Name changes in the R example files (outside of the package)

examples/datamart/createModelOverview.sh

@@ -3,12 +3,12 @@
 # Run an R notebook on the given inputfile with just the model data. This
 # example shows how to run the notebook when there is no predictor data.
 
-# Location of the GIT checkout of the CDH tools
-cdhtools="~/Documents/pega/cdh-datascientist-tools"
-modeloverviewnotebook="$cdhtools/examples/datamart/healthcheck.Rmd"
+# Location of the GIT checkout of the Pega Data Scientist tools
+pdstools="~/Documents/pega/pega-datascientist-tools"
+modeloverviewnotebook="$pdstools/examples/datamart/healthcheck.Rmd"
 
 # Predictor data. This can be a CSV or any other of the supported formats.
-source="$cdhtools/data/pr_data_dm_admmart_mdl_fact.csv"
+source="$pdstools/data/pr_data_dm_admmart_mdl_fact.csv"
 
 # Generated file
 output="`pwd`/DMSample\ Adaptive\ Models\ Overview.html"

examples/datamart/createModelReport.sh

@@ -2,12 +2,12 @@
 
 # Run an R notebook on the given inputfile with predictor binning data
 
-# Location of the GIT checkout of the CDH tools
-cdhtools="~/Documents/pega/cdh-datascientist-tools"
-modelreportnotebook="$cdhtools/examples/datamart/modelreport.Rmd"
+# Location of the GIT checkout of the Pega Data Scientist tools
+pdstools="~/Documents/pega/pega-datascientist-tools"
+modelreportnotebook="$pdstools/examples/datamart/modelreport.Rmd"
 
 # Predictor data. This can be a CSV or any other of the supported formats.
-source="$cdhtools/data/pr_data_dm_admmart_pred.csv"
+source="$pdstools/data/pr_data_dm_admmart_pred.csv"
 
 # Model ID to use
 modelid="277a2c48-8888-5b71-911e-443d52c9b50f"

examples/datamart/healthcheck.Rmd

@@ -1,7 +1,7 @@
 ---
 title: "`r params$title`"
 subtitle: "`r params$subtitle`"
-author: "Pega CDH Tools"
+author: "Pega"
 date: "`r Sys.Date()`"
 output:
   html_document:
@@ -59,7 +59,7 @@ params:
 library(pdstools)
 
 # include below when developing the library
-# sapply(list.files("~/Documents/pega/cdh-datascientist-tools/r/R", "*.R", full.names = T), source)
+# sapply(list.files("~/Documents/pega/pega-datascientist-tools/r/R", "*.R", full.names = T), source)
 
 library(data.table)
 library(lubridate)
@@ -82,10 +82,10 @@ knitr::opts_chunk$set(
 # ADM Datamart Health Check
 
 This document gives a generic and global overview of the Adaptive models 
-and predictors. It is generated from an R notebook in the [CDH Tools](https://github.com/pegasystems/cdh-datascientist-tools). That repository
+and predictors. It is generated from an R notebook in the [Pega Data Scientist Tools](https://github.com/pegasystems/pega-datascientist-tools). That repository
 of tools and scripts also contains a notebook to generate stand-alone
 model reports for individual models, please refer 
-to the [Wiki](https://github.com/pegasystems/cdh-datascientist-tools/wiki).
+to the [Wiki](https://github.com/pegasystems/pega-datascientist-tools/wiki).
 
 This document provides a first-level scan of the models after which a 
 deeper and more customer specific deeper dive can be done.
@@ -306,7 +306,7 @@ plt <- plotPerformanceSuccessRateBubbleChart(datamart,
                                              filter = function(mdls)
                                              { 
                                                m <- filterLatestSnapshotOnly(mdls)[ResponseCount >= 100] 
-                                               m[, OhMyGoodness := (cdhtools::auc2GINI(Performance) + pmin(Positives, as.integer(params$min_positives_for_maturity)) * (1.0/as.integer(params$min_positives_for_maturity)))/2]
+                                               m[, OhMyGoodness := (pdstools::auc2GINI(Performance) + pmin(Positives, as.integer(params$min_positives_for_maturity)) * (1.0/as.integer(params$min_positives_for_maturity)))/2]
                                                return(m)
                                              }, 
                                              facets = c("ConfigurationName", "Direction", "Channel"),

examples/datamart/modelreport.Rmd

@@ -1,7 +1,7 @@
 ---
 title: "`r params$title`"
 subtitle: "`r params$modeldescription`"
-author: "Pega CDH Tools"
+author: "Pega"
 date: "`r Sys.Date()`"
 output:
   html_document:
@@ -38,7 +38,7 @@ params:
 library(pdstools)
 
 # include below when developing the library
-# sapply(list.files("~/Documents/pega/cdh-datascientist-tools/r/R", "*.R", full.names = T), source)
+# sapply(list.files("~/Documents/pega/pega-datascientist-tools/r/R", "*.R", full.names = T), source)
 
 library(data.table)
 library(lubridate)

examples/datamart/offlinereports.sh

@@ -1,8 +1,8 @@
 #!/bin/bash
 
-# Location of the GIT checkout of the CDH tools
+# Location of the GIT checkout of the Pega Data Scientist tools
 
-cdhtools="~/Documents/pega/cdh-datascientist-tools"
+pdstools="~/Documents/pega/pega-datascientist-tools"
 
 # Location of the input data
 
@@ -17,8 +17,8 @@ modellist="cdhsample-modellist.txt"
 
 # Location of the notebooks (unless copied/modified these defaults should be fine)
 
-modeloverviewnotebook="$cdhtools/examples/datamart/healthcheck.Rmd"
-modelreportnotebook="$cdhtools/examples/datamart/modelreport.Rmd"
+modeloverviewnotebook="$pdstools/examples/datamart/healthcheck.Rmd"
+modelreportnotebook="$pdstools/examples/datamart/modelreport.Rmd"
 
 # Run the model overview notebook
 

examples/datamart/predictionsAndPredictiveModels.Rmd

@@ -6,10 +6,10 @@ output:
 ---
 
 ```{r, echo=F, warning=F, error=F, include=FALSE}
-library(cdhtools)
+library(pdstools)
 
 # include below when developing the library
-# sapply(list.files("~/Documents/pega/cdh-datascientist-tools/r/R", "*.R", full.names = T), source)
+# sapply(list.files("~/Documents/pega/pega-datascientist-tools/r/R", "*.R", full.names = T), source)
 
 library(data.table)
 library(lubridate)
@@ -26,7 +26,7 @@ theme_set(theme_light())
 
 See https://docs.pega.com/decision-management-reference-materials/database-tables-monitoring-models and https://techdocs.rpega.com/x/nYjM.
 
-Recommended approach to export them is described in https://github.com/pegasystems/cdh-datascientist-tools/wiki/How-to-export-and-use-the-ADM-Datamart
+Recommended approach to export them is described in https://github.com/pegasystems/pega-datascientist-tools/wiki/How-to-export-and-use-the-ADM-Datamart
 
 Internal doc on the tables: https://techdocs.rpega.com/x/cYD2Ag
 
@@ -59,7 +59,7 @@ Notifications are stored in
 
 ```{r}
 dmSnapshots <- readDSExport("Data-DM-Snapshot_pyGetSnapshot", "../../data")
-dmSnapshots[, pySnapShotTime := cdhtools::fromPRPCDateTime(pySnapShotTime)]
+dmSnapshots[, pySnapShotTime := pdstools::fromPRPCDateTime(pySnapShotTime)]
 dmSnapshots[, pyValue := as.numeric(pyValue)]
 
 dmSnapshots %>% head() %>% kable() %>% kable_paper(bootstrap_options = "striped")
@@ -72,7 +72,7 @@ Binary distribution
 
 ```{r}
 dmBinaryDistribution <- readDSExport("Data-DM-BinaryDistribution_pyGetBinaryDistribution", "../../data")
-dmBinaryDistribution[, pySnapShotTime := cdhtools::fromPRPCDateTime(pySnapShotTime)]
+dmBinaryDistribution[, pySnapShotTime := pdstools::fromPRPCDateTime(pySnapShotTime)]
 
 dmBinaryDistribution %>% head() %>% kable() %>% kable_paper(bootstrap_options = "striped")
 ```
@@ -105,7 +105,7 @@ calculate the metrics shown to the user in Prediction Studio. Once the metric ha
 
 ```{r}
 dmSummary <- readDSExport("Data-DM-Summary_pyGetSummaries", "../../data")
-dmSummary[, pySnapShotTime := cdhtools::fromPRPCDateTime(pySnapShotTime)]
+dmSummary[, pySnapShotTime := pdstools::fromPRPCDateTime(pySnapShotTime)]
 
 dmSummary %>% head() %>% kable() %>% kable_paper(bootstrap_options = "striped")
 ```