Package {gcplyr}

numeric vector of x values

numeric vector of y values

One of c("x", "y", "both"), determining whether the function will return the x value of the centroid, the y value of the centroid, or a vector containing x then y

vector, of length 2, delimiting the x range over which the centroid should be calculated (where NA can be provided for the area to be calculated from the start or to the end of the data)

Value to be subtracted from y values before calculating the centroid

A vector of logical values indicating which x and y values should be included (TRUE) or excluded (FALSE).

a logical indicating whether missing values should be removed

a logical indicating whether y values below zero should be treated as zeros. If FALSE, the centroid for negative y values will be calculated normally, effectively pulling the centroid towards the x axis.

logical whether warning should be issued when xlim is lower than the lowest x value or higher than the highest x value.

logical whether warning should be issued when neg.rm == FALSE but some y values are below 0.

Other arguments to pass to centroid

numeric vector of y values in which to identify local extrema

Optional numeric vector of corresponding x values

Arguments that set the width/height of the window used to search for local extrema.

window_width is in units of x.

window_width_n is in units of number of data points.

window_height is the maximum change in y a single extrema-search step is allowed to take.

window_width_n_frac is as a fraction of the total number of data points.

For example, the function will not pass a peak or valley more than window_width_n data points wide, nor a peak/valley taller or deeper than window_height.

A narrower width will be more sensitive to narrow local maxima/minima, while a wider width will be less sensitive to local maxima/minima. A smaller height will be more sensitive to shallow local maxima/minima, while a larger height will be less sensitive to shallow maxima/minima.

One of c("index", "x", "y"), determining whether the function will return the index, x value, or y value associated with the identified extremas

logical for which classes of local extrema to return

Should the first and last values in y be included if they are in the returned vector of extrema?

A vector of logical values indicating which x and y values should be included (TRUE) or excluded (FALSE).

If return = "index", index will be for the whole vector and not the subset of the vector

logical whether NA's should be removed before analyzing

Deprecated, use window_width instead

Deprecated, use window_width_n instead

Deprecated, use window_height instead

(for first_maxima and first_minima), other parameters to pass to find_local_extrema

numeric or character arguments

a logical indicating whether missing values should be removed.

a logical indicating whether NA should be returned when there are no non-missing arguments passed to min or max (often because na.rm = TRUE but all values are NA)

Formula specifying the numeric response (density) and numeric predictor (time).

data.frame containing variables in formula

A vector of predictor values to smooth along (e.g. time)

A vector of response values to be smoothed (e.g. density).

Number of data points wide the moving window is (therefore, must be an odd number of points)

Width of the moving window (in units of x)

Width of the window (as a fraction of the total number of data points).

Width of the window (as a fraction of the range of x)

logical whether NA's should be removed before analyzing

logical whether warning should be issued when predictor variable that data is sorted by is non-numeric.

numeric vector of y values in which to identify threshold crossing event(s)

Optional numeric vector of corresponding x values

Threshold y value of interest

One of c("index", "x"), determining whether the function will return the index or x value associated with the threshold-crossing event.

If index, it will refer to the data point immediately after the crossing event.

If x, it will use linear interpolation and the data points immediately before and after the threshold-crossing to return the exact x value when the threshold crossing occurred

logical for whether crossing events where y rises above threshold should be returned

logical for whether crossing events where y falls below threshold should be returned

logical for whether startpoint should be returned when the startpoint is above threshold and return_rising = TRUE, or when the startpoint is below threshold and return_falling = TRUE

A vector of logical values indicating which x and y values should be included (TRUE) or excluded (FALSE).

If return = "index", index will be for the whole vector and not the subset of the vector

logical whether NA's should be removed before analyzing. If return = 'index', indices will refer to the original y vector including NA values

(for first_above and first_below) other arguments to pass to find_threshold_crosses

numeric (logical, integer, or double) vector or an R object for which the internal coercion to double works whose min or max is searched for.

logical, indicating if an empty value should be returned as NA (the default) or as integer(0) (the same as which.min and which.max).

numeric vector of x values

numeric vector of y values

vector, of length 2, delimiting the x range over which the area under the curve should be calculated (where NA can be provided for the area to be calculated from the start or to the end of the data)

Value to be subtracted from y values before calculating area under the curve

A vector of logical values indicating which x and y values should be included (TRUE) or excluded (FALSE).

a logical indicating whether missing values should be removed

a logical indicating whether y values below zero should be treated as zeros. If FALSE, area under the curve for negative y values will be calculated normally, effectively subtracting from the returned value.

logical whether warning should be issued when xlim is lower than the lowest x value or higher than the highest x value.

logical whether warning should be issued when neg.rm == FALSE but some y values are below 0.

A tidydesign data.frame (e.g. as created by make_tidydesign)

NULL or a string to use for concatenating design elements together. If NULL each design column will be put into its own block. If a string, that string will be used to paste together all design elements and all design elements will be returned in a single block

A string used when concatenating rownames and column names to create well names

Header for newly-created column containing the well names

Data to calculate difference or derivative of

vector of x values provided as a simple numeric.

One of c("difference", "derivative") for whether the differences in y should be returned, or the derivative of y with respect to x

When percapita = TRUE, the per-capita difference or derivative is returned

numeric to scale x by in derivative calculation

Set x_scale to the ratio of the units of x to the desired units. E.g. if x is in seconds, but the desired derivative is in units of /minute, set x_scale = 60 (since there are 60 seconds in 1 minute).

y-value associated with a "blank" where the density is 0. Is required when percapita = TRUE.

If a vector of blank values is specified, blank values are assumed to be in the same order as unique(subset_by)

An optional vector as long as y. y will be split by the unique values of this vector and the derivative for each group will be calculated independently of the others.

This provides an internally-implemented approach similar to group_by and mutate

Set how many data points are used to determine the slope at each point.

When all are NULL, calc_deriv calculates the difference or derivative of each point with the next point, appending NA at the end.

When one or multiple are specified, a linear regression is fit to all points in the window to determine the slope.

window_width_n specifies the width of the window in number of data points. window_width specifies the width of the window in units of x. window_width_n_frac specifies the width of the window as a fraction of the total number of data points.

When using multiple window specifications at the same time, windows are conservative. Points included in each window will meet all of the window_width, window_width_n, and window_width_n_frac.

A value of window_width_n = 3 or window_width_n = 5 is often a good default.

One of c("linear", "log") specifying the transformation of y-values.

'log' is only available when calculating per-capita derivatives using a fitting approach (when non-default values are specified for window_width or window_width_n).

For per-capita growth expected to be exponential or nearly-exponential, "log" is recommended, since exponential growth is linear when log-transformed. However, log-transformations must be used with care, since y-values at or below 0 will become undefined and results will be more sensitive to incorrect values of blank.

logical whether NA's should be removed before analyzing

logical whether warning should be issued when calc_deriv is being called on ungrouped data and subset_by = NULL.

logical whether warning should be issued when log(y) produced warnings.

logical whether warning should be issued when log(y) produced infinite values that will be treated as NA.

logical whether warning should be issued when only one data point is in the window set by window_width_n, window_width, or window_width_n_frac, and so NA will be returned.

vector of per-capita derivative data to calculate the equivalent doubling time of

numeric to scale per-capita derivative values by

Set x_scale to the ratio of the the units of y to the desired units. E.g. if y is in per-second, but the desired doubling time is in minutes, x_scale = 60 (since there are 60 seconds in 1 minute).

object from which to extract element(s)

index specifying element to extract.

logical indicating whether NA should be returned when all(is.na(i)) == TRUE.

a logical indicating whether missing values should be removed.

numeric vector of y values in which to identify local extrema

Optional numeric vector of corresponding x values

Width of the window (in units of x) used to search for local extrema. A narrower width will be more sensitive to narrow local maxima/minima, while a wider width will be less sensitive to local maxima/minima.

The maximum number of data points a single extrema-search step is allowed to take. For example, when maxima-finding, the function will not pass a valley consisting of more than window_width_n data points.

A smaller window_width_n will be more sensitive to narrow local maxima/minima, while a larger window_width_n will be less sensitive to narrow local maxima/minima.

If not provided, defaults to ~0.2*length(y)

The maximum change in y a single extrema-search step is allowed to take. For example, when maxima-finding, the function will not pass a valley deeper than window_height.

A smaller window_height will be more sensitive to shallow local maxima/minima, while a larger window_height will be less sensitive to shallow maxima/minima.

One of c("index", "x", "y"), determining whether the function will return the index, x value, or y value associated with the first maxima in y values

Should the first or last value in y be allowed to be returned?

Other parameters to pass to find_local_extrema

A vector of column names in Excel-style base-26 letter format (any values that are already in base-10 will be returned as-is)

A vector giving the values of the predictor variable.

A vector giving the values of the response variable. If y is missing or NULL, the responses are assumed to be specified by x, with x the index vector.

Additional arguments passed to smooth.spline.

logical whether NA's should be removed before analyzing. Required to be TRUE if any x or y values are NA.

A vector of filepaths relative to the current working directory where each filepath is a single plate read to be read by read_blocks.

vector of names corresponding to each design element (each block). Inferred from filenames, if not specified.

When keep_blocknames = TRUE, the output will have a column containing these values, with the column name specified by block_name_header.

When join_as_cols = TRUE, the block_names are also used as the output column names for each separated design column.

When keep_blocknames = TRUE, the column name of the column containing the block_names.

logical indicating whether blocks (if there are multiple) should be joined as columns (i.e. describe the same plate) in the tidy output. If FALSE, blocks are joined as rows (i.e. describe different plates) in the tidy output.

If designs have been pasted together, this specifies the string they should be split apart by via separate_tidy.

When join_as_cols = FALSE and sep is not specified, all the design values will be in a column named by values_colname. For other cases, see the Value section.

When sep is specified, into sets the names of the columns after splitting (see Value section for behavior when into is not set).

logical indicating whether the column containing block_names (or those inferred from file names) should be retained in the output. By default, blocknames are retained only if join_as_cols = FALSE.

logical indicating whether warning should be raised when multiple blocks are joined as rows (join_as_cols = FALSE) and sep is specified, but into is not specified.

Deprecated, use join_as_cols instead

Other arguments to pass to read_blocks, paste_blocks, trans_block_to_wide, trans_wide_to_tidy, or separate_tidy.

See Details for more information

vector of filenames (as strings), each of which is a block-shaped file containing measures data. File formats can be .csv, .xls, or .xlsx

Number of plates. If multiple plates uninterleave will be used to separate blockmeasures into those plates accordingly

(optional) Names to put onto the plates when output

string to use as separator for well names between rowname and column name

Other arguments to pass to read_blocks, uninterleave, or trans_block_to_wide

vector of x values (typically time)

vector of y values (typically density)

vector of derivative values (typically per-capita derivative)

y-value associated with a "blank" where the density is 0. Is required when trans_y = TRUE.

A vector of blank values may be specified only when all of slope, x1, y1, and y0 are provided as vectors

One of c("linear", "log") specifying the transformation of y-values.

'log' is the default, producing calculations of lag time assuming a transition to exponential growth

'linear' is available for alternate uses

a logical indicating whether missing values or values that become NA or infinite during log-transformation should be removed

Slope to project from x1,y1 to y0 (typically per-capita growth rate). If not provided, will be calculated as max(deriv)

x value (typically time) to project slope from. If not provided, will be calculated as x[which.max(deriv)].

y value (typically density) to project slope from. If not provided, will be calculated as y[which.max(deriv)].

y value (typically density) to find intersection of slope from x1, y1 with. If not provided, will be calculated as min(y)

logical whether warning should be issued when log(y) produced warnings.

logical whether warning should be issued when log(y) produced infinite values that will be treated as NA.

logical whether warning should be issued when min(y) does not equal min(y[!is.na(x)]).

logical whether warning should be issued when there are multiple points in deriv that are tied for the highest, and only the first will be used.

logical whether warning should be issued when some, but not all, inputs are vectorized, and only one lag time value will be returned.

logical whether warning should be issued when calculated lag time is less than the minimum value of x.

logical whether warning should be issued when an unexpected number of blank values was provided and only the first will be used

Number of rows and columns in the plate data

Names of the rows, columns of the plate blockmeasures data

The name of the field containing the block_names

One of c("blocks", "blocks_pasted", "wide", "tidy") denoting the format of the resulting data.frame

For easy merging with tidymeasures, leave as default of 'tidy'.

For human-readability to confirm design is correct, choose 'blocks' or 'blocks_pasted'.

For writing to block-shaped file(s), choose 'blocks' or 'blocks_pasted'.

If block_row_names or block_col_names are not specified, then names will be generated automatically according to wellnames_numeric.

If wellnames_numeric is TRUE, rows and columns will be numbered with "R" and "C" prefixes, respectively.

If wellnames_numeric is FALSE, rows will be lettered A through Z, while columns will be numbered

A string used when concatenating rownames and column names to create well names, when output_format = "wide" or output_format = "tidy"

Header for newly-created column containing the well names, when output_format = "tidy"

When wellnames are created for output_format = "wide" or output_format = "tidy" by paste-ing the rownames and column names, should the column names come first.

Value in the lookup table for the split pattern values that corresponds to the first value in the vector.

Lookup table by default is c(1,2,...,8,9,A,B,...Y,Z,a,b,...,y,z). If, for example, lookup_tbl_start = "A", then the lookup table will now be c(A,B,...Y,Z,a,b,...,y,z)

character to split pattern elements provided in ... by, if they're not already a vector

Each ... argument must be named, and must be a list with five elements:

1. a vector of the values

2. a vector of the rows the pattern should be applied to

3. a vector of the columns the pattern should be applied to

4. a string or vector denoting the pattern in which the values should be filled into the rows and columns specified.

   If it's a string, will be split by pattern_split. Pattern will be used as the indices of the values vector.

   0's refer to NA. The pattern will be recycled as necessary to fill all the wells of the rows and columns specified.

5. a logical for whether this pattern should be filled byrow

vector of values to use

vector of rows where pattern applies

vector of cols where pattern applies

numeric pattern itself, where numbers refer to entries in values

logical for whether pattern should be created by row

Number of the vignette the example object or file is created in.

Number of the example the object or file is created in.

The directory files should be saved into.

Number of rows and columns in the plate data

Names of the rows, columns of the plate blockmeasures data

A string used when concatenating rownames and column names to create well names

Header for newly-created column containing the well names

If block_row_names or block_col_names are not specified, should rows and columns be named using Excel-style base-26 lettering for rows and numbering for columns? If FALSE, rows and columns will be numbered with "R" and "C" prefix.

Value in the lookup table for the split pattern values that corresponds to the first value in the vector.

Lookup table by default is c(1,2,...,8,9,A,B,...Y,Z,a,b,...,y,z). If, for example, lookup_tbl_start = "A", then the lookup table will now be c(A,B,...Y,Z,a,b,...,y,z)

character to split pattern elements provided in ... by

In the wellnames created by paste-ing the rownames and column names, should the column names come first

Each ... argument must be a list with five elements:

1. a vector of the values

2. a vector of the rows the pattern should be applied to

3. a vector of the columns the pattern should be applied to

4. a string of the pattern itself, where numbers refer to the indices in the values vector

   0's refer to NA

   This pattern will be split using pattern_split, which defaults to every character

5. a logical for whether this pattern should be filled byrow

Argument specifying which smoothing method should be used. Options include "moving-average", "moving-median", "loess", "gam", and "smooth.spline".

A data.frame with possible tuning values. The columns should be named the same as the tuning parameters.

Note that, when using train, the tuneGrid must be passed both to this function as well as directly to train.

First data.frame, or list of data.frames, to be joined

Second data.frame, or list of data.frames, to be joined

A character vector of variables to join by, passed directly to the join function

Should only complete_cases of the resulting data.frame be returned?

A logical indicating whether x or y is a list containing data.frames that should be merged together before being merged with the other

Column name for where names(x) or names(y) will be entered in if collapse = TRUE.

If a value of NA then names(x) or names(y) will not be put into a column in the returned data.frame

Type of join used to merge x and y. Options are 'full' (default), 'inner', 'left', and 'right'.

• A full join keeps all observations in x and y

• A left join keeps all observations in x

• A right join keeps all observations in y

• An inner join only keeps observations found in both x and y (inner joins are not appropriate in most cases because observations are frequently dropped).

See full_join, left_join, right_join, or inner_join for more details

logical, should a warning be passed when the output has more rows than x and more rows than y?

Other arguments to pass to the underlying join function. See full_join, left_join, right_join, or inner_join for options.

Blocks, either a single data.frame or a list of data.frames

string to use as separator for output pasted values

A logical indicating the existence of nested metadata in the blockmeasures list, e.g. as is typically output by read_blocks. If NULL, will attempt to infer existence of nested metadata

A vector of known predictor values.

A vector of known response values.

A vector of new predictor values for which the response value will be predicted

Boolean indicating whether values of newdata that are out of the domain of x should be predicted (by extrapolating the slope from the endpoints of x). If FALSE, such values will be returned as NA.

logical whether NA's should be removed before making predictions

The data.frame to be printed

Boolean for whether column names should be printed

Boolean for whether row names should be printed

A vector of filepaths relative to the current working directory where each filepath is a single plate read

(optional) the type(s) of the files. Options include:

"csv", "xls", or "xlsx".

"tbl" or "table" to use read.table to read the file, "csv2" to use read.csv2, "delim" to use read.delim, or "delim2" to use read.delim2.

If none provided, read_blocks will infer filetype(s) from the extension(s) in files. When extension is not "csv", "xls", or "xlsx", will use "table".

(optional) the rows and columns where the measures data are located in files.

Can be a vector or list the same length as files, or a single value that applies to all files. Values can be numeric or a string that will be automatically converted to numeric by from_excel.

If not provided, data is presumed to begin on the first row and column of the file(s) and end on the last row and column of the file(s).

(optional) If data is in .xls or .xlsx files, which sheet it is located on. Defaults to the first sheet if not specified

(optional) non-density data that should be associated with each read blockmeasures. A named list where each item in the list is either: a vector of length 2, or a list containing two vectors.

In the former case, each vector should provide the row and column where the metadata is located in all of the blockmeasures input files.

In the latter case, the first vector should provide the rows where the metadata is located in each of the corresponding input files, and the second vector should provide the columns where the metadata is located in each of the corresponding input files. (This case is typically used when reading multiple blocks from a single file.)

(optional) vector of names corresponding to each plate in files. If not provided, block_names are inferred from the filenames

The name of the metadata field containing the block_names

If block_names are inferred from filenames, should the leading './' (if any) be retained

If block_names are inferred from filenames, should the path (if any) be retained

If block_names are inferred from filenames, should the file extension (if any) be retained

TRUE, FALSE, or NA, or a vector of such values, indicating whether the file(s) contains the column names as its first line. If header = NA will attempt to infer the presence of column names. If header = FALSE or no column names are inferred when header = NA, column names will be generated automatically according to wellnames_numeric

TRUE, FALSE, or NA, or a vector of such values, indicating whether the file(s) contains the row names as its first column. If sider = NA will attempt to infer the presence of row names. If sider = FALSE or no row names are inferred when sider = NA, row names will be generated automatically according to wellnames_numeric

If row names and column names are not provided in the input data.frame as specified by header and sider, then names will be generated automatically according to wellnames_numeric.

If wellnames_numeric is TRUE, rows and columns will be numbered with "R" and "C" prefixes, respectively.

If wellnames_numeric is FALSE, rows will be lettered A through Z, while columns will be numbered

A character vector of strings which are to be interpreted as NA values by read.csv, read_xls, read_xlsx, or read.table

Deprecated, use filetype instead

Deprecated, use block_names_header instead

Other arguments passed to read.csv, read_xls, read_xlsx, or read.table

A vector of filepaths (relative to current working directory) where each one is a tidy-shaped data file

(optional) the type(s) of the files. Options include:

"csv", "xls", or "xlsx".

"tbl" or "table" to use read.table to read the file, "csv2" to use read.csv2, "delim" to use read.delim, or "delim2" to use read.delim2.

If none provided, read_tidys will infer filetype(s) from the extension(s) in files. When extension is not "csv", "xls", or "xlsx", will use "table".

(optional) the rows and columns where the data are located in files.

Can be a vector or list the same length as files, or a single value that applies to all files. Values can be numeric or a string that will be automatically converted to numeric by from_excel.

If not provided, data is presumed to begin on the first row and column of the file(s) and end on the last row and column of the file(s).

The sheet of the input files where data is located (if input files are .xls or .xlsx). If not specified defaults to the first

Names to give the tidy files read in. By default uses the file names if not specified. These names may be added to the resulting data.frame depending on the value of the names_to_col argument

Should the run names (provided in run_names or inferred from files) be added as a column to the output?

If run_names_header is TRUE, they will be added with the column name run_name

If run_names_header is FALSE, they will not be added.

If run_names_header is a string, they will be added and the column name will be the string specified for run_names_header.

If run_names_header is NULL, they only will be added if there are multiple tidy data.frames being read. In which case, the column name will be run_name

If run_names are inferred from filenames, should the leading './' (if any) be retained

If run_names are inferred from filenames, should the path (if any) be retained

If run_names are inferred from filenames, should the file extension (if any) be retained

A character vector of strings which are to be interpreted as NA values by read.csv, read_xls, read_xlsx, or read.table

Deprecated, use filetype instead

Deprecated, use run_names_header instead

Other arguments passed to read.csv, read_xls, read_xlsx, or read.table sheet

A vector of filepaths (relative to current working directory) where each one is a widemeasures set of data

(optional) the type(s) of the files. Options include:

"csv", "xls", or "xlsx".

"tbl" or "table" to use read.table to read the file, "csv2" to use read.csv2, "delim" to use read.delim, or "delim2" to use read.delim2.

If none provided, read_wides will infer filetype(s) from the extension(s) in files. When extension is not "csv", "xls", or "xlsx", will use "table".

(optional) the rows and columns where the data are located in files.

Can be a vector or list the same length as files, or a single value that applies to all files. Values can be numeric or a string that will be automatically converted to numeric by from_excel.

If not provided, data is presumed to begin on the first row and column of the file(s) and end on the last row and column of the file(s).

logical for whether there is a header in the data. If FALSE columns are simply numbered. If TRUE, the first row of the data (startrow if specified) is used as the column names

The sheet of the input files where data is located (if input files are .xls or .xlsx). If not specified defaults to the first sheet

Names to give the widemeasures read in. By default uses the file names if not specified

Should the run names (provided in run_names or inferred from files) be added as a column to the widemeasures? If run_names_header is NULL, they will not be. If run_names_header is a string, that string will be the column header for the column where the names will be stored

If run_names are inferred from filenames, should the leading './' (if any) be retained

If run_names are inferred from filenames, should the path (if any) be retained

If run_names are inferred from filenames, should the file extension (if any) be retained

(optional) non-spectrophotometric data that should be associated with each read widemeasures. A named list where each item in the list is either: a vector of length 2, or a list containing two vectors.

In the former case, each vector should provide the row and column where the metadata is located in all of the blockmeasures input files.

In the latter case, the first vector should provide the rows where the metadata is located in each of the corresponding input files, and the second vector should provide the columns where the metadata is located in each of the corresponding input files. (This case is typically used when reading multiple blocks from a single file.)

A character vector of strings which are to be interpreted as NA values by read.csv, read_xls, read_xlsx, or read.table

Deprecated, use filetype instead

Deprecated, use run_names_header instead

Other arguments passed to read.csv, read_xls, read_xlsx, or read.table

A data.frame

Column name or position

A character vector of the new column names. Use NA to omit the variable in the output.

If NULL, separate_tidy will attempt to infer the new column names by splitting the column name of col

Separator between columns passed to separate:

If character, sep is interpreted as a regular expression.

If numeric, sep is interpreted as character positions to split at. Positive values start at 1 at the far-left of the string; negative values start at -1 at the far-right of the string. The length of sep should be one less than into

logical dictating if strings matching any of na.strings will be coerced into NA values after separating.

A character vector of strings which are to be interpreted as NA values if coerce_NA == TRUE

logical whether column names for into should be printed in a message when inferred

Other arguments passed to separate

Arguments passed to loess, gam, moving_average, moving_median, or smooth.spline. Typically includes tuning parameter(s), which in some cases are required. See Details for more information.

An (often optional) vector of predictor values to smooth along (e.g. time)

A vector of response values to be smoothed (e.g. density). If NULL, formula and data must be provided via ...

Argument specifying which smoothing method should be used to smooth data. Options include "moving-average", "moving-median", "loess", "gam", and "smooth.spline".

An optional vector as long as y. y will be split by the unique values of this vector and the smoothed data for each group will be calculated independently of the others.

This provides an internally-implemented approach similar to group_by and mutate

logical whether entire object returned by fitting function should be returned. If FALSE, just fitted values are returned.

logical whether warning should be issued when smooth_data is being called on ungrouped data and subset_by = NULL.

logical whether warning should be issued when gam is used without s in the formula.

A point on the line

An additional point on the line

An additional point on the line

The slope of the line

logical indicating whether the returned value(s) should be named according to what they are (m, x2, y2, x3, or y3)

A vector of numbers in base-10

Arguments passed to smooth_data. These arguments cannot overlap with any of those to be tuned.

A vector of predictor values to smooth along (e.g. time)

A vector of response values to be smoothed (e.g. density).

Argument specifying which smoothing method should be used. Options include "moving-average", "moving-median", "loess", "gam", and "smooth.spline".

A string vector that defines a pre-processing of the predictor data. The default is no pre-processing. See train for more details.

A numeric vector of case weights. This argument currently does not affect any train_smooth_data models.

A string that specifies what summary metric will be used to select the optimal model. By default, possible values are "RMSE" and "Rsquared" for regression. See train for more details.

A logical: should the metric be maximized or minimized?

A list of values that define how this function acts. See train and trainControl for more details.

A data.frame with possible tuning values, or a named list containing vectors with possible tuning values. If a data frame, the columns should be named the same as the tuning parameters. If a list, the elements of the list should be named the same as the tuning parameters. If a list, expand.grid will be used to make all possible combinations of tuning parameter values.

An integer denoting the amount of granularity in the tuning parameter grid. By default, this argument is the number of levels for each tuning parameter that should be generated. If trControl has the option search = "random", this is the maximum number of tuning parameter combinations that will be generated by the random search. (NOTE: If given, this argument must be named.)

A logical indicating whether the entire result of train should be returned, or only the results element.

Blocks, either a single data.frame or a list of data.frames

string to use as separator for well names between row name and column name (ordered according to colnames_first

A logical indicating the existence of nested metadata in the blockmeasures list, e.g. as is typically output by read_blocks. If NULL, will attempt to infer existence of nested metadata

In the wellnames created by paste-ing the rownames and column names, should the column names come first?

A single wide-shaped data.frame, or a list of wide-shaped data.frame's

Specifies which columns have data vs are ID's (in pivot_longer parlance). Each can be a single vector (which will be applied for all data.frames) or a list of vectors, with each vector corresponding to the same-index data.frame in wides

Entries that are NA in the list will not be used

If neither data_cols nor id_cols are specified, user must provide arguments to pivot_longer via ... for at least the cols argument and these arguments provided via ... will be used for all wides data.frame's

Specifies the output column names created by pivot_longer. Each can be provided as vectors the same length as wides

logical indicating whether values will be coerced to numeric. See below for when this may be overridden by arguments passed in ...

Other arguments to be passed to pivot_longer Note that including values_transform here will override the behavior of values_to_numeric

A list of R objects

How many output sub lists there should be (i.e. how many groups the interleaved list should be divided into)

list of block-shaped data to be written to file

NULL, a character string naming a file to write to, or a vector of character strings naming files to write to.

A file name is required when output_format = "single"

A file name can be specified when output_format = "pasted", or file can be set to NULL as long as block_name_location = "filename" (where pasted block_name metadata will be used for the file name)

File names can be specified when output_format = "multiple", or file can be set to NULL as long as block_name_location = "filename" (where the block_name metadata will be used for the file names)

One of "single", "pasted", "multiple".

"single" will write all blocks into a single csv file, with an empty row between successive blocks.

"pasted" will paste all blocks together using a paste_sep, and then write that now-pasted block to a single csv file.

"multiple" will write each block to its own csv file.

Either NULL, 'filename' or 'file'.

If NULL, block_name_location will be automatically selected based on output_format. For output_format = 'single' and output_format = 'pasted', block_name_location defaults to 'file'. For output_format = 'multiple', block_name_location defaults to 'filename'

If 'filename', the block_name metadata will be used as the output file name(s) when no file name(s) are provided, or appended to file name(s) when they have been provided.

If 'file', the block_name metadata will be included as a row in the output file.

The name of the field containing the block_names

When output_format = 'pasted', what character will be used to paste together blocks.

What character will be used to paste together filenames when block_name_location = 'filename'.

The string to use for missing values in the data.

The directory that file(s) will be written into. When dir = NULL, writes to the current working directory. (Can only be used when file = NULL)

Other arguments passed to write.table