def _load_solarcal_splines():
"""load the spline data that gets used in solarcal."""
try:
cur_dir = os.path.dirname(__file__)
solarcal_splines = {
'seated': csv_to_num_matrix(os.path.join(
cur_dir, '_mannequin', 'seatedspline.csv')),
'standing': csv_to_num_matrix(os.path.join(
cur_dir, '_mannequin', 'standingspline.csv'))}
except IOError:
solarcal_splines = {}
print('Failed to import projection factor splines from CSV.'
'\nA simpler interoplation method for Solarcal will be used.')
return solarcal_splines
def test_csv_to_matrix():
"""Test the csv_to_matrix functions."""
path = './tests/fixtures/epw/tokyo.epw'
epw_mtx = futil.csv_to_matrix(path)
assert len(epw_mtx) == 8768
with pytest.raises(Exception):
epw_mtx = futil.csv_to_num_matrix(path)
data_header = Header.from_dict(json.load(json_file))
a_per = data_header.analysis_period
continuous = True if a_per.st_hour == 0 and a_per.end_hour == 23 else False
if not continuous:
dates = a_per.datetimes
# parse the grids_info.json with the correct order of the grid files
with open(os.path.join(_comf_result, 'grids_info.json')) as json_file:
grid_list = json.load(json_file)
# loop through the grid CSV files, parse their results, and build data collections
comf_matrix = []
for grid in grid_list:
grid_name = grid['full_id'] if 'full_id' in grid else 'id'
metadata = {'grid': grid_name}
grid_file = os.path.join(_comf_result, '{}.csv'.format(grid_name))
data_matrix = csv_to_num_matrix(grid_file)
grid_data = []
for i, row in enumerate(data_matrix):
header = data_header.duplicate()
header.metadata = metadata.copy()
header.metadata['sensor_index'] = i
data = HourlyContinuousCollection(header, row) if continuous else \
HourlyDiscontinuousCollection(header, row, dates)
grid_data.append(data)
comf_matrix.append(grid_data)
# wrap the maptrix into an object so that it does not slow the Grasshopper UI
comf_mtx = objectify_output('{} Matrix'.format(data_header.data_type.name),
comf_matrix)