Mathematical Morphology in Any Number of Dimensions
This package provides tools for performing mathematical
morphology operations, such as erosion and dilation, on data of
arbitrary dimensionality. It can also be used for smoothing and
other image processing-style operations.

Mathematical morphology in any number of dimensions
This package provides tools for performing mathematical morphology operations, such as erosion and dilation, on data of arbitrary dimensionality. It can also be used for resampling, filtering, smoothing and other image processing-style operations.

stats, methods, graphics, grDevices, reportr, Rcpp
Provides tools for performing mathematical morphology operations, such as erosion and dilation, on data of arbitrary dimensionality. Can also be used for resampling, filtering, smoothing and other image processing-style operations.

Provides tools for performing mathematical morphology operations,
such as erosion and dilation, on data of arbitrary dimensionality. Can also
be used for finding connected components, resampling, filtering, smoothing
and other image processing-style operations.

R interface to POSIX mmap and Window's MapViewOfFile

R interface to POSIX mmap and Window's MapViewOfFile.

Uses memory-mapping to enable the random access of elements of
a text file of characters separated by characters as if it was a simple
R(cpp) matrix.
'RcppExports.R' 'extract.R' 'file-dim.R' 'mmapchar.R'
'mmapcharr-package.r' 'utils.R'

Uses memory-mapping to enable the random access of elements of
a text file of characters separated by characters as if it were a simple
R(cpp) matrix.

c(
person(given = "Adithi R.", family = "Upadhya", email = "adithi@ilklabs.com", role = c("aut", "cre", "cph")),
person(given = "Pratyush", family = "Agrawal", email = "pratyush@ilklabs.com", role = "dtc"),
person(given = "Sreekanth", family = "Vakacherla", email = "sree.hcu@gmail.com", role = c("aui", "ctb")),
person(given = "Meenakshi", family = "Kushwaha", email = "meenakshi@ilklabs.com", role = c("aut", "cph")))
Mobile-monitoring or "sensors on a mobile platform", is an increasingly
popular approach to measure high-resolution pollution data at the street level.
Coupled with location data, spatial visualisation of air-quality parameters
helps detect localized areas of high air-pollution, also called hotspots.
In this approach, portable sensors are mounted on a vehicle and driven on
predetermined routes to collect high frequency data (1 Hz).
'mmaqshiny' is for analysing, visualising and spatial mapping of
high-resolution air-quality data collected by specific devices installed on
a moving platform. 1 Hz data of PM2.5 (mass concentrations of particulate
matter with size less than 2.5 microns), Black carbon mass concentrations
(BC), ultra-fine particle number concentrations, carbon dioxide along with
GPS coordinates and relative humidity (RH) data collected by popular
portable instruments (TSI DustTrak-8530, Aethlabs microAeth-AE51, TSI CPC3007,
LICOR Li-830, Garmin GPSMAP 64s, Omega USB RH probe respectively). It
incorporates device specific cleaning and correction algorithms. RH correction
is applied to DustTrak PM2.5 following the Chakrabarti et al., (2004)
<doi:10.1016/j.atmosenv.2004.03.007>. Provision is given to add linear
regression coefficients for correcting the PM2.5 data (if required). BC data
will be cleaned for the vibration generated noise, by adopting the statistical
procedure as explained in Apte et al., (2011) <doi:10.1016/j.atmosenv.2011.05.028>,
followed by a loading correction as suggested by Ban-Weiss et al., (2009)
<doi:10.1021/es8021039>. For the number concentration data, provision is
given for dilution correction factor (if a diluter is used with CPC3007;
default value is 1). The package joins the raw, cleaned and corrected data
from the above said instruments and outputs as a downloadable csv file.
htmltools, Cairo, xts, lubridate, zoo, caTools, ggplot2,
data.table, DT, dplyr, leaflet, stringr, shiny, XML, shinyjs,
plotly
Adithi R. Upadhya [aut, cre, cph],
Pratyush Agrawal [dtc],
Sreekanth Vakacherla [aui, ctb],
Meenakshi Kushwaha [aut, cph]