From d53283cfad5b7001e161f6c762f82bca4a19edac Mon Sep 17 00:00:00 2001 From: paulgovan Date: Sun, 3 Dec 2017 07:14:36 -0600 Subject: [PATCH] Update tests --- inst/bn/figure/unnamed-chunk-8-1.png | Bin 8909 -> 8965 bytes inst/bn/tests/mytest-expected/001.png | Bin 74919 -> 78183 bytes inst/bn/tests/mytest-expected/002.png | Bin 73785 -> 73898 bytes inst/bn/tests/mytest-expected/003.json | 322 ++++++++++++++++++++++-- inst/bn/tests/mytest-expected/003.png | Bin 69320 -> 77935 bytes inst/bn/tests/mytest-expected/004.json | 324 +++++++++++++++++++++++-- inst/bn/tests/mytest-expected/004.png | Bin 53835 -> 57358 bytes inst/bn/tests/mytest-expected/005.json | 221 ----------------- inst/bn/tests/mytest-expected/005.png | Bin 49596 -> 0 bytes inst/bn/tests/mytest.R | 22 +- inst/bn/ui.R | 5 +- 11 files changed, 617 insertions(+), 277 deletions(-) delete mode 100644 inst/bn/tests/mytest-expected/005.json delete mode 100644 inst/bn/tests/mytest-expected/005.png diff --git 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"CVP", "file": null, "homeIntro": 0, "inferenceIntro": 0, "iss": 10, "measuresIntro": 0, "met": "bayes", - "net": "1", - "Node": "B", + "net": "3", + "Node": "PCWP", "nodeMeasure": "mb", - "nodeNames": "A", + "nodeNames": "CVP", "param": "dotplot", "parametersIntro": 0, "rmd": "## Sample Code\nHere is some sample markdown to help illustrate the editor.\n\n### Get some sample data and show the first few values\n### Use `dat()` to get the active data set\n```{r}\ndat <- learning.test\nhead(dat)\n```\n\n### Learn the structure of the network\n```{r}\ndag <- bnlearn::cextend(bnlearn::gs(dat))\n```\n\n### Plot the force directed network\n```{r}\nnetworkData <- data.frame(bnlearn::arcs(dag))\n\nnetworkD3::simpleNetwork(\n networkData,\n Source = \"from\",\n Target = \"to\"\n)\n```\n\n### Print the network score\n```{r}\nbnlearn::score(dag, dat)\n```\n\n### Fit the model parameters and show the CPT for node A\n```{r}\nfit <- bnlearn::bn.fit(dag, dat)\nfit$A\n```\n\n### Plot the model parameters for node A\n```{r}\nbnlearn::bn.fit.barchart(fit[[\"A\"]])\n```\n\n### Get the Markov blanket for node A\n```{r}\nbnlearn::mb(dag, \"A\")\n```\n\n### Plot a d3 heatmap of the adjacency matrix\n```{r}\nheatmaply::heatmaply(\n bnlearn::amat(dag),\n grid_gap = 1,\n colors = blues9,\n dendrogram = \"both\",\n symm = TRUE,\n margins = c(100, 100, NA, 0),\n hide_colorbar = TRUE\n)\n````\n\n### Generate some random data from the network and show the first few values\n```{r}\nset.seed(1)\nsimData <- bnlearn::rbn(fit, n = 100, dat)\nhead(simData)\n```\n\n```{r}\n# Put your own code here...\n", @@ -49,7 +49,7 @@ ] }, "condPlot": { - "src": "[image data sha1: 5403a00b234137d6e112d1e70d43e2cb6e67a22a]", + "src": "[image data sha1: 38409767041e523d99b55352024c9df9863dbfe9]", "width": 458, "height": 400, "coordmap": [ @@ -77,7 +77,7 @@ ] }, "distPlot": { - "src": "[image data sha1: 7959b96e06062b55c369e3fa319f0ec042da0682]", + "src": "[image data sha1: ce0a6633c3cf11ec0b51d5764a8adc194fd69b48]", "width": 458, "height": 400, "coordmap": [ @@ -108,20 +108,164 @@ "x": { "links": { "source": [ + 24, + 11, + 31, + 31, + 4, + 13, + 13, + 23, + 28, + 10, + 26, + 26, + 21, + 21, + 21, + 21, + 19, + 19, + 19, + 25, + 17, + 17, + 17, + 17, + 6, + 20, + 20, + 20, + 30, + 30, + 3, + 3, + 3, + 9, + 12, + 12, + 12, + 12, + 8, + 8, + 29, + 27, 0, - 0, - 1, - 2, - 5 + 32, + 32, + 32, + 32, + 32, + 33, + 33, + 35, + 35, + 34 ], "target": [ + 20, + 19, + 2, 1, - 3, + 2, + 9, + 12, + 25, + 31, + 27, + 18, + 35, + 17, + 32, + 33, + 35, + 24, + 20, + 30, + 29, + 26, + 29, + 33, + 35, + 34, + 5, + 16, + 30, + 4, + 16, + 31, + 21, + 0, + 12, 4, + 14, + 15, 3, - 4 + 14, + 15, + 28, + 28, + 7, + 26, + 17, + 27, + 0, + 33, + 7, + 18, + 6, + 34, + 22 ], "value": [ + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, 1, 1, 1, @@ -129,6 +273,54 @@ 1 ], "colour": [ + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", + "#666", "#666", "#666", "#666", @@ -138,14 +330,74 @@ }, "nodes": { "name": [ - "A", - "B", - "C", - "D", - "E", - "F" + "ACO2", + "APL", + "BP", + "CCHL", + "CO", + "CVP", + "DISC", + "ECO2", + "ERCA", + "ERLO", + "FIO2", + "HIST", + "HR", + "HRBP", + "HREK", + "HRSA", + "HYP", + "INT", + "KINK", + "LVF", + "LVV", + "MINV", + "MVS", + "PAP", + "PCWP", + "PMB", + "PRSS", + "PVS", + "SAO2", + "SHNT", + "STKV", + "TPR", + "VALV", + "VLNG", + "VMCH", + "VTUB" ], "group": [ + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + 1, 1, 1, 1, @@ -154,6 +406,36 @@ 1 ], "nodesize": [ + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, + 8, 8, 8, 8, @@ -212,7 +494,7 @@ } ] }, - "score": "-23873.13" + "score": "-218149.6" }, "export": { diff --git a/inst/bn/tests/mytest-expected/004.png b/inst/bn/tests/mytest-expected/004.png index 85737279aa5aaed88b6a0565dce5ac84701ec3e6..ffaecec2cedf01a8d4e2249e1b9654751b8b502d 100644 GIT binary patch delta 41522 zcmce8WmH^kvn2!%!9#Ee9^8Uk65Im>cXxMaI3&2cTY`q*5Zv7%NN{W1-E|J{JKwtZ z&it8QbJj{=b)P={NIko%cI{#?7cR05uH0M*@QNC(e|+M3tQ&G6;5V!iF&!%8H8$6y zdEe{*ayj>1fFtAU460ZPB_;1TC*F;C<^1;*L!%XyU$m4)0*8j=H|LT zK*@dkN06kv{N{v$@W%PhMAPkVQCC;jpIW|WxBq+vM1s&ApdAPeZbu^lsCboe>x_Sk)V5|SjP5Vz z?Y?Q-o7#u>tqrjW6 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\n
\n

5<\/h3>\n

Arcs<\/p>\n <\/div>\n

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ShinyDriver$new("../", seed = 123) app$snapshotInit("mytest") -Sys.sleep(1) app$snapshot() -Sys.sleep(3) +Sys.sleep(2) app$setInputs(sidebarMenu = "structure") -Sys.sleep(5) +Sys.sleep(4) app$snapshot() +app$setInputs(net = "3") app$setInputs(alg = "hc") app$setInputs(type = "aic") app$setInputs(sidebarMenu = "parameters") @@ -14,22 +14,20 @@ Sys.sleep(1) app$snapshot() app$setInputs(met = "bayes") app$setInputs(param = "dotplot") -app$setInputs(Node = "B") +app$setInputs(Node = "PCWP") app$setInputs(sidebarMenu = "inference") Sys.sleep(1) app$snapshot() -app$setInputs(evidenceNode = "B") -app$setInputs(evidence = "a") -app$setInputs(event = "C") +app$setInputs(evidenceNode = "PCWP") +app$setInputs(evidence = "HIGH") +app$setInputs(event = "HIST") app$setInputs(sidebarMenu = "measures") -Sys.sleep(1) -app$snapshot() app$setInputs(nodeMeasure = "nbr") -app$setInputs(nodeNames = "B") +app$setInputs(nodeMeasure = "parents") +app$setInputs(nodeNames = "PCWP") app$setInputs(dendrogram = "row") app$setInputs(sidebarMenu = "editor") app$setInputs(bookmark = "click") app$setInputs(sidebarMenu = "structure") -app$setInputs(net = "3") app$setInputs(dataInput = "2") app$uploadFile(file = "learning_test.csv") diff --git a/inst/bn/ui.R b/inst/bn/ui.R index e970ea7..b33a588 100644 --- a/inst/bn/ui.R +++ b/inst/bn/ui.R @@ -563,11 +563,10 @@ shinydashboard::dashboardPage( title = "Adjacency Matrix", status = "success", collapsible = TRUE, - width = 8 - # , + width = 8, # d3 heatmap - # plotly::plotlyOutput("netTable") + plotly::plotlyOutput("netTable") ) ),