latqcdtools.base.cleanData

clipRange(array, col=None, minVal=-inf, maxVal=inf) -> numpy.ndarray

Throw out any elements of array that lie outside the interval (minVal,maxVal). Note this
renders arrays finite. 

deleteCol(array, col) -> numpy.ndarray

Remove a column of a 2d np.ndarray.

Args:
    array (np.ndarray)
    col (int): Remove this column 

Returns:
    np.ndarray: array with row removed

deleteRow(array, row) -> numpy.ndarray

Remove a row of a 2d np.ndarray.

Args:
    array (np.ndarray)
    row (int): Remove this row 

Returns:
    np.ndarray: array with row removed

excludeAtCol(table, col=None, atVal=inf) -> numpy.ndarray

Return everything except those rows of table where col has exactly the value atVal. 

intersectAtCol(table1, table2, col)

Return only those rows of table1 and table2 that have identical elements in column col. 

restrictAtCol(table, col, atVal, rtol=None, atol=None) -> numpy.ndarray

Return only those rows of table where col has exactly the value atVal. 

spliceAtCol(table1, table2, col, atVal) -> numpy.ndarray

Assuming two tables table1 and table2 have common values in column col, create a new
table, where table1 has corresponding entries less than atVal in col, and table 2
has corresponding entries greater than atVal.