prl900

runtime: python37

service: pycloud-wms

prl900

Flask==1.0.2
numpy==1.15.4
numexpr==2.6.9
matplotlib==3.0.2
gdal==2.2.2
google-cloud-storage

prl900

from google.cloud import storage
from glob import glob
from os.path import basename, join

gsbucket = "nsw_water_compliance"

def upload_files(gsbucket, dst_path, src_path, wildcard="*"):
    storage_client = storage.Client()
    bucket = storage_client.bucket(gsbucket)
    file_paths = glob("{}/{}".format(src_path, wildcard))

prl900

package main

import (
	"fmt"
	"image"
	"image/color"
	"image/png"
	"os"
)

prl900

import xarray as xr
import numpy as np

tp = xr.open_dataset("EU_TP_ERAI.nc").tp[:].data.astype(np.float32)
print(tp.shape)
np.savez("/g/data/fj4/scratch/tp", tp[:, :, :])

z = xr.open_dataset("EU_Z_ERAI.nc").z[:].data.astype(np.float32)
print(z.shape)
np.savez("/g/data/fj4/scratch/z", z[:, :, :, :])

prl900

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import BatchNormalization, Conv2D
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.callbacks import CSVLogger
from matplotlib import pyplot as plt
import numpy as np


def GetModel(conv1_size):
    model = Sequential()

prl900

from pyproj import Proj, transform
import math

xExtentModis  = 1111950.519666
yExtentModis  = 1111950.519667
sinu_proj = "+proj=sinu +lon_0=0 +x_0=0 +y_0=0 +a=6371007.181 +b=6371007.181 +units=m +no_defs "
wgs84_proj = "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs "

def xy2tile(x, y):
    return int(math.floor(x/xExtentModis)) + 18, -1*int(math.ceil(y/yExtentModis)) + 9

prl900

prl900

import numpy as np
import xarray as xr

# Load ERA5 geopotential levels
era5_ds1 = xr.open_dataset("./datasets/GEOP1000_GAN_2017.nc")
era5_ds2 = xr.open_dataset("./datasets/GEOP800_GAN_2017.nc")
era5_ds3 = xr.open_dataset("./datasets/GEOP500_GAN_2017.nc")
era5_times = era5_ds1.time[:].data

# Load ERA5 total precipitation

prl900

import datacube
from datacube.storage import masking
import matplotlib.pyplot as plt
import numpy as np

dc = datacube.Datacube(app='load-data-example')

query = {
        'lat': (-35.27, -35.33),
        'lon': (149.07, 149.15),