tImprove sampling when generating irregular packings - Granular.jl - Julia package for granular dynamics simulation
(HTM) git clone git://src.adamsgaard.dk/Granular.jl
(DIR) Log
(DIR) Files
(DIR) Refs
(DIR) README
(DIR) LICENSE
---
(DIR) commit 718e4f5ed4e304281c1af295e803b8261fdc7a0a
(DIR) parent 3241cf58da25204c6fc0cf2d20da73b1619ef790
(HTM) Author: Anders Damsgaard <andersd@riseup.net>
Date: Wed, 20 Dec 2017 22:53:59 -0500
Improve sampling when generating irregular packings
Diffstat:
M src/packing.jl | 54 ++++++++++++++++++++++---------
M test/packing.jl | 13 +++++++++----
2 files changed, 47 insertions(+), 20 deletions(-)
---
(DIR) diff --git a/src/packing.jl b/src/packing.jl
t@@ -66,12 +66,20 @@ Return random point in spherical annulus between `(r_i + r_j)` and `2.*(r_i +
r_j)` around `x_i`. Note: there is slightly higher point density towards (r_i +
r_j).
"""
-function generateNeighboringPoint(x_i::Vector, r_i::Real, r_j::Real,
- max_padding_factor::Real)
+function generateNeighboringPoint(x_i::Vector, r_i::Real,
+ r_max::Real, r_min::Real;
+ padding::Real=0.)
- R = rand() * (r_i + r_j) * max_padding_factor + 2. * (r_i + r_j)
+ if padding > 0.
+ r_j = r_min + (rand()*0.5 + 0.5)*(r_max - r_min)
+ else
+ r_j = r_min + rand()*(r_max - r_min) # between r_min and r_max
+ end
+ #r_j = r_min + rand()*(r_i - r_min) # between r_min and r_i
+ #R = rand() * (r_i + r_j) * max_padding_factor + 2. * (r_i + r_j)
+ R = r_i + r_j + padding
T = rand() * 2. * pi
- return [x_i[1] + R * sin(T), x_i[2] + R * cos(T)]
+ return [x_i[1] + R * sin(T), x_i[2] + R * cos(T)], r_j
end
export irregularPacking!
t@@ -88,17 +96,13 @@ in arbitrary dimensions"](https://doi.org/10.1145/1278780.1278807). The
* `radius_min::Real`: smallest grain radius to use.
* `sample_limit::Integer=30`: number of points to sample around each grain
before giving up.
-* `max_padding_factor::Real=2.`: this factor scales the padding to use during ice
- floe generation in numbers of grain diameters.
* `seed::Integer`: seed value to the pseudo-random number generator.
* `verbose::Bool=true`: show diagnostic information to stdout.
-
"""
function irregularPacking!(simulation::Simulation;
radius_max::Real=.1,
radius_min::Real=.1,
sample_limit::Integer=30,
- max_padding_factor::Real=2.,
thickness::Real=1.,
seed::Integer=1,
verbose::Bool=true)
t@@ -136,8 +140,7 @@ function irregularPacking!(simulation::Simulation;
# Step 2: While the active list is not empty, choose a random index `i` from
# it. Generate up to `sample_limit` points chosen uniformly from the
- # spherical annulus between radius `2*(r_i+r_j)` and
- # `max_padding_factor*2*(r_i+r_j)` around `x_i`.
+ # distance `(r_i+r_j)` around `x_i`.
# For each point in turn, check if it is within distance r of existing
# samples (using the background grid to only test nearby samples). If a
# point is adequately far from existing samples, emit it as the next sample
t@@ -150,21 +153,35 @@ function irregularPacking!(simulation::Simulation;
sw = zeros(2); se = zeros(2); ne = zeros(2); nw = zeros(2)
nx, ny = size(grid.xh)
n = 0
+ neighbor_found = false
while !isempty(active_list)
i = rand(1:length(active_list))
- deleteat!(active_list, i)
x_active = simulation.grains[i].lin_pos
r_active = simulation.grains[i].contact_radius
- r_candidate = rand()*(radius_max - radius_min) + radius_min
+ #r_candidate = rand()*(radius_max - radius_min) + radius_min
+
+ neighbor_found = false
for j=1:sample_limit
- x_candidate = generateNeighboringPoint(x_active, r_active,
- r_candidate,
- max_padding_factor)
+ # add points at wider distance for the first 10 iterations, and
+ # afterwards directly neighboring points
+ if j <= 2
+ x_candidate, r_candidate = generateNeighboringPoint(x_active,
+ r_active,
+ radius_max,
+ radius_min,
+ padding=2.0*radius_max)
+ else
+ x_candidate, r_candidate = generateNeighboringPoint(x_active,
+ r_active,
+ radius_max,
+ radius_min)
+ end
+
if !(isPointInGrid(grid, x_candidate))
continue # skip this candidate
t@@ -210,11 +227,16 @@ function irregularPacking!(simulation::Simulation;
thickness, verbose=false)
sortGrainsInGrid!(simulation, grid)
push!(active_list, length(simulation.grains))
+ neighbor_found = true
end
end
+ if !neighbor_found
+ deleteat!(active_list, i)
+ end
println("Active points: $(length(active_list))")
n += 1
- plotGrains(simulation, filetype="$n.png", show_figure=false)
+ filepostfix = @sprintf("packing.%05d.png", n)
+ plotGrains(simulation, filetype=filepostfix, show_figure=false)
end
if verbose
info("Generated $(length(simulation.grains) - np_init) points")
(DIR) diff --git a/test/packing.jl b/test/packing.jl
t@@ -40,12 +40,17 @@ end
info("Testing irregular (Poisson-disk) packing generation (monodisperse size)")
-sim = Granular.createSimulation()
+sim = Granular.createSimulation("poisson1")
sim.ocean = Granular.createRegularOceanGrid([1, 1, 1], [1., 1., 1.])
Granular.irregularPacking!(sim,
radius_max=.1,
radius_min=.1,
- sample_limit=30,
- max_padding_factor=2.,
- thickness=1.,
+ verbose=true)
+
+info("Testing irregular (Poisson-disk) packing generation (wide PSD)")
+sim = Granular.createSimulation("poisson2")
+sim.ocean = Granular.createRegularOceanGrid([1, 1, 1], [1., 1., 1.])
+Granular.irregularPacking!(sim,
+ radius_max=.1,
+ radius_min=.001,
verbose=true)