This folder contains code used to compare setaria growth in different environments.
-
inputs/
-
scripts/
folder:
select | |
t.treatment_id :: text as treatmentDbId, | |
t.site_id :: text as observationUnitDbId, | |
t.variable_id :: text as observationVariableDbId, | |
v.name as observationVariableName, | |
t.id :: text as observationDbId, | |
t.mean :: text as value, | |
t.date as observationTimeStamp, | |
s.sitename as observationUnitName, | |
t.cultivar_id :: text as germplasmDbId, |
n_sim <- 10000 | |
mu <- -10 | |
sd <- 2 | |
n <- 30 | |
z <- array(NA, c(3,n_sim)) | |
for(i in 1:n_sim){ | |
x <- rnorm(n, mu, sd) | |
z[1, i] <- mean(x) |
<?xml version="1.0"?><pecan> | |
<info> | |
<notes/> | |
<userid>-1</userid> | |
<username/> | |
<date>2021/01/28 19:56:08 +0000</date> | |
</info> | |
<outdir>/data/workflows/PEcAn_99000000009</outdir> | |
<database> | |
<bety> |
import pgzrun | |
import time | |
import random | |
WIDTH = 400 | |
HEIGHT = 400 | |
guy = Actor("purple_guy") | |
guy.pos = (200, 200) | |
guy.angle = -25 |
library(tidyverse) | |
library(wesanderson) | |
library(cowplot) | |
library(lubridate) | |
allfields <- read_csv('~/Downloads/canopycover_ratiomask.csv') %>% | |
mutate(method = 'French') | |
field3 <- read_csv('~/Downloads/canopycover_ratiomask_field3.csv') %>% | |
mutate(method = 'French') | |
all_tr <- read_csv('~/Downloads/allcanopycover (1).csv') %>% select(-X1) %>% | |
mutate(method = 'Li') |
--- | |
title: "Meta analysis plot organization" | |
output: html_document | |
--- | |
```{r setup, include=FALSE} | |
knitr::opts_chunk$set(echo = TRUE) | |
``` | |
## Lets look at what MA outputs look like |
# from https://pygame-zero.readthedocs.io/en/stable/introduction.html | |
import pgzrun | |
#import random | |
WIDTH = 500 | |
HEIGHT = 1000 | |
alien = Actor('alien') | |
alien.pos = WIDTH/2, HEIGHT/2 |
Formula | What It Accounts for | Limitations | How to Use it | Misc. | Citation(s) |
---|
6000001885 PI_598070 | |
6000001886 PI_533997 | |
6000001887 PI_597946 | |
6000001888 PI_533937 | |
6000001889 PI_655984 | |
6000001890 PI_659695 | |
6000001891 PI_656058 | |
6000001892 PI_533769 | |
6000001893 PI_576364 | |
6000001894 PI_533750 |