Prepare for CRAN v0.2.6 Release

* Replaced `if()` conditions comparing `class()` to string with `inherits()` * Added `future::plan(future::multisession)` in tests to remove the files in temp directory * Updated maintainer contact information
machiela-lab · Dec 1, 2022 · 92cda75 · 92cda75
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diff --git a/.gitignore b/.gitignore
@@ -45,3 +45,6 @@ rsconnect/
 
 # Sandboxes
 inst/doc
+
+# CRAN
+CRAN-SUBMISSION
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,17 +1,17 @@
 Package: sparrpowR
 Title: Power Analysis to Detect Spatial Relative Risk Clusters
-Version: 0.2.5
-Date: 2022-02-04
+Version: 0.2.6
+Date: 2022-12-01
 Authors@R:
     c(person(given = "Ian D.",
              family = "Buller",
              role = c("aut", "cre", "cph"),
-             email = "ian.buller@nih.gov",
+             email = "ian.buller@alumni.emory.edu",
              comment = c(ORCID = "0000-0001-9477-8582")),
       person(given = "Derek W.",
              family = "Brown",
              role = c("aut", "cph"),
-             email = "[email protected]",
+             email = "[email protected]",
              comment = c(ORCID = "0000-0001-8393-1713")),
       person(given = "Mitchell J.",
              family = "Machiela",
@@ -24,18 +24,18 @@ Authors@R:
              email = "[email protected]"),
       person(given = "NCI",
              role = c("cph", "fnd")))
-Maintainer: Ian D. Buller <ian.buller@nih.gov>
+Maintainer: Ian D. Buller <ian.buller@alumni.emory.edu>
 Description: Calculate the statistical power to detect clusters using kernel-based 
         spatial relative risk functions that are estimated using the 'sparr' package.
         Details about the 'sparr' package methods can be found in the tutorial: Davies
-        et al. (2018) <doi:10.1002/sim.7577>.  Details about kernel density estimation 
-        can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>.  More 
+        et al. (2018) <doi:10.1002/sim.7577>. Details about kernel density estimation 
+        can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>. More 
         information about relative risk functions using kernel density estimation can 
         be found in J. F. Bithell (1991) <doi:10.1002/sim.4780101112>.
 License: Apache License (>= 2.0)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.1
 Depends: 
     R (>= 3.5.0),
 Imports: 

diff --git a/NEWS.md b/NEWS.md
@@ -1,5 +1,10 @@
 # sparrpowR (development version)
 
+# sparrpowR v0.2.6
+* Replaced `if()` conditions comparing `class()` to string with `inherits()`
+* Added `future::plan(future::multisession)` in tests to remove the files in temp directory
+* Updated maintainer contact information
+
 # sparrpowR v0.2.5
 * Updated dependencies `spatstat.core` and `spatstat.linnet` packages based on feedback from the Spatstat Team (Adrian Baddeley and Ege Rubak). All random generators in `spatstat.core` were moved to a new package `spatstat.random`
   * `spatstat.geom`, `spatstat.core`, `spatstat.linnet`, and `spatstat (>=2.0-0)` are no longer Depends.

diff --git a/R/jitter_power.R b/R/jitter_power.R
@@ -5,7 +5,7 @@
 #' @param obs_data A bivariate point pattern (a multitype point pattern of object of class "ppp") with two types of points in a factor valued mark.
 #' @param sim_total Integer, specifying the number of simulation iterations to perform.
 #' @param samp_control Character string specifying whether to randomize the control locations uniformly (\code{samp_control="uniform"}), with complete spatial randomness (\code{samp_control="CSR"}), or multivariate normal (\code{samp_control="MVN"}).
-#' @param s_control Optional. Numeric value for the standard deviation of the multivariate normal distribution in the units of the \code{obs_data}.  The default value (1) assumes a unit square window. Ignored if Ignored if \code{samp_control="uniform"} or \code{samp_control="CSR"}.
+#' @param s_control Optional. Numeric value for the standard deviation of the multivariate normal distribution in the units of the \code{obs_data}. The default value (1) assumes a unit square window. Ignored if Ignored if \code{samp_control="uniform"} or \code{samp_control="CSR"}.
 #' @param alpha Optional. Numeric value of the critical p-value (default=0.05).
 #' @param p_correct Optional. Character string specifying whether to apply a correction for multiple comparisons including a False Discovery Rate \code{p_correct = "FDR"}, a Sidak correction \code{p_correct = "uncorrelated Sidak"}, and a Bonferroni correction \code{p_correct = "uncorrelated Bonferroni"}. If \code{p_correct = "none"} (the default), then no correction is applied. 
 #' @param parallel Logical. If TRUE, will execute the function in parallel. If FALSE (the default), will not execute the function in parallel.
@@ -97,7 +97,7 @@ jitter_power <- function(obs_data,
   }
 
   # Input
-  if (class(obs_data) != "ppp"){
+  if (!inherits(obs_data, "ppp")) {
     stop("Argument 'obs_data' must be of class 'ppp'")
   }
 

diff --git a/R/package.R b/R/package.R
@@ -2,7 +2,7 @@
 #'
 #' Computes the statistical power for the spatial relative risk function.
 #'
-#' @details For a two-group comparison (e.g., cases v. controls) the 'sparrpowR' package calculates the statistical power to detect clusters using the kernel-based spatial relative risk function that is estimated using the 'sparr' package. Details about the 'sparr' package methods can be found in the tutorial: Davies et al. (2018) \doi{10.1002/sim.7577}.  Details about kernel density estimation can be found in J. F. Bithell (1990) \doi{10.1002/sim.4780090616}.  More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) \doi{10.1002/sim.4780101112}.
+#' @details For a two-group comparison (e.g., cases v. controls) the 'sparrpowR' package calculates the statistical power to detect clusters using the kernel-based spatial relative risk function that is estimated using the 'sparr' package. Details about the 'sparr' package methods can be found in the tutorial: Davies et al. (2018) \doi{10.1002/sim.7577}. Details about kernel density estimation can be found in J. F. Bithell (1990) \doi{10.1002/sim.4780090616}. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) \doi{10.1002/sim.4780101112}.
 #' 
 #' This package provides a function to compute the statistical power for the spatial relative risk function with various theoretical spatial sampling strategies. The 'sparrpowR' package also provides a function to compute the statistical power for the spatial relative risk function for scenarios where one group (e.g., cases) have been observed and a theoretical sampling strategy for the second group (e.g., controls) is desired. The 'sparrpowR' package also provides visualization of data and statistical power.
 #' 
@@ -31,7 +31,7 @@
 #' @author Ian D. Buller\cr \emph{Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.} \cr\cr
 #' Derek W. Brown\cr \emph{Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.}
 #' 
-#' Maintainer: I.D.B. \email{ian.buller@@nih.gov}
+#' Maintainer: I.D.B. \email{ian.buller@@alumni.emory.edu.gov}
 #'
 #' @keywords package
 NULL

diff --git a/R/spatial_data.R b/R/spatial_data.R
@@ -15,7 +15,7 @@
 #' @param y_control Numeric value, or numeric vector, of y-coordinate(s) of case cluster(s). Ignored if \code{samp_control != "MVN"}.
 #' @param r_case Optional. Numeric value, or numeric vector, of radius (radii) of case cluster(s) in the units of \code{win}. Ignored if \code{samp_case = "MVN"}.
 #' @param r_control Optional. Numeric value, or numeric vector, of radius (radii) of control cluster(s) in the units of \code{win}. Ignored if \code{samp_control != "clustered"}.
-#' @param s_case Optional. Numeric value, or numeric vector, for the standard deviation(s) of the multivariate normal distribution for case locations in the units of \code{win}.  Ignored if \code{samp_control != "MVN"}.
+#' @param s_case Optional. Numeric value, or numeric vector, for the standard deviation(s) of the multivariate normal distribution for case locations in the units of \code{win}. Ignored if \code{samp_control != "MVN"}.
 #' @param s_control Optional. Numeric value, or numeric vector, for the standard deviation(s) of the multivariate normal distribution for control locations in the units of \code{win}. Ignored if \code{samp_control != "MVN"}.
 #' @param l_case Optional. A single positive number, a vector of positive numbers, a function(x,y, ...), or a pixel image. Intensity of the Poisson process for case clusters. Ignored if \code{samp_control != "IPP"}.
 #' @param l_control Optional. A single positive number, a vector of positive numbers, a function(x,y, ...), or a pixel image. Intensity of the Poisson process for control clusters. Ignored if \code{samp_control = "uniform"}, \code{samp_control = "systematic"}, \code{samp_control = "MVN"}, or \code{samp_control = "CSR"}.
@@ -158,7 +158,7 @@ spatial_data <- function(win = spatstat.geom::unit.square(),
     }
 
     if (samp_case == "IPP"){
-      if (class(lamb) != "function") {
+      if (!inherits(lamb, "function")) {
         stop("The argument 'l_case' should be an intensity function")
       }
       win_case <- spatstat.geom::disc(radius = rad, centre = c(0.5, 0.5), ...)
@@ -194,7 +194,7 @@ spatial_data <- function(win = spatstat.geom::unit.square(),
     }
 
     if (samp_control == "IPP") {
-      if (class(lamb) != "function") {
+      if (!inherits(lamb, "function")) {
         stop("The argument 'l_control' should be an intensity function")
       }
       x <- spatstat.random::rpoispp(lambda = lamb, win = wind, ...)

diff --git a/R/spatial_power.R b/R/spatial_power.R
@@ -217,7 +217,7 @@ spatial_power <- function(win = spatstat.geom::unit.square(),
      }
 
     if (samp_case == "IPP") {
-      if (class(lamb) != "function") {
+      if (!inherits(lamb, "function")) {
         stop("The argument 'l_case' should be an intensity function")
        }
       win_case <- spatstat.geom::disc(radius = rad, centre = c(0.5, 0.5), ...)
@@ -253,7 +253,7 @@ spatial_power <- function(win = spatstat.geom::unit.square(),
      }
 
     if (samp_control == "IPP") {
-      if (class(lamb) != "function") {
+      if (!inherits(lamb, "function")) {
         stop("The argument 'l_control' should be an intensity function")
       }
       x <- spatstat.random::rpoispp(lambda = lamb, win = win, ...)

diff --git a/README.md b/README.md
@@ -7,10 +7,10 @@ sparrpowR: Power analysis to detect spatial relative clusters <img src="man/figu
 [![CRAN RStudio mirror downloads](https://cranlogs.r-pkg.org/badges/grand-total/sparrpowR?color=blue)](https://r-pkg.org/pkg/sparrpowR)
 [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
 ![GitHub last commit](https://img.shields.io/github/last-commit/machiela-lab/sparrpowR)
-[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5347998.svg)](https://doi.org/10.5281/zenodo.5347998)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5347997.svg)](https://doi.org/10.5281/zenodo.5347997)
 <!-- badges: end -->
 
-**Date repository last updated**: August 08, 2022
+**Date repository last updated**: December 01, 2022
 
 <h2 id="overview">
 
@@ -202,4 +202,4 @@ When citing this package for publication, please follow:
 
 ### Questions? Feedback?
 
-For questions about the package please contact the maintainer [Dr. Ian D. Buller](mailto:ian.buller@nih.gov) or [submit a new issue](https://github.com/machiela-lab/sparrpowR/issues).
+For questions about the package please contact the maintainer [Dr. Ian D. Buller](mailto:ian.buller@alumni.emory.edu) or [submit a new issue](https://github.com/machiela-lab/sparrpowR/issues).
diff --git a/cran-comments.md b/cran-comments.md
@@ -1,17 +1,14 @@
-## This is the ninth resubmission
+## This is the tenth resubmission
 
 * Actions taken since previous submission:
-  * Updated dependencies `spatstat.core` and `spatstat.linnet` packages based on feedback from the Spatstat Team (Adrian Baddeley and Ege Rubak). All random generators in `spatstat.core` were moved to a new package `spatstat.random`
-    * `spatstat.geom`, `spatstat.core`, `spatstat.linnet`, and `spatstat (>=2.0-0)` are no longer Depends
-    * `spatstat.geom` and `spatstat.random` are now Imports
-    * `spatstat.data` is now Suggests
-    * [See the GitHub merge pull request](https://github.com/machiela-lab/sparrpowR/commit/4df5d85343dd222c9d4b1ae30f894ed6482bcb52)
-  * Fixed annotation typos in the `pval_correct()` function
+  * Replaced `if()` conditions comparing `class()` to string with `inherits()`
+  * Added `future::plan(future::multisession)` in tests to remove the files in temp directory
+  * Updated maintainer contact information
 
 * Documentation for `pval_correct()` references a doi <https://doi.org/10.2307/2283989> that throws a NOTE but is a valid URL
 
 ## Test environments
-* local OS X install, R 4.1.2
+* local OS X install, R 4.2.1
 * win-builder, (devel, release, oldrelease)
 * Rhub
   * Fedora Linux, R-devel, clang, gfortran

diff --git a/man/jitter_power.Rd b/man/jitter_power.Rd
diff --git a/man/sparrpowR-package.Rd b/man/sparrpowR-package.Rd
diff --git a/man/spatial_data.Rd b/man/spatial_data.Rd
diff --git a/tests/testthat.R b/tests/testthat.R
@@ -7,3 +7,4 @@ library(sparrpowR)
 options(parallelly.makeNodePSOCK.setup_strategy = "sequential")
 
 test_check("sparrpowR")
+future::plan(future::sequential)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -7,3 +7,4 @@ library(sparrpowR)
		options(parallelly.makeNodePSOCK.setup_strategy = "sequential")

		test_check("sparrpowR")
		future::plan(future::sequential)