nmr_integrate_regions {AlpsNMR} | R Documentation |
Integrate given regions and return a data frame with them
nmr_integrate_regions(samples, regions, ...) ## S3 method for class 'nmr_dataset_1D' nmr_integrate_regions( samples, regions, fix_baseline = TRUE, excluded_regions_as_zero = FALSE, set_negative_areas_to_zero = FALSE, ... )
samples |
A nmr_dataset object |
regions |
A named list. Each element of the list is a region, given as a named numeric vector of length two with the range to integrate. The name of the region will be the name of the column |
... |
Keep for compatibility |
fix_baseline |
A logical. If |
excluded_regions_as_zero |
A logical. It determines the behaviour of the
integration when integrating regions that have been excluded. If If |
set_negative_areas_to_zero |
A logical. Ignored if |
An nmr_dataset_peak_table object
Other peak detection functions:
Pipelines
,
nmr_baseline_threshold()
,
nmr_identify_regions_blood()
,
nmr_identify_regions_cell()
,
nmr_identify_regions_urine()
,
regions_from_peak_table()
,
validate_nmr_dataset_peak_table()
Other peak integration functions:
Pipelines
,
computes_peak_width_ppm()
,
nmr_identify_regions_blood()
,
nmr_identify_regions_cell()
,
nmr_identify_regions_urine()
,
validate_nmr_dataset_peak_table()
Other nmr_dataset_1D functions:
[.nmr_dataset_1D()
,
computes_peak_width_ppm()
,
file_lister()
,
files_to_rDolphin()
,
format.nmr_dataset_1D()
,
is.nmr_dataset_1D()
,
load_and_save_functions
,
new_nmr_dataset_1D()
,
nmr_align_find_ref()
,
nmr_baseline_removal()
,
nmr_baseline_threshold()
,
nmr_exclude_region()
,
nmr_interpolate_1D()
,
nmr_meta_add()
,
nmr_meta_export()
,
nmr_meta_get_column()
,
nmr_meta_get()
,
nmr_normalize()
,
nmr_pca_build_model()
,
nmr_pca_outliers_filter()
,
nmr_pca_outliers_plot()
,
nmr_pca_outliers_robust()
,
nmr_pca_outliers()
,
nmr_ppm_resolution()
,
plot.nmr_dataset_1D()
,
plot_webgl()
,
print.nmr_dataset_1D()
,
rdCV_PLS_RF_ML()
,
rdCV_PLS_RF()
,
save_files_to_rDolphin()
,
to_ChemoSpec()
,
validate_nmr_dataset_peak_table()
,
validate_nmr_dataset()
#Creating a dataset dataset <- new_nmr_dataset_1D(ppm_axis = 1:10, data_1r = matrix(sample(0:99,replace = TRUE), nrow = 10), metadata = list(external = data.frame(NMRExperiment = c("10", "20", "30", "40", "50", "60", "70", "80", "90", "100")))) # Integrating selected regions peak_table_integration = nmr_integrate_regions( samples = dataset, regions = list(ppm = c(2,5)), fix_baseline = TRUE) #Creating a dataset dataset <- new_nmr_dataset_1D(ppm_axis = 1:10, data_1r = matrix(sample(0:99,replace = TRUE), nrow = 10), metadata = list(external = data.frame(NMRExperiment = c("10", "20", "30", "40", "50", "60", "70", "80", "90", "100")))) # Integrating selected regions peak_table_integration = nmr_integrate_regions( samples = dataset, regions = list(ppm = c(2,5)), fix_baseline = TRUE)