/
fig3_analyzePlot.R
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fig3_analyzePlot.R
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rm(list=ls())
library(ggplot2)
library(ppcor)
library(mgcv)
library(visreg)
library(scatterplot3d)
library(metR)
library(imager)
library(tidyverse)
library(lmerTest)
library(lavaan)
library(car)
library(data.table)
library(raincloudplots) # need to install from GitHub https://github.com/jorvlan/raincloudplots
setwd('/Users/dalezhou/Box/contemplativeControlCode/daleManuscriptCodeReplication/')
load('data/df_proc.RData')
############
# ANALYSIS #
############
# load data
energy_cost_zero_to_control <- read.csv('results/energy_cost_zero_to_control.txt', sep=' ', header=F)
energy_cost_zero_to_mindfulness <- read.csv('results/energy_cost_zero_to_mindfulness.txt', sep=' ', header=F)
energy_cost_zero_to_mindfulness_natural_react <- read.csv('results/energy_cost_zero_to_mindfulness_natural_react.txt', sep=' ', header=F)
stability_control_react <-read.csv('results/stability_control_react.txt', sep=' ', header=F)
stability_mindfulness_alc_react <-read.csv('results/stability_mindfulness_alc_react.txt', sep=' ', header=F)
stability_mindfulness_downreg <-read.csv('results/stability_mindfulness_downreg.txt', sep=' ', header=F)
########################################################################
# energy for between-group control alc react <-> mindfulness alc react #
########################################################################
df_plot <- as.data.frame(cbind(as.numeric(c(energy_cost_zero_to_control, energy_cost_zero_to_mindfulness_natural_react)), c(rep('energy_cost_zero_to_control', 145), rep('energy_cost_zero_to_mindfulness_natural_react', 145)), paste0("region_", 1:145)))
colnames(df_plot) <- c('energy', 'condition', 'region')
df_plot$energy <- log10(as.numeric(df_plot$energy))
df_plot$condition <- as.factor(df_plot$condition)
df_plot$region <- as.factor(df_plot$region)
df_1x1 <- data_1x1(
array_1 = df_plot$energy[which(df_plot$condition=="energy_cost_zero_to_control")],
array_2 = df_plot$energy[which(df_plot$condition=="energy_cost_zero_to_mindfulness_natural_react")],
jit_distance = 0.09,
jit_seed = 321
)
raincloud_2_aligned <- raincloud_1x1_repmes(
data = df_1x1,
colors = (c('dodgerblue', 'darkorange')),
fills = (c('dodgerblue', 'darkorange')),
line_color = 'gray',
line_alpha = .3,
size = 1,
alpha = .6,
align_clouds = TRUE) +
scale_x_continuous(breaks=c(1,2), labels=c("energy_cost_zero_to_control", "energy_cost_zero_to_mindfulness_natural_react"), limits=c(0, 3)) +
xlab("Time") +
ylab("Score") +
theme_classic()
raincloud_2_aligned
cairo_ps(file = "figs/energyControl_energyMindfulNaturalReact.eps", onefile = FALSE, fallback_resolution = 600)
raincloud_2_aligned
dev.off()
t.test(as.numeric(log10(energy_cost_zero_to_control)), as.numeric(log10(energy_cost_zero_to_mindfulness_natural_react)))
##########################################################################################################
# stability for between-group control condition natural react versus mindfulness condition natural react #
##########################################################################################################
df_plot <- as.data.frame(cbind(as.numeric(c(stability_control_react, stability_mindfulness_alc_react)), c(rep('stability_control_react', 145), rep('stability_mindfulness_alc_react', 145)), paste0("region_", 1:145)))
colnames(df_plot) <- c('energy', 'condition', 'region')
df_plot$energy <- log10(as.numeric(df_plot$energy))
df_plot$condition <- as.factor(df_plot$condition)
df_plot$region <- as.factor(df_plot$region)
df_1x1 <- data_1x1(
array_1 = 1/(df_plot$energy[which(df_plot$condition=="stability_control_react")]),
array_2 = 1/(df_plot$energy[which(df_plot$condition=="stability_mindfulness_alc_react")]),
jit_distance = 0.09,
jit_seed = 321
)
raincloud_2_aligned <- raincloud_1x1_repmes(
data = df_1x1,
colors = (c('dodgerblue', 'darkorange')),
fills = (c('dodgerblue', 'darkorange')),
line_color = 'gray',
line_alpha = .3,
size = 1,
alpha = .6,
align_clouds = TRUE) +
scale_x_continuous(breaks=c(1,2), labels=c("stability_control_react", "stability_mindfulness_alc_react"), limits=c(0, 3)) +
xlab("Time") +
ylab("Score") +
theme_classic()
raincloud_2_aligned
cairo_ps(file = "figs/energyStability_energyMindfulNaturalReact.eps", onefile = FALSE, fallback_resolution = 600)
raincloud_2_aligned
dev.off()
t.test(as.numeric(1/log10(stability_control_react)), as.numeric(1/log10(stability_mindfulness_alc_react)))
############################################################################
# energy for between-group control alc react <-> mindfulness mindful react #
############################################################################
df_plot <- as.data.frame(cbind(as.numeric(c(energy_cost_zero_to_control, energy_cost_zero_to_mindfulness)), c(rep('energy_cost_zero_to_control', 145), rep('energy_cost_zero_to_mindfulness', 145)), paste0("region_", 1:145)))
colnames(df_plot) <- c('energy', 'condition', 'region')
df_plot$energy <- log10(as.numeric(df_plot$energy))
df_plot$condition <- as.factor(df_plot$condition)
df_plot$region <- as.factor(df_plot$region)
# pd = position_dodge(0.15)
# ggplot(data=df_plot, mapping=aes(x=condition, y=energy, group=region)) +
# geom_line(aes(),position=pd) +
# geom_point(aes(color=condition),size=1, position=pd) +
# theme_classic() + theme(legend.position = "none")
df_1x1 <- data_1x1(
array_1 = df_plot$energy[which(df_plot$condition=="energy_cost_zero_to_control")],
array_2 = df_plot$energy[which(df_plot$condition=="energy_cost_zero_to_mindfulness")],
jit_distance = 0.09,
jit_seed = 321
)
raincloud_2_aligned <- raincloud_1x1_repmes(
data = df_1x1,
colors = (c('dodgerblue', 'darkorange')),
fills = (c('dodgerblue', 'darkorange')),
line_color = 'gray',
line_alpha = .3,
size = 1,
alpha = .6,
align_clouds = TRUE) +
scale_x_continuous(breaks=c(1,2), labels=c("energy_cost_zero_to_control", "energy_cost_zero_to_mindfulness"), limits=c(0, 3)) +
xlab("Time") +
ylab("Score") +
theme_classic()
raincloud_2_aligned
cairo_ps(file = "figs/energyControl_energyControlvsMindfulReact.eps", onefile = FALSE, fallback_resolution = 600)
raincloud_2_aligned
dev.off()
t.test(as.numeric(log10(energy_cost_zero_to_control)), as.numeric(log10(energy_cost_zero_to_mindfulness)))
################################################################################################
# energy for between-group control stability alc react <-> mindfulness stability mindful react #
################################################################################################
df_plot <- as.data.frame(cbind(as.numeric(c(stability_control_react, stability_mindfulness_downreg)), c(rep('stability_control_react', 145), rep('stability_mindfulness_downreg', 145)), paste0("region_", 1:145)))
colnames(df_plot) <- c('energy', 'condition', 'region')
df_plot$energy <- log10(as.numeric(df_plot$energy))
df_plot$condition <- as.factor(df_plot$condition)
df_plot$region <- as.factor(df_plot$region)
# pd = position_dodge(0.15)
# ggplot(data=df_plot, mapping=aes(x=condition, y=energy, group=region)) +
# geom_line(aes(),position=pd) +
# geom_point(aes(color=condition),size=1, position=pd) +
# theme_classic() + theme(legend.position = "none")
df_1x1 <- data_1x1(
array_1 = 1/df_plot$energy[which(df_plot$condition=="stability_control_react")],
array_2 = 1/df_plot$energy[which(df_plot$condition=="stability_mindfulness_downreg")],
jit_distance = 0.09,
jit_seed = 321
)
raincloud_2_aligned <- raincloud_1x1_repmes(
data = df_1x1,
colors = (c('dodgerblue', 'darkorange')),
fills = (c('dodgerblue', 'darkorange')),
line_color = 'gray',
line_alpha = .3,
size = 1,
alpha = .6,
align_clouds = TRUE) +
scale_x_continuous(breaks=c(1,2), labels=c("stability_control_react", "stability_mindfulness_downreg"), limits=c(0, 3)) +
xlab("Time") +
ylab("Score") +
theme_classic()
raincloud_2_aligned
cairo_ps(file = "figs/energyStability_ControlvsMindfulReact.eps", onefile = FALSE, fallback_resolution = 600)
raincloud_2_aligned
dev.off()
t.test(as.numeric(1/log10(stability_control_react)), as.numeric(1/log10(stability_mindfulness_downreg)))