Supplement/comparison_tools/helpers.py
def load_reference_data(name=None):
    """
    Fetch LAtools reference data from online repository.

    Parameters
    ----------
    name : str<
        Which data to download. Can be one of 'culture_reference',
        'culture_test', 'downcore_reference', 'downcore_test', 'iolite_reference'
        or 'zircon_reference'.
        If None, all are downloaded and returned as a dict.

    Returns
    -------
    pandas.DataFrame or dict.
    """
    base_url = 'https://docs.google.com/spreadsheets/d/e/2PACX-1vQJfCeuqrtFFMAeSpA9rguzLAo9OVuw50AHhAULuqjMJzbd3h46PK1KjF69YiJAeNAAjjMDkJK7wMpG/pub?gid={:}&single=true&output=csv'
    gids = {'culture_reference': '0',
            'culture_test': '1170065442',
            'downcore_reference': '190752797',
            'downcore_test': '721359794',
            'iolite_reference': '483581945',
            'zircon_reference': '1355554964'}

    if name is None:
        out = {}
        for nm, gid in gids.items():
            url = base_url.format(gid)
            tmp = pd.read_csv(url, header=[0], index_col=[0, 1])
            tmp.index.names = ['sample', 'rep']
            tmp.columns.names = ['analyte']
            tmp.sort_index(1, inplace=True)
            out[nm] = tmp
    else:
        gid = gids[name]
        url = base_url.format(gid)
        out = pd.read_csv(url, index_col=[0, 1])
        out.columns.names = ['analyte']
        out.sort_index(1, inplace=True)
    return out
def load_reference_data(name=None):
    base_url = 'https://docs.google.com/spreadsheets/d/e/2PACX-1vQJfCeuqrtFFMAeSpA9rguzLAo9OVuw50AHhAULuqjMJzbd3h46PK1KjF69YiJAeNAAjjMDkJK7wMpG/pub?gid={:}&single=true&output=csv'
    gids = {'culture_reference': '0',
            'culture_test': '1170065442',
            'downcore_reference': '190752797',
            'downcore_test': '721359794',
            'iolite_reference': '483581945',
            'zircon_reference': '1355554964'}

    if name is None:
        out = {}
        for nm, gid in gids.items():
            url = base_url.format(gid)
            tmp = pd.read_csv(url, header=[0], index_col=[0, 1])
            tmp.index.names = ['sample', 'rep']
            tmp.columns.names = ['analyte']
            tmp.sort_index(1, inplace=True)
            out[nm] = tmp
    else:
        gid = gids[name]
        url = base_url.format(gid)
        out = pd.read_csv(url, index_col=[0, 1])
        out.columns.names = ['analyte']
        out.sort_index(1, inplace=True)
    return out
def load_reference_data ( name = None ) : base_url = 'https://docs.google.com/spreadsheets/d/e/2PACX-1vQJfCeuqrtFFMAeSpA9rguzLAo9OVuw50AHhAULuqjMJzbd3h46PK1KjF69YiJAeNAAjjMDkJK7wMpG/pub?gid={:}&single=true&output=csv' gids = { 'culture_reference' : '0' , 'culture_test' : '1170065442' , 'downcore_reference' : '190752797' , 'downcore_test' : '721359794' , 'iolite_reference' : '483581945' , 'zircon_reference' : '1355554964' } if name is None : out = { } for nm , gid in gids . items ( ) : url = base_url . format ( gid ) tmp = pd . read_csv ( url , header = [ 0 ] , index_col = [ 0 , 1 ] ) tmp . index . names = [ 'sample' , 'rep' ] tmp . columns . names = [ 'analyte' ] tmp . sort_index ( 1 , inplace = True ) out [ nm ] = tmp else : gid = gids [ name ] url = base_url . format ( gid ) out = pd . read_csv ( url , index_col = [ 0 , 1 ] ) out . columns . names = [ 'analyte' ] out . sort_index ( 1 , inplace = True ) return out
Fetch LAtools reference data from online repository.

    Parameters
    ----------
    name : str<
        Which data to download. Can be one of 'culture_reference',
        'culture_test', 'downcore_reference', 'downcore_test', 'iolite_reference'
        or 'zircon_reference'.
        If None, all are downloaded and returned as a dict.

    Returns
    -------
    pandas.DataFrame or dict.
Fetch LAtools reference data from online repository .