CRAN Package Check Results for Package gestalt

Last updated on 2019-03-27 00:47:56 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.6 2.16 30.89 33.05 ERROR
r-devel-linux-x86_64-debian-gcc 0.1.6 2.37 24.90 27.27 OK
r-devel-linux-x86_64-fedora-clang 0.1.6 43.13 OK
r-devel-linux-x86_64-fedora-gcc 0.1.6 39.09 OK
r-devel-windows-ix86+x86_64 0.1.6 7.00 45.00 52.00 OK
r-patched-linux-x86_64 0.1.6 2.08 30.05 32.13 OK
r-patched-solaris-x86 0.1.6 58.70 OK
r-release-linux-x86_64 0.1.6 2.23 29.50 31.73 OK
r-release-windows-ix86+x86_64 0.1.6 5.00 55.00 60.00 OK
r-release-osx-x86_64 0.1.6 OK
r-oldrel-windows-ix86+x86_64 0.1.6 4.00 43.00 47.00 OK
r-oldrel-osx-x86_64 0.1.6 OK

Check Details

Version: 0.1.6
Check: whether package can be installed
Result: WARN
    Found the following significant warnings:
     Warning: unable to re-encode 'compose.R' lines 63, 68, 71, 82, 94, 98, 106, 109, 114, 115, 127, 138, 154, 163, 164, 172, 178, 181, 202, 224, 232, 237, 263, 275, 289, 290, 371, 372, 375, 376
     Warning: unable to re-encode 'constant.R' lines 14, 106
     Warning: unable to re-encode 'partial.R' lines 9, 16, 22, 25
     Warning: unable to re-encode 'fn.R' lines 87, 95, 96, 98, 99, 104, 109, 120, 160, 181, 188, 212, 277
     Warning: unable to re-encode 'context.R' lines 6, 8, 56, 60, 94, 101, 102, 122, 131, 132
     Warning: unable to re-encode 'posure.R' lines 20, 33, 48, 49
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.1.6
Check: for unstated dependencies in examples
Result: WARN
    Warning in parse(file = files, n = -1L) :
     invalid input found on input connection 'gestalt-Ex.R'
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.1.6
Check: examples
Result: ERROR
    Running examples in 'gestalt-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: constant
    > ### Title: Values as Functions
    > ### Aliases: constant variable
    >
    > ### ** Examples
    >
    > # Function with a constant return value
    > val <- {message("Computing from scratch"); mtcars} %>>>%
    + split(.$cyl) %>>>%
    + lapply(function(data) lm(mpg ~ wt, data)) %>>>%
    + lapply(summary) %>>>%
    + sapply(`[[`, "r.squared")
    >
    > # With every invocation, `val()` is computed anew:
    > val()
    Computing from scratch
     4 6 8
    0.5086326 0.4645102 0.4229655
    > val()
    Computing from scratch
     4 6 8
    0.5086326 0.4645102 0.4229655
    >
    > # Declaring `val` as a constant ensures that its value is computed only once.
    > # On subsequent calls, the computed value is simply fetched:
    > const <- constant(val)
    > const()
    Computing from scratch
     4 6 8
    0.5086326 0.4645102 0.4229655
    > const()
     4 6 8
    0.5086326 0.4645102 0.4229655
    >
    > # As values, `val()` and `const()` are identical. But `const()`, moreover,
    > # has structure, namely the function `const`:
    > const
    Constant Function:
    <Function Composition>
    In order of application:
    
    [[1]]
     function (..., . = ..1)
     {
     message("Computing from scratch")
     mtcars
     }
     <environment: 0x3ac85f8>
    
    [[2]]
     function (..., . = ..1)
     split(., .$cyl)
     <environment: 0x3ac85f8>
    
    [[3]]
     function (..., . = ..1)
     lapply(., function(data) lm(mpg ~ wt, data))
     <environment: 0x3ac5118>
    
    [[4]]
     function (..., . = ..1)
     lapply(., summary)
     <environment: 0x3abe768>
    
    [[5]]
     function (..., . = ..1)
     sapply(., `[[`, "r.squared")
     <bytecode: 0x40222c8>
    
    Recover the list of functions with 'as.list()'.
    >
    > # For instance, you can inspect the intermediate summaries:
    > head(const, -1)()
    Computing from scratch
    $`4`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Min 1Q Median 3Q Max
    -4.1513 -1.9795 -0.6272 1.9299 5.2523
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 39.571 4.347 9.104 7.77e-06 ***
    wt -5.647 1.850 -3.052 0.0137 *
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 3.332 on 9 degrees of freedom
    Multiple R-squared: 0.5086, Adjusted R-squared: 0.454
    F-statistic: 9.316 on 1 and 9 DF, p-value: 0.01374
    
    
    $`6`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Mazda RX4 Mazda RX4 Wag Hornet 4 Drive Valiant Merc 280
     -0.1250 0.5840 1.9292 -0.6897 0.3547
     Merc 280C Ferrari Dino
     -1.0453 -1.0080
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 28.409 4.184 6.789 0.00105 **
    wt -2.780 1.335 -2.083 0.09176 .
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 1.165 on 5 degrees of freedom
    Multiple R-squared: 0.4645, Adjusted R-squared: 0.3574
    F-statistic: 4.337 on 1 and 5 DF, p-value: 0.09176
    
    
    $`8`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Min 1Q Median 3Q Max
    -2.1491 -1.4664 -0.8458 1.5711 3.7619
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 23.8680 3.0055 7.942 4.05e-06 ***
    wt -2.1924 0.7392 -2.966 0.0118 *
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 2.024 on 12 degrees of freedom
    Multiple R-squared: 0.423, Adjusted R-squared: 0.3749
    F-statistic: 8.796 on 1 and 12 DF, p-value: 0.01179
    
    
    >
    > # Which can itself be a constant:
    > summ <- constant(head(const, -1))
    > summ()
    Computing from scratch
    $`4`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Min 1Q Median 3Q Max
    -4.1513 -1.9795 -0.6272 1.9299 5.2523
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 39.571 4.347 9.104 7.77e-06 ***
    wt -5.647 1.850 -3.052 0.0137 *
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 3.332 on 9 degrees of freedom
    Multiple R-squared: 0.5086, Adjusted R-squared: 0.454
    F-statistic: 9.316 on 1 and 9 DF, p-value: 0.01374
    
    
    $`6`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Mazda RX4 Mazda RX4 Wag Hornet 4 Drive Valiant Merc 280
     -0.1250 0.5840 1.9292 -0.6897 0.3547
     Merc 280C Ferrari Dino
     -1.0453 -1.0080
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 28.409 4.184 6.789 0.00105 **
    wt -2.780 1.335 -2.083 0.09176 .
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 1.165 on 5 degrees of freedom
    Multiple R-squared: 0.4645, Adjusted R-squared: 0.3574
    F-statistic: 4.337 on 1 and 5 DF, p-value: 0.09176
    
    
    $`8`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Min 1Q Median 3Q Max
    -2.1491 -1.4664 -0.8458 1.5711 3.7619
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 23.8680 3.0055 7.942 4.05e-06 ***
    wt -2.1924 0.7392 -2.966 0.0118 *
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 2.024 on 12 degrees of freedom
    Multiple R-squared: 0.423, Adjusted R-squared: 0.3749
    F-statistic: 8.796 on 1 and 12 DF, p-value: 0.01179
    
    
    > summ()
    $`4`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Min 1Q Median 3Q Max
    -4.1513 -1.9795 -0.6272 1.9299 5.2523
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 39.571 4.347 9.104 7.77e-06 ***
    wt -5.647 1.850 -3.052 0.0137 *
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 3.332 on 9 degrees of freedom
    Multiple R-squared: 0.5086, Adjusted R-squared: 0.454
    F-statistic: 9.316 on 1 and 9 DF, p-value: 0.01374
    
    
    $`6`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Mazda RX4 Mazda RX4 Wag Hornet 4 Drive Valiant Merc 280
     -0.1250 0.5840 1.9292 -0.6897 0.3547
     Merc 280C Ferrari Dino
     -1.0453 -1.0080
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 28.409 4.184 6.789 0.00105 **
    wt -2.780 1.335 -2.083 0.09176 .
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 1.165 on 5 degrees of freedom
    Multiple R-squared: 0.4645, Adjusted R-squared: 0.3574
    F-statistic: 4.337 on 1 and 5 DF, p-value: 0.09176
    
    
    $`8`
    
    Call:
    lm(formula = mpg ~ wt, data = data)
    
    Residuals:
     Min 1Q Median 3Q Max
    -2.1491 -1.4664 -0.8458 1.5711 3.7619
    
    Coefficients:
     Estimate Std. Error t value Pr(>|t|)
    (Intercept) 23.8680 3.0055 7.942 4.05e-06 ***
    wt -2.1924 0.7392 -2.966 0.0118 *
    ---
    Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    
    Residual standard error: 2.024 on 12 degrees of freedom
    Multiple R-squared: 0.423, Adjusted R-squared: 0.3749
    F-statistic: 8.796 on 1 and 12 DF, p-value: 0.01179
    
    
    >
    > ## Not run:
    > ##D # Think of `%>>>%` combined with `constant()` as a lazy, structured
    > ##D # alternative to the magrittr `%>%` operator.
    > ##D library(magrittr)
    > ##D
    > ##D val2 <- mtcars %>%
    > ##D split(.$cyl) %>%
    > ##D lapply(function(data) lm(mpg ~ wt, data)) %>%
    > ##D lapply(summary) %>%
    > ##D sapply(`[[`, "r.squared")
    > ##D
    > ##D # `val2` and `const()` are identical values. But whereas `val2` is computed
    > ##D # immediately and carries no structure, `const` embodies the process that
    > ##D # produces its value, and allows you to defer its realization to the
    > ##D # invocation `const()`.
    > ##D stopifnot(identical(val2, const()))
    > ## End(Not run)
    >
    > <ERROR: re-encoding failure from encoding 'UTF-8'>
    # Use `variable()` to recover the original (+ val_var <- variable(const)
    > stopifnot(identical(val_var, val))
    Error in identical(val_var, val) : object 'val_var' not found
    Calls: stopifnot -> identical
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang