## ----include = FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = FALSE, warning = FALSE, fig.width = 7) Sys.setlocale(locale="english") ## ----echo=FALSE---------------------------------------------------------- library ("knitr") ## ------------------------------------------------------------------------ library ("AeRobiology") ## ----eval=FALSE, echo = TRUE--------------------------------------------- # install.packages("AeRobiology") # library (AeRobiology) ## ----echo = TRUE--------------------------------------------------------- data("munich_pollen") ## ----eval=FALSE, echo = TRUE--------------------------------------------- # install.packages("readxl") # library (readxl) ## ----eval=FALSE, echo = TRUE--------------------------------------------- # Mydata<-read_xlsx("C:/Users/Antonio/Desktop/Prueba Markdown/mydata.xlsx") # ## ----eval=FALSE, echo = TRUE--------------------------------------------- # Mydata<-read_xlsx("C:/Users/Antonio/Desktop/Prueba Markdown/mydata.xlsx", sheet=2) # ## ----echo=TRUE, results='hold'------------------------------------------- str(munich_pollen) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- QualityControl<-quality_control(munich_pollen, result = "table") ## ----echo=TRUE, results='hold'------------------------------------------- head(QualityControl) ## ----echo=TRUE, fig.keep='first', results='hide'------------------------ quality_control(munich_pollen, result = "plot") ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- quality_control(munich_pollen, int.window = 4, perc.miss = 50, ps.method = "percentage", perc = 80) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- Interpolated<-interpollen(munich_pollen[,c(1,6)], method="lineal", plot = TRUE, result = "long") ## ----echo=TRUE, results='hold'------------------------------------------- head(Interpolated) ## ----echo=TRUE, results='hide'------------------------------------------- CompleteData<-interpollen(munich_pollen[,c(1,6)], method="lineal", plot = FALSE, result = "wide") ## ----echo=TRUE, eval=FALSE----------------------------------------------- # calculate_ps(munich_pollen, method="percentage", interpolation=TRUE, int.method = "lineal", plot = F) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- i<-interpollen(munich_pollen[,c(1,6)], method="movingmean", factor = 2, plot = TRUE) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- i2<-interpollen(munich_pollen[,c(1,6)], method="spline", ndays=3, spar=0.7, plot = FALSE) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- i3<-interpollen(munich_pollen[,c(1,6)], method="spline", ndays=5, spar=0.2, plot = TRUE) ## ----echo=TRUE, results='hide', fig.keep='last'-------------------------- i4<-interpollen(munich_pollen, method="tseries", plot = TRUE) ## ----echo = TRUE, results='hide', fig.keep='last', warning=FALSE--------- pollen_season <- calculate_ps(munich_pollen) ## ----echo = FALSE, fig.keep='all', warning=FALSE------------------------- knitr::kable(pollen_season[24:31, ] , format = "html", booktabs = TRUE) ## ----echo = TRUE, fig.keep='last', warning=FALSE------------------------- calculate_ps(munich_pollen[,c(1,6)], plot = TRUE) ## ----echo=TRUE, results='hide', fig.keep='first', eval=FALSE------------- # calculate_ps(munich_pollen[,c(1,6)], method = "percentage", perc = 90, export.result = TRUE) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- calculate_ps(munich_pollen[,c(1,6)], method = "percentage", perc = 90, export.result = FALSE, int.method = "spline") ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- calculate_ps(munich_pollen[,c(1,6)], method = "percentage", perc = 75, export.result = FALSE, interpolation = FALSE) ## ----echo=TRUE, results='hide', fig.keep='first', warning=FALSE---------- pollen_season<-calculate_ps(munich_pollen[,c(1,6)], method = "logistic", derivative = 5, reduction=FALSE) ## ----echo = FALSE, fig.keep='all', warning=FALSE------------------------- knitr::kable(pollen_season, format = "html", booktabs = TRUE ) ## ----echo=TRUE, results='hide', fig.keep='first', warning=FALSE---------- pollen_season<-calculate_ps(munich_pollen[,c(1,6)], method = "logistic", derivative = 6, reduction=FALSE, red.level = 0.8) ## ----echo = FALSE, fig.keep='all', warning=FALSE------------------------- knitr::kable(pollen_season, format = "html", booktabs = TRUE) ## ----echo=TRUE, results='hide', fig.keep='first', warning=FALSE---------- pollen_season<-calculate_ps(munich_pollen[,c(1,6)], method = "clinical", type = "birch") ## ----echo = FALSE, fig.keep='all', warning=FALSE------------------------- knitr::kable(pollen_season, format = "html", booktabs = TRUE) ## ----echo=TRUE, results='hide', fig.keep='first', warning=FALSE---------- pollen_season<-calculate_ps(munich_pollen[,c(1,6)], method = "clinical", n.clinical = 5, window.clinical = 7, th.pollen = 10, th.sum = 100, th.day = 100) ## ----echo = FALSE, fig.keep='all', warning=FALSE------------------------- knitr::kable(pollen_season, format = "html", booktabs = TRUE) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- calculate_ps(munich_pollen[,c(1,6)], method = "grains", window.grains = 3, th.pollen = 2 ) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- calculate_ps(munich_pollen[,c(1,6)], method = "moving", man = 7, th.ma = 4) ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- calculate_ps(munich_pollen[,c(1,3)], method = "moving", man = 7, th.ma = 4, def.season = "interannual") ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- calculate_ps(munich_pollen[,c(1,6)], method = "percentage", perc=95, def.season = "peak") ## ----echo=TRUE, results='hide', fig.keep='first'------------------------- CompleteData<-interpollen(munich_pollen, method="spline", ndays=3, spar=0.7, plot = TRUE, maxdays = 3, result = "wide") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_ps(CompleteData, pollen.type="Alnus", year=2013, fill.col = "orange", axisname = "AeRobiology custom units") ## ----echo = TRUE, results='hide',fig.keep='all', warning=FALSE----------- pollen_calendar(munich_pollen, method = "heatplot", period = "daily", color = "green", interpolation = FALSE) ## ----echo = TRUE, fig.keep='all', warning=FALSE-------------------------- average_values<-pollen_calendar(munich_pollen, method = "heatplot", period = "daily", color = "green", interpolation = FALSE, result = "table") knitr::kable(average_values[82:90, ], format = "html", booktabs = TRUE) ## ----echo = TRUE, results='hide',fig.keep='all', warning=FALSE----------- pollen_calendar(data = munich_pollen, method = "heatplot", period = "daily", color = "red", method.classes = "custom", n.classes = 5, classes = c(5, 25, 50, 200), interpolation = FALSE) ## ----echo = TRUE, results='hide',fig.keep='all', warning=FALSE----------- pollen_calendar(data = munich_pollen, method = "heatplot", period = "daily", color = "purple", method.classes = "custom", n.classes = 5, classes = c(5, 25, 50, 200), start.month = 11, na.remove = FALSE, interpolation = FALSE) ## ----echo = TRUE, results='hide',fig.keep='all', warning=FALSE----------- pollen_calendar(data = munich_pollen, method = "heatplot", period = "weekly", color = "blue", method.classes = "exponential", n.types = 4, y.start = 2011, y.end = 2014, interpolation = FALSE) ## ----echo = TRUE, results='hide',fig.keep='all', warning=FALSE----------- pollen_calendar(data = munich_pollen, method = "phenological", n.types = 5, y.start = 2011, y.end = 2014, interpolation = FALSE) ## ----echo = TRUE, results='hide',fig.keep='all', warning=FALSE----------- pollen_calendar(data = munich_pollen, method = "phenological", perc1 = 90, perc2 = 95, th.pollen = 5, interpolation = FALSE) ## ----echo = TRUE, results='hide', fig.keep='all', warning=FALSE---------- pollen_calendar(data = munich_pollen, method = "violinplot", y.start = 2012, y.end = 2015, interpolation = FALSE) ## ----echo = TRUE, results='hide', fig.keep='all', warning=FALSE---------- pollen_calendar(data = munich_pollen, method = "violinplot", th.pollen = 10, na.rm = FALSE, interpolation = FALSE) ## ----echo = TRUE, results='hide',fig.keep='all', eval=FALSE-------------- # iplot_pollen(munich_pollen, year = 2012) # iplot_years(munich_pollen, pollen = "Betula") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_summary(munich_pollen, pollen = "Betula") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_summary(munich_pollen, pollen = "Betula", mave = 5) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_summary(munich_pollen, pollen = "Betula", mave = 5, normalized = TRUE) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_normsummary(munich_pollen, pollen = "Betula", color.plot = "red") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_normsummary(munich_pollen, pollen = "Betula", color.plot = "green", mave = 5, normalized = TRUE) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- analyse_trend(munich_pollen, interpolation = FALSE, export.result = FALSE, export.plot = FALSE, result="plot") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- analyse_trend(munich_pollen, interpolation = FALSE, export.result = FALSE, export.plot = FALSE, split = FALSE, quantil = 1, result="plot") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- analyse_trend(munich_pollen, interpolation = FALSE, export.result = FALSE, export.plot = FALSE, split=FALSE, quantil = 0.5, result="plot") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- analyse_trend(munich_pollen, interpolation = FALSE, export.result = FALSE, export.plot = FALSE, significant = 1, result = "plot") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- analyse_trend(munich_pollen, interpolation = FALSE, export.result = FALSE, export.plot = FALSE, significant = 1, result="table") ## ----echo = TRUE, results='hide',fig.keep='all', eval=FALSE-------------- # plot_trend(munich_pollen, interpolation = FALSE, export.plot = TRUE, export.result = TRUE) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- iplot_abundance(munich_pollen, interpolation = FALSE, export.plot = FALSE, export.result = FALSE) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- iplot_abundance(munich_pollen, interpolation = FALSE, export.plot = FALSE, export.result = FALSE, n.types = 3) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- iplot_abundance(munich_pollen, interpolation = FALSE, export.plot = FALSE, export.result = FALSE, n.types = 3, y.start = 2011, y.end = 2011, col.bar = "#d63131") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- iplot_abundance(munich_pollen, interpolation = FALSE, export.plot = FALSE, export.result = FALSE, n.types = 3, y.start = 2011, y.end = 2011, col.bar = "#d63131", type.plot = "dynamic") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- iplot_pheno(munich_pollen, method= "percentage", perc=80, int.method="spline", n.types = 8) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- iplot_pheno(munich_pollen, method= "clinical", n.clinical = 3, int.method="spline", n.types = 4) ## ----echo = TRUE, results='hide',fig.keep='all', eval=FALSE-------------- # iplot_pheno(munich_pollen, method= "clinical", n.clinical = 3, int.method="spline", n.types = 4, type.plot = "dynamic") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_ps(munich_pollen, pollen.type="Alnus", year=2011) ## ----echo = TRUE, results='hold', error=TRUE----------------------------- plot_ps(munich_pollen, pollen.type="Alnuscdscscr", year=2011) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_ps(munich_pollen, pollen.type="Alnus", year=2013, method= "percentage", perc=95 ,int.method = "lineal") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_ps(munich_pollen, pollen.type="Alnus", year=2013, method= "percentage", perc=95 ,int.method = "movingmean") ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_ps(munich_pollen, pollen.type="Alnus", year=2013, days = 90) ## ----echo = TRUE, results='hide',fig.keep='all'-------------------------- plot_ps(munich_pollen, pollen.type="Alnus", year=2013, fill.col = "orange", axisname = "AeRobiology custom units") ## ----echo = FALSE, warning=FALSE, message=FALSE-------------------------- library(ggplot2) library(dplyr) ## ----echo = TRUE--------------------------------------------------------- data("POMO_pollen") ## ----echo = TRUE, message=FALSE------------------------------------------ plot_hour(POMO_pollen) ## ----message=FALSE------------------------------------------------------- TO<-plot_hour(POMO_pollen, result ="table") knitr::kable(TO[1:10,], caption = "3-Hourly patterns", row.names = FALSE, digits = 1, format = "html", booktabs = TRUE) ## ---- message=FALSE, echo=TRUE------------------------------------------- plot_hour(POMO_pollen, locations = TRUE) ## ---- message=FALSE, echo=TRUE------------------------------------------- plot_heathour(POMO_pollen) ## ---- message=FALSE, echo=TRUE------------------------------------------- plot_heathour(POMO_pollen, low.col = "darkgreen", mid.col = "moccasin", high.col = "brown") ## ---- message=FALSE, echo=TRUE------------------------------------------- plot_heathour(POMO_pollen, locations = TRUE)