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comunas_SCL.Rmd
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comunas_SCL.Rmd
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---
title: "R Notebook"
output: html_notebook
---
```{r}
library("tseriesChaos", lib.loc="C:/Users/ignac/anaconda3/envs/rstudio/lib/R/library")
require(scatterplot3d)
library("dplyr", lib.loc="C:/Users/ignac/anaconda3/envs/rstudio/lib/R/library")
library("dplyr", lib.loc="C:/Users/ignac/anaconda3/envs/rstudio/lib/R/library")
library(readr)
```
```{r}
library(readr)
lowest_sp_deaths <- read_csv("C:/Users/ignac/OneDrive - Universidad de Chile/Escritorio/Modelamietno Matematico/Chaos-Presence-SARS-CoV-II/lowest_sp_deaths")
low_sp_deaths <- read_csv("C:/Users/ignac/OneDrive - Universidad de Chile/Escritorio/Modelamietno Matematico/Chaos-Presence-SARS-CoV-II/low_sp_deaths")
middle_sp_deaths <- read_csv("C:/Users/ignac/OneDrive - Universidad de Chile/Escritorio/Modelamietno Matematico/Chaos-Presence-SARS-CoV-II/middle_sp_deaths")
high_sp_deaths <- read_csv("C:/Users/ignac/OneDrive - Universidad de Chile/Escritorio/Modelamietno Matematico/Chaos-Presence-SARS-CoV-II/high_sp_deaths")
highest_sp_deaths <- read_csv("C:/Users/ignac/OneDrive - Universidad de Chile/Escritorio/Modelamietno Matematico/Chaos-Presence-SARS-CoV-II/highest_sp_deaths")
lowest_sp_deaths = lowest_sp_deaths[[1]]
low_sp_deaths = low_sp_deaths[[1]]
middle_sp_deaths = middle_sp_deaths[[1]]
high_sp_deaths = high_sp_deaths[[1]]
highest_sp_deaths = highest_sp_deaths[[1]]
windows()
lm <- 40
mutual_lowest_sp_deaths = mutual(lowest_sp_deaths, lag.max=lm)
windows()
lm <- 40
mutual_low_sp_deaths = mutual(low_sp_deaths, lag.max=lm)
windows()
lm <- 40
mutual_middle_sp_deaths = mutual(middle_sp_deaths, lag.max=lm)
windows()
lm <- 40
mutual_high_sp_deaths = mutual(high_sp_deaths, lag.max=lm)
windows()
lm <- 40
mutual_highest_sp_deaths = mutual(highest_sp_deaths, lag.max=lm)
# Lo pasamos a csv para trabajar en python
df <- data.frame(mutual_lowest_sp_deaths = as.vector(mutual_lowest_sp_deaths),
mutual_low_sp_deaths = as.vector(mutual_low_sp_deaths),
mutual_middle_sp_deaths = as.vector(mutual_middle_sp_deaths),
mutual_high_sp_deaths = as.vector(mutual_high_sp_deaths),
mutual_highest_sp_deaths = as.vector(mutual_highest_sp_deaths))
write.csv(df,"C:\\Users\\ignac\\OneDrive - Universidad de Chile\\Escritorio\\Modelamietno Matematico\\Chaos-Presence-SARS-CoV-II\\data_para_R\\AMI_comunas_SCL.csv", row.names = FALSE)
```
```{r}
# Veamos una estimacion de la Theiler Window
library("nonlinearTseries", lib.loc="C:/Users/ignac/anaconda3/envs/rstudio/lib/R/library")
windows()
require(nonlinearTseries)
spaceTimePlot(time.series=lowest_sp_deaths,embedding.dim=3,time.lag=4,
time.step=1,number.time.steps=50, numberPercentages=10,do.plot=TRUE,
main="",xlab="Separation in time",ylab="Separation in space")
# da 13
windows()
require(nonlinearTseries)
spaceTimePlot(time.series=low_sp_deaths,embedding.dim=3,time.lag=5,
time.step=1,number.time.steps=50, numberPercentages=10,do.plot=TRUE,
main="",xlab="Separation in time",ylab="Separation in space")
# da 13
windows()
require(nonlinearTseries)
spaceTimePlot(time.series=middle_sp_deaths,embedding.dim=3,time.lag=5,
time.step=1,number.time.steps=50, numberPercentages=10,do.plot=TRUE,
main="",xlab="Separation in time",ylab="Separation in space")
# da 15
windows()
require(nonlinearTseries)
spaceTimePlot(time.series=high_sp_deaths,embedding.dim=3,time.lag=8,
time.step=1,number.time.steps=50, numberPercentages=10,do.plot=TRUE,
main="",xlab="Separation in time",ylab="Separation in space")
# da 15
windows()
require(nonlinearTseries)
spaceTimePlot(time.series=highest_sp_deaths,embedding.dim=3,time.lag=11,
time.step=1,number.time.steps=50, numberPercentages=10,do.plot=TRUE,
main="",xlab="Separation in time",ylab="Separation in space")
# da 10
```
```{r}
# Calculamos la dimension con FNN
windows()
m.max<- 6 # embedding dimensions: from 1 to m_max
d<- 4 # tentative time delay (see below)
tw<- 13 # Theiler window
rt<- 20 # escape factor
eps<- sd(lowest_sp_deaths) # neighbourhood diameter
fn_lowest_sp_deaths <- false.nearest(lowest_sp_deaths,m.max,d,tw,rt,eps)
fn_lowest_sp_deaths
plot(fn_lowest_sp_deaths) # da una dimension de inmersion m = 3
windows()
m.max<- 6 # embedding dimensions: from 1 to m_max
d<- 5 # tentative time delay (see below)
tw<- 13 # Theiler window
rt<- 20 # escape factor
eps<- sd(low_sp_deaths) # neighbourhood diameter
fn_low_sp_deaths <- false.nearest(low_sp_deaths,m.max,d,tw,rt,eps)
fn_low_sp_deaths
plot(fn_low_sp_deaths) # da una dimension de inmersion m = 2-3
windows()
m.max<- 6 # embedding dimensions: from 1 to m_max
d<- 5 # tentative time delay (see below)
tw<- 13 # Theiler window
rt<- 20 # escape factor
eps<- sd(middle_sp_deaths) # neighbourhood diameter
fn_middle_sp_deaths <- false.nearest(middle_sp_deaths,m.max,d,tw,rt,eps)
fn_middle_sp_deaths
plot(fn_middle_sp_deaths) # da una dimension de inmersion m = 2-3
windows()
m.max<- 6 # embedding dimensions: from 1 to m_max
d<- 5 # tentative time delay (see below)
tw<- 13 # Theiler window
rt<- 10 # escape factor
eps<- sd(high_sp_deaths) # neighbourhood diameter
fn_high_sp_deaths <- false.nearest(high_sp_deaths,m.max,d,tw,rt,eps)
fn_high_sp_deaths
plot(fn_high_sp_deaths) # da una dimension de inmersion m = 3
windows()
m.max<- 6 # embedding dimensions: from 1 to m_max
d<- 6 # tentative time delay (see below)
tw<- 13 # Theiler window
rt<- 10 # escape factor
eps<- sd(highest_sp_deaths) # neighbourhood diameter
fn_highest_sp_deaths <- false.nearest(highest_sp_deaths,m.max,d,tw,rt,eps)
fn_highest_sp_deaths
plot(fn_highest_sp_deaths) # da una dimension de inmersion m = 3-4
```
```{r}
windows()
S_nu_lowest_sp_deaths <- lyap_k(lowest_sp_deaths,m=3,d=4,t=13,k=4,ref=270,s=50,eps=0.3)
plot(S_nu_lowest_sp_deaths,xlab = expression(paste(nu)),ylab=expression(paste("S",(nu))))
S_nu_lowest_sp_deaths = as.vector(S_nu_lowest_sp_deaths)
windows()
S_nu_low_sp_deaths <- lyap_k(low_sp_deaths,m=3,d=5,t=13,k=4,ref=270,s=50,eps=0.3)
plot(S_nu_low_sp_deaths,xlab = expression(paste(nu)),ylab=expression(paste("S",(nu))))
S_nu_low_sp_deaths = as.vector(S_nu_low_sp_deaths)
windows()
S_nu_middle_sp_deaths <- lyap_k(middle_sp_deaths,m=3,d=5,t=13,k=4,ref=270,s=50,eps=0.3)
plot(S_nu_middle_sp_deaths,xlab = expression(paste(nu)),ylab=expression(paste("S",(nu))))
S_nu_middle_sp_deaths = as.vector(S_nu_middle_sp_deaths)
windows()
S_nu_high_sp_deaths <- lyap_k(high_sp_deaths,m=3,d=5,t=13,k=4,ref=270,s=50,eps=0.3)
plot(S_nu_high_sp_deaths,xlab = expression(paste(nu)),ylab=expression(paste("S",(nu))))
S_nu_high_sp_deaths = as.vector(S_nu_high_sp_deaths)
windows()
S_nu_highest_sp_deaths <- lyap_k(highest_sp_deaths,m=3,d=6,t=10,k=4,ref=250,s=50,eps=0.3)
plot(S_nu_highest_sp_deaths,xlab = expression(paste(nu)),ylab=expression(paste("S",(nu))))
S_nu_highest_sp_deaths = as.vector(S_nu_highest_sp_deaths)
```
```{r}
df_S_nu_comunas_SCL <- data.frame(S_nu_lowest_sp_deaths = as.vector(S_nu_lowest_sp_deaths),
S_nu_low_sp_deaths = as.vector(S_nu_low_sp_deaths),
S_nu_middle_sp_deaths = as.vector(S_nu_middle_sp_deaths),
S_nu_high_sp_deaths = as.vector(S_nu_high_sp_deaths),
S_nu_highest_sp_deaths = as.vector(S_nu_highest_sp_deaths))
write.csv(df_S_nu_comunas_SCL,"C:\\Users\\ignac\\OneDrive - Universidad de Chile\\Escritorio\\Modelamietno Matematico\\Chaos-Presence-SARS-CoV-II\\data_para_R\\S_nu_comunas_SCL.csv", row.names = FALSE)
```