7dbd17a5aa
Former-commit-id:133dc97f67[formerlya02aeb236c] [formerly9f19e3f712] [formerly133dc97f67[formerlya02aeb236c] [formerly9f19e3f712] [formerly06a8b51d6d[formerly9f19e3f712[formerly 64fa9254b946eae7e61bbc3f513b7c3696c4f54f]]]] Former-commit-id:06a8b51d6dFormer-commit-id:9bb8decbcf[formerly8e80217e59] [formerly377dcd10b9[formerly3360eb6c5f]] Former-commit-id:377dcd10b9Former-commit-id:e2ecdcfe33
70 lines
2.2 KiB
Python
70 lines
2.2 KiB
Python
##
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# This software was developed and / or modified by Raytheon Company,
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# pursuant to Contract DG133W-05-CQ-1067 with the US Government.
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#
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# U.S. EXPORT CONTROLLED TECHNICAL DATA
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# This software product contains export-restricted data whose
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# export/transfer/disclosure is restricted by U.S. law. Dissemination
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# to non-U.S. persons whether in the United States or abroad requires
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# an export license or other authorization.
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#
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# Contractor Name: Raytheon Company
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# Contractor Address: 6825 Pine Street, Suite 340
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# Mail Stop B8
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# Omaha, NE 68106
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# 402.291.0100
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#
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# See the AWIPS II Master Rights File ("Master Rights File.pdf") for
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# further licensing information.
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###
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## @file Gradient.py
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from numpy import empty, shape, NaN
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import Vector
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##
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# Calculate the X and Y gradient arrays of a 2+D array of scalars.
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#
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# @param scalar: Array of scalar values
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# @param dx: Spacing between data points in X direction.
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# @param dy: Spacing between data points in Y direction.
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# @return: gradient of scalar
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# @rtype: tuple(u, v)
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def execute(scalar, dx, dy):
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"Calculate the 2D gradient arrays of a 2+D scalar array."
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result_u = empty(shape(scalar), dtype=scalar.dtype)
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result_v = empty(shape(scalar), dtype=scalar.dtype)
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# Left/rt edges of result_u can't be calculated.
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result_u[:,0] = NaN
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result_u[:,-1] = NaN
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# Top/bot edges of result_v can't be calculated.
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result_v[0,:] = NaN
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result_v[-1,:] = NaN
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# If dx and dy are arrays, remove extra cells.
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shapedx = shape(dx)
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if len(shapedx) < sum(shapedx):
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dx = dx[:,1:-1]
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shapedy = shape(dy)
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if len(shapedy) < sum(shapedy):
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dy = dy[1:-1,:]
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# assume dx and dy are never zero
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# dx = masked_values(dx, 0.0, copy=False)
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# dy = masked_values(dy, 0.0, copy=False)
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# calculate d(scalar)/dx
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ans_u = scalar[:,2:] - scalar[:,0:-2]
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ans_u = ans_u/(2 * dx)
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# calculate d(scalar)/dy
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ans_v = scalar[0:-2,:] - scalar[2:,:]
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ans_v = ans_v/(2 * dy)
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result_u[:,1:-1] = ans_u
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result_v[1:-1,:] = ans_v
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return Vector.execute(result_u, result_v)
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