scens_plot_: Plot scenario and variable comparison figures
In rabutler-usbr/crssplot: Create Standard CRSS Plots
Description
Usage
Arguments
Details
Value
Examples
Description
scens_plot_boxplot() is similar to scens_plot_range() and
scens_plot_cloud(), except it uses boxplots to show the range for each
year. The boxplot are based on CRSSIO::stat_boxplot_custom(), so whiskers
extend to 5th and 95th percentiles, and outliers are shown for points beyond
those percentiles.
scens_plot_cloud() plots the range of results for multiple scenarios. The
range is shown as a shaded region (cloud) extending from the 10th to 90th
percentiles, along with a solid line for the median. Typically
this is done for only one variable, but multiple variables can be provided
and will be shown as separate facets.
Additionally, scens_plot_cloud() can use the "fill_label" option.
Plotting functions that are designed to largely compare across scenarios
are the scens_plot_*() family, while those designed to compare across
variables are the vars_plot_*() family. However, both families will facet
across the other dimention, e.g., scens_plot_*() will facet by variable.
scens_plot_probs() plots probability plots, i.e., the chance of a variable
occurring. Different scenarios are shown as different colors, and if there
are different variables (vars) they are shown as different facets.
scen_plot_range() plots the range of results for multiple scenarios. The
range is shown as lines for 10th, 50th, and 90th percentiles. Typically
this is done for only one variable, but multiple variables can be provided
and will be shown as separate facets.
var_plot_trace_scatter() creates a trace number vs. value scatter plot for
a single year and variable. If multiple scenarios are specified the
scenarios are shown as different facets.
vars_plot_heatmap() creates a heatmap based on the percentage of traces
that fall into each bin, i.e., variable. The heatmap is years on the x axis
and variables on the y axis, with the color representing the percent of
traces in a given variable. Works with the title, subtitle, caption,
y_lab, color_label, legend_wrap, facet_scales, facet_nrow,
and facet_ncol plot options.
vars_plot_probs() plots the probabilities for multiple variables on a a
single plot. Different vars are shown as different colors, and if there are
multiple scenarios they are shown as different facets. The variables'
probabilities can be shown as lines (plot_type = "line") or as stacked bars
(plot_type = "stacked bar"). For stacked bars, care should be taken by user
to ensure summing probabilities makes sense.
Usage
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scens_plot_boxplot(
df,
vars,
years = NULL,
scenarios = NULL,
plot_colors = NULL,
scen_labels = NULL,
...
)
scens_plot_cloud(
df,
vars,
historical = NULL,
years = NULL,
scenarios = NULL,
plot_colors = NULL,
scen_labels = NULL,
connect_historical = TRUE,
...
)
scens_plot_probs(
df,
vars,
years = NULL,
scenarios = NULL,
plot_colors = NULL,
scen_labels = NULL,
...
)
scens_plot_range(
df,
vars,
years = NULL,
scenarios = NULL,
plot_colors = NULL,
scen_labels = NULL,
...
)
var_plot_trace_scatter(
df,
scenarios,
years,
vars,
color_by = NULL,
plot_colors = NULL,
...
)
vars_plot_heatmap(
df,
scenarios,
years = NULL,
vars = NULL,
var_labels = NULL,
...
)
vars_plot_probs(
df,
scenarios,
years = NULL,
vars = NULL,
plot_colors = NULL,
var_labels = NULL,
plot_type = "line",
...
)
Arguments
df
Data frame. Must have "Year", "Variable", "ScenarioGroup", and
"Value" columns.
vars
Character vector specifying the variable(s) to use (found in
df$Variable). If NULL, use all variables in df. Must be specified in
scens_plot_*() family. For vars_plot_heatmap(), the order that vars
are provided will be used to order the heatmap from top to bottom.
years
Numeric vector specifying the years to show. If NULL, use all
years in df.
scenarios
Character vector specifying the scenarios to use (found in
df$ScenarioGroup). If NULL, use all scenarios in df. Must be
specified in vars_plot_*() family.
plot_colors
Named character vector to set custom plot colors. Names
should match scenarios found in df$ScenarioGroup.
scen_labels
Named character vector to set custom legend labels for the
scenarios. Used to show legend labels that are different from values found
in df$ScenarioGroup.
...
Parameters passed to other functions. See details.
historical
Data frame of historical data to add to the figure. Must
have a "Year" column, and the same number of additional columns as the
length of vars. If there is only one variable, then the column names in
this data frame do not matter (except for Year). However, if there are
more than one variable, then the column names must match those in vars.
connect_historical
If historical data are provided, and this is
TRUE, then the historical year prior to the first projected year of data
will be "connected" to the projections so as to provide a connected look
to the plot. If FALSE, then projected data are shown as they natively
exist in df and if historical data are not provided this has no affect
on the output.
color_by
For var_plot_trace_scatter(), the points can be colored
based on a specified column in the df. This should be specified as a
string, and should exist in df.
var_labels
Similar to scen_labels, this is a named character that
allows the user to cusomize the variable names that show up in the legend.
plot_type
For vars_plot_probs(), should the plot use lines
('line'), or stacked bars ('stacked bar'). Can also use 1 or 2,
respectively.
Details
... is used to pass additional options to ggplot functions. The following
are used:
"title", "subtitle", and "caption" are passed to ggplot2::labs().
"color_label" and "y_lab" are also passed using color and y parameters,
respectively.
"legend_wrap" is used to modify labels in legends etc. by calling
stringr::str_wrap() on the appropriate variable, with
width = legend_wrap.
"facet_scales", "facet_nrow", and "facet_ncol" are all passed to
ggplot2::facet_wrap().
scens_plot_probs() and scens_plot_range() will use the following
additional options: "y", "title", "color_label", "legend_wrap",
"facet_scales", "facet_nrow", and "facet_ncol".
The legend order can be modified by converting "ScenarioGroup" column to a
factor before calling scens_plot_*(), with the levels specifying the
order the scenarios will show up in the legend.
Value
gg object.
Examples
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# quick simple plot using 1 variable and all years
scens_plot_boxplot(ex_pe, vars = "powell_dec_pe")
# fully customized for multiple variables, custom colors, and custom names
tst_names <- c("April ST 2007 UCRC" = "Scen 1", "April ST CT" = "Scen 2")
pal <- c("April ST 2007 UCRC" = "#fc8d62", "April ST CT" = "#8da0cb")
scens_plot_boxplot(
ex_pe,
vars = c("powell_dec_pe", "mead_dec_pe"),
years = 2021:2036,
title = "Mead and Powell", subtitle = "End-of-December Elevation",
y_lab = "(feet)", caption = "Results from April 20xx",
facet_scales = "free_y",
plot_colors = pal,
scen_labels = tst_names,
legend_wrap = 10
)
scens_plot_probs(ex_pe, "powell_wy_min_lt_3525", y_lab = "percent")
# quick simple plot of one variable
scens_plot_range(ex_pe, "mead_dec_pe")
# now add ylabel
scens_plot_range(ex_pe, "mead_dec_pe", y_lab = "feet")
# show two variables
scens_plot_range(
ex_pe,
c("powell_dec_pe", "mead_dec_pe"),
facet_scales = "free_y"
)
# subset scenarios
scens_plot_range(ex_pe, "mead_dec_pe", scenarios = "April ST CT")
# custom colors and scenario labels + add title and caption
pc <- c("April ST CT" = "red", "April ST 2007 UCRC" = "black")
sl <- c("April ST CT" = "s1", "April ST 2007 UCRC" = "s2")
scens_plot_range(ex_pe,
"powell_dec_pe",
plot_colors = pc,
scen_labels = sl,
title = "PE",
caption = "this is a caption"
)
# change to two rows in stead of two columns for showing two variables
scens_plot_range(
ex_pe,
c("powell_dec_pe", "mead_dec_pe"),
facet_scales = "free_y",
facet_nrow = 2
)
# scatter plot for Mead elevation in Dec. 2021
var_plot_trace_scatter(
ex_pe,
vars = "mead_dec_pe",
years = 2021,
scenarios = "April ST CT"
)
# add in a new variable to be used to color the points:
zz <- dplyr::mutate(ex_pe, color_cat = dplyr::case_when(
Value > 1095 ~ "No concern",
Value > 1076 ~ "Some concern",
Value > 1074 ~ "Moderate concern",
TRUE ~ "concern")
)
cc <- c("No concern" = "grey20", "Some concern" = "blue",
"Moderate concern" = "steelblue", "concern" = "red")
# color by the new variable, and show two scenarios:
gg <- var_plot_trace_scatter(
zz,
vars = "mead_dec_pe",
years = 2021,
scenarios = c("April ST CT", "April ST 2007 UCRC"),
color_by = "color_cat"
)
vv <- c("mead_min_lt_1000", "mead_min_lt_1020", "powell_wy_min_lt_3490",
"powell_dec_lt_3525")
gg <- vars_plot_probs(ex_pe, "April ST CT", vars = vv, years = 2020:2026)
# or show both scenarios:
ss <- unique(ex_pe$ScenarioGroup)
gg <- vars_plot_heatmap(ex_pe, ss, vars = vv, years = 2020:2026)
vv <- c("mead_min_lt_1000", "mead_min_lt_1020", "powell_wy_min_lt_3490",
"powell_dec_lt_3525")
gg <- vars_plot_probs(ex_pe, "April ST CT", vars = vv)
# it does not make sense to stack bars for these 4 variables, but you can:
gg <- vars_plot_probs(
ex_pe,
"April ST CT",
vars = vv,
plot_type = "stacked bar"
)
rabutler-usbr/crssplot documentation built on Feb. 6, 2022, 3:33 p.m.
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Description Usage Arguments Details Value Examples
Description
scens_plot_boxplot() is similar to scens_plot_range() and
scens_plot_cloud(), except it uses boxplots to show the range for each
year. The boxplot are based on CRSSIO::stat_boxplot_custom(), so whiskers
extend to 5th and 95th percentiles, and outliers are shown for points beyond
those percentiles.
scens_plot_cloud() plots the range of results for multiple scenarios. The
range is shown as a shaded region (cloud) extending from the 10th to 90th
percentiles, along with a solid line for the median. Typically
this is done for only one variable, but multiple variables can be provided
and will be shown as separate facets.
Additionally, scens_plot_cloud() can use the "fill_label" option.
Plotting functions that are designed to largely compare across scenarios
are the scens_plot_*() family, while those designed to compare across
variables are the vars_plot_*() family. However, both families will facet
across the other dimention, e.g., scens_plot_*() will facet by variable.
scens_plot_probs() plots probability plots, i.e., the chance of a variable
occurring. Different scenarios are shown as different colors, and if there
are different variables (vars) they are shown as different facets.
scen_plot_range() plots the range of results for multiple scenarios. The
range is shown as lines for 10th, 50th, and 90th percentiles. Typically
this is done for only one variable, but multiple variables can be provided
and will be shown as separate facets.
var_plot_trace_scatter() creates a trace number vs. value scatter plot for
a single year and variable. If multiple scenarios are specified the
scenarios are shown as different facets.
vars_plot_heatmap() creates a heatmap based on the percentage of traces
that fall into each bin, i.e., variable. The heatmap is years on the x axis
and variables on the y axis, with the color representing the percent of
traces in a given variable. Works with the title, subtitle, caption,
y_lab, color_label, legend_wrap, facet_scales, facet_nrow,
and facet_ncol plot options.
vars_plot_probs() plots the probabilities for multiple variables on a a
single plot. Different vars are shown as different colors, and if there are
multiple scenarios they are shown as different facets. The variables'
probabilities can be shown as lines (plot_type = "line") or as stacked bars
(plot_type = "stacked bar"). For stacked bars, care should be taken by user
to ensure summing probabilities makes sense.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | scens_plot_boxplot(
df,
vars,
years = NULL,
scenarios = NULL,
plot_colors = NULL,
scen_labels = NULL,
...
)
scens_plot_cloud(
df,
vars,
historical = NULL,
years = NULL,
scenarios = NULL,
plot_colors = NULL,
scen_labels = NULL,
connect_historical = TRUE,
...
)
scens_plot_probs(
df,
vars,
years = NULL,
scenarios = NULL,
plot_colors = NULL,
scen_labels = NULL,
...
)
scens_plot_range(
df,
vars,
years = NULL,
scenarios = NULL,
plot_colors = NULL,
scen_labels = NULL,
...
)
var_plot_trace_scatter(
df,
scenarios,
years,
vars,
color_by = NULL,
plot_colors = NULL,
...
)
vars_plot_heatmap(
df,
scenarios,
years = NULL,
vars = NULL,
var_labels = NULL,
...
)
vars_plot_probs(
df,
scenarios,
years = NULL,
vars = NULL,
plot_colors = NULL,
var_labels = NULL,
plot_type = "line",
...
)
|
Arguments
df |
Data frame. Must have "Year", "Variable", "ScenarioGroup", and "Value" columns. |
vars |
Character vector specifying the variable(s) to use (found in
|
years |
Numeric vector specifying the years to show. If |
scenarios |
Character vector specifying the scenarios to use (found in
|
plot_colors |
Named character vector to set custom plot colors. Names
should match scenarios found in |
scen_labels |
Named character vector to set custom legend labels for the
scenarios. Used to show legend labels that are different from values found
in |
... |
Parameters passed to other functions. See details. |
historical |
Data frame of historical data to add to the figure. Must
have a "Year" column, and the same number of additional columns as the
length of |
connect_historical |
If |
color_by |
For |
var_labels |
Similar to |
plot_type |
For |
Details
... is used to pass additional options to ggplot functions. The following
are used:
"title", "subtitle", and "caption" are passed to
ggplot2::labs(). "color_label" and "y_lab" are also passed usingcolorandyparameters, respectively."legend_wrap" is used to modify labels in legends etc. by calling
stringr::str_wrap()on the appropriate variable, withwidth = legend_wrap."facet_scales", "facet_nrow", and "facet_ncol" are all passed to
ggplot2::facet_wrap().
scens_plot_probs() and scens_plot_range() will use the following
additional options: "y", "title", "color_label", "legend_wrap",
"facet_scales", "facet_nrow", and "facet_ncol".
The legend order can be modified by converting "ScenarioGroup" column to a
factor before calling scens_plot_*(), with the levels specifying the
order the scenarios will show up in the legend.
Value
gg object.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 | # quick simple plot using 1 variable and all years
scens_plot_boxplot(ex_pe, vars = "powell_dec_pe")
# fully customized for multiple variables, custom colors, and custom names
tst_names <- c("April ST 2007 UCRC" = "Scen 1", "April ST CT" = "Scen 2")
pal <- c("April ST 2007 UCRC" = "#fc8d62", "April ST CT" = "#8da0cb")
scens_plot_boxplot(
ex_pe,
vars = c("powell_dec_pe", "mead_dec_pe"),
years = 2021:2036,
title = "Mead and Powell", subtitle = "End-of-December Elevation",
y_lab = "(feet)", caption = "Results from April 20xx",
facet_scales = "free_y",
plot_colors = pal,
scen_labels = tst_names,
legend_wrap = 10
)
scens_plot_probs(ex_pe, "powell_wy_min_lt_3525", y_lab = "percent")
# quick simple plot of one variable
scens_plot_range(ex_pe, "mead_dec_pe")
# now add ylabel
scens_plot_range(ex_pe, "mead_dec_pe", y_lab = "feet")
# show two variables
scens_plot_range(
ex_pe,
c("powell_dec_pe", "mead_dec_pe"),
facet_scales = "free_y"
)
# subset scenarios
scens_plot_range(ex_pe, "mead_dec_pe", scenarios = "April ST CT")
# custom colors and scenario labels + add title and caption
pc <- c("April ST CT" = "red", "April ST 2007 UCRC" = "black")
sl <- c("April ST CT" = "s1", "April ST 2007 UCRC" = "s2")
scens_plot_range(ex_pe,
"powell_dec_pe",
plot_colors = pc,
scen_labels = sl,
title = "PE",
caption = "this is a caption"
)
# change to two rows in stead of two columns for showing two variables
scens_plot_range(
ex_pe,
c("powell_dec_pe", "mead_dec_pe"),
facet_scales = "free_y",
facet_nrow = 2
)
# scatter plot for Mead elevation in Dec. 2021
var_plot_trace_scatter(
ex_pe,
vars = "mead_dec_pe",
years = 2021,
scenarios = "April ST CT"
)
# add in a new variable to be used to color the points:
zz <- dplyr::mutate(ex_pe, color_cat = dplyr::case_when(
Value > 1095 ~ "No concern",
Value > 1076 ~ "Some concern",
Value > 1074 ~ "Moderate concern",
TRUE ~ "concern")
)
cc <- c("No concern" = "grey20", "Some concern" = "blue",
"Moderate concern" = "steelblue", "concern" = "red")
# color by the new variable, and show two scenarios:
gg <- var_plot_trace_scatter(
zz,
vars = "mead_dec_pe",
years = 2021,
scenarios = c("April ST CT", "April ST 2007 UCRC"),
color_by = "color_cat"
)
vv <- c("mead_min_lt_1000", "mead_min_lt_1020", "powell_wy_min_lt_3490",
"powell_dec_lt_3525")
gg <- vars_plot_probs(ex_pe, "April ST CT", vars = vv, years = 2020:2026)
# or show both scenarios:
ss <- unique(ex_pe$ScenarioGroup)
gg <- vars_plot_heatmap(ex_pe, ss, vars = vv, years = 2020:2026)
vv <- c("mead_min_lt_1000", "mead_min_lt_1020", "powell_wy_min_lt_3490",
"powell_dec_lt_3525")
gg <- vars_plot_probs(ex_pe, "April ST CT", vars = vv)
# it does not make sense to stack bars for these 4 variables, but you can:
gg <- vars_plot_probs(
ex_pe,
"April ST CT",
vars = vv,
plot_type = "stacked bar"
)
|
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