Size Distribution

Particula-beta Index / Particula Beta / Data / Process / Size Distribution

Auto-generated documentation for particula_beta.data.process.size_distribution module.

iterate_merge_distributions

Show source in size_distribution.py:364

Merge two sets of particle size distributions using linear weighting.

Arguments

• concentration_lower - The concentration of particles in the lower distribution.
• diameters_lower - The diameters corresponding to the lower distribution.
• concentration_upper - The concentration of particles in the upper distribution.
• diameters_upper - The diameters corresponding to the upper distribution.

Returns

Tuple: - The merged diameter distribution. - The merged concentration distribution.

Signature

def iterate_merge_distributions(
    concentration_lower: np.ndarray,
    diameters_lower: np.ndarray,
    concentration_upper: np.ndarray,
    diameters_upper: np.ndarray,
) -> tuple[np.ndarray, np.ndarray]: ...

mean_properties

Show source in size_distribution.py:22

Calculate the mean properties of the size distribution.

Arguments

• sizer_dndlogdp - Array of particle concentrations in each bin.
• sizer_diameter - Array of bin center diameters.
• total_concentration - Optional; the total concentration of particles in the distribution. If not provided, it will be calculated.
• sizer_limits - Optional; the lower and upper limits of the size range of interest. If not provided, the full range will be used.

Returns

Tuple: - Total concentration of particles in the distribution. - Total mass of particles in the distribution. - Mean diameter of the distribution by number. - Mean diameter of the distribution by volume. - Geometric mean diameter of the distribution. - Mode diameter of the distribution by number. - Mode diameter of the distribution by volume.

Signature

def mean_properties(
    sizer_dndlogdp: np.ndarray,
    sizer_diameter: np.ndarray,
    total_concentration: Optional[float] = None,
    sizer_limits: Optional[list] = None,
) -> Tuple[float, float, float, float, float, float, float]: ...

merge_distributions

Show source in size_distribution.py:275

Merge two particle size distributions using linear weighting, accounting for mobility versus aerodynamic diameters.

Arguments

• concentration_lower - The concentration of particles in the lower distribution.
• diameters_lower - The diameters corresponding to the lower distribution.
• concentration_upper - The concentration of particles in the upper distribution.
• diameters_upper - The diameters corresponding to the upper distribution.

Returns

Tuple: - - new_2d - The merged concentration distribution. - - new_diameter - The merged diameter distribution.

Notes

Add process the moblity vs aerodynamic diameters

Signature

def merge_distributions(
    concentration_lower: np.ndarray,
    diameters_lower: np.ndarray,
    concentration_upper: np.ndarray,
    diameters_upper: np.ndarray,
) -> tuple[np.ndarray, np.ndarray]: ...

merge_size_distribution

Show source in size_distribution.py:410

Merge two particle size distributions using linear weighting. The concentrations should be in dN/dlogDp.

Arguments

• stream_lower - The stream with the lower size range, e.g., from an SMPS.
• stream_upper - The stream with the upper size range, e.g., from an OPS or APS.
• lower_units - The units of the lower distribution. Default is 'nm'.
• upper_units - The units of the upper distribution. Default is 'um'.

Returns

• Stream - A stream object containing the merged size distribution.

Signature

def merge_size_distribution(
    stream_lower: Stream,
    stream_upper: Stream,
    lower_units: str = "nm",
    upper_units: str = "um",
) -> object: ...

See also

• Stream

resample_distribution

Show source in size_distribution.py:453

Resample a particle size distribution to a new set of diameters using numpy interpolation. Extrapolated values will be set to NaN.

Arguments

• stream - The stream object containing the size distribution to resample.
• new_diameters - The new diameters to which the distribution will be resampled.
• concentration_scale - The concentration scale of the distribution. Options are 'dn/dlogdp', 'dn', 'pms' (which is equivalent to 'dn'), or 'pdf'. Default is 'dn/dlogdp'.
• clone - Whether to clone the stream before resampling. Default is False.

Returns

• Stream - The resampled stream object.

Signature

def resample_distribution(
    stream: Stream,
    new_diameters: np.ndarray,
    concentration_scale: str = "dn/dlogdp",
    clone: bool = False,
) -> Stream: ...

See also

• Stream

sizer_mean_properties

Show source in size_distribution.py:113

Calculate the mean properties of the size distribution and return the updated stream.

Arguments

• stream - The stream containing the size distribution data to process.
• sizer_limits - A list specifying the lower and upper limits of the size range of interest, in the units specified by diameter_units. Default is None, which means the full range is used.
• density - The density of the particles in g/cm³. Default is 1.5 g/cm³.
• diameter_units - The units of the diameter. Default is 'nm'. The specified units will be converted to nanometers.

Returns

• Stream - The updated stream with the mean properties added.

Signature

def sizer_mean_properties(
    stream: Stream,
    sizer_limits: Optional[List[float]] = None,
    density: float = 1.5,
    diameter_units: str = "nm",
) -> Stream: ...

See also

• Stream