matteodefelice

Keybase proof

I hereby claim:

• I am matteodefelice on github.
• I am matteodefelice (https://keybase.io/matteodefelice) on keybase.
• I have a public key whose fingerprint is 438B DC6E F6CB 8095 4C67 72E3 3D6D 00F8 A83F FA3C

To claim this, I am signing this object:

matteodefelice

library(dplyr)
library(lubridate)
PATH = '/opt/data/ENTSOE/'
DIR  = 'AggregatedGenerationPerType'
YEARs = 2015:2016
MONTHs = 1:12
gen_data = list()
for (YEAR in YEARs) {
  for (MONTH in MONTHs) {
    filename = paste0(PATH, DIR , sprintf("/%d_%d_%s.csv", YEAR, MONTH, DIR))

matteodefelice

## List of files to import
library(tidyverse)
library(stringr)
BASEPATH = '/opt/data/ECEM/ERA/adjusted/'
files = list.files(BASEPATH, pattern = "*csv", recursive = T)
orig_files = files[str_detect(files, 'output')]

# fix double __
files = stringr::str_replace(orig_files, '__', '_')
field_names = c('category', 'generation','originator',

matteodefelice

## This script upload all the csv files into the DIR directory into a sqlite database

library(tidyr) # for data wrangling...
library(dplyr) # ...and connecting with the db
library(readr) # to read the csv files

# Create the db, delete any existing version before running this script
# if we want to use another dbms, there are dplyr::src_mysql, dplyr::src_postgres...
db_name = src_sqlite("ecem_data.sqlite", create = T) 

matteodefelice

##
library(tidyverse)
library(lubridate)
source("process_escii_csv.R")

files <- list.files(
  path = "/opt/data/ECEM/DEMONSTRATOR/demonstrator-061217/DEM",
  pattern = glob2rx("*PWR*01d*NT*"),
  full.names = TRUE
)

matteodefelice

#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
server = ECMWFDataServer()
for i in range(2017, 2018):
    server.retrieve({
        "class": "ei",
        "dataset": "interim",
        "date": str(i) + '0101/' + str(i) + '0201/' + str(i) + '0301/' + str(i) + '0401/' + str(i) + '0501/' + str(i) + '0601/' + str(i) + '0701/' + str(i) + '0801/' + str(i) + '0901/' + str(i) + '1001/' + str(i) + '1101/' + str(i) + '1201',
        "expver": "1",
        "grid": "0.75/0.75",

matteodefelice

import cdstoolbox as ct

@ct.application(title='100m Wind Speed')
@ct.input.dropdown('show_year', values=range(2008, 2018))
@ct.input.dropdown('region', values=['Europe', 'China'])
@ct.input.text('month', type = int, label='Month', default=7)
@ct.input.text('day', type = int, label='Day', default=1)

@ct.output.figure()
def plot_map(show_year, region, month, day):

matteodefelice

import cdstoolbox as ct

@ct.application(title='PV Power Potential', 
               description = 'Computation of PV Power potential for a specific day using the dimensionless described in Mavromatakis et al. https://doi.org/10.1016/j.renene.2009.11.010',
               abstract = 'Lorem Ipsum')
@ct.input.dropdown('show_year', values=range(2010, 2017))
@ct.input.dropdown('region', values=['Europe', 'China'])
@ct.input.text('month', type = int, label='Month', default=7)
@ct.input.text('day', type = int, label='Day', default=1)

matteodefelice

matteodefelice

import cdsapi
import os

c = cdsapi.Client()

VARS = ['100m_u_component_of_wind','100m_v_component_of_wind','10m_u_component_of_wind', '10m_v_component_of_wind', '2m_temperature','surface_solar_radiation_downward_clear_sky','surface_solar_radiation_downwards', '2m_dewpoint_temperature','mean_sea_level_pressure']

YEARS = [x for x in map(str, range(1979, 2019))]

for V in VARS: