|
645 | 645 | "doc": "Returns a tuple containing the IJK indices of the grid cell with global index g.\n\n:return: A a tuple containing the IJK indices of the grid cell with global index g.\n:type: tuple(int,int,int)"
|
646 | 646 | },
|
647 | 647 | "EclipseGrid_getCellVolume1G": {
|
648 |
| - "signature": "EclipseGrid.getCellVolume1G(g: int) -> double", |
| 648 | + "signature": "EclipseGrid.getCellVolume(g: int) -> double", |
649 | 649 | "doc": "Returns the cell volume for the grid cell at the global index g.\n\n:param g: The global index of the grid cell.\n:type g: int\n:return: The volume of the grid cell.\n:type: double"
|
650 | 650 | },
|
651 | 651 | "EclipseGrid_getCellVolume3": {
|
652 |
| - "signature": "EclipseGrid.getCellVolume3(i: int, j: int, k: int) -> double", |
| 652 | + "signature": "EclipseGrid.getCellVolume(i: int, j: int, k: int) -> double", |
653 | 653 | "doc": "Returns the cell volume for a grid cell identified by its (i, j, k) indices.\n\n:param i: The I index of the grid cell.\n:type i: int\n:param j: The J index of the grid cell.\n:type j: int\n:param k: The K index of the grid cell.\n:type k: int\n:return: The volume of the grid cell identified by the (i, j, k) indices.\n:type: double"
|
654 | 654 | },
|
655 | 655 | "EclipseGrid_getCellVolumeAll": {
|
656 |
| - "signature": "EclipseGrid.getCellVolumeAll() -> numpy.ndarray[double]", |
| 656 | + "signature": "EclipseGrid.getCellVolume() -> numpy.ndarray[double]", |
657 | 657 | "doc": "Returns a `numpy.ndarray <https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html>`_ containing the volumes of all grid cells. Each entry in the array corresponds to the volume of a grid cell, with the array index matching the global index of that cell.\n\n:return: A numpy.ndarray each entry represents the volume of a grid cell, the index being to the global index.\n:type: numpy.ndarray[double]"
|
658 | 658 | },
|
659 | 659 | "EclipseGrid_getCellVolumeMask": {
|
660 |
| - "signature": "EclipseGrid.getCellVolumeMask(mask: list[int]) -> numpy.ndarray[double]", |
661 |
| - "doc": "Returns the cell volumes for the cells with the global ids given in the input list.\n\n:return: The cell volumes for the given cells.\n:type: numpy.ndarray[double]" |
| 660 | + "signature": "EclipseGrid.getCellVolume(mask: list[int]) -> numpy.ndarray[double]", |
| 661 | + "doc": "Returns the cell volumes for the selected cells.\n\n:param mask: List containing one entry per grid cell, if the entry in the list is '1', this cell is selected by the mask.\n:type mask: list[int]\n:return: The cell volumes for the given cells.\n:type: numpy.ndarray[double]" |
662 | 662 | },
|
663 | 663 | "EclipseGrid_getCellDepth1G": {
|
664 |
| - "signature": "EclipseGrid.getCellDepth1G(g: int) -> double", |
| 664 | + "signature": "EclipseGrid.getCellDepth(g: int) -> double", |
665 | 665 | "doc": "Returns the depth of the grid cell corresponding to the given global index.\n\n:param g: The global index of the grid cell.\n:type g: int\n:return: The depth of the grid cell with the specified global index.\n:type: double"
|
666 | 666 | },
|
667 | 667 | "EclipseGrid_getCellDepth3": {
|
668 |
| - "signature": "EclipseGrid.getCellDepth3(i: int, j: int, k: int) -> double", |
| 668 | + "signature": "EclipseGrid.getCellDepth(i: int, j: int, k: int) -> double", |
669 | 669 | "doc": "Returns the depth of the grid cell specified by the given IJK indices.\n\n:param i: The I index of the grid cell.\n:type i: int\n:param j: The J index of the grid cell.\n:type j: int\n:param k: The K index of the grid cell.\n:type k: int\n:return: The depth of the grid cell with the specified IJK indices.\n:type: double"
|
670 | 670 | },
|
671 | 671 | "EclipseGrid_getCellDepthAll": {
|
672 |
| - "signature": "EclipseGrid.getCellDepthAll() -> numpy.ndarray[double]", |
| 672 | + "signature": "EclipseGrid.getCellDepth() -> numpy.ndarray[double]", |
673 | 673 | "doc": "Returns a `numpy.ndarray <https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html>`_ containing the depths of all grid cells. Each entry in the array corresponds to the depth of a grid cell, with the array index matching the global index of that cell.\n\n:return: A numpy.ndarray each entry represents the depth of a grid cell, and the index being the global index.\n:type: numpy.ndarray[double]"
|
674 | 674 | },
|
675 | 675 | "EclipseGrid_getCellDepthMask": {
|
676 | 676 | "signature": "EclipseGrid.getCellDepthMask(mask: list[int]) -> numpy.ndarray[double]",
|
677 |
| - "doc": "Returns the depths for the cell with the global ids given in the input list.\n\n:return: The depths for the given cells.\n:type: numpy.ndarray[double]" |
| 677 | + "doc": "Returns the depths for the selected cells.\n\n:param mask: List containing one entry per grid cell, if the entry in the list is '1', this cell is selected by the mask.\n:type mask: list[int]\n:return: The depths for the given cells.\n:type: numpy.ndarray[double]" |
678 | 678 | },
|
679 | 679 | "eclArrType": {
|
680 | 680 | "type": "class",
|
|
752 | 752 | "doc": "Represents an Eclipse Restart file. This class inherits from the class EclFile."
|
753 | 753 | },
|
754 | 754 | "ERst_init": {
|
755 |
| - "signature": "opm.io.ecl.ERst.__init__(filename: str)", |
756 |
| - "doc": "Initializes the ERst object by loading the Restart file (and the underlying EclFile) from the specified path.\n\n:param filename: The path to the Restart file.\n:type filename: str" |
| 755 | + "signature": "opm.io.ecl.ERst.__init__(filename: str) -> ERst", |
| 756 | + "doc": "Initializes the ERst object by loading the Restart file (and the underlying EclFile) from the specified path.\n\n:param filename: The path to the Restart file.\n:type filename: str\n:return: The ERst object.\n:type: ERst" |
757 | 757 | },
|
758 | 758 | "ERst_has_report_step": {
|
759 | 759 | "signature": "opm.io.ecl.ERst.__has_report_step(report_step: int) -> bool",
|
|
794 | 794 | "ERst_get_data_vector": {
|
795 | 795 | "signature": "opm.io.ecl.ERst.get_erst_vector(name: str, report_step: int, occurrence: int) -> tuple[numpy.ndarray, eclArrType]",
|
796 | 796 | "doc": "Retrieves the data array of the given name a the given occurrence at the given report step.\n\n:param name: The name of the arrays.\n:type name: str\n:param report_step: The report step.\n:type report_step: int\n:param occurrence: The occurrence to retrieve.\n:type occurrence: int\n:return: A tuple containing the data array and its associated type.\n:rtype: tuple[numpy.ndarray, eclArrType]"
|
| 797 | + }, |
| 798 | + "ESmry": { |
| 799 | + "type": "class", |
| 800 | + "signature": "opm.io.ecl.ESmry", |
| 801 | + "doc": "Handles summary data from Eclipse simulations." |
| 802 | + }, |
| 803 | + "ESmry_init": { |
| 804 | + "signature": "opm.io.ecl.ESmry.__init__(filename: str, load_base_run: bool = False) -> ESmry", |
| 805 | + "doc": "Initializes the ESmry object by loading the summary file.\n\n:param filename: Path to the .SMSPEC or .ESMRY file.\n:type filename: str\n:param load_base_run: Whether to load base run data. Default is False.\n:type load_base_run: bool\n:return: The ESmry object.\n:rtype: ESmry" |
| 806 | + }, |
| 807 | + "ESmry_contains": { |
| 808 | + "signature": "opm.io.ecl.ESmry.__contains__(key: str) -> bool", |
| 809 | + "doc": "Checks if the specified key exists in the summary data.\n\n:param key: The key to check.\n:type key: str\n:return: True if the key exists, otherwise False.\n:rtype: bool" |
| 810 | + }, |
| 811 | + "ESmry_make_esmry_file": { |
| 812 | + "signature": "opm.io.ecl.ESmry.make_esmry_file() -> None", |
| 813 | + "doc": "Generates an ESMRY file from an SMSPEC input file." |
| 814 | + }, |
| 815 | + "ESmry_len": { |
| 816 | + "signature": "opm.io.ecl.ESmry.__len__() -> int", |
| 817 | + "doc": "Returns the number of time steps in the summary data.\n\n:return: The number of available time steps.\n:rtype: int" |
| 818 | + }, |
| 819 | + "ESmry_get_all": { |
| 820 | + "signature": "opm.io.ecl.ESmry.__get_all(key: str) -> numpy.ndarray", |
| 821 | + "doc": "Retrieves the summary vector for the given key.\n\n:param key: The key.\n:type key: str\n:return: The summary for the specified key.\n:rtype: numpy.ndarray" |
| 822 | + }, |
| 823 | + "ESmry_get_at_rstep": { |
| 824 | + "signature": "opm.io.ecl.ESmry.__get_at_rstep(key: str) -> numpy.ndarray", |
| 825 | + "doc": "Retrieves the report step summary vector for the given key.\n\n:param key: The key.\n:type key: str\n:return: The report step summary for the specified key.\n:rtype: numpy.ndarray" |
| 826 | + }, |
| 827 | + "ESmry_start_date": { |
| 828 | + "signature": "opm.io.ecl.ESmry.start_date -> datetime.datetime", |
| 829 | + "doc": "The start date of the summary data as a `datetime.datetime <https://docs.python.org/3/library/datetime.html#datetime.datetime>`_.\n\n:return: The start date.\n:rtype: datetime.datetime" |
| 830 | + }, |
| 831 | + "ESmry_keys1": { |
| 832 | + "signature": "opm.io.ecl.ESmry.keys() -> list[str]", |
| 833 | + "doc": "Retrieves a list of summary keys.\n\n:return: A list of available summary keys.\n:rtype: list[str]" |
| 834 | + }, |
| 835 | + "ESmry_keys2": { |
| 836 | + "signature": "opm.io.ecl.ESmry.keys(pattern: str) -> list[str]", |
| 837 | + "doc": "Retrieves a list of summary keys matching the given pattern.\n\n:param pattern: A pattern to filter the keys.\n:type pattern: str\n:return: A list of available summary keys.\n:rtype: list[str]" |
| 838 | + }, |
| 839 | + "ESmry_dates": { |
| 840 | + "signature": "opm.io.ecl.ESmry.dates() -> list[datetime.datetime]", |
| 841 | + "doc": "Retrieves a list of dates corresponding to the time steps in the summary data.\n\n:return: A list of dates.\n:rtype: list[datetime.datetime]" |
| 842 | + }, |
| 843 | + "ESmry_units": { |
| 844 | + "signature": "opm.io.ecl.ESmry.units(field: str) -> str", |
| 845 | + "doc": "Retrieves the unit for a given field.\n\n:param field: The field name.\n:type field: str\n:return: The unit corresponding to the specified field.\n:rtype: str" |
| 846 | + }, |
| 847 | + "EGrid": { |
| 848 | + "type": "class", |
| 849 | + "signature": "opm.io.ecl.EGrid", |
| 850 | + "doc": "Represents an Eclipse Grid file." |
| 851 | + }, |
| 852 | + "EGrid_init": { |
| 853 | + "signature": "opm.io.ecl.EGrid.__init__(filename: str, grid_name: str = 'global') -> EGrid", |
| 854 | + "doc": "Initializes an EGrid object by loading the grid file.\n\n:param filename: Path to the grid file.\n:type filename: str\n:param grid_name: The name of the grid (default is 'global').\n:type grid_name: str\n:return: The EGrid object.\n:rtype: EGrid" |
| 855 | + }, |
| 856 | + "EGrid_active_cells": { |
| 857 | + "signature": "opm.io.ecl.EGrid.active_cells -> int", |
| 858 | + "doc": "Returns the number of active cells in the grid.\n\n:return: Number of active cells.\n:type: int" |
| 859 | + }, |
| 860 | + "EGrid_dimension": { |
| 861 | + "signature": "opm.io.ecl.EGrid.dimension -> tuple[int, int, int]", |
| 862 | + "doc": "Returns the dimensions of the grid.\n\n:return: The (x,y,z) dimensions.\n:type: tuple[int, int, int]" |
| 863 | + }, |
| 864 | + "EGrid_ijk_from_global_index": { |
| 865 | + "signature": "opm.io.ecl.EGrid.ijk_from_global_index(global_index: int) -> tuple[int, int, int]", |
| 866 | + "doc": "Converts a global index to IJK indices.\n\n:param global_index: The global index of the cell.\n:type global_index: int\n:return: The (I, J, K) indices.\n:type: tuple[int, int, int]" |
| 867 | + }, |
| 868 | + "EGrid_ijk_from_active_index": { |
| 869 | + "signature": "opm.io.ecl.EGrid.ijk_from_active_index(active_index: int) -> tuple[int, int, int]", |
| 870 | + "doc": "Converts an active cell index to IJK indices.\n\n:param active_index: The active cell index.\n:type active_index: int\n:return: The (I, J, K) indices.\n:type: tuple[int, int, int]" |
| 871 | + }, |
| 872 | + "EGrid_active_index": { |
| 873 | + "signature": "opm.io.ecl.EGrid.active_index(i: int, j: int, k: int) -> int", |
| 874 | + "doc": "Returns the active index corresponding to the given IJK index.\n\n:param i: The i index.\n:type i: int\n:param j: The j index.\n:type j: int\n:param k: The k index.\n:type k: int\n:return: The active cell index.\n:type: int" |
| 875 | + }, |
| 876 | + "EGrid_global_index": { |
| 877 | + "signature": "opm.io.ecl.EGrid.global_index(i: int, j: int, k: int) -> int", |
| 878 | + "doc": "Returns the global index corresponding to the given IJK index.\n\n:param i: The i index.\n:type i: int\n:param j: The j index.\n:type j: int\n:param k: The k index.\n:type k: int\n:return: The global index.\n:type: int" |
| 879 | + }, |
| 880 | + "EGrid_export_mapaxes": { |
| 881 | + "signature": "opm.io.ecl.EGrid.export_mapaxes() -> tuple[double, 8]", |
| 882 | + "doc": "Exports the map axes transformation for visualization.\n\n:return: tuple[double, 8]" |
| 883 | + }, |
| 884 | + "EGrid_xyz_from_ijk": { |
| 885 | + "signature": "opm.io.ecl.EGrid.xyz_from_ijk(i: int, j: int, k: int) -> tuple[tuple[double, 8], tuple[double, 8], tuple[double, 8]]", |
| 886 | + "doc": "Computes the XYZ coordinates of the 8 cell corners given its ijk indices.\n\n:param i: The i index of the cell.\n:type i: int\n:param j: The j index of the cell.\n:type j: int\n:param k: The k index of the cell.\n:type k: int\n:return: The XYZ coordinates, as three tuples.\n:type: tuple[tuple[double, 8], tuple[double, 8], tuple[double, 8]]" |
| 887 | + }, |
| 888 | + "EGrid_xyz_from_ijk_mapaxes": { |
| 889 | + "signature": "opm.io.ecl.EGrid.xyz_from_ijk(i: int, j: int, k: int, apply_mapaxes: bool) -> tuple[tuple[double, 8], tuple[double, 8], tuple[double, 8]]", |
| 890 | + "doc": "Computes the XYZ coordinates of the 8 cell corners given its ijk indices.\n\n:param i: The i index of the cell.\n:type i: int\n:param j: The j index of the cell.\n:type j: int\n:param k: The k index of the cell.\n:type k: int\n:param apply_mapaxes: Boolean to indicate if a mapaxes tranformation (if available) should be carried out before.\n:type apply_mapaxes: bool\n:return: The XYZ coordinates, as three tuples.\n:type: tuple[tuple[double, 8], tuple[double, 8], tuple[double, 8]]" |
| 891 | + }, |
| 892 | + "EGrid_xyz_from_active_index": { |
| 893 | + "signature": "opm.io.ecl.EGrid.xyz_from_active_index(active_index: int) -> tuple[tuple[double, 8], tuple[double, 8], tuple[double, 8]]", |
| 894 | + "doc": "Computes the XYZ coordinates of a cell given its active index.\n\n:param active_index: The active cell index.\n:type active_index: int\n:return: XYZ coordinates.\n:type: tuple[float, float, float]" |
| 895 | + }, |
| 896 | + "EGrid_xyz_from_active_index_mapaxes": { |
| 897 | + "signature": "opm.io.ecl.EGrid.xyz_from_active_index(active_index: int, apply_mapaxes: bool) -> tuple[tuple[double, 8], tuple[double, 8], tuple[double, 8]]", |
| 898 | + "doc": "Computes the XYZ coordinates of a cell given its active index.\n\n:param active_index: The active cell index.\n:type active_index: int\n:param apply_mapaxes: Boolean to indicate if a mapaxes tranformation (if available) should be carried out before.\n:type apply_mapaxes: bool\n:return: XYZ coordinates.\n:type: tuple[float, float, float]" |
| 899 | + }, |
| 900 | + "EGrid_cellvolumes": { |
| 901 | + "signature": "opm.io.ecl.EGrid.cellvolumes() -> numpy.ndarray", |
| 902 | + "doc": "Returns an array containing the volume of each cell in the grid.\n\n:return: A NumPy array containing cell volumes.\n:type: numpy.ndarray" |
| 903 | + }, |
| 904 | + "EGrid_cellvolumes_mask": { |
| 905 | + "signature": "opm.io.ecl.EGrid.cellvolumes(mask: list[int]) -> numpy.ndarray", |
| 906 | + "doc": "Returns an array containing the volume of the selected cells.\n\n:param mask: List containing one entry per grid cell, if the entry in the list is '1', this cell is selected by the mask.\n:type mask: list[int]\n:return: A NumPy array containing cell volumes.\n:type: numpy.ndarray" |
797 | 907 | }
|
798 | 908 |
|
799 | 909 | }
|
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