cpelley

from functools import wraps
import os


def proc_stat():
    pid = os.getpid()
    fnme = os.path.join('/', 'proc', str(pid), 'status')

    fields = ['VmSize', 'VmRSS', 'VmPeak', 'VmHWM']
    with open(fnme, 'r') as fh:

cpelley

import os
import biggus
import iris
import numpy as np


print iris.__file__, iris.__version__
print biggus.__file__, biggus.__version__

cpelley

from netCDF4 import Dataset
import numpy as np
import os


def process_usage():
    fnme = os.path.join('/', 'proc', str(os.getpid()), 'status')
    usage = {}
    with open(fnme, 'r') as fh:
        for line in fh:

cpelley

def plot_data(*args, **kwargs):
    save = kwargs.pop('save', False)

    import matplotlib.pyplot as plt
    import iris.plot as iplt

    markers = ('+', 'x', 's')

    if save is True:
        plt.switch_backend('Agg')

cpelley

{
 "metadata": {
  "name": "",
  "signature": "sha256:1ccaf1d6efde449dc4d273823364434c19bdd068d41587570ffde0a5be796216"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [

cpelley

{
 "metadata": {
  "name": "",
  "signature": "sha256:9e9b8e73d2e084ca27d4015fe246597f8a1595a35b0bee658170be3636d8c30a"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [

cpelley

import warnings

import iris
import biggus
from iris.analysis._area_weighted import AreaWeightedRegridder \
    as _AreaWeightedRegridder
from iris.experimental.regrid import regrid_weighted_curvilinear_to_rectilinear
import iris.experimental.regrid as eregrid
from iris.analysis._regrid import RectilinearRegridder
import numpy as np

cpelley

import iris
import numpy as np
from shapely.geometry import Polygon


def horizontal_grid(cube):
    return cube.coord(axis='x'), cube.coord(axis='y')


def transform_bbox(points, src_crs, tgt_crs):

cpelley

#!/usr/bin/env python2.7
import subprocess
import sys


DEBUG = False
SVN_EXEC = '/usr/bin/svn'


class SVNError(Exception):

cpelley

>>> import numpy as np
>>> arr = np.ma.array([1, 2, 3, 4], mask=[False, True, False, True])
>>> arr2 = arr.reshape((2, 2))
>>> arr2
masked_array(data =
 [[1 --]
 [3 --]],
             mask =
 [[False  True]
 [False  True]],