Introduction

UI for Microclimatic data for ecological forecasting

API Reference

Refer to

• [R API ]https://github.com/ajijohn/microclimRapi
• [Python API] https://github.com/ajijohn/microclim-api

API keys are to requested prior to interacting with APIs.

Binder

Jupyter+R:

Requirements

• NodeJs >= 6.x

Configurations

setup auth.js with API Keys for Google/Twitter/LinkedIn

Dependencies

Needs MongoDB

sudo apt install -y mongodb

Verify the service’s status:

sudo systemctl status mongodb

To restart MongoDB

sudo systemctl restart mongodb

Use MongoDB shell to create the database and the collections

mongo 

• Create a database 'ebm'
  • Create collections 'post','requests','sessions','users'

Install

$ git clone git://github.com/ajijohn/ebm.git
$ cd ebm
$ npm install

if not found/npm not installed - do the below for Ubuntu

sudo apt update
sudo apt install nodejs
sudo apt install npm

Check the node version

nodejs -v

We have tested on 10.19

$ npm start

$ npm install -g forever

Starting the app

forever start bin/www

Then visit http://localhost:3000/

Communication

Once filtering is done via the microclim.org site, an email will be delivered to your mailbox with the details of the extracted file.

Usage

Note the link from the previous section, and to use the NetCDF file, see the vignette below

# author - Aji John
# credit - http://geog.uoregon.edu/bartlein/courses/geog607/Rmd/netCDF_01.htm


library(chron)
library(RColorBrewer)
library(lattice)
library(ncdf4)

url="http://s3-us-west-2.amazonaws.com/microclim/58741743311c3c0e99dac83d/BGAP_output_interval-daily_aggregation-avg_times-19810101-19810122_created-2017-01-09-2316.nc"
dfile="BGAP_output_interval-daily_aggregation-avg_times-19810101-19810122_created-2017-01-09-2316.nc"

download.file(url, destfile=dfile)

# open a NetCDF file
ncin <- nc_open(dfile)
print(ncin)

lon <- ncvar_get(ncin, "lon")
nlon <- dim(lon)
head(lon)

lat <- ncvar_get(ncin, "lat", verbose = F)
nlat <- dim(lat)
head(lat)

#Number of colums - would be 2 by 2 matrix
print(c(nlon, nlat))

# Number of days multiplied by the granularity (hourly/daily etc)
t <- ncvar_get(ncin, "time")
tunits <- ncatt_get(ncin, "time", "units")
nt <- dim(t)

dname <- "BGAP"  # note: specific to the variabe being s  seclected
tmp.array <- ncvar_get(ncin, dname)

dlname <- ncatt_get(ncin, dname, "long_name")
dunits <- ncatt_get(ncin, dname, "units")
fillvalue <- ncatt_get(ncin, dname, "_FillValue")
dim(tmp.array)

# print the global variables
# reconfirm what was used to filter

created <- ncatt_get(ncin, 0, "createdOn")
startdate <- ncatt_get(ncin, 0, "startdate")
enddate <- ncatt_get(ncin, 0, "enddate")
varname <- ncatt_get(ncin, 0, "varname")

Tests

$ npm test

DOI

License

Apache