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61 lines
1.6 KiB
Python
61 lines
1.6 KiB
Python
# -*- coding: utf-8 -*-
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"""
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This python module implements visualization techniques/modes
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Copyright (C) 2018 SINTEF ICT
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This program 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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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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"""
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import numpy as np
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from matplotlib.colors import Normalize
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def genSchlieren(rho):
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#Compute length of z-component of normalized gradient vector
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normal = np.gradient(rho) #[x, y, 1]
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length = 1.0 / np.sqrt(normal[0]**2 + normal[1]**2 + 1.0)
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schlieren = np.power(length, 128)
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return schlieren
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def genVorticity(rho, rho_u, rho_v):
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u = rho_u / rho
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v = rho_v / rho
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u = np.sqrt(u**2 + v**2)
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u_max = u.max()
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du_dy, _ = np.gradient(u)
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_, dv_dx = np.gradient(v)
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#Length of curl
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curl = dv_dx - du_dy
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return curl
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def genColors(rho, rho_u, rho_v, cmap, vmax, vmin):
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schlieren = genSchlieren(rho)
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curl = genVorticity(rho, rho_u, rho_v)
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colors = Normalize(vmin, vmax, clip=True)(curl)
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colors = cmap(colors)
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for k in range(3):
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colors[:,:,k] = colors[:,:,k]*schlieren
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return colors |