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tfix grid generation, increase random variability of point positioning - granul… |
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git clone git://src.adamsgaard.dk/granular-channel-hydro |
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--- |
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commit 8983440e41f994aedaf6b34648e690dedb03818a |
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parent 6ce83970ccaba7dd7c4f0ad316ce4f25f1e38e30 |
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Author: Anders Damsgaard Christensen <[email protected]> |
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Date: Fri, 13 Jan 2017 22:35:01 -0800 |
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fix grid generation, increase random variability of point positioning |
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Diffstat: |
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M granular_channel_drainage/model.py | 53 +++++++++++++++++++----------… |
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1 file changed, 32 insertions(+), 21 deletions(-) |
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--- |
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diff --git a/granular_channel_drainage/model.py b/granular_channel_drainage/mod… |
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t@@ -14,7 +14,8 @@ class model: |
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''' |
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self.name = name |
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- def generateVoronoiDelaunayGrid(self, Lx, Ly, N, structure='pseudorandom'): |
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+ def generateVoronoiDelaunayGrid(self, Lx, Ly, Nx, Ny, |
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+ structure='pseudorandom'): |
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''' |
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Generate a Voronoi Delaunay grid with randomly positioned nodes using |
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Landlab. |
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t@@ -25,8 +26,10 @@ class model: |
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:param Ly: A tuple containing the length along y of the model |
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domain. |
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:type Ly: float |
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- :param N: The number of random model nodes in the model. |
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- :type N: int |
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+ :param Nx: The number of random model nodes along ``x`` in the model. |
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+ :type Nx: int |
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+ :param Ny: The number of random model nodes along ``y`` in the model. |
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+ :type Ny: int |
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:param structure: The type of numeric distribution used to seed the |
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grid. A ``random`` grid will produce uniformly random-distributed |
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grid points, while ``pseudorandom`` (default) will add random noise |
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t@@ -36,36 +39,44 @@ class model: |
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self.grid_type = 'VoronoiDelaunay' |
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if structure == 'random': |
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- x = numpy.random.rand(N)*Lx |
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- y = numpy.random.rand(N)*Ly |
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+ x = numpy.random.rand(Nx*Ny)*Lx |
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+ y = numpy.random.rand(Nx*Ny)*Ly |
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elif structure == 'pseudorandom': |
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- noise_amplitude = Lx/(N**0.5)*0.01 |
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- x = numpy.linspace(0, Lx, N) + \ |
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- numpy.random.normal(0., noise_amplitude, N) |
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- y = numpy.linspace(0, Ly, N) + \ |
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- numpy.random.normal(0., noise_amplitude, N) |
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- print x |
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- print y |
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- x = numpy.random.shuffle(x) # why does this return an empty array? |
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- y = numpy.random.shuffle(y) |
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- print x |
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- print y |
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+ #noise_amplitude = Lx/(N**0.5)*0.001 |
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+ #noise_amplitude = 1. |
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+ #x = numpy.linspace(0, Lx, N) #+ \ |
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+ #numpy.random.normal(0., noise_amplitude, N) |
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+ #y = numpy.linspace(0, Ly, N) #+ \ |
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+ #numpy.random.normal(0., noise_amplitude, N) |
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+ #numpy.random.shuffle(x) |
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+ #numpy.random.shuffle(y) |
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+ xPoints = numpy.linspace(0., Lx, Nx) |
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+ yPoints = numpy.linspace(0., Ly, Ny) |
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+ gridPoints = numpy.array([[x,y] for y in yPoints for x in xPoints]) |
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+ gridPoints[::2, 1] = gridPoints[::2, 1] + Lx/Nx*0.5 |
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+ N = len(gridPoints[:, 0]) |
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+ x = gridPoints[:, 0] + numpy.random.normal(0, Lx/Nx*0.10, N) |
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+ y = gridPoints[:, 1] + numpy.random.normal(0, Ly/Ny*0.10, N) |
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self.grid = landlab.grid.VoronoiDelaunayGrid(x, y) |
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self.grid.add_zeros('node', 'bed__topographic__elevation') |
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self.grid.add_zeros('node', 'surface__topographic__elevation') |
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- def plotGrid(self, save=False, saveformat='pdf'): |
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- #landlab.plot.imshow_grid(self.grid, self.grid.node_x) |
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+ def plotGrid(self, field='nodes', |
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+ save=False, saveformat='pdf'): |
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fig = plt.figure() |
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- plt.plot(self.grid.x_of_node, self.grid.y_of_node, '.') |
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- plt.xlabel('$x$ [m]') |
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- plt.ylabel('$y$ [m]') |
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+ if field == 'nodes': |
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+ plt.plot(self.grid.node_x, self.grid.node_y, '.') |
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+ plt.axis('equal') |
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+ else: |
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+ landlab.plot.imshow_grid(self.grid, field) |
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+ plt.tight_layout() |
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if save: |
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plt.savefig('grid.' + saveformat) |
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else: |
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plt.show() |
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+ plt.clf() |
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plt.close() |
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