tsimulation_sheardisp_plot.jl - seaice-experiments - sea ice experiments using Granular.jl
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tsimulation_sheardisp_plot.jl (1211B)
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1 #/usr/bin/env julia
2 ENV["MPLBACKEND"] = "Agg"
3 import PyPlot
4 import LsqFit
5
6 const id_prefix = "mohr_coulomb"
7 const vel_shear = 1.0
8
9 # Normal stresses for consolidation and shear [Pa]
10 const N_list = [20e3]
11
12 ypos = Float64[]
13 xdisp = Float64[]
14 sim_id = ""
15
16 alpha=0.7
17
18 for kind in ["mu0.3_sigma_c0kPa", "mu0.0_sigma_c200kPa"]
19 for N in N_list
20
21 #mohr_coulomb_mu0.3_sigma_c0kPa.pdf-seed1-shear-N20000.0Pa-vel_shear1.0m-s-data
22 sim_id = "$(id_prefix)_$(kind).pdf-seed1-shear-N$(N)Pa-vel_shear$(vel_shear)m-s"
23 info(sim_id)
24 data = readdlm(sim_id * "/ypos-xdisp.csv", ',', skipstart=1)
25
26 xdisp = data[:,1]
27 ypos = data[:,5]
28
29 if kind == "mu0.3_sigma_c0kPa"
30 PyPlot.plot(xdisp, ypos, "xk", label="Frictional DEM", alpha=alpha)
31
32 elseif kind == "mu0.0_sigma_c200kPa"
33 PyPlot.plot(xdisp, ypos, "+b", label="Cohesive DEM", alpha=alpha)
34
35 else
36 error("kind $kind not understood")
37 end
38 end
39 end
40
41 # Annotation
42 PyPlot.ylabel("\$y\$ [m]")
43 PyPlot.xlabel("Displacement along \$x\$ [m]")
44 #PyPlot.xlim(minimum(N_list)*0.9/1e3, maximum(N_list)*1.1/1e3)
45 PyPlot.legend()
46 PyPlot.savefig(id_prefix * "-xdisp.pdf")
47 PyPlot.clf()