| add_clusters | Find and extract clusters from a dataset |
| add_Date_col | Create a Date column in the dataset |
| add_photoperiod | Calculate photoperiod and boundary times |
| add_states | Add states to a dataset based on groups and start/end times |
| add_Time_col | Create a Time-of-Day column in the dataset |
| aggregate_Date | Aggregate dates to a single day |
| aggregate_Datetime | Aggregate Datetime data |
| alphaopic.action.spectra | Alphaopic (+ photopic) action spectra |
| barroso_lighting_metrics | Circadian lighting metrics from Barroso et al. (2014) |
| bright_dark_period | Brightest or darkest continuous period |
| Brown2reference | Add Brown et al. (2022) reference illuminance to a dataset |
| Brown_check | Check whether a value is within the recommended illuminance/MEDI levels by Brown et al. (2022) |
| Brown_cut | Create a state column that cuts light levels into sections by Brown et al. (2022) |
| Brown_rec | Set the recommended illuminance/MEDI levels by Brown et al. (2022) |
| centroidLE | Centroid of light exposure |
| count_difftime | Counts the Time differences (epochs) per group (in a grouped dataset) |
| create_Timedata | create_Timedata |
| cut_Datetime | Create Datetime bins for visualization and calculation |
| data2reference | Create reference data from other data |
| Datetime2Time | Convert Datetime columns to Time columns |
| Datetime_breaks | Create a (shifted) sequence of Datetimes for axis breaks |
| Datetime_limits | Find or set sensible limits for Datetime axis |
| disparity_index | Disparity index |
| dominant_epoch | Determine the dominant epoch/interval of a dataset |
| dose | Calculate the dose (value·hours) |
| dst_change_handler | Handle jumps in Daylight Savings (DST) that are missing in the data |
| dst_change_summary | Get a summary of groups where a daylight saving time change occurs. |
| durations | Calculate duration of data in each group |
| duration_above_threshold | Duration above/below threshold or within threshold range |
| exponential_moving_average | Exponential moving average filter (EMA) |
| exp_zero_inflated | Add a defined number to a numeric and log transform it |
| extract_clusters | Find and extract clusters from a dataset |
| extract_gaps | Extract gap episodes from the data |
| extract_metric | Add metrics to extracted sSummary |
| extract_photoperiod | Calculate photoperiod and boundary times |
| extract_states | Extract summaries of states |
| filter_Date | Filter Datetimes in a dataset. |
| filter_Datetime | Filter Datetimes in a dataset. |
| filter_Datetime_multiple | Filter multiple times based on a list of arguments. |
| filter_Time | Filter Times in a dataset. |
| frequency_crossing_threshold | Frequency of crossing light threshold |
| gain.ratio.tables | Gain / Gain-ratio tables to normalize counts |
| gapless_Datetimes | Create a gapless sequence of Datetimes |
| gap_finder | Check for and output gaps in a dataset |
| gap_handler | Fill implicit gaps in a light logger dataset |
| gap_table | Tabular summary of data and gaps in all groups |
| gg_day | Create a simple Time-of-Day plot of light logger data, faceted by Date |
| gg_days | Create a simple datetime plot of light logger data, faceted by group |
| gg_doubleplot | Double Plots |
| gg_gaps | Visualize gaps and irregular data |
| gg_heatmap | Plot a heatmap across days and times of day |
| gg_overview | Plot an overview of dataset intervals with implicit missing data |
| gg_photoperiod | Add photoperiods to gg_day() or gg_days() plots |
| gg_state | Add states to gg_day() or gg_days() plots |
| has_gaps | Does a dataset have implicit gaps |
| has_irregulars | Does a dataset have irregular data |
| import | Import a light logger dataset or related data |
| import_adjustment | Adjust device imports or make your own |
| import_Dataset | Import a light logger dataset or related data |
| import_Statechanges | Import data that contain 'Datetimes' of 'Statechanges' |
| interdaily_stability | Interdaily stability (IS) |
| interval2state | Adds a state column to a dataset from interval data |
| intradaily_variability | Intradaily variability (IV) |
| join_datasets | Join similar Datasets |
| ll_import_expr | Get the import expression for a device |
| log_zero_inflated | Add a defined number to a numeric and log transform it |
| mean_daily | Calculate mean daily metrics from daily summary |
| mean_daily_metric | Calculate mean daily metrics from Time Series |
| midpointCE | Midpoint of cumulative light exposure. |
| normalize_counts | Normalize counts between sensor outputs |
| number_states | Number non-consecutive state occurrences |
| nvRC | Non-visual circadian response |
| nvRC_circadianBias | Performance metrics for circadian response |
| nvRC_circadianDisturbance | Performance metrics for circadian response |
| nvRC_metrics | Performance metrics for circadian response |
| nvRC_relativeAmplitudeError | Performance metrics for circadian response |
| nvRD | Non-visual direct response |
| nvRD_cumulative_response | Cumulative non-visual direct response |
| period_above_threshold | Length of longest continuous period above/below threshold |
| photoperiod | Calculate photoperiod and boundary times |
| pulses_above_threshold | Pulses above threshold |
| remove_partial_data | Remove groups that have too few data points |
| reverse2_trans | Create a reverse transformation function specifically for date scales |
| sample.data.environment | Sample of wearable data combined with environmental data |
| sample.data.irregular | Sample of highly irregular wearable data |
| sc2interval | Statechange (sc) Timestamps to Intervals |
| sleep_int2Brown | Recode Sleep/Wake intervals to Brown state intervals |
| solar_noon | Calculate photoperiod and boundary times |
| spectral_integration | Integrate spectral irradiance with optional weighting |
| spectral_reconstruction | Reconstruct spectral irradiance from sensor counts |
| summarise_numeric | Summarize numeric columns in dataframes to means |
| summarize_numeric | Summarize numeric columns in dataframes to means |
| supported_devices | Get all the supported devices in LightLogR |
| symlog_trans | Scale positive and negative values on a log scale |
| threshold_for_duration | Find threshold for given duration |
| timing_above_threshold | Mean/first/last timing above/below threshold. |