray_count))
                if not sens_lines:
                    break
                sens_mtx = ((float(v) for v in ln.strip().split())
                            for ln in sens_lines)
                s_facs = []
                for sens_facs in zip(*sens_mtx):
                    s_facs.append(sum(sens_facs) / (math.pi * ray_count))
                view_fac_mtx.append(s_facs)

        # write the final view factors into a CSV file
        view_file = os.path.join(folder, '{}.csv'.format(name))
        with open(view_file, 'w') as v_file:
            for facs in view_fac_mtx:
                v_file.write(','.join((str(v) for v in facs)) + '\n')
    except Exception:
        _logger.exception('Failed to comput view factor contributions.')
        sys.exit(1)
    else:
        sys.exit(0)
                                  'captured_views')
except:
    home_folder = os.getenv('HOME') or os.path.expanduser('~')
    default_folder = os.path.join(home_folder, 'captured_views')

try:
    from ladybug_rhino.grasshopper import all_required_inputs, bring_to_front
    from ladybug_rhino.viewport import viewport_by_name, capture_view
except ImportError as e:
    raise ImportError('\nFailed to import ladybug_rhino:\n\t{}'.format(e))

if all_required_inputs(ghenv.Component) and _capture:
    # ensure the component runs last on the canvas
    bring_to_front(ghenv.Component)

    # prepare the folder
    folder = _folder_ if _folder_ is not None else default_folder
    preparedir(folder, remove_content=False)

    # get the viewport objects
    vp_names = viewport_ if len(viewport_) != 0 else [None]
    viewports = [viewport_by_name(vp) for vp in vp_names]

    # save the viewports to images
    for i, view_p in enumerate(viewports):
        f_name = _file_name if len(viewports) == 1 else \
            '{}_{}'.format(_file_name, vp_names[i])
        file_p = os.path.join(folder, f_name)
        fp = capture_view(view_p, file_p, width_, height_, mode_, transparent_)
        print(fp)
示例#30
0
    def run(self,
            settings=None,
            radiance_check=False,
            openstudio_check=False,
            energyplus_check=False,
            queenbee_path=None,
            silent=False,
            debug_folder=None):
        """Run the recipe using the queenbee local run command.

        Args:
            settings: An optional RecipeSettings object or RecipeSettings string
                to dictate the settings of the recipe run (eg. the number of
                workers or the project folder). If None, default settings will
                be assumed. (Default: None).
            radiance_check: Boolean to note whether the installed version of
                Radiance should be checked before executing the recipe. If there
                is no compatible version installed, an exception will be raised
                with a clear error message. (Default: False).
            openstudio_check: Boolean to note whether the installed version of
                OpenStudio should be checked before executing the recipe. If there
                is no compatible version installed, an exception will be raised
                with a clear error message. (Default: False).
            energyplus_check: Boolean to note whether the installed version of
                EnergyPlus should be checked before executing the recipe. If there
                is no compatible version installed, an exception will be raised
                with a clear error message. (Default: False).
            queenbee_path: Optional path to the queenbee executable. If None, the
                queenbee within the ladybug_tools Python folder will be used.
                Setting this to just 'queenbee' will use the system Python.
            silent: Boolean to note whether the recipe should be run silently on
                Windows (True) or with a command window (False). (Default: False).
            debug_folder: An optional path to a debug folder. If debug folder is
                provided all the steps of the simulation will be executed inside
                the debug folder which can be used for furthur inspection.

        Returns:
            Path to the project folder containing the recipe results.
        """
        # perform any simulation engine checks
        if radiance_check:
            check_radiance_date()
        if openstudio_check:
            check_openstudio_version()
        if energyplus_check:
            check_energyplus_version()

        # parse the settings or use default ones
        if settings is not None:
            settings = RecipeSettings.from_string(settings) \
                if isinstance(settings, str) else settings
        else:
            settings = RecipeSettings()

        # get the folder out of which the recipe will be executed
        folder = self.default_project_folder if settings.folder is None \
            else settings.folder
        if not os.path.isdir(folder):
            preparedir(folder)  # create the directory if it's not there

        # delete any existing result files unless reload_old is True
        if not settings.reload_old and self.simulation_id is not None:
            wf_folder = os.path.join(folder, self.simulation_id)
            if os.path.isdir(wf_folder):
                nukedir(wf_folder, rmdir=True)

        # write the inputs JSON for the recipe and set up the environment variables
        inputs_json = self.write_inputs_json(folder,
                                             cpu_count=settings.workers)
        genv = {}
        genv['PATH'] = rad_folders.radbin_path
        genv['RAYPATH'] = rad_folders.radlib_path
        env_args = ['--env {}="{}"'.format(k, v) for k, v in genv.items()]

        # create command
        qb_path = os.path.join(folders.python_scripts_path, 'queenbee') \
            if queenbee_path is None else queenbee_path
        command = '"{qb_path}" local run "{recipe_folder}" ' \
            '"{project_folder}" -i "{user_inputs}" --workers {workers} ' \
            '{environment} --name {simulation_name}'.format(
                qb_path=qb_path, recipe_folder=self.path, project_folder=folder,
                user_inputs=inputs_json, workers=settings.workers,
                environment=' '.join(env_args),
                simulation_name=self.simulation_id
            )
        if debug_folder is not None:
            command += ' --debug "{}"'.format(debug_folder)

        # execute command
        shell = False if os.name == 'nt' and not silent else True
        if settings.report_out:
            process = subprocess.Popen(command,
                                       stdout=subprocess.PIPE,
                                       stderr=subprocess.PIPE,
                                       shell=shell)
            result = process.communicate()
            print(result[0])
            print(result[1])
        else:
            process = subprocess.Popen(command, shell=shell)
            result = process.communicate()  # freeze the canvas while running
        return folder