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04091ad77d
Use commit 0e1e780fd6f18ce93119061e36a4fca9711bc020 Excluded multibuild folder, as this caused git issues
115 lines
4.7 KiB
Python
115 lines
4.7 KiB
Python
#!/usr/bin/env python
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# Copyright (C) 2018 Equinor ASA, Norway.
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#
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# The file 'test_grid.pandas' is part of ERT - Ensemble based Reservoir Tool.
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#
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# ERT is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# ERT is distributed in the hope that it will be useful, but WITHOUT ANY
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# WARRANTY; without even the implied warranty of MERCHANTABILITY or
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# FITNESS FOR A PARTICULAR PURPOSE.
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#
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# See the GNU General Public License at <http://www.gnu.org/licenses/gpl.html>
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# for more details.
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import numpy as np
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import pandas as pd
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from ecl import EclTypeEnum
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from ecl.eclfile import EclKW
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from ecl.grid import EclGrid
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from tests import EclTest
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class GridPandasTest(EclTest):
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def test_dataframe_actnum(self):
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grid = EclGrid.create_rectangular( (2,3,1), (1,1,1) , actnum=[1, 1, 0, 0, 1, 1])
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df = grid.export_index(True)
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index_matrix = np.array([ [0, 0, 0, 0],
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[1, 0, 0, 1],
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[0, 2, 0, 2],
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[1, 2, 0, 3] ])
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assert( np.array_equal(df.values, index_matrix) )
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kw_int_active = EclKW('int_act', 4, EclTypeEnum.ECL_INT_TYPE)
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kw_int_active[0] = 9
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kw_int_active[1] = 8
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kw_int_active[2] = 7
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kw_int_active[3] = 6
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data = grid.export_data(df, kw_int_active)
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assert( len(data) == 4 )
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assert( np.array_equal(data, np.array([9, 8, 7, 6])) )
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kw_float_active = EclKW('float_at', 4, EclTypeEnum.ECL_FLOAT_TYPE)
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kw_float_active[0] = 10.5
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kw_float_active[1] = 9.25
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kw_float_active[2] = 2.0
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kw_float_active[3] = 1.625
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data = grid.export_data(df, kw_float_active)
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assert( len(data) == 4 )
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assert( np.array_equal(data, np.array([10.5, 9.25, 2.0, 1.625])) )
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kw_int_global = EclKW('int_glob', 6, EclTypeEnum.ECL_INT_TYPE)
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kw_int_global[0] = 0
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kw_int_global[1] = 2
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kw_int_global[2] = 4
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kw_int_global[3] = 6
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kw_int_global[4] = 8
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kw_int_global[5] = 9
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data = grid.export_data(df, kw_int_global)
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assert( len(data) == 4)
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assert( np.array_equal(data, np.array([0, 2, 8, 9])) )
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kw_double_global = EclKW('double_g', 6, EclTypeEnum.ECL_DOUBLE_TYPE)
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kw_double_global[0] = 1.1
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kw_double_global[1] = 2.2
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kw_double_global[2] = 3.3
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kw_double_global[3] = 4.4
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kw_double_global[4] = 5.5
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kw_double_global[5] = 6.6
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data = grid.export_data(df, kw_double_global)
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assert( np.array_equal(data, np.array([1.1, 2.2, 5.5, 6.6])) )
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df = grid.export_index() #DataFrame has now 6 rows
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global_index = df.index;
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assert( np.array_equal(global_index, np.array([0, 1, 2, 3, 4, 5])) )
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data = grid.export_data(df, kw_int_active, 9999)
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assert( np.array_equal(data, np.array([9, 8, 9999, 9999, 7, 6])) )
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data = grid.export_data(df, kw_float_active, 2222.0)
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assert( np.array_equal(data, np.array([10.5, 9.25, 2222.0, 2222.0, 2.0, 1.625])) )
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def test_dataframe_grid_data(self):
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grid = EclGrid.create_rectangular( (2,3,1), (1,1,1) , actnum=[1, 1, 0, 0, 1, 1])
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index_frame = grid.export_index()
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volume_data = grid.export_volume(index_frame)
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assert( len(volume_data) == 6 )
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assert( np.array_equal(volume_data, np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0])) )
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position_data = grid.export_position(index_frame)
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x_pos = position_data[:, 0]
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y_pos = position_data[:, 1]
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z_pos = position_data[:, 2]
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assert( np.array_equal(x_pos, np.array([0.5, 1.5, 0.5, 1.5, 0.5, 1.5])) )
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assert( np.array_equal(y_pos, np.array([0.5, 0.5, 1.5, 1.5, 2.5, 2.5])) )
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assert( np.array_equal(z_pos, np.array([0.5, 0.5, 0.5, 0.5, 0.5, 0.5])) )
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corner_data = grid.export_corners(index_frame)
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compare = np.array([[0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0],
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[1.0, 0.0, 0.0, 2.0, 0.0, 0.0, 1.0, 1.0, 0.0, 2.0, 1.0, 0.0, 1.0, 0.0, 1.0, 2.0, 0.0, 1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0],
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[0.0, 1.0, 0.0, 1.0, 1.0, 0.0, 0.0, 2.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 2.0, 1.0, 1.0, 2.0, 1.0],
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[1.0, 1.0, 0.0, 2.0, 1.0, 0.0, 1.0, 2.0, 0.0, 2.0, 2.0, 0.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 2.0, 1.0, 2.0, 2.0, 1.0],
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[0.0, 2.0, 0.0, 1.0, 2.0, 0.0, 0.0, 3.0, 0.0, 1.0, 3.0, 0.0, 0.0, 2.0, 1.0, 1.0, 2.0, 1.0, 0.0, 3.0, 1.0, 1.0, 3.0, 1.0],
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[1.0, 2.0, 0.0, 2.0, 2.0, 0.0, 1.0, 3.0, 0.0, 2.0, 3.0, 0.0, 1.0, 2.0, 1.0, 2.0, 2.0, 1.0, 1.0, 3.0, 1.0, 2.0, 3.0, 1.0]])
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assert( np.array_equal(corner_data, compare) )
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