Skip to main content

lc

class LC​

Reads liquid chromatography runs in CDF format

Methods​

from_cdf(cdf_data: bytes)
        Reads in CDF data from Agilent LC and stores it in the class
get_elution_peaks(chromatogram: pd.Series, peak_prominence_threshold=10, num_peaks_to_find=None)
        Get elution peaks from raw chromatogram data

function LC.init​

Initialize LC class

function LC.from_cdf​

Reads in CDF data from Agilent LC and stores it in the class

Parameters​

cdf_data : bytes
        CDF data in bytes

function LC.get_elution_peaks​

Get elution peaks from raw chromatogram data

Parameters​

chromatogram : pd.DataFrame
        Pandas Series with time as index
peak_prominence_threshold : int, optional
        Minimum prominence of peaks to be considered, by default 10
num_peaks_to_find : int, optional
        Number of peaks to find

function LC.decode_peaks_name​

Decodes the peak names from bytes to strings; move peak name to front of DataFrame

Parameters​

df_peaks : pd.DataFrame
        Dataframe containing peak names

Returns​

pd.DataFrame
        Dataframe with peak names decoded

function LC.get_cdf_dataframes​

Loads in the cdf data and proceeses it into dataframes, extracting the chromotography data,
peak info table, and metadata.

Parameters​

cdf_data : bytes
        CDF data in bytes containing HPLC run data

Returns​

Dict[str, pd.DataFrame]
        Dictionary containing dataframes for metadata, peak info, and chromatography data

function LC.compare_aia_files​

Compare 2 AIA files, printing out differences

Parameters​

ds_base : nc.Dataset
        Base AIA file
ds_cmp : nc.Dataset
        Comparison AIA file

function LC.verify_aia_file​

Verifies AIA fields against spec.    E1948-98 is the original spec.

Parameters​

ds : nc.Dataset
        AIA file
spec : str
        Spec to validate against