monkeybutter

package main

import (
	"bufio"
	"fmt"
	"os"
	"strings"
	"sync"
)

monkeybutter

monkeybutter

package main

import (
	"bufio"
	"flag"
	"fmt"
	"io"
	"log"
	"net/http"
	"net/url"

monkeybutter

package main

import (
	"fmt"
	"unsafe"
)

func main() {
	table := [2][2]uint8{{0, 1}, {2, 3}}
	fmt.Printf("%T, %d\n", table, table)

monkeybutter

import glob
import pandas as pd

df = pd.read_csv("/g/data1/ep1_2/z00/prl900/L8_AU_WGS84_A25/original_scene_list.csv")
print(len(df.index))

total_files = 0
size = 0.0

scenes = glob.glob(df['filepath'][1] + "/*")

monkeybutter

package main

import (
	"fmt"
	"io/ioutil"
	"os"
	"os/exec"
	"path/filepath"
	"runtime"
	"sync"

monkeybutter

# 1.- Band datasets don't have attributes
# 2.- Timestamp is missing from GDAL conversions

import h5py
import numpy as np
import argparse

def aggregator(location):
    id = location.split("/")[-1]
    with h5py.File(location + ".nc", 'w') as aggfile:

monkeybutter

package main

import (
	"fmt"
	"io/ioutil"
	"os"
	"os/exec"
	"path/filepath"
	"runtime"
	"sync"

monkeybutter

import os
import h5py

# Returns min_lat, min_lon, max_lat, max_lon from NetCDF file
def extent_extractor(path):
    with h5py.File(path, 'r') as band:

        geot = [float(x) for x in band["crs"].attrs["GeoTransform"].decode('UTF-8').split(", ")]
        shape = band["Band2"].shape

monkeybutter

import pandas as pd

#Scene list from AWS
df_aws = pd.read_csv("/Users/pablo/Desktop/scene_list (1)")
#Scene list from NCI
df_nci = pd.read_csv("/Users/pablo/Desktop/out.csv")

print(len(df_aws.index))
df_aws = df_aws.drop_duplicates()
print(len(df_aws.index))