gempy.core.data_modules.stack.Series

class gempy.core.data_modules.stack.Series(faults, series_names: Optional[list] = None)

Class that contains the functionality and attributes related to the series. Notice that series does not only refers to stratigraphic series but to any set of surfaces which will be interpolated together (comfortably).

Parameters

• faults (Faults) – [s0] Class that encapsulate faulting related content. Mainly, which surfaces/surfaces are faults. The fault network—i.e. which faults offset other faults—and fault types—finite vs infinite.

• series_names (Optional[list]) – name of the series. They are also ordered

df

Pandas data frame containing the series and the surfaces contained on them. TODO describe df columns

Type

pn.core.frame.DataFrames

faults

Type

Faults

Examples using Series

1.2: Data Structure and Manipulation

Methods

__init__(faults[, series_names])	Initialize self.
add_series(series_list[, reset_order_series])	Add series to the df
delete_series(indices[, reset_order_series])	[s1] Drop specified labels from rows or columns.
modify_order_series(new_value, series_name)	Replace to the new location the old series
rename_series(new_categories)	[s0] Rename categories.
reorder_series(new_categories)	[s0] Reorder categories as specified in new_categories.
reset_order_series()	Reset the column order series to monotonic ascendant values.
set_bottom_relation(series_list, bottom_relation)	Set the bottom relation between the series and the one below.
set_series_index(series_order[, …])	Rewrite the index of the series df
sort_series()
update_faults_index_rename()
update_faults_index_reorder()

__init__(faults, series_names: Optional[list] = None)

Initialize self. See help(type(self)) for accurate signature.

reset_order_series()

Reset the column order series to monotonic ascendant values.

set_series_index(series_order: Union[list, numpy.ndarray], reset_order_series=True)

Rewrite the index of the series df

Parameters

• series_order (list) – List with names and order of series.

• reset_order_series (bool) – if true [s0] Reset the column order series to monotonic ascendant values.

Returns

Series

Return type

Series

set_bottom_relation(series_list: Union[str, list], bottom_relation: Union[str, list])

Set the bottom relation between the series and the one below.

Parameters

• series_list (str, list) – name or list of names of the series to apply the functionality

• bottom_relation (str{Onlap, Erode, Fault}, list[str]) –

Returns

gempy.core.data_modules.stack.Stack

add_series(series_list: Union[str, list], reset_order_series=True)

Add series to the df

Parameters

• series_list (str, list) – name or list of names of the series to apply the functionality

• reset_order_series (bool) – if true [s0] Reset the column order series to monotonic ascendant values.

Returns

Series

delete_series(indices: Union[str, Iterable], reset_order_series=True)

[s1] Drop specified labels from rows or columns.

Parameters

• indices (str, list) – name or list of names of the series to apply the functionality

• reset_order_series (bool) – if true [s0] Reset the column order series to monotonic ascendant values.

Returns

Series

rename_series(new_categories: Union[dict, list])

[s0] Rename categories.

Parameters

new_categories (list, dict) –

• list-like: all items must be unique and the number of items in the new categories must match the existing number of categories.

• dict-like: specifies a mapping from old categories to new. Categories not contained in the mapping are passed through and extra categories in the mapping are ignored.

Returns:

reorder_series(new_categories: Union[list, numpy.ndarray])

[s0] Reorder categories as specified in new_categories. [s1] Return a sorted copy of the index.

Parameters

new_categories (list) – list with all series names in the desired order.

Returns

Series

modify_order_series(new_value: int, series_name: str)

Replace to the new location the old series

Parameters

• new_value (int) – New location

• series_name (str) – name of the series to be moved

Returns

Series