diff --git a/DEVELOPER_NOTES.md b/DEVELOPER_NOTES.md index 72c899b..8be83de 100644 --- a/DEVELOPER_NOTES.md +++ b/DEVELOPER_NOTES.md @@ -27,9 +27,9 @@ generated won't run properly. ## Generating the notebooks -To generate notebooks do `include("path/to/HelloJulia/src/generate_all.jl")`. For some tutorials, a notebook -may not be generated, because of some known issue. A warning will be issued and you'll -need to generate the relevant notebook by hand. +To generate notebooks do `> julia HelloJulia/src/generate_all.jl`. For some tutorials, a +notebook may not be generated, because of some known issue. A warning will be issued and +you'll need to generate the relevant notebook by hand. For example, to generate an executed python notebook for `notebooks/01_first_steps/`, copy `notebook.unexecuted.ipynb` to `notebook.ipynb`; execute the latter file and save. diff --git a/Manifest.toml b/Manifest.toml index 0664ef6..42cd762 100644 --- a/Manifest.toml +++ b/Manifest.toml @@ -2,7 +2,7 @@ julia_version = "1.10.3" manifest_format = "2.0" -project_hash = "2edfe41f97de8e611b2e9ed77953e997d683e955" +project_hash = "216dfc3d9c6ec25313c025bc5f5c0b55962d1f00" [[deps.ARFFFiles]] deps = ["CategoricalArrays", "Dates", "Parsers", "Tables"] @@ -414,12 +414,6 @@ git-tree-sha1 = "bfc1187b79289637fa0ef6d4436ebdfe6905cbd6" uuid = "e2d170a0-9d28-54be-80f0-106bbe20a464" version = "1.0.0" -[[deps.DataValues]] -deps = ["DataValueInterfaces", "Dates"] -git-tree-sha1 = "d88a19299eba280a6d062e135a43f00323ae70bf" -uuid = "e7dc6d0d-1eca-5fa6-8ad6-5aecde8b7ea5" -version = "0.4.13" - [[deps.Dates]] deps = ["Printf"] uuid = "ade2ca70-3891-5945-98fb-dc099432e06a" @@ -519,18 +513,6 @@ git-tree-sha1 = "98fdf08b707aaf69f524a6cd0a67858cefe0cfb6" uuid = "792122b4-ca99-40de-a6bc-6742525f08b6" version = "0.3.0" -[[deps.Electron]] -deps = ["Base64", "FilePaths", "JSON", "Pkg", "Sockets", "URIParser", "UUIDs"] -git-tree-sha1 = "a53025d3eabe23659065b3c5bba7b4ffb1327aa0" -uuid = "a1bb12fb-d4d1-54b4-b10a-ee7951ef7ad3" -version = "3.1.2" - -[[deps.ElectronDisplay]] -deps = ["Base64", "Electron", "FilePaths", "IteratorInterfaceExtensions", "JSON", "Markdown", "TableShowUtils", "TableTraits"] -git-tree-sha1 = "714865b8d0ec66d90283acc737da9e534307f5e6" -uuid = "d872a56f-244b-5cc9-b574-2017b5b909a8" -version = "1.0.1" - [[deps.EnumX]] git-tree-sha1 = "bdb1942cd4c45e3c678fd11569d5cccd80976237" uuid = "4e289a0a-7415-4d19-859d-a7e5c4648b56" @@ -1990,12 +1972,6 @@ deps = ["Dates"] uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76" version = "1.0.3" -[[deps.TableShowUtils]] -deps = ["DataValues", "Dates", "JSON", "Markdown", "Unicode"] -git-tree-sha1 = "2a41a3dedda21ed1184a47caab56ed9304e9a038" -uuid = "5e66a065-1f0a-5976-b372-e0b8c017ca10" -version = "0.2.6" - [[deps.TableTraits]] deps = ["IteratorInterfaceExtensions"] git-tree-sha1 = "c06b2f539df1c6efa794486abfb6ed2022561a39" @@ -2074,12 +2050,6 @@ git-tree-sha1 = "4d4ed7f294cda19382ff7de4c137d24d16adc89b" uuid = "981d1d27-644d-49a2-9326-4793e63143c3" version = "0.1.0" -[[deps.URIParser]] -deps = ["Unicode"] -git-tree-sha1 = "53a9f49546b8d2dd2e688d216421d050c9a31d0d" -uuid = "30578b45-9adc-5946-b283-645ec420af67" -version = "0.4.1" - [[deps.URIs]] git-tree-sha1 = "67db6cc7b3821e19ebe75791a9dd19c9b1188f2b" uuid = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4" diff --git a/Project.toml b/Project.toml index 59e77e3..64e3898 100644 --- a/Project.toml +++ b/Project.toml @@ -9,7 +9,6 @@ CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0" Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f" -ElectronDisplay = "d872a56f-244b-5cc9-b574-2017b5b909a8" IJulia = "7073ff75-c697-5162-941a-fcdaad2a7d2a" MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7" Measurements = "eff96d63-e80a-5855-80a2-b1b0885c5ab7" diff --git a/notebooks/01_first_steps/my_first_plot.png b/notebooks/01_first_steps/my_first_plot.png index a782bbe..151a563 100644 Binary files a/notebooks/01_first_steps/my_first_plot.png and b/notebooks/01_first_steps/my_first_plot.png differ diff --git a/notebooks/01_first_steps/notebook.ipynb b/notebooks/01_first_steps/notebook.ipynb index 4eb9bc0..ac0eda8 100644 --- a/notebooks/01_first_steps/notebook.ipynb +++ b/notebooks/01_first_steps/notebook.ipynb @@ -1212,7 +1212,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "0.5373161485486371" + "text/plain": "0.12823221151675346" }, "metadata": {}, "execution_count": 50 @@ -1230,7 +1230,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "3×4 Matrix{Float64}:\n 0.156884 0.965893 0.822031 0.175844\n 0.263368 0.389618 0.341254 0.288944\n 0.545627 0.789382 0.801309 0.207644" + "text/plain": "3×4 Matrix{Float64}:\n 0.767869 0.33608 0.355736 0.504577\n 0.287555 0.0272392 0.0125789 0.0329924\n 0.932469 0.619542 0.793721 0.129464" }, "metadata": {}, "execution_count": 51 @@ -1248,7 +1248,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "3×4 Matrix{Float64}:\n 0.779817 -0.519889 0.534122 -1.55778\n 0.0072398 1.49424 -0.0276442 -2.16914\n 1.15712 1.28477 -0.260504 0.594076" + "text/plain": "3×4 Matrix{Float64}:\n -0.750847 -0.337114 -0.66027 -0.121947\n 0.233333 0.570418 0.0371203 -0.185875\n 0.546442 -1.50898 -0.472898 -1.65925" }, "metadata": {}, "execution_count": 52 @@ -1266,7 +1266,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "-80" + "text/plain": "111" }, "metadata": {}, "execution_count": 53 @@ -1284,7 +1284,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "10-element Vector{Char}:\n 'c': ASCII/Unicode U+0063 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'c': ASCII/Unicode U+0063 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'c': ASCII/Unicode U+0063 (category Ll: Letter, lowercase)\n 'a': ASCII/Unicode U+0061 (category Ll: Letter, lowercase)" + "text/plain": "10-element Vector{Char}:\n 'c': ASCII/Unicode U+0063 (category Ll: Letter, lowercase)\n 'a': ASCII/Unicode U+0061 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'a': ASCII/Unicode U+0061 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'c': ASCII/Unicode U+0063 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)\n 'a': ASCII/Unicode U+0061 (category Ll: Letter, lowercase)\n 'b': ASCII/Unicode U+0062 (category Ll: Letter, lowercase)" }, "metadata": {}, "execution_count": 54 @@ -1318,7 +1318,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "\"ttub5SwnG2VXA0UMwjkc0XRvMxHKn5\"" + "text/plain": "\"hdgbEJkwYzk7cvYzC0TZgoB6IhRjBr\"" }, "metadata": {}, "execution_count": 56 @@ -1345,7 +1345,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "0.39534950422987486" + "text/plain": "0.43411148096562874" }, "metadata": {}, "execution_count": 58 @@ -1364,7 +1364,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "0.6192953665657467" + "text/plain": "0.6842032464186547" }, "metadata": {}, "execution_count": 59 @@ -1410,7 +1410,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "Distributions.Gamma{Float64}(α=0.5148824829610816, θ=2.0240393033364423)" + "text/plain": "Distributions.Gamma{Float64}(α=0.5180049365433226, θ=1.9516255137766076)" }, "metadata": {}, "execution_count": 61 @@ -1428,7 +1428,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "1.0421423821126854" + "text/plain": "1.010951650420181" }, "metadata": {}, "execution_count": 62 @@ -1446,7 +1446,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "0.4863847498413582" + "text/plain": "0.47426857396897515" }, "metadata": {}, "execution_count": 63 @@ -1464,7 +1464,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "0.2464039067819249" + "text/plain": "0.24744673997102484" }, "metadata": {}, "execution_count": 64 @@ -1513,8 +1513,7 @@ "outputs": [], "cell_type": "code", "source": [ - "using CairoMakie\n", - "CairoMakie.activate!(type = \"png\")" + "using CairoMakie" ], "metadata": {}, "execution_count": 67 @@ -1525,9 +1524,9 @@ "output_type": "execute_result", "data": { "text/plain": "Figure()", - "image/png": 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", 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", "text/html": [ - "" + "" ] }, "metadata": {}, diff --git a/notebooks/01_first_steps/notebook.jl b/notebooks/01_first_steps/notebook.jl index 6c5a536..3053a0a 100644 --- a/notebooks/01_first_steps/notebook.jl +++ b/notebooks/01_first_steps/notebook.jl @@ -350,9 +350,7 @@ using PkgOnlineHelp # ## Plotting -using ElectronDisplay #src using CairoMakie -CairoMakie.activate!(type = "png") #- diff --git a/notebooks/01_first_steps/notebook.pluto.jl b/notebooks/01_first_steps/notebook.pluto.jl index 6bfdffb..666926a 100644 --- a/notebooks/01_first_steps/notebook.pluto.jl +++ b/notebooks/01_first_steps/notebook.pluto.jl @@ -414,11 +414,8 @@ md"Uncomment and execute the next line to launch Distribution documentation in y # ╔═╡ 2a96dfa7-cf5a-4e7f-8704-dbab8e09b4f1 md"## Plotting" -# ╔═╡ 912dc07c-b98e-45fb-a02f-27b6c05e4d02 -begin - using CairoMakie - CairoMakie.activate!(type = "png") -end +# ╔═╡ abf0bff8-2645-4597-a02f-27b6c05e4d02 +using CairoMakie # ╔═╡ 8c61ce1f-4ef7-47c9-bea4-3d467d48781c begin @@ -472,7 +469,7 @@ md"The following shows that named tuples share some behaviour with dictionaries: # ╔═╡ cb2c42bf-21b5-4e04-9727-ed822e4fd85d begin - t = (x = 1, y = "cat", z = 4.5 + t = (x = 1, y = "cat", z = 4.5) keys(t) end @@ -606,7 +603,7 @@ md""" # ╟─60aef579-9404-4272-8f78-ab549ef1544e # ╠═a35c0fe8-afc4-4eaf-a8a4-a53f5149481e # ╟─2a96dfa7-cf5a-4e7f-8704-dbab8e09b4f1 -# ╠═912dc07c-b98e-45fb-a02f-27b6c05e4d02 +# ╠═abf0bff8-2645-4597-a02f-27b6c05e4d02 # ╠═8c61ce1f-4ef7-47c9-bea4-3d467d48781c # ╠═bf64e629-d0bc-4e89-97c5-2979af8a507d # ╟─a7f061b8-d1ed-4b1f-b639-63c76c72c513 diff --git a/notebooks/01_first_steps/notebook.unexecuted.ipynb b/notebooks/01_first_steps/notebook.unexecuted.ipynb index 1f5e51b..2638b4a 100644 --- a/notebooks/01_first_steps/notebook.unexecuted.ipynb +++ b/notebooks/01_first_steps/notebook.unexecuted.ipynb @@ -964,8 +964,7 @@ "outputs": [], "cell_type": "code", "source": [ - "using CairoMakie\n", - "CairoMakie.activate!(type = \"png\")" + "using CairoMakie" ], "metadata": {}, "execution_count": null diff --git a/notebooks/03_machine_learning/notebook.ipynb b/notebooks/03_machine_learning/notebook.ipynb index b172be3..025d018 100644 --- a/notebooks/03_machine_learning/notebook.ipynb +++ b/notebooks/03_machine_learning/notebook.ipynb @@ -524,7 +524,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "untrained Machine; caches model-specific representations of data\n model: FillImputer(features = Symbol[], …)\n args: \n 1:\tSource @296 ⏎ ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Count}, AbstractVector{ScientificTypesBase.Multiclass{3}}, AbstractVector{ScientificTypesBase.Textual}, AbstractVector{Union{Missing, ScientificTypesBase.Multiclass{3}}}, AbstractVector{ScientificTypesBase.Multiclass{2}}}}\n" + "text/plain": "untrained Machine; caches model-specific representations of data\n model: FillImputer(features = Symbol[], …)\n args: \n 1:\tSource @090 ⏎ ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Count}, AbstractVector{ScientificTypesBase.Multiclass{3}}, AbstractVector{ScientificTypesBase.Textual}, AbstractVector{Union{Missing, ScientificTypesBase.Multiclass{3}}}, AbstractVector{ScientificTypesBase.Multiclass{2}}}}\n" }, "metadata": {}, "execution_count": 18 @@ -838,7 +838,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "untrained Machine; caches model-specific representations of data\n model: DecisionTreeClassifier(max_depth = 0, …)\n args: \n 1:\tSource @201 ⏎ ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Count}, AbstractVector{ScientificTypesBase.Multiclass{2}}, AbstractVector{ScientificTypesBase.Multiclass{3}}, AbstractVector{ScientificTypesBase.Textual}}}\n 2:\tSource @746 ⏎ AbstractVector{ScientificTypesBase.Multiclass{2}}\n" + "text/plain": "untrained Machine; caches model-specific representations of data\n model: DecisionTreeClassifier(max_depth = 0, …)\n args: \n 1:\tSource @126 ⏎ ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Count}, AbstractVector{ScientificTypesBase.Multiclass{2}}, AbstractVector{ScientificTypesBase.Multiclass{3}}, AbstractVector{ScientificTypesBase.Textual}}}\n 2:\tSource @872 ⏎ AbstractVector{ScientificTypesBase.Multiclass{2}}\n" }, "metadata": {}, "execution_count": 29 @@ -870,7 +870,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "trained Machine; caches model-specific representations of data\n model: DecisionTreeClassifier(max_depth = 0, …)\n args: \n 1:\tSource @201 ⏎ ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Count}, AbstractVector{ScientificTypesBase.Multiclass{2}}, AbstractVector{ScientificTypesBase.Multiclass{3}}, AbstractVector{ScientificTypesBase.Textual}}}\n 2:\tSource @746 ⏎ AbstractVector{ScientificTypesBase.Multiclass{2}}\n" + "text/plain": "trained Machine; caches model-specific representations of data\n model: DecisionTreeClassifier(max_depth = 0, …)\n args: \n 1:\tSource @126 ⏎ ScientificTypesBase.Table{Union{AbstractVector{ScientificTypesBase.Continuous}, AbstractVector{ScientificTypesBase.Count}, AbstractVector{ScientificTypesBase.Multiclass{2}}, AbstractVector{ScientificTypesBase.Multiclass{3}}, AbstractVector{ScientificTypesBase.Textual}}}\n 2:\tSource @872 ⏎ AbstractVector{ScientificTypesBase.Multiclass{2}}\n" }, "metadata": {}, "execution_count": 30 diff --git a/notebooks/99_solutions_to_exercises/notebook.ipynb b/notebooks/99_solutions_to_exercises/notebook.ipynb index 18a1962..4315efc 100644 --- a/notebooks/99_solutions_to_exercises/notebook.ipynb +++ b/notebooks/99_solutions_to_exercises/notebook.ipynb @@ -142,14 +142,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "mu = 0.04613526193186938\n", - "var = 1.8731469207202927\n" + "mu = 0.008482224153903957\n", + "var = 2.128483561088485\n" ] }, { "output_type": "execute_result", "data": { - "text/plain": "1.8731469207202927" + "text/plain": "2.128483561088485" }, "metadata": {}, "execution_count": 4 @@ -178,112 +178,9 @@ "output_type": "execute_result", "data": { "text/plain": "Figure()", - "image/png": 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", + "text/html": [ + "" ] }, "metadata": {}, @@ -299,7 +196,6 @@ "ys = f.(xs);\n", "\n", "using CairoMakie\n", - "CairoMakie.activate!(type = \"svg\")\n", "\n", "fig = hist(samples, normalization=:pdf)\n", "lines!(xs, ys)\n", diff --git a/notebooks/99_solutions_to_exercises/notebook.jl b/notebooks/99_solutions_to_exercises/notebook.jl index 176f835..b3735fb 100644 --- a/notebooks/99_solutions_to_exercises/notebook.jl +++ b/notebooks/99_solutions_to_exercises/notebook.jl @@ -62,8 +62,6 @@ xs = -5:(0.1):5 ys = f.(xs); using CairoMakie -using ElectronDisplay #src -CairoMakie.activate!(type = "svg") #nb fig = hist(samples, normalization=:pdf) lines!(xs, ys) diff --git a/notebooks/99_solutions_to_exercises/notebook.pluto.jl b/notebooks/99_solutions_to_exercises/notebook.pluto.jl index a4c01b0..a3e9d27 100644 --- a/notebooks/99_solutions_to_exercises/notebook.pluto.jl +++ b/notebooks/99_solutions_to_exercises/notebook.pluto.jl @@ -75,7 +75,7 @@ begin @show mu var end -# ╔═╡ f5122507-66bb-49ea-a0de-1721c1bc2df2 +# ╔═╡ 8130ea17-aa57-4733-a0de-1721c1bc2df2 begin d = Normal(0, sqrt(2)) f(x) = pdf(d, x) @@ -84,7 +84,6 @@ begin ys = f.(xs); using CairoMakie - CairoMakie.activate!(type = "svg") fig = hist(samples, normalization=:pdf) lines!(xs, ys) @@ -155,7 +154,7 @@ md""" # ╟─860bb453-c2f1-446d-8d7e-8e449afd1c48 # ╟─cd6e9fce-e54a-48c3-a949-7f3bd292fe31 # ╠═2da628f3-c301-4e4d-8514-99938a2932db -# ╠═f5122507-66bb-49ea-a0de-1721c1bc2df2 +# ╠═8130ea17-aa57-4733-a0de-1721c1bc2df2 # ╟─4f939d4a-e802-4b7d-bca8-7eec7950fd82 # ╟─63f410ea-c37a-4761-9873-1b1430e635cc # ╠═cb2c42bf-21b5-4e04-b43e-d0ebe87da176 diff --git a/notebooks/99_solutions_to_exercises/notebook.unexecuted.ipynb b/notebooks/99_solutions_to_exercises/notebook.unexecuted.ipynb index 8f0be67..29f2898 100644 --- a/notebooks/99_solutions_to_exercises/notebook.unexecuted.ipynb +++ b/notebooks/99_solutions_to_exercises/notebook.unexecuted.ipynb @@ -140,7 +140,6 @@ "ys = f.(xs);\n", "\n", "using CairoMakie\n", - "CairoMakie.activate!(type = \"svg\")\n", "\n", "fig = hist(samples, normalization=:pdf)\n", "lines!(xs, ys)\n", diff --git a/notebooks/mandelbrot/notebook.ipynb b/notebooks/mandelbrot/notebook.ipynb index ea68f24..a5f5222 100644 --- a/notebooks/mandelbrot/notebook.ipynb +++ b/notebooks/mandelbrot/notebook.ipynb @@ -106,7 +106,7 @@ "name": "stdout", "output_type": "stream", "text": [ - " 0.009891 seconds (5.28 k allocations: 332.234 KiB, 98.28% compilation time)\n" + " 0.011320 seconds (5.28 k allocations: 332.234 KiB, 98.37% compilation time)\n" ] }, { @@ -149,7 +149,7 @@ "name": "stdout", "output_type": "stream", "text": [ - " 0.000145 seconds (43 allocations: 2.109 KiB)\n" + " 0.000189 seconds (43 allocations: 2.109 KiB)\n" ] }, { @@ -190,7 +190,7 @@ "name": "stdout", "output_type": "stream", "text": [ - " 0.035204 seconds (26.63 k allocations: 1.729 MiB, 99.02% compilation time)\n" + " 0.038862 seconds (26.63 k allocations: 1.729 MiB, 99.03% compilation time)\n" ] }, { diff --git a/notebooks/secret_sauce/notebook.ipynb b/notebooks/secret_sauce/notebook.ipynb index cb84916..c4ceeb7 100644 --- a/notebooks/secret_sauce/notebook.ipynb +++ b/notebooks/secret_sauce/notebook.ipynb @@ -92,7 +92,7 @@ "name": "stdout", "output_type": "stream", "text": [ - " 0.003674 seconds (537 allocations: 37.133 KiB, 95.45% compilation time)\n" + " 0.003671 seconds (537 allocations: 37.133 KiB, 95.27% compilation time)\n" ] }, { @@ -135,7 +135,7 @@ "name": "stdout", "output_type": "stream", "text": [ - " 0.000151 seconds (43 allocations: 2.156 KiB)\n" + " 0.000152 seconds (43 allocations: 2.156 KiB)\n" ] }, { @@ -206,7 +206,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "3-element Vector{Float64}:\n 0.7431637368576477\n 0.030701177164791704\n 0.15852663813312062" + "text/plain": "3-element Vector{Float64}:\n 0.6203553053582552\n 0.6122479425520462\n 0.7573644719199655" }, "metadata": {}, "execution_count": 6 @@ -226,13 +226,13 @@ "name": "stdout", "output_type": "stream", "text": [ - " 0.002530 seconds (432 allocations: 29.953 KiB, 94.16% compilation time)\n" + " 0.003196 seconds (432 allocations: 29.953 KiB, 94.61% compilation time)\n" ] }, { "output_type": "execute_result", "data": { - "text/plain": "3-element Vector{Float64}:\n 0.8314233209161767\n 0.9282456668245344\n 0.36794638988610495" + "text/plain": "3-element Vector{Float64}:\n 0.9647031650112521\n 0.6214013313566943\n 1.0831088350498796" }, "metadata": {}, "execution_count": 7 @@ -258,13 +258,13 @@ "name": "stdout", "output_type": "stream", "text": [ - " 0.000123 seconds (44 allocations: 2.234 KiB)\n" + " 0.000139 seconds (44 allocations: 2.234 KiB)\n" ] }, { "output_type": "execute_result", "data": { - "text/plain": "3-element Vector{Float64}:\n 0.8314233209161767\n 0.9282456668245344\n 0.36794638988610495" + "text/plain": "3-element Vector{Float64}:\n 0.9647031650112521\n 0.6214013313566943\n 1.0831088350498796" }, "metadata": {}, "execution_count": 8 @@ -715,7 +715,7 @@ { "output_type": "execute_result", "data": { - "text/plain": "2×3 Matrix{Float64}:\n 4.0 4.0 4.0\n 4.0 5.0 5.0" + "text/plain": "2×3 Matrix{Float64}:\n 4.0 5.0 5.0\n 4.0 5.0 5.0" }, "metadata": {}, "execution_count": 26