Showing 13 of 44 files from the diff.

@@ -12,12 +12,13 @@
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12 12
#    See the License for the specific language governing permissions and
13 13
#    limitations under the License.
14 14
15 -
#' Autoplot fitdist
15 +
#' Autoplot 
16 16
#'
17 17
#' Plots the cumulative distribution function (cdf) using the ggplot2
18 18
#' generic.
19 19
#'
20 20
#' @inheritParams params
21 +
#' @seealso [ggplot2::autoplot()] and [ssd_plot_cdf()] 
21 22
#' @export
22 23
#' @examples
23 24
#' ggplot2::autoplot(boron_lnorm)
@@ -26,8 +27,7 @@
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26 27
  ssd_plot_cdf(object)
27 28
}
28 29
29 -
#' @describeIn autoplot.fitdist Autoplot fitdists
30 -
#'
30 +
#' @rdname autoplot.fitdist
31 31
#' @export
32 32
#' @examples
33 33
#' ggplot2::autoplot(boron_dists)
@@ -36,7 +36,7 @@
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36 36
  ssd_plot_cdf(object)
37 37
}
38 38
39 -
#' @describeIn autoplot.fitdist Autoplot fitdistcens
39 +
#' @rdname autoplot.fitdist 
40 40
#' @export
41 41
#' @examples
42 42
#' fluazinam_lnorm$censdata$right[3] <- fluazinam_lnorm$censdata$left[3] * 1.5
@@ -45,4 +45,4 @@
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45 45
autoplot.fitdistcens <- function(object, ...) {
46 46
  chk_unused(...)
47 47
  ssd_plot_cdf(object)
48 -
}
48 +
}

@@ -28,7 +28,7 @@
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28 28
#' dburrIII3 gives the density, pburrIII3 gives the distribution function,
29 29
#' qburrIII3 gives the quantile function, and rburrIII3 generates random samples.
30 30
#' @name burrIII3
31 -
#' @seealso [actuar::dburr()]
31 +
#' @seealso [actuar::dburr()] 
32 32
#' @examples
33 33
#' x <- rburrIII3(1000)
34 34
#' hist(x, freq = FALSE, col = "gray", border = "white")
@@ -58,7 +58,7 @@
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58 58
  if(!length(q)) return(numeric(0))
59 59
  if(log.p) p <- exp(p)
60 60
  q <- suppressWarnings(actuar::qburr(1-p, shape1=exp(lshape1), shape2=exp(lshape2), scale=exp(lscale), 
61 -
                     lower.tail=lower.tail))
61 +
                                      lower.tail=lower.tail))
62 62
  1/q
63 63
}
64 64

@@ -44,7 +44,7 @@
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44 44
#' @export
45 45
qlgumbel <- function(p, locationlog = 0, scalelog = 1, lower.tail = TRUE, log.p = FALSE) {
46 46
  qdist("gumbel", p = p,  location = locationlog, scale = scalelog,
47 -
          lower.tail = lower.tail, log.p = log.p, .lgt = TRUE)
47 +
        lower.tail = lower.tail, log.p = log.p, .lgt = TRUE)
48 48
}
49 49
50 50
#' @rdname lgumbel

@@ -17,7 +17,7 @@
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  grob
18 18
}
19 19
20 -
#' Base ggproto classes for ggplot2
20 +
#' Base ggproto Classes for ggplot2
21 21
#'
22 22
#' @seealso [ggplot2::ggplot2-ggproto()]
23 23
#' @name ssdtools-ggproto
@@ -81,14 +81,14 @@
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81 81
    start$x <- 0.0001
82 82
    end <- data
83 83
    end$y <- -Inf
84 -
84 +
    
85 85
    data <- rbind(start, data, end)
86 86
    GeomPath$draw_panel(data, panel_params, coord)
87 87
  },
88 -
88 +
  
89 89
  default_aes = aes(colour = "black", size = 0.5, linetype = "dotted", alpha = NA),
90 90
  required_aes = c("xintercept", "yintercept"),
91 -
91 +
  
92 92
  draw_key = draw_key_path
93 93
)
94 94
@@ -102,35 +102,35 @@
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    colour = NA, fill = "grey20", size = 0.5, linetype = 1,
103 103
    alpha = NA
104 104
  ),
105 -
105 +
  
106 106
  required_aes = c("y", "xmin", "xmax"),
107 -
107 +
  
108 108
  draw_key = draw_key_polygon,
109 -
109 +
  
110 110
  handle_na = function(data, params) {
111 111
    data
112 112
  },
113 -
113 +
  
114 114
  draw_group = function(data, panel_params, coord, na.rm = FALSE) {
115 115
    if (na.rm) data <- data[stats::complete.cases(data[c("y", "xmin", "xmax")]), ]
116 116
    data <- data[order(data$group, data$y), ]
117 -
117 +
    
118 118
    # Check that aesthetics are constant
119 119
    aes <- unique(data[c("colour", "fill", "size", "linetype", "alpha")])
120 120
    if (nrow(aes) > 1) {
121 121
      err("Aesthetics can not vary with a ribbon.")
122 122
    }
123 123
    aes <- as.list(aes)
124 -
124 +
    
125 125
    missing_pos <- !stats::complete.cases(data[c("y", "xmin", "xmax")])
126 126
    ids <- cumsum(missing_pos) + 1
127 127
    ids[missing_pos] <- NA
128 -
128 +
    
129 129
    positions <- plyr::summarise(data,
130 -
      y = c(y, rev(y)), x = c(xmax, rev(xmin)), id = c(ids, rev(ids))
130 +
                                 y = c(y, rev(y)), x = c(xmax, rev(xmin)), id = c(ids, rev(ids))
131 131
    )
132 132
    munched <- coord_munch(coord, positions, panel_params)
133 -
133 +
    
134 134
    ggname("geom_ribbon", grid::polygonGrob(
135 135
      munched$x, munched$y,
136 136
      id = munched$id,

@@ -12,9 +12,11 @@
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12 12
#    See the License for the specific language governing permissions and
13 13
#    limitations under the License.
14 14
15 -
#' Predict fitdist
15 +
#' Predict 
16 16
#'
17 17
#' @inheritParams params
18 +
#' @seealso [stats::predict()]
19 +
#' @family predict
18 20
#' @export
19 21
#' @examples
20 22
#' predict(boron_lnorm, percent = c(5L, 50L))
@@ -22,22 +24,18 @@
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22 24
                            nboot = 1000, parallel = NULL, ncpus = 1,
23 25
                            ...) {
24 26
  chk_unused(...)
25 -
  if (missing(ci)) {
26 -
    deprecate_soft("0.1.0", "ssdtools::predict(ci = )",
27 -
      details = "In particular, the `ci` has been switched from TRUE to FALSE. To retain the previous behaviour of calculating confidence intervals set `ci = TRUE`.",
28 -
      id = "predict"
29 -
    )
27 +
  if(missing(ci)) {
28 +
    deprecate_soft("0.1.0", "ssdtools::predict(ci = )", details = "In particular, the `ci` has been switched from TRUE to FALSE. To retain the previous behaviour of calculating confidence intervals set `ci = TRUE`.", 
29 +
                   id = "predict")
30 30
  }
31 -
31 +
  
32 32
  ssd_hc(object,
33 -
    percent = percent, ci = ci, level = level,
34 -
    nboot = nboot, parallel = parallel, ncpus = ncpus
33 +
         percent = percent, ci = ci, level = level,
34 +
         nboot = nboot, parallel = parallel, ncpus = ncpus
35 35
  )
36 36
}
37 37
38 -
#' Predict censored fitdist
39 -
#'
40 -
#' @inheritParams params
38 +
#' @rdname predict.fitdist
41 39
#' @export
42 40
#' @examples
43 41
#' predict(fluazinam_lnorm, percent = c(5L, 50L))
@@ -45,21 +43,17 @@
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45 43
                                nboot = 1000, parallel = NULL, ncpus = 1,
46 44
                                ...) {
47 45
  chk_unused(...)
48 -
  if (missing(ci)) {
49 -
    deprecate_soft("0.1.0", "ssdtools::predict(ci = )",
50 -
      details = "In particular, the `ci` has been switched from TRUE to FALSE. To retain the previous behaviour of calculating confidence intervals set `ci = TRUE`.",
51 -
      id = "predict"
52 -
    )
46 +
  if(missing(ci)) {
47 +
    deprecate_soft("0.1.0", "ssdtools::predict(ci = )", details = "In particular, the `ci` has been switched from TRUE to FALSE. To retain the previous behaviour of calculating confidence intervals set `ci = TRUE`.", 
48 +
                   id = "predict")
53 49
  }
54 50
  ssd_hc(object,
55 -
    percent = percent, ci = ci, level = level,
56 -
    nboot = nboot, parallel = parallel, ncpus = ncpus
51 +
         percent = percent, ci = ci, level = level,
52 +
         nboot = nboot, parallel = parallel, ncpus = ncpus
57 53
  )
58 54
}
59 55
60 -
#' Predict fitdists
61 -
#'
62 -
#' @inheritParams params
56 +
#' @rdname predict.fitdist 
63 57
#' @export
64 58
#' @examples
65 59
#' predict(boron_dists)
@@ -68,22 +62,18 @@
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68 62
                             average = TRUE, ic = "aicc",
69 63
                             ...) {
70 64
  chk_unused(...)
71 -
  if (missing(ci)) {
72 -
    deprecate_soft("0.1.0", "ssdtools::predict(ci = )",
73 -
      details = "In particular, the `ci` has been switched from TRUE to FALSE. To retain the previous behaviour of calculating confidence intervals set `ci = TRUE`.",
74 -
      id = "predict"
75 -
    )
65 +
  if(missing(ci)) {
66 +
    deprecate_soft("0.1.0", "ssdtools::predict(ci = )", details = "In particular, the `ci` has been switched from TRUE to FALSE. To retain the previous behaviour of calculating confidence intervals set `ci = TRUE`.", 
67 +
                   id = "predict")
76 68
  }
77 69
  ssd_hc(object,
78 -
    percent = percent, ci = ci, level = level,
79 -
    nboot = nboot, parallel = parallel, ncpus = ncpus,
80 -
    average = average, ic = ic
70 +
         percent = percent, ci = ci, level = level,
71 +
         nboot = nboot, parallel = parallel, ncpus = ncpus,
72 +
         average = average, ic = ic
81 73
  )
82 74
}
83 75
84 -
#' Predict censored fitdists
85 -
#'
86 -
#' @inheritParams params
76 +
#' @rdname predict.fitdist 
87 77
#' @export
88 78
#' @examples
89 79
#' predict(fluazinam_dists)
@@ -91,15 +81,13 @@
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91 81
                                 level = 0.95, nboot = 1000, parallel = NULL, ncpus = 1,
92 82
                                 average = TRUE, ic = "aic", ...) {
93 83
  chk_unused(...)
94 -
  if (missing(ci)) {
95 -
    deprecate_soft("0.1.0", "ssdtools::predict(ci = )",
96 -
      details = "In particular, the `ci` has been switched from TRUE to FALSE. To retain the previous behaviour of calculating confidence intervals set `ci = TRUE`.",
97 -
      id = "predict"
98 -
    )
84 +
  if(missing(ci)) {
85 +
    deprecate_soft("0.1.0", "ssdtools::predict(ci = )", details = "In particular, the `ci` has been switched from TRUE to FALSE. To retain the previous behaviour of calculating confidence intervals set `ci = TRUE`.", 
86 +
                   id = "predict")
99 87
  }
100 88
  ssd_hc(object,
101 -
    percent = percent, ci = ci, level = level,
102 -
    nboot = nboot, parallel = parallel, ncpus = ncpus,
103 -
    average = average, ic = ic
89 +
         percent = percent, ci = ci, level = level,
90 +
         nboot = nboot, parallel = parallel, ncpus = ncpus,
91 +
         average = average, ic = ic
104 92
  )
105 93
}

@@ -1,6 +1,7 @@
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1 1
2 -
#' Get the Number of Parameters
2 +
#' Number of Parameters
3 3
#'
4 +
#' Get the Number of Parameters
4 5
#' @inheritParams params
5 6
#'
6 7
#' @return A count indicating the number of parameters.
@@ -24,4 +25,4 @@
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24 25
25 26
#' @describeIn npars Get the Number of parameters
26 27
#' @export
27 -
npars.fitdists <- function(x, ...) vapply(x, npars, 1L)
28 +
npars.fitdists <- function(x, ...) vapply(x, npars, 1L)

@@ -43,8 +43,8 @@
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43 43
  deprecate_soft("0.1.2", "pburrIII2()", "pllogis()", id = "xburrIII2",
44 44
                 details = "The 'burrIII2' distribution has been deprecated for the identical 'llogis' distribution.")
45 45
  pllogis(q, locationlog = locationlog, scalelog = scalelog,
46 -
            lower.tail = lower.tail,
47 -
            log.p = log.p)
46 +
          lower.tail = lower.tail,
47 +
          log.p = log.p)
48 48
}
49 49
50 50
#' @rdname burrIII2
@@ -65,7 +65,7 @@
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65 65
  rllogis(n, locationlog = locationlog, scalelog = scalelog)
66 66
}
67 67
68 -
#' @rdname llogis
68 +
#' @rdname burrIII2
69 69
#' @export
70 70
sburrIII2 <- function(x) {
71 71
  deprecate_soft("0.1.2", "sburrIII2()", "sllogis()", id = "xburrIII2",

@@ -38,7 +38,7 @@
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38 38
#' @export
39 39
plnorm <- function(q, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE) {
40 40
  pdist("lnorm", q = q, meanlog = meanlog, sdlog = sdlog, 
41 -
             lower.tail = lower.tail, log.p = log.p)
41 +
        lower.tail = lower.tail, log.p = log.p)
42 42
}
43 43
44 44
#' @rdname lnorm
@@ -61,4 +61,4 @@
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61 61
    meanlog = mean(log(x), na.rm = TRUE),
62 62
    sdlog = sd(log(x), na.rm = TRUE)
63 63
  ))
64 -
}
64 +
}

@@ -15,21 +15,23 @@
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15 15
plot_coord_scale <- function(data, xlab, ylab) {
16 16
  chk_string(xlab)
17 17
  chk_string(ylab)
18 -
18 +
  
19 19
  list(
20 20
    coord_trans(x = "log10"),
21 21
    scale_x_continuous(xlab,
22 -
      breaks = scales::trans_breaks("log10", function(x) 10^x),
23 -
      labels = comma_signif
22 +
                       breaks = scales::trans_breaks("log10", function(x) 10^x),
23 +
                       labels = comma_signif
24 24
    ),
25 25
    scale_y_continuous(ylab,
26 -
      labels = scales::percent, limits = c(0, 1),
27 -
      breaks = seq(0, 1, by = 0.2), expand = c(0, 0)
26 +
                       labels = scales::percent, limits = c(0, 1),
27 +
                       breaks = seq(0, 1, by = 0.2), expand = c(0, 0)
28 28
    )
29 29
  )
30 30
}
31 31
32 32
#' SSD Plot
33 +
#' 
34 +
#' Plots species sensitivity data.
33 35
#' @inheritParams params
34 36
#' @export
35 37
#' @examples
@@ -46,10 +48,10 @@
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46 48
  chk_numeric(pred$est)
47 49
  chk_numeric(pred$lcl)
48 50
  chk_numeric(pred$ucl)
49 -
51 +
  
50 52
  chk_number(shift_x)
51 53
  chk_range(shift_x, c(1, 1000))
52 -
54 +
  
53 55
  chk_string(left)
54 56
  chk_string(right)
55 57
  if (!is.null(label)) chk_string(label)
@@ -62,11 +64,11 @@
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62 64
    chk_gt(length(hc))
63 65
    chk_subset(hc, pred$percent)
64 66
  }
65 -
67 +
  
66 68
  chk_superset(colnames(data), c(left, right, label, shape))
67 -
69 +
  
68 70
  gp <- ggplot(pred, aes_string(x = "est"))
69 -
71 +
  
70 72
  if (ci) {
71 73
    if (ribbon) {
72 74
      gp <- gp + geom_xribbon(aes_string(xmin = "lcl", xmax = "ucl", y = "percent/100"), alpha = 0.2)
@@ -81,15 +83,15 @@
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81 83
    data <- data[order(data[[label]]), ]
82 84
  }
83 85
  gp <- gp + geom_line(aes_string(y = "percent/100"), color = if (ribbon) "black" else "red")
84 -
85 -
86 +
  
87 +
  
86 88
  if (!is.null(hc)) {
87 89
    gp <- gp + geom_hcintersect(
88 90
      data = pred[pred$percent %in% hc, ],
89 91
      aes_string(xintercept = "est", yintercept = "percent/ 100")
90 92
    )
91 93
  }
92 -
94 +
  
93 95
  if (left == right) {
94 96
    gp <- gp + geom_ssd(data = data, aes_string(
95 97
      x = left, shape = shape,
@@ -102,9 +104,9 @@
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102 104
    data$arrowleft <- data$right / 2
103 105
    data$arrowright <- data$left * 2
104 106
    data$y <- ssd_ecd(data$xmean)
105 -
107 +
    
106 108
    arrow <- arrow(length = unit(0.1, "inches"))
107 -
109 +
    
108 110
    gp <- gp + geom_line(aes_string(y = "percent")) +
109 111
      geom_segment(
110 112
        data = data[data$xmin != data$xmax, ],
@@ -127,7 +129,7 @@
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127 129
      )
128 130
  }
129 131
  gp <- gp + plot_coord_scale(data, xlab = xlab, ylab = ylab)
130 -
132 +
  
131 133
  if (!is.null(label)) {
132 134
    data$percent <- ssd_ecd(data[[left]])
133 135
    data[[left]] <- data[[left]] * shift_x
@@ -136,6 +138,7 @@
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136 138
      hjust = 0, size = size, fontface = "italic"
137 139
    )
138 140
  }
139 -
141 +
  
140 142
  gp
141 143
}
144 +

@@ -14,7 +14,7 @@
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14 14
15 15
#' Plot Cumulative Distribution Function
16 16
#'
17 -
#' Plots the cdf.
17 +
#' Plots the cumulative distribution function (cdf).
18 18
#'
19 19
#' @inheritParams params
20 20
#' @export
@@ -32,11 +32,11 @@
Loading
32 32
  chk_string(xlab)
33 33
  chk_string(ylab)
34 34
  chk_unused(...)
35 -
35 +
  
36 36
  pred <- ssd_hc(x, percent = 1:99)
37 -
37 +
  
38 38
  pred$Distribution <- pred$dist
39 -
39 +
  
40 40
  ggplot(pred, aes_string(x = "est")) +
41 41
    geom_line(aes_string(
42 42
      y = "percent/100", color = "Distribution",
@@ -55,11 +55,11 @@
Loading
55 55
  chk_string(xlab)
56 56
  chk_string(ylab)
57 57
  chk_unused(...)
58 -
58 +
  
59 59
  data <- data.frame(x = x$data)
60 -
60 +
  
61 61
  pred <- ssd_hc(x, percent = 1:99)
62 -
62 +
  
63 63
  ggplot(pred, aes_string(x = "est")) +
64 64
    geom_line(aes_string(y = "percent/100")) +
65 65
    geom_ssd(data = data, aes_string(x = "x")) +
@@ -77,22 +77,22 @@
Loading
77 77
  chk_string(xlab)
78 78
  chk_string(ylab)
79 79
  chk_unused(...)
80 -
80 +
  
81 81
  data <- x$censdata
82 -
82 +
  
83 83
  data$xmin <- pmin(data$left, data$right, na.rm = TRUE)
84 84
  data$xmax <- pmax(data$left, data$right, na.rm = TRUE)
85 85
  data$xmean <- rowMeans(data[c("left", "right")], na.rm = TRUE)
86 86
  data$arrowleft <- data$right / 2
87 87
  data$arrowright <- data$left * 2
88 88
  data$y <- ssd_ecd(data$xmean)
89 -
89 +
  
90 90
  pred <- ssd_hc(x, percent = 1:99)
91 -
91 +
  
92 92
  gp <- ggplot(pred, aes_string(x = "est"))
93 -
93 +
  
94 94
  arrow <- arrow(length = unit(0.1, "inches"))
95 -
95 +
  
96 96
  gp + geom_line(aes_string(y = "percent/100")) +
97 97
    geom_segment(
98 98
      data = data[data$xmin != data$xmax, ],
@@ -123,12 +123,12 @@
Loading
123 123
ssd_plot_cdf.fitdists <- function(x, xlab = "Concentration", ylab = "Species Affected", ...) {
124 124
  chk_string(xlab)
125 125
  chk_string(ylab)
126 -
126 +
  
127 127
  pred <- ssd_hc(x, average = FALSE, percent = 1:99)
128 128
  pred$Distribution <- pred$dist
129 -
129 +
  
130 130
  data <- data.frame(x = x[[1]]$data)
131 -
131 +
  
132 132
  ggplot(pred, aes_string(x = "est")) +
133 133
    geom_line(aes_string(
134 134
      y = "percent/100", color = "Distribution",
@@ -136,4 +136,4 @@
Loading
136 136
    )) +
137 137
    geom_ssd(data = data, aes_string(x = "x")) +
138 138
    plot_coord_scale(data, xlab = xlab, ylab = ylab)
139 -
}
139 +
}

@@ -18,7 +18,7 @@
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18 18
#'
19 19
#' @inheritParams ggplot2::layer
20 20
#' @inheritParams ggplot2::geom_point
21 -
#' @seealso [geom_ssd()]
21 +
#' @seealso [geom_ssd()] and [ssd_plot_cdf()]
22 22
#' @export
23 23
#' @examples
24 24
#' ggplot2::ggplot(boron_data, ggplot2::aes(x = Conc)) +
@@ -40,6 +40,7 @@
Loading
40 40
#'
41 41
#' @inheritParams ggplot2::layer
42 42
#' @inheritParams ggplot2::geom_point
43 +
#' @family gpplot
43 44
#' @export
44 45
geom_xribbon <- function(mapping = NULL, data = NULL, stat = "identity",
45 46
                         position = "identity", na.rm = FALSE, show.legend = NA,
@@ -57,6 +58,8 @@
Loading
57 58
#'
58 59
#' @inheritParams ggplot2::layer
59 60
#' @inheritParams ggplot2::geom_point
61 +
#' @seealso [ssd_plot_cdf()]
62 +
#' @family gpplot
60 63
#' @export
61 64
#' @examples
62 65
#' ggplot2::ggplot(boron_data, ggplot2::aes(x = Conc)) +
@@ -78,6 +81,7 @@
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78 81
#' @inheritParams ggplot2::layer
79 82
#' @inheritParams ggplot2::geom_path
80 83
#' @inheritParams params
84 +
#' @family gpplot
81 85
#' @export
82 86
#' @examples
83 87
#' ggplot2::ggplot(boron_data, ggplot2::aes(x = Conc)) +
@@ -90,7 +94,7 @@
Loading
90 94
    mapping <- aes(xintercept = xintercept)
91 95
    show.legend <- FALSE
92 96
  }
93 -
97 +
  
94 98
  if (!missing(yintercept)) {
95 99
    if (!missing(xintercept)) {
96 100
      data$yintercept <- yintercept
@@ -101,7 +105,7 @@
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    }
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    show.legend <- FALSE
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  }
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  layer(
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    geom = GeomHcintersect, data = data, mapping = mapping, stat = StatIdentity,
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    position = PositionIdentity, show.legend = show.legend, inherit.aes = FALSE,

@@ -18,6 +18,7 @@
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#' @inheritParams params
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#'
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#' @return A flag.
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#' @family is
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#' @export
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#'
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#' @examples
@@ -34,6 +35,7 @@
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#' @inheritParams params
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#'
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#' @return A flag.
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#' @family is
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#' @export
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#'
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#' @examples
@@ -49,6 +51,7 @@
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#' @inheritParams params
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#'
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#' @return A flag.
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#' @family is
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#' @export
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#'
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#' @examples
@@ -64,6 +67,7 @@
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#' @inheritParams params
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#'
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#' @return A flag.
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#' @family is
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#' @export
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#'
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#' @examples
@@ -72,4 +76,4 @@
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#' is.fitdistscens(fluazinam_dists)
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is.fitdistscens <- function(x) {
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  inherits(x, "fitdistscens")
75 -
}
79 +
}

@@ -15,14 +15,13 @@
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#' Number of Observations
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#'
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#' @inheritParams params
18 +
#' @seealso [stats::nobs()]
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#' @export
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#' @examples
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#' stats::nobs(boron_lnorm)
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nobs.fitdist <- function(object, ...) object$n
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#' Number of Observations
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#'
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#' @inheritParams params
24 +
#' @rdname nobs.fitdist 
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#' @export
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#' @examples
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#' stats::nobs(fluazinam_lnorm)
@@ -30,3 +29,4 @@
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#' @export
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nobs.fitdists <- function(object, ...) nobs(object[[1]])
32 +
Files Coverage
R 96.02%
src 94.44%
Project Totals (41 files) 95.84%
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1
comment: false
2

3
coverage:
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  status:
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    project:
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      default:
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        target: auto
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        threshold: 1%
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        informational: true
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    patch:
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      default:
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        target: auto
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        threshold: 1%
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        informational: true
Sunburst
The inner-most circle is the entire project, moving away from the center are folders then, finally, a single file. The size and color of each slice is representing the number of statements and the coverage, respectively.
Icicle
The top section represents the entire project. Proceeding with folders and finally individual files. The size and color of each slice is representing the number of statements and the coverage, respectively.
Grid
Each block represents a single file in the project. The size and color of each block is represented by the number of statements and the coverage, respectively.
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