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api_state()
Check API State
decompose_2_fct()
Decompose data from two sensors
filtering()
Filter by selected criteria.
Not all criteria need to be filled in. Unfilled criteria are set by default so that no filtering is performed.
gg_na_dist()
gg_na_dist
The function gives a graphical representation of NA's distribution (monthly) during a selected period for one sensor.
gg_na_heatmap()
gg_na_heatmap
This function generates a heatmap representation of the proportion of missing values (NA) for different sensors over monthly periods during a selected time frame.
gg_working_sensor()
gg_working_sensor
the function gives a graphical representation of the sensors operation during a selected period,
the representation can be grouped or individual
imp_na()
Impute Missing Data using Linear Interpolation
import_sensor()
Imports data associated with a list of sensors
import_sensor_comp()
Import Sensor Data and Combine
na_prop()
Visualisation NA stats
plot_comparaison()
Comparison time period
plot_deseas()
Plot decomposed data
plot_hour_threshold()
Plots the number of vehicles in each direction for a selected sensor, aswell as the average speed and traffic volume
by hour of the day.
plot_speed()
Visualize speed proportion evolution with trafic
plot_threshold()
Plot Threshold on Speed Chart
prep_comp_data()
Prepares and completes road traffic data by replacing missing hour values with NA
prep_view_data()
Prepare and filter data for viewing
retrieve_sensor()
Retrieves data associated with a sensor from the Telraam API
set_telraam_token()
Saves an Authentication Token for the telraam API
simple_plot()
Number of cars and Heavies as a function of time
write_update_data()
Write or update the sensor data in the data folder
write_update_data_comp()
Write or update the sensor data in the data folder