Package 'OpeNoise'

Title: Environmental Noise Pollution Data Analysis
Description: Provides analyse, interpret and understand noise pollution data. Data are typically regular time series measured with sound meter. The package is partially described in Fogola, Grasso, Masera and Scordino (2023, <DOI:10.61782/fa.2023.0063>).
Authors: Pasquale Scordino [aut, cre], Simone Sperotto [ctb], Stefano Masera [ctb], Daniele Grasso [ctb], Jacopo Fogola [ctb]
Maintainer: Pasquale Scordino <[email protected]>
License: GPL (>= 3)
Version: 0.2-18
Built: 2024-11-21 07:21:23 UTC
Source: CRAN

Help Index

Plot acoustic quantile

Description

Returns a plot of acoustic quantile of 1/3 band frequency

Usage

AcousticQuantilePlot(df, Cols, Quantile, TimeZone = "UTC")

Arguments

df

is a dataframe
Cols

vector of index cols (1/3 band frequency)
Quantile

quantile, for example 0.95
TimeZone

Time zone dataset (default is UTC)

Value

an OpeNoise object of class ggplot

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Plot reverse quantile of 1/3 band frequency

library(lubridate)

datasetI <- dataset_impulsive1
datasetH <- dfImpulsiveTrasform(datasetI)

AcousticQuantilePlot(df = datasetH, Cols =c(3:38), Quantile = 0.95,
                     TimeZone = "UTC")

Weighting acoustic table

Description

Weighting acoustic table

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Calculate reverse Percentile for period

Description

Returns a vector of acoustic percetile

Usage

AcuDNPercentile(df, parameter, from, to, period)

Arguments

df

is a dataframe with Leq data
parameter

is a parameter, example "LAeq"
from

is start hour
to

is end hour
period

is a period night or day

Value

a list of acoustic percentil values by night and daily period

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Calculate reverse quantile of a dataframe by period

data("exampleHourlyData")

AcuDNPercentile(df = exampleHourlyData,
                parameter = "leq",
                from = "5",
                to = "22",
                period = "night")[1:5]

Calculate reverse Percentile

Description

Returns a vector of acoustic percentile

Usage

AcuPercentile(x)

Arguments

x

is a vector with Leq data

Value

vector of acoustic percentil values

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Calculate reverse quantile of a vector of values

#data(PTFA)

AcuPercentile(PTFA$LAeq)

Calculate daily and nightly energetic mean period

Description

Returns a dataframe with energetic mean

Usage

avr.day.night(x, variable, period = "day", stat = "n_mean", ...)

Arguments

x

is a data frame
variable

is variable to apply function
period

is "day" or "night"
stat

is "n_mean" or "e_mean" like mean and energetic mean
...

another arguments

Value

dataframe of energetic mean values by night or daily period

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Calculate energetic mean in nightly period (22-06)

#data(exampleHourlyData)

avr.day.night(exampleHourlyData, "leq", period = "night",
              stat = "e_mean")[1:5, ]

# Calculate energetic mean in daily period (06-22)
avr.day.night(exampleHourlyData, "leq", period = "day",
              stat = "e_mean")[1:5, ]

# Calculate mean in daily period (06-22)
avr.day.night(exampleHourlyData, "leq", period = "day",
              stat = "n_mean")[1:5, ]

Noise dataset of impulsive event (100 ms acquisition time)

Description

Noise dataset of impulsive event (100 ms acquisition time)

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Noise dataset of impulsive event (100 ms acquisition time)

Description

Noise dataset of impulsive event (100 ms acquisition time)

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Calculate energetic sum or difference of values

Description

Returns energetic sum or difference of values

Usage

dbsum(x, y, operator)

Arguments

x

is first value or vector
y

is second value or vector
operator

is 1 for sum and -1 for difference

Value

vector of values contain energetic sum or difference

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Calculate energetic sum or difference of values

dbsum(x = 55, y = 33, operator = 1)
dbsum(x = c(55 , 66), y = c(45, 50), operator = 1)

dbsum(x = c(70 , 68), y = c(55, 66), operator = -1)

Time decomposition

Description

Trasform time from hours, minutes and seconds to seconds

Usage

deco.time(x, y, z, verbose = TRUE)

Arguments

x

are hours
y

are minutes
z

are seconds
verbose

logic argument that on or off message (default is TRUE)

Value

time decomposition in seconds

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Convert H:M:S to seconds
x = 5  # Hours
y = 25 # minutes
z = 50 # seconds

deco.time(x = x, y = y, z = z)

Table's 1/3 octave bandwidth

Description

Table's 1/3 octave bandwidth

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Trasform impulsive dataframe (100 ms samples) in dataframe (1s samples)

Description

Returns a dataframe (1s samples)

Usage

dfImpulsiveTrasform(dfImpulsive, statistic = energetic.mean)

Arguments

dfImpulsive

is a dataframe for impulse (data acquired at 100 ms)
statistic

is energetic mean (default)

Value

dataframe

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data("dataset_impulsive1")
#data("dataset_impulsive2")

dfImpulsiveTrasform(dfImpulsive = dataset_impulsive1,
                    statistic = energetic.mean)[1:5, ]

Weigth logaritmic mean

Description

Calculate weigth logarithmic mean respect to time

Usage

energetic_w.mean(x, t)

Arguments

x

is a vector of value in decibel (dB)
t

is a vector of time string "HH:MM:SS"

Value

weigth logarithmic mean respect to time

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Calculate weight energetic mean
energetic_w.mean(x = c(55.0, 70.0) , t = c("03:55:22", "01:33:12"))

Logarithmic mean

Description

Calculate logarithmic mean

Usage

energetic.mean(x)

Arguments

x

is a vector of value in decibel (dB)

Value

logarithmic mean

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Calculate energetic mean of vector's values of Leq
energetic.mean(c(55, 88, 66, 51, 70))

Function that calculate min value

Description

calculate min value

Usage

energetic.min(y)

Arguments

y

is a numeric vector

Value

energetic min vector value

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Noise hourly data of misure in environmental open space

Description

Noise hourly data of misure in environmental open space

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Extract index and name of markers

Description

Returns a list of index and name

Usage

ExtractIndexMark(filemarks, dataset, mp)

Arguments

filemarks

is a dataframe with date and markers
dataset

is dataframe in analysis
mp

is a name of misure point

Value

list of index and names

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data(PTFA)
#data("markers")

ExtractIndexMark(filemarks = markers , dataset = PTFA, mp = "PTFA")

Calculate Holidays date (Gregorian calendar)

Description

Returns a vector of holiday dates (Gregorian calendar)

Usage

HolidaysDate(year_holiday)

Arguments

year_holiday

is year example "2022" like character

Value

string vector of date

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

HolidaysDate(2022)

Calculate hourly energetic mean

Description

Returns a dataframe with hourly energetic mean

Usage

HourlyEmean(df, variable, timeZone = "Europe/Rome")

Arguments

df

is a dataframe with date (Y-m-d H:M:S) and variables
variable

is a variable name
timeZone

is time zone defoult is Europe/Rome

Value

dataframe of hourly energetic mean values

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data(PTFA)

HourlyEmean(df = PTFA, variable = "LAeq")

Calculate Intrusive Index (UNI/TS 11844 march 2022)

Description

Returns a number

Usage

IntrusiveIndex(dfa, dfr, BW)

Arguments

dfa

is a dataframe Lfa (enviromental sound levels) 1/3 octave specta data
dfr

is a dataframe Lfr (residual sound levels) 1/3 octave specta data
BW

a vector of 1/3 octave bandwidth data

Value

string of intrusive index

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Calculation of the intrusiveness index

library(OpeNoise)
library(lubridate)

data("dataset_impulsive1")
data("dfBW")

# dataset handling
df_Imp_sec <- dfImpulsiveTrasform(dataset_impulsive1,
                                  statistic = energetic.mean)
df_Imp_sec$date <- ymd_hms(df_Imp_sec$date, tz = "Europe/Rome")

# extraction of frequency bands from the dataset
freqDF <- df_Imp_sec[, grep("LZeq\\.", names(df_Imp_sec))]

################################################################################

#                  INTRUSIVENESS INDEX CALCULATION FUNCTION

################################################################################
dfa <- freqDF # Environmental dataset simulation
dfr <- freqDF

# Residual dataset simulation by subtracting 4 from dfa
dfr[c(5,8,12,15), ] <- dfr[c(5,8,12,15), ] - 4

BW <- dfBW$BW # bandwidth

# application of the function
IntrusiveIndex(dfa, dfr, BW)

Parameters table of equal loudness curve A (ISO 226:1987 “Acoustics – Normal equal-loudness-level contours”)

Description

Parameters table of equal loudness curve A (ISO 226:1987 “Acoustics – Normal equal-loudness-level contours”)

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Calculate daily or total Lden (Day-evening-night level)

Description

Returns a dataframe with Lden

Usage

LdenCalculator(dataframe, variable, type = "daily", ...)

Arguments

dataframe

is a dataframe
variable

is name of variable
type

is "daily" or "total"
...

is another arguments

Value

dataframe with Lden values

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data("exampleHourlyData")

LdenCalculator(dataframe = exampleHourlyData, variable = "leq",
               type = "daily")

LdenCalculator(dataframe = exampleHourlyData, variable = "leq",
               type = "total")

Dataset with markers

Description

Dataset with markers

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Add index and name of markers in misure dataframe

Description

Returns a dataframe

Usage

Maskapply(filemarks, dataset, mp)

Arguments

filemarks

is a dataframe with date and markers
dataset

is dataframe in analysis
mp

is a name of misure point

Value

dataframe with add marker column

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data(PTFA)
#data(markers)

Maskapply(filemarks = markers, dataset = PTFA, mp = "PTFA")[1:10, c(1, 2, 45)]

Noise data of misure in house open window condition

Description

Noise data of misure in house open window condition

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Noise data of misure in house close window condition

Description

Noise data of misure in house close window condition

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Plot time history and compare frequency components

Description

Returns a plot

Usage

PlotNoiseTHcompare(
  df,
  variable,
  listvar = NULL,
  mp,
  runleq = TRUE,
  y_lim = c(20, 80)
)

Arguments

df

is a dataframe
variable

is Leq or another variable to plot first
listvar

are names of frequency component you want compare
mp

is a misure point
runleq

is logical value that plot running leq line
y_lim

y axe range

Value

ggplot object

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data(P1FA)

PlotNoiseTHcompare(df = P1FA ,
                   variable = "LAeq",
                   listvar = c("LZFmin.100",
                               "LZFmin.250"), mp = "P1FA",
                   runleq = TRUE,
                   y_lim = c(30, 70))

Plot time history of noise misure with marker and running Leq

Description

Returns a time history plot

Usage

PlotNoiseTimeHistory(
  df = NULL,
  variable = NULL,
  filemarks = NULL,
  escl_marks = NULL,
  mp,
  y_lim = c(20, 80)
)

Arguments

df

is a dataframe with date, leq and markers
variable

is a string name of column you want plot
filemarks

is a dataframe with date and markers
escl_marks

is mark that you want esclude in plot
mp

is a name of misure point
y_lim

y axes range

Value

ggplot object

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data(P1FA)
#data(markers)

PlotNoiseTimeHistory(df = P1FA, variable = "LAeq", mp = "P1FA", y_lim = c(40, 65))

PlotNoiseTimeHistory(df = P1FA, variable = "LAeq", mp = "P1FA",
                     filemarks = markers, y_lim = c(40, 65))

PlotNoiseTimeHistory(df = P1FA, variable = "LAeq", mp = "P1FA", escl_marks = "escludi",
                     y_lim = c(40, 65))

Plot spectrogram

Description

Returns a spectrogram

Usage

PlotSpectrogram(df, coLs, plot_title = NULL)

Arguments

df

is a dataframe
coLs

is cols index to plot
plot_title

is title of plot

Value

ggplot object

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data(P1FA)

PlotSpectrogram(df = P1FA, coLs = c(3:38) , plot_title = "Spettrogram LZFmin")

Noise data of misure in house open window condition

Description

Noise data of misure in house open window condition

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Noise data of misure in house close window condition

Description

Noise data of misure in house close window condition

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Round to Multiple

Description

Returns a number rounded to the nearest specified multiple.

Usage

RoundTo(x, multiple = 1, FUN = round)

Arguments

x

is a vector of value in decibel (dB)
multiple

numeric. The multiple to which the number is to be rounded. Default is 1.
FUN

the rounding function as character or as expression. Can be one out of trunc, ceiling, round (default) or floor.

Value

value or vector of values rounded

Author(s)

Andri Signorell [email protected]

Examples

#data("P1FA")

RoundTo(x = P1FA$LAeq, multiple = 0.5)[1:10]

Calculate running Leq

Description

Returns a vector of energetic mean of Leq......

Usage

runningLeq(x)

Arguments

x

is a vector of values in decibel (dB)

Value

vector of mobile energetic average values

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data("P1FA")

runningLeq(x = P1FA$LAeq)[1:10]

Function research pure tone

Description

research pure tone

Usage

search.tone(x, statistic = energetic.mean, plot.tone = FALSE)

Arguments

x

is a dataframe with llfmin...
statistic

is statistic used default is energetic.mean
plot.tone

is logic argument default is false don't plot result

Value

plot of 1/3 octave frequency and isofonic curve A (ISO 226:1987)

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Search pure tone from PTFA dataset
# dataframe have to contain date and LLfmin (minor value of Linear level frequency)
search.tone(PTFA[, c(3:38)], plot.tone = FALSE)

# Plot result
search.tone(PTFA[, c(3:38)], plot.tone = TRUE)

Search impulsive event

Description

Returns a list with dataframe of peaks impulsive and a plot

Usage

searchImpulse(df, cri1 = 6, cri2 = -10, Threshold = 30)

Arguments

df

is a impulse dataframe, samples of 100 ms
cri1

is first criteria 6dB (LAImax - LASmax > 6dB)
cri2

is second criteria -10dB ((LAFmax - 10dB) < 1s)
Threshold

is minimun level for detect peaks

Value

list contain a dataframe of peaks values and a plot of it

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

#data("dataset_impulsive1")
#data("dataset_impulsive2")

searchImpulse(df = dataset_impulsive1)
searchImpulse(df = dataset_impulsive2)

Calculate SEL (Single Event Level)

Description

Returns SEL

Usage

SELcalc(x, t)

Arguments

x

is value in dB
t

is period in second

Value

value of cumulative energy in 1 second

Author(s)

Pasquale Scordino [email protected]

Simone Sperotto [email protected]

Examples

# Calculate SEL (Single Event Level)

SELcalc(x = 66.8, t = 938)