honeybee_radiance_postprocess.util module¶
Post-processing utility functions.
- honeybee_radiance_postprocess.util.array_memory_size(sensors: int, sun_up_hours: int, ncomp: int = None, dtype: ~numpy.dtype = <class 'numpy.float32'>, gigabyte: bool = True) float[source]¶
Calculate the memory size of an array before creating or loading an array.
- Parameters:
sensors – Number of sensors in the array.
sun_up_hours – Number of sun up hours in the array.
ncomp – Optional number of components for each element in the array, e.g., if the data is in RGB format then this value must be set to 3. Defaults to None.
dtype – The data type of the array. Defaults to np.float32.
gigabyte – Boolean toggle to output the memory size in gigabytes. Defaults to True.
- Returns:
The memory size of an array.
- Return type:
float
- honeybee_radiance_postprocess.util.binary_mtx_dimension(filepath: str) Tuple[int, int, int, int, str][source]¶
Return binary Radiance matrix dimensions if exist.
This function returns NROWS, NCOLS, NCOMP and number of header lines including the white line after last header line.
- Parameters:
filepath – Full path to Radiance file.
- Returns:
nrows, ncols, ncomp, line_count, fmt
- honeybee_radiance_postprocess.util.check_array_dim(array: ndarray, dim: int)[source]¶
Check NumPy array dimension.
- Parameters:
array – A NumPy array.
dim – The dimension to check against.
- honeybee_radiance_postprocess.util.filter_array(array: ndarray, mask: ndarray) ndarray[source]¶
Filter a NumPy array by a masking array. The array will be passed as is if the mask is None.
- Parameters:
array – A NumPy array to filter.
mask – A NumPy array of ones/zeros or True/False.
- Returns:
A filtered NumPy array.