| 219 | | Like {{{numpy.core.ma}}}, the {{{ndarray}}}-based implementation of {{{MaskedArray}}} is limited when working with records: you can mask any record of the array, but not a field in a record. If you need this feature, you may want to give {{{mrecords}}} a try (available in the {{{sandbox/maskedarray package of Scipy}}}), that defines a new class, {{{MaskedRecord}}}. An instance of this class accepts a {{{recarray}}} as data, and uses two masks: the {{{recordmask}}} has as many entries as records in the array, each entry with the same fields as a record, but of boolean types, indicating whether a field is masked or not; an entry is flagged as masked in the {{{mask}}} array if at least one field is masked. A few examples in the file should give you an idea of what can be done. Note that {{{maskedrecordarray}}} is still quite experimental... |
| | 219 | Like {{{numpy.core.ma}}}, the {{{ndarray}}}-based implementation of {{{MaskedArray}}} is limited when working with records: you can mask any record of the array, but not a field in a record. If you need this feature, you may want to give {{{mrecords}}} a try (available in the {{{maskedarra}}} directory in the scipy sandbox). This module defines a new class, {{{MaskedRecord}}}. An instance of this class accepts a {{{recarray}}} as data, and uses two masks: the {{{fieldmask}}} has as many entries as records in the array, each entry with the same fields as a record, but of boolean types: they indicate whether the field is masked or not; a record entry is flagged as masked in the {{{mask}}} array if all the fields are masked. A few examples in the file should give you an idea of what can be done. Note that {{{mrecords}}} is still experimental... |
