alcantarar

% relies on data and functions from https://github.com/alcantarar/dryft.
% Please cite the paper if you use it.
%
% This script reads in vgrf data, filters it, identifies stance phase,
% separates each stance phase, normalizes to stance phase, then plots 
% the mean +/- SD vgrf waveform.
%
% Ryan Alcantara | ryansalcantara@gmail.com

alcantarar

library(ggplot2)
library(dplyr)
library(Metrics)

## Import discrete variables ----
data <- read.csv('data_from_matlab_gui.csv', header = TRUE) # csv compiled from GUI data
data$sub <- as.factor(data$sub)

## Plot Correlation across Slopes ----
ggplot(data = data, 

alcantarar

alcantarar

library(tidyr)
library(caret)
library(quantregForest)
library(ggplot2)
library(ggridges)

head(mtcars)
qrf<- train(mpg ~ cyl + disp + hp + drat + wt, data = mtcars, method = 'qrf')  # train QRF model
n_cars = 8
class(qrf$finalModel) <- 'randomForest'

alcantarar

Data Discontinuity

https://twitter.com/kfreeze17/status/1262435536280539136

Kenzie, you've got a fun situation because in POE2_Data_Discontinuity.xls, it's not just the signal exceeding the +/- 180 range. It's a signal exceeding 2x, 3x... the +/-180 range! I wasn't able to fix it completely with the time I currently have, but I think a place to start is breaking the trial into slices based on the "jumps" occurring in the signal. After you break the trial into slices, you need to shift signals by a certain amount and in a particular direction. That amount will depend on two things:

1. the first value in that slice
2. the number of times the signal has consecutively exceeded the range in the same direction.

What I thought would work is puting some shifting code into a while loop that keeps checking and shifting the slices until

alcantarar

pre_race = c(-5,-4,-3,0,0,0,0,0,0,3,4,5)
post_race_0 = c(-5,2,2,2,2,2,2,3,5,10,20,30)
post_race_24 = c(-5,-2,-1,0,0,0,1,1,1,1,2,3)


y = c(pre_race, post_race_0, post_race_24)
time = rep(c('pre','0hr post', '24hr post'), each = 12)
x = rep(as.factor(1), length(y))

alcantarar

# you need to install Biopython:
# pip install biopython

# Full discussion:
# https://marcobonzanini.wordpress.com/2015/01/12/searching-pubmed-with-python/

from Bio import Entrez

def search(query):
    Entrez.email = 'your.email@example.com'