R: Wrangle and Analyze Growth Curve Data

# Wrangle and Analyze Growth Curve Data

## Documentation for package ‘gcplyr’ version 1.12.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

auc | Calculate area under the curve
block_tidydesign | Turn tidydesign into block format
calc_deriv | Calculate derivatives of vector of data
centroid | Calculate centroid
CentroidFunctions | Calculate centroid
centroid_both | Calculate centroid
centroid_x | Calculate centroid
centroid_y | Calculate centroid
doubling_time | Calculate doubling time equivalent of per-capita growth rate
example_design_tidy | Design for example growth curve data A tidy-shaped dataset with the experimental design (i.e. plate layout) for the example data included with 'gcplyr'.
example_widedata | Example noisy growth curve data in wide format
example_widedata_noiseless | Example growth curve data in wide format
ExtremaFunctions | Find local extrema of a numeric vector
extr_val | Extract parts of an object
find_local_extrema | Find local extrema of a numeric vector
find_threshold_crosses | Find point(s) when a numeric vector crosses some threshold
first_above | Find point(s) when a numeric vector crosses some threshold
first_below | Find point(s) when a numeric vector crosses some threshold
first_maxima | Find local extrema of a numeric vector
first_minima | Find local extrema of a numeric vector
first_peak | Find the first local maxima of a numeric vector
from_excel | A function that converts base-26 Excel-style letters to numbers
gc_smooth.spline | Fit a Smoothing Spline
import_blockdesigns | Import blockdesigns
import_blockmeasures | Import blockmeasures
lag_time | Calculate lag time
makemethod_train_smooth_data | Create method argument for train of growth curve smoothers
make_design | Make design data.frame(s)
make_designpattern | Make design pattern
make_example | Create R objects or files as seen in vignette examples
make_tidydesign | Make tidy design data.frames
max_gc | Maxima and Minima
mdp | Make design pattern
merge_dfs | Collapse a list of dataframes, or merge two dataframes together
MinMaxGC | Maxima and Minima
min_gc | Maxima and Minima
MovingWindowFunctions | Moving window smoothing
moving_average | Moving window smoothing
moving_median | Moving window smoothing
paste_blocks | Paste a list of blocks into a single block
predict_interpolation | Predict data by linear interpolation from existing data
print_df | Nicely print the contents of a data.frame
read_blocks | Read blocks
read_tidys | Read tidy-shaped files
read_wides | Read wides
separate_tidy | Separate a column into multiple columns
smooth_data | Smooth data
solve_linear | Return missing information about a line
ThresholdFunctions | Find point(s) when a numeric vector crosses some threshold
to_excel | A function that converts numbers into base-26 Excel-style letters
train_smooth_data | Test efficacy of different smoothing parameters
trans_block_to_wide | Transform blocks to wides
trans_wide_to_tidy | Pivot wide-shaped into tidy
uninterleave | Uninterleave list
WhichMinMaxGC | Where is the Min() or Max() or first TRUE or FALSE?
which_max_gc | Where is the Min() or Max() or first TRUE or FALSE?
which_min_gc | Where is the Min() or Max() or first TRUE or FALSE?
write_blocks | Write block designs to csv