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tFix continued line indentation - sphere - GPU-based 3D discrete element method… |
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git clone git://src.adamsgaard.dk/sphere |
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Log |
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Refs |
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LICENSE |
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--- |
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commit 439019dc191d4e17968abd9d9ea70164a2489b84 |
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parent 84e33bd162733d251f944d84b1d799bc6951f4b7 |
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Author: Anders Damsgaard <[email protected]> |
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Date: Mon, 2 Sep 2019 15:20:47 +0200 |
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Fix continued line indentation |
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Diffstat: |
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M python/sphere.py | 241 ++++++++++++++++++-----------… |
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1 file changed, 138 insertions(+), 103 deletions(-) |
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--- |
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diff --git a/python/sphere.py b/python/sphere.py |
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t@@ -313,19 +313,19 @@ class sim: |
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# Fluid velocities [m/s] |
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self.v_f = numpy.zeros((self.num[0], self.num[1], self.num[2], sel… |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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# Fluid pressures [Pa] |
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self.p_f = numpy.zeros((self.num[0], self.num[1], self.num[2]), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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# Fluid cell porosities [-] |
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self.phi = numpy.zeros((self.num[0], self.num[1], self.num[2]), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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# Fluid cell porosity change [1/s] |
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self.dphi = numpy.zeros((self.num[0], self.num[1], self.num[2]), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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# Fluid density [kg/(m^3)] |
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self.rho_f = numpy.ones(1, dtype=numpy.float64) * 1.0e3 |
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t@@ -365,8 +365,8 @@ class sim: |
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# Hold pressures constant in fluid cell (0: True, 1: False) |
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self.p_f_constant = numpy.zeros((self.num[0], |
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- self.num[1], |
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- self.num[2]), dtype=numpy.int32) |
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+ self.num[1], |
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+ self.num[2]), dtype=numpy.int32) |
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# Navier-Stokes |
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if self.cfd_solver[0] == 0: |
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t@@ -1113,15 +1113,15 @@ class sim: |
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self.bonds[i, 0] = numpy.fromfile(fh, dtype=numpy.uint32, … |
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self.bonds[i, 1] = numpy.fromfile(fh, dtype=numpy.uint32, … |
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self.bonds_delta_n = numpy.fromfile(fh, dtype=numpy.float64, |
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- count=self.nb0) |
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+ count=self.nb0) |
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self.bonds_delta_t = numpy.fromfile(fh, dtype=numpy.float64, |
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- count=self.nb0*self.nd)\ |
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- .reshape(self.nb0, self.nd) |
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+ count=self.nb0*self.nd)\ |
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+ .reshape(self.nb0, self.nd) |
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self.bonds_omega_n = numpy.fromfile(fh, dtype=numpy.float64, |
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- count=self.nb0) |
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+ count=self.nb0) |
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self.bonds_omega_t = numpy.fromfile(fh, dtype=numpy.float64, |
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- count=self.nb0*self.nd)\ |
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- .reshape(self.nb0, self.nd) |
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+ count=self.nb0*self.nd)\ |
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+ .reshape(self.nb0, self.nd) |
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else: |
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self.nb0 = 0 |
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t@@ -1135,101 +1135,126 @@ class sim: |
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self.mu = numpy.fromfile(fh, dtype=numpy.float64, count=1) |
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self.v_f = numpy.empty((self.num[0], |
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- self.num[1], |
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- self.num[2], |
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- self.nd), dtype=numpy.float64) |
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+ self.num[1], |
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+ self.num[2], |
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+ self.nd), dtype=numpy.float64) |
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self.p_f = numpy.empty((self.num[0], |
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- self.num[1], |
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- self.num[2]), dtype=numpy.float64) |
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+ self.num[1], |
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+ self.num[2]), dtype=numpy.float64) |
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self.phi = numpy.empty((self.num[0], |
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- self.num[1], |
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- self.num[2]), dtype=numpy.float64) |
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+ self.num[1], |
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+ self.num[2]), dtype=numpy.float64) |
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self.dphi = numpy.empty((self.num[0], |
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- self.num[1], |
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- self.num[2]), dtype=numpy.float64) |
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+ self.num[1], |
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+ self.num[2]), dtype=numpy.float64) |
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for z in numpy.arange(self.num[2]): |
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for y in numpy.arange(self.num[1]): |
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for x in numpy.arange(self.num[0]): |
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self.v_f[x, y, z, 0] = numpy.fromfile(fh, |
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- dtype=numpy.flo… |
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- count=1) |
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+ dtype=numpy.… |
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+ count=1) |
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self.v_f[x, y, z, 1] = numpy.fromfile(fh, |
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+ dtype=numpy.… |
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+ count=1) |
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+ self.v_f[x, y, z, 2] = numpy.fromfile(fh, |
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+ dtype=numpy.… |
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+ count=1) |
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+ self.p_f[x, y, z] = numpy.fromfile(fh, |
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dtype=numpy.flo… |
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count=1) |
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- self.v_f[x, y, z, 2] = numpy.fromfile(fh, |
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+ self.phi[x, y, z] = numpy.fromfile(fh, |
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dtype=numpy.flo… |
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count=1) |
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- self.p_f[x, y, z] = numpy.fromfile(fh, dtype=numpy… |
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- count=1) |
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- self.phi[x, y, z] = numpy.fromfile(fh, dtype=numpy… |
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- count=1) |
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- self.dphi[x, y, z] = numpy.fromfile(fh, dtype=nump… |
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- count=1)\ |
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+ self.dphi[x, y, z] = numpy.fromfile(fh, |
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+ dtype=numpy.fl… |
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+ count=1)\ |
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/(self.time_dt*self.ndem) |
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if self.version >= 0.36: |
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- self.rho_f = numpy.fromfile(fh, dtype=numpy.float64, count… |
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- self.p_mod_A = numpy.fromfile(fh, dtype=numpy.float64, cou… |
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- self.p_mod_f = numpy.fromfile(fh, dtype=numpy.float64, cou… |
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- self.p_mod_phi = numpy.fromfile(fh, dtype=numpy.float64, c… |
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+ self.rho_f = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.p_mod_A = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.p_mod_f = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.p_mod_phi = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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if self.version >= 2.12 and self.cfd_solver[0] == 1: |
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- self.bc_xn = numpy.fromfile(fh, dtype=numpy.int32, cou… |
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- self.bc_xp = numpy.fromfile(fh, dtype=numpy.int32, cou… |
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- self.bc_yn = numpy.fromfile(fh, dtype=numpy.int32, cou… |
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- self.bc_yp = numpy.fromfile(fh, dtype=numpy.int32, cou… |
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+ self.bc_xn = numpy.fromfile(fh, dtype=numpy.int32, |
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+ count=1) |
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+ self.bc_xp = numpy.fromfile(fh, dtype=numpy.int32, |
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+ count=1) |
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+ self.bc_yn = numpy.fromfile(fh, dtype=numpy.int32, |
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+ count=1) |
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+ self.bc_yp = numpy.fromfile(fh, dtype=numpy.int32, |
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+ count=1) |
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self.bc_bot = numpy.fromfile(fh, dtype=numpy.int32, count=… |
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self.bc_top = numpy.fromfile(fh, dtype=numpy.int32, count=… |
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- self.free_slip_bot = numpy.fromfile(fh, dtype=numpy.int32,… |
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- self.free_slip_top = numpy.fromfile(fh, dtype=numpy.int32,… |
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+ self.free_slip_bot = numpy.fromfile(fh, dtype=numpy.int32, |
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+ count=1) |
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+ self.free_slip_top = numpy.fromfile(fh, dtype=numpy.int32, |
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+ count=1) |
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if self.version >= 2.11: |
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- self.bc_bot_flux = numpy.fromfile(fh, dtype=numpy.floa… |
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- count=1) |
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- self.bc_top_flux = numpy.fromfile(fh, dtype=numpy.floa… |
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- count=1) |
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+ self.bc_bot_flux = numpy.fromfile(fh, |
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+ dtype=numpy.float64, |
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+ count=1) |
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+ self.bc_top_flux = numpy.fromfile(fh, |
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+ dtype=numpy.float64, |
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+ count=1) |
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else: |
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self.bc_bot_flux = numpy.zeros(1, dtype=numpy.float64) |
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self.bc_top_flux = numpy.zeros(1, dtype=numpy.float64) |
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if self.version >= 2.15: |
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self.p_f_constant = numpy.empty((self.num[0], |
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- self.num[1], |
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- self.num[2]), |
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- dtype=numpy.int32) |
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+ self.num[1], |
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+ self.num[2]), |
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+ dtype=numpy.int32) |
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for z in numpy.arange(self.num[2]): |
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for y in numpy.arange(self.num[1]): |
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for x in numpy.arange(self.num[0]): |
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self.p_f_constant[x, y, z] = \ |
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- numpy.fromfile(fh, dtype=numpy.int32, … |
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+ numpy.fromfile(fh, dtype=numpy.int32, |
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+ count=1) |
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else: |
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self.p_f_constant = numpy.zeros((self.num[0], |
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- self.num[1], |
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- self.num[2]), |
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- dtype=numpy.int32) |
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+ self.num[1], |
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+ self.num[2]), |
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+ dtype=numpy.int32) |
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if self.version >= 2.0 and self.cfd_solver == 0: |
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- self.gamma = numpy.fromfile(fh, dtype=numpy.float64, count… |
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- self.theta = numpy.fromfile(fh, dtype=numpy.float64, count… |
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- self.beta = numpy.fromfile(fh, dtype=numpy.float64, count=… |
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- self.tolerance = numpy.fromfile(fh, dtype=numpy.float64, c… |
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- self.maxiter = numpy.fromfile(fh, dtype=numpy.uint32, coun… |
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+ self.gamma = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.theta = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.beta = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.tolerance = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.maxiter = numpy.fromfile(fh, dtype=numpy.uint32, |
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+ count=1) |
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if self.version >= 1.01: |
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- self.ndem = numpy.fromfile(fh, dtype=numpy.uint32, cou… |
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+ self.ndem = numpy.fromfile(fh, dtype=numpy.uint32, |
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+ count=1) |
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else: |
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self.ndem = 1 |
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if self.version >= 1.04: |
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- self.c_phi = numpy.fromfile(fh, dtype=numpy.float64, c… |
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- self.c_v = numpy.fromfile(fh, dtype=numpy.float64, cou… |
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+ self.c_phi = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.c_v = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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if self.version == 1.06: |
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self.c_a = numpy.fromfile(fh, dtype=numpy.float64, |
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- count=1) |
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+ count=1) |
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elif self.version >= 1.07: |
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- self.dt_dem_fac = numpy.fromfile(fh, dtype=numpy.f… |
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- count=1) |
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+ self.dt_dem_fac = numpy.fromfile(fh, |
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+ dtype=numpy.float… |
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+ count=1) |
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else: |
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self.c_a = numpy.ones(1, dtype=numpy.float64) |
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else: |
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t@@ -1243,42 +1268,51 @@ class sim: |
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self.f_sum = numpy.empty_like(self.x) |
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for i in numpy.arange(self.np): |
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- self.f_d[i, :] = numpy.fromfile(fh, dtype=numpy.fl… |
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- count=self.nd) |
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+ self.f_d[i, :] = numpy.fromfile(fh, |
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+ dtype=numpy.float6… |
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+ count=self.nd) |
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for i in numpy.arange(self.np): |
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- self.f_p[i, :] = numpy.fromfile(fh, dtype=numpy.fl… |
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- count=self.nd) |
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+ self.f_p[i, :] = numpy.fromfile(fh, |
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+ dtype=numpy.float6… |
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+ count=self.nd) |
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for i in numpy.arange(self.np): |
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- self.f_v[i, :] = numpy.fromfile(fh, dtype=numpy.fl… |
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- count=self.nd) |
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+ self.f_v[i, :] = numpy.fromfile(fh, |
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+ dtype=numpy.float6… |
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+ count=self.nd) |
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for i in numpy.arange(self.np): |
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- self.f_sum[i, :] = numpy.fromfile(fh, dtype=numpy.… |
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- count=self.nd) |
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+ self.f_sum[i, :] = numpy.fromfile(fh, |
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+ dtype=numpy.floa… |
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+ count=self.nd) |
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else: |
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self.f_d = numpy.zeros((self.np, self.nd), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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self.f_p = numpy.zeros((self.np, self.nd), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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self.f_v = numpy.zeros((self.np, self.nd), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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self.f_sum = numpy.zeros((self.np, self.nd), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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elif self.version >= 2.0 and self.cfd_solver == 1: |
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- self.tolerance = numpy.fromfile(fh, dtype=numpy.float64, c… |
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- self.maxiter = numpy.fromfile(fh, dtype=numpy.uint32, coun… |
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+ self.tolerance = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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+ self.maxiter = numpy.fromfile(fh, dtype=numpy.uint32, |
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+ count=1) |
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self.ndem = numpy.fromfile(fh, dtype=numpy.uint32, count=1) |
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- self.c_phi = numpy.fromfile(fh, dtype=numpy.float64, count… |
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+ self.c_phi = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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self.f_p = numpy.empty_like(self.x) |
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for i in numpy.arange(self.np): |
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self.f_p[i, :] = numpy.fromfile(fh, dtype=numpy.float6… |
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- count=self.nd) |
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- self.beta_f = numpy.fromfile(fh, dtype=numpy.float64, coun… |
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+ count=self.nd) |
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+ self.beta_f = numpy.fromfile(fh, dtype=numpy.float64, |
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+ count=1) |
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self.k_c = numpy.fromfile(fh, dtype=numpy.float64, count=1) |
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if self.version >= 1.02: |
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- self.color = numpy.fromfile(fh, dtype=numpy.int32, count=self.… |
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+ self.color = numpy.fromfile(fh, dtype=numpy.int32, |
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+ count=self.np) |
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else: |
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self.color = numpy.zeros(self.np, dtype=numpy.int32) |
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t@@ -2181,7 +2215,7 @@ class sim: |
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def red(ratio): |
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return numpy.fmin(1.0, 0.209*ratio**3. - 2.49*ratio**2. + 3.0*… |
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- + 0.0109) |
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+ + 0.0109) |
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def green(ratio): |
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return numpy.fmin(1.0, -2.44*ratio**2. + 2.15*ratio + 0.369) |
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def blue(ratio): |
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t@@ -2650,12 +2684,12 @@ class sim: |
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# Max. and min. coordinates of world |
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self.origo = numpy.array([numpy.amin(self.x[:, 0] - self.radius[:]), |
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- numpy.amin(self.x[:, 1] - self.radius[:]), |
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- numpy.amin(self.x[:, 2] - self.radius[:])]) \ |
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+ numpy.amin(self.x[:, 1] - self.radius[:]), |
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+ numpy.amin(self.x[:, 2] - self.radius[:])]) \ |
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- margin*r_max |
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self.L = numpy.array([numpy.amax(self.x[:, 0] + self.radius[:]), |
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- numpy.amax(self.x[:, 1] + self.radius[:]), |
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- numpy.amax(self.x[:, 2] + self.radius[:])]) \ |
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+ numpy.amax(self.x[:, 1] + self.radius[:]), |
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+ numpy.amax(self.x[:, 2] + self.radius[:])]) \ |
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+ margin*r_max |
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cellsize_min = 2.1 * r_max |
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t@@ -2864,7 +2898,7 @@ class sim: |
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''' |
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bondparticles = numpy.unique(numpy.random.random_integers(0, high=self… |
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- size=int(self.np*r… |
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+ size=int(sel… |
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if bondparticles.size % 2 > 0: |
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bondparticles = bondparticles[:-1].copy() |
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bondparticles = bondparticles.reshape(int(bondparticles.size/2), |
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t@@ -3026,8 +3060,8 @@ class sim: |
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self.w_vel = numpy.array([1, 0, 0, 0, 0]) * wvel |
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self.w_sigma0 = numpy.array([0, 1, 1, 1, 1]) * normal_stress |
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self.w_n = numpy.array(([0, 0, -1], [-1, 0, 0], |
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- [1, 0, 0], [0, -1, 0], [0, 1, 0]), |
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- dtype=numpy.float64) |
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+ [1, 0, 0], [0, -1, 0], [0, 1, 0]), |
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+ dtype=numpy.float64) |
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self.w_x = numpy.zeros(5) |
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self.w_m = numpy.zeros(5) |
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self.w_force = numpy.zeros(5) |
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t@@ -3070,7 +3104,7 @@ class sim: |
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|
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# Fix horizontal velocity to 0.0 of lowermost particles |
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d_max_below = numpy.max(self.radius[numpy.nonzero(self.x[:, 2] < |
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- (z_max-z_min)*0.3)])*2.0 |
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+ (z_max-z_min)*0.3)])… |
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I = numpy.nonzero(self.x[:, 2] < (z_min + d_max_below)) |
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self.fixvel[I] = 1 |
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self.angvel[I, 0] = 0.0 |
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t@@ -3082,7 +3116,7 @@ class sim: |
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|
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# Fix horizontal velocity to specific value of uppermost particles |
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d_max_top = numpy.max(self.radius[numpy.nonzero(self.x[:, 2] > |
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- (z_max-z_min)*0.7)])*2.0 |
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+ (z_max-z_min)*0.7)])*2… |
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I = numpy.nonzero(self.x[:, 2] > (z_max - d_max_top)) |
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self.fixvel[I] = 1 |
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self.angvel[I, 0] = 0.0 |
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t@@ -3349,7 +3383,7 @@ class sim: |
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self.rho_f = numpy.ones(1, dtype=numpy.float64) * rho |
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self.p_f = numpy.ones((self.num[0], self.num[1], self.num[2]), |
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- dtype=numpy.float64) * p |
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+ dtype=numpy.float64) * p |
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if hydrostatic: |
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t@@ -3374,11 +3408,11 @@ class sim: |
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self.v_f = numpy.zeros((self.num[0], self.num[1], self.num[2], self.nd… |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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self.phi = numpy.ones((self.num[0], self.num[1], self.num[2]), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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self.dphi = numpy.zeros((self.num[0], self.num[1], self.num[2]), |
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- dtype=numpy.float64) |
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+ dtype=numpy.float64) |
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self.p_mod_A = numpy.zeros(1, dtype=numpy.float64) # Amplitude [Pa] |
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self.p_mod_f = numpy.zeros(1, dtype=numpy.float64) # Frequency [Hz] |
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t@@ -3392,7 +3426,7 @@ class sim: |
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self.bc_top_flux = numpy.zeros(1, dtype=numpy.float64) |
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|
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self.p_f_constant = numpy.zeros((self.num[0], self.num[1], self.num[2]… |
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- dtype=numpy.int32) |
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+ dtype=numpy.int32) |
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|
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# Fluid solver type |
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# 0: Navier Stokes (fluid with inertia) |
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t@@ -4018,7 +4052,7 @@ class sim: |
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self.bonds_delta_t = numpy.array([[0.0, 0.0, 0.0]], dtype=numpy.ui… |
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else: |
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self.bonds_delta_t = numpy.vstack((self.bonds_delta_t, |
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- [0.0, 0.0, 0.0])) |
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+ [0.0, 0.0, 0.0])) |
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|
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if not hasattr(self, 'bonds_omega_n'): |
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self.bonds_omega_n = numpy.array([0.0], dtype=numpy.uint32) |
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t@@ -4027,10 +4061,11 @@ class sim: |
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self.bonds_omega_n = numpy.append(self.bonds_omega_n, [0.0]) |
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|
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if not hasattr(self, 'bonds_omega_t'): |
|
- self.bonds_omega_t = numpy.array([[0.0, 0.0, 0.0]], dtype=numpy.ui… |
|
+ self.bonds_omega_t = numpy.array([[0.0, 0.0, 0.0]], |
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+ dtype=numpy.uint32) |
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else: |
|
self.bonds_omega_t = numpy.vstack((self.bonds_omega_t, |
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- [0.0, 0.0, 0.0])) |
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+ [0.0, 0.0, 0.0])) |
|
|
|
# Increment the number of bonds with one |
|
self.nb0 += 1 |
|
t@@ -4715,7 +4750,7 @@ class sim: |
|
shell=True) |
|
contactdata = numpy.loadtxt('../output/' + self.sid + '.contacts.txt') |
|
self.pairs = numpy.array((contactdata[:, 0], contactdata[:, 1]), |
|
- dtype=numpy.int32) |
|
+ dtype=numpy.int32) |
|
self.overlaps = numpy.array(contactdata[:, 2]) |
|
|
|
def findCoordinationNumber(self): |
|
t@@ -5520,11 +5555,11 @@ class sim: |
|
# plot defined max compressive stress from tau/N ratio |
|
ax.scatter(0., # prescribed stress |
|
numpy.degrees(numpy.arctan(self.shearStress('defined')/ |
|
- self.currentNormalStress('defined'))), |
|
+ self.currentNormalStress('define… |
|
marker='o', c='none', edgecolor='blue', s=300) |
|
ax.scatter(0., # actual stress |
|
numpy.degrees(numpy.arctan(self.shearStress('effective')/ |
|
- self.currentNormalStress('effective'))… |
|
+ self.currentNormalStress('effect… |
|
marker='+', color='blue', s=300) |
|
|
|
ax.set_rmax(90) |
|
t@@ -5561,7 +5596,7 @@ class sim: |
|
# angle: 0 when vertical, 90 when horizontal |
|
#hist, bins = numpy.histogram(datadata[:, 6], bins=10) |
|
_, _, _ = plt.hist(90. - diplist, bins=range(0, 100, 10), |
|
- alpha=0.75, facecolor='gray') |
|
+ alpha=0.75, facecolor='gray') |
|
theta_sigma1 = numpy.degrees(numpy.arctan( |
|
self.currentNormalStress('defined')/\ |
|
self.shearStress('defined'))) |
|
t@@ -6747,7 +6782,7 @@ class sim: |
|
raise ValueError |
|
|
|
s = numpy.r_[2*tau[0]-tau[smoothing:1:-1], tau, |
|
- 2*tau[-1]-tau[-1:-smoothing:-1]] |
|
+ 2*tau[-1]-tau[-1:-smoothing:-1]] |
|
|
|
if smoothing_window == 'flat': # moving average |
|
w = numpy.ones(smoothing, 'd') |
