save changes

Project.toml

@@ -17,6 +17,7 @@ GarishPrint = "b0ab02a7-8576-43f7-aa76-eaa7c3897c54"
 Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 ProgressLogging = "33c8b6b6-d38a-422a-b730-caa89a2f386c"
 QuadGK = "1fd47b50-473d-5c70-9696-f719f8f3bcdc"
@@ -25,3 +26,9 @@ Serialization = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
 TOML = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
 TerminalLoggers = "5d786b92-1e48-4d6f-9151-6b4477ca9bed"
 UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
+
+[weakdeps]
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+
+[extensions]
+PlotsExt = ["Plots"]

scripts/main.toml

@@ -1,4 +1,4 @@
-njobs = 800
+njobs = 1
 seed = 1234
 walltime = "3-00:00:00"
 
@@ -12,31 +12,33 @@ path = "data"
 tags = []
 
 [sample]
-nrepeat = 200
-nsamples = 500_000
+nrepeat = 2
+nsamples = 200_000
 nthrows = 10
 observables = ["E", "E^2", "M", "M^2", "accept_rate"]
 
     [sample.option]
     nburns = 5000
     order = "random"
+    [sample.option.gauge]
+    steps = 5
 
 [fields]
-start = 0.0
+start = 0.2
 step = 0.01
-stop = 1.0
+stop = 0.2
 
 [temperatures]
-start = 20.0
-step = -0.05
+start = 1.5
+step = -0.02
 stop = 0.05
 
 [checkpoint.temperatures]
-start = 5.0
-step = -0.05
+start = 1.5
+step = -0.02
 stop = 0.05
 
 [checkpoint.fields]
-start = 0.0
+start = 0.2
 step = 0.01
-stop = 1.0
+stop = 0.2

scripts/plot2.jl

@@ -22,7 +22,10 @@ begin
 end
 
 # ╔═╡ c3279e72-838e-49b5-b3dd-c1dc7f301ece
-df = DataFrame(CSV.File("../data/crunch/c8ec6624-cace-11ed-0795-d1e27c39ff1f.csv"))
+df = DataFrame(CSV.File("../data/crunch/9f158064-cd81-11ed-3d1e-8f05d75ea3ad.csv"))
+
+# ╔═╡ 7aa2e82b-f0fa-4cae-bba7-5f70adff77eb
+hasproperty(df, "E(std)")
 
 # ╔═╡ d21e5512-632e-4ae1-8d42-cdb1f98311bb
 gdf = groupby(df, [:field])
@@ -61,11 +64,16 @@ plot(
 	title="h=$(gdf[h].field[1])"
 )
 
-# ╔═╡ 6175d2f3-2a41-4d8c-afaa-d3836e986e41
-maximum(gdf[77]."Cv(std)")
-
-# ╔═╡ 6048db65-70b9-4936-954a-87b2db57e5b1
-maximum(gdf[77]."Cv(mean)")
+# ╔═╡ 52746088-57f6-46d7-b8da-8d1988622f75
+plot(
+	gdf[h]."temp", gdf[h]."χ(mean)",
+	yerror=map(gdf[h]."χ(std)") do x
+		isnan(x) ? 0.0 : x
+	end,
+	legend=nothing,
+	xlabel="temperature", ylabel="χ(mean)",
+	title="h=$(gdf[h].field[1])"
+)
 
 # ╔═╡ d7157f73-a8b5-43bf-b888-ed4fc20d50ed
 maximum(gdf[57]."Cv(tau)")
@@ -109,16 +117,28 @@ end
 # ╔═╡ 18237a59-3057-4a72-9dbe-c22fcc26b568
 heatmap(hs, Ts, M; xlabel="h", ylabel="T")
 
+# ╔═╡ 36db7a3d-1bb8-4e13-b278-78d428d32f43
+χ = let
+	ret = zeros(length(gdf[1].temp), length(gdf))
+	for (h_idx, df) in enumerate(gdf), (T_idx, T) in enumerate(df.temp)
+		ret[end - T_idx + 1, h_idx] = df."χ(mean)"[T_idx] / maximum(df."χ(mean)")
+	end
+	ret
+end
+
+# ╔═╡ 50db1938-1fdc-4fff-80f1-bab842a2338c
+heatmap(hs, Ts, χ; xlabel="h", ylabel="T")
+
 # ╔═╡ Cell order:
 # ╠═de9f08e2-ce67-11ed-3a88-838fff267690
 # ╠═c3279e72-838e-49b5-b3dd-c1dc7f301ece
+# ╠═7aa2e82b-f0fa-4cae-bba7-5f70adff77eb
 # ╠═d21e5512-632e-4ae1-8d42-cdb1f98311bb
 # ╠═8a37f5bd-75b3-435e-9a17-615977321b33
 # ╠═85f64587-79aa-423a-809e-5dcd22d25837
 # ╠═60019633-dc6f-4078-9601-c141df4b46c1
 # ╠═bb6c87a4-8d3c-462a-bef3-8f15c84281a0
-# ╠═6175d2f3-2a41-4d8c-afaa-d3836e986e41
-# ╠═6048db65-70b9-4936-954a-87b2db57e5b1
+# ╠═52746088-57f6-46d7-b8da-8d1988622f75
 # ╠═d7157f73-a8b5-43bf-b888-ed4fc20d50ed
 # ╠═9e3a937b-fb32-45da-8a74-c4dc0e76f4bd
 # ╠═79921671-272f-4a50-a5e7-0b05d236689f
@@ -129,3 +149,5 @@ heatmap(hs, Ts, M; xlabel="h", ylabel="T")
 # ╠═e8395949-5f7b-40f9-bb70-2c2719489b79
 # ╠═fb067387-529d-4849-8d4f-da4943f0c939
 # ╠═18237a59-3057-4a72-9dbe-c22fcc26b568
+# ╠═36db7a3d-1bb8-4e13-b278-78d428d32f43
+# ╠═50db1938-1fdc-4fff-80f1-bab842a2338c

scripts/resample.toml

@@ -0,0 +1,32 @@
+parent = "de20d208-d0c5-11ed-0e75-eb6afa48009a"
+njobs = 1
+walltime = "1-00:00:00"
+
+[shape]
+ndims = 4
+size = 4
+p = 3
+
+[storage]
+path = "data"
+tags = []
+
+[sample]
+nrepeat = 10
+nthrows = 10
+nsamples = 100000
+observables = ["E", "E^2", "M", "M^2", "accept_rate"]
+
+    [sample.option]
+    nburns = 5000
+    order = "random"
+
+[fields]
+stop = 0.8
+step = 0.01
+start = 0.8
+
+[temperatures]
+stop = 0.05
+step = -0.1
+start = 2.0

src/mc/obs.jl

@@ -11,7 +11,7 @@ end
 
 collect!(::Observable{T}, ::MarkovChain) where T = error("Observable $(T) not implemented")
 
-function finalize!(ob::Observable, ::MarkovChain, nsamples::Int)
+function finalize!(ob::Observable, mc::MarkovChain, nsamples::Int)
     ob.value /= nsamples
     ob.final = true
     return ob

test/Project.toml

@@ -8,3 +8,4 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"

test/mc/status.jl

@@ -30,3 +30,10 @@ end # testset
         @test new_E - old_E == delta_E
     end
 end # testset
+
+cm = CellMap(4, 2, (2, 3))
+energy(cm, trues(nspins(cm)), 0.1)
+energy(cm, trues(nspins(cm)), 0.2)
+energy(cm, trues(nspins(cm)), 0.3)
+energy(cm, trues(nspins(cm)), 0.4)
+energy(cm, trues(nspins(cm)), 0.5)