{
"metadata": {
"name": "EGU"
},
"nbformat": 2,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": true,
"input": [
"import numpy as np",
"import matplotlib.pyplot as plt"
],
"language": "python",
"outputs": [],
"prompt_number": 40
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def readxbgrid(xname='x.grd', yname=\"y.grd\"):",
" X = np.loadtxt(xname)",
" Y = np.loadtxt(yname)",
" return X, Y",
"",
"class Grid(object):",
" def __init__(self, *args, **kwargs):",
" self.properties = {}",
" self.shape = None",
" self.X = None",
" self.Y = None",
" ",
" @staticmethod",
" def fromfile(filename):",
" grid = Grid()",
" grid.filename = filename",
" grid.shape = None",
" rows = []",
" with open(filename) as f:",
" for line in f:",
" line = line.strip()",
" # skip comments and empty lines",
" if line.startswith('*') or not line :",
" continue",
" elif '=' in line:",
" key, value = line.split('=')",
" if 'Coordinate' in key:",
" grid.properties[key.strip()] = value.strip()",
" if 'ETA' in key:",
" row = value.split()",
" n, row = row[0], row[1:]",
" while len(row) < grid.shape[1]:",
" line = f.next()",
" row.extend(line.split())",
" rows.append(row)",
" # Read grid size",
" elif grid.shape == None:",
" # line should contain size",
" # convert to nrow x ncolumns",
" grid.shape = tuple(np.array(line.split()[::-1], dtype='int'))",
" assert len(grid.shape) == 2, \"Expected shape (2,), got {}, (subgrids not supported)\".format(grid.shape)",
" # also read next line",
" line = f.next()",
" grid.properties['xori'], grid.properties['yori'], grid.properties['alfori'] = np.array(line.split(), dtype='float')",
" # rows now contains",
" #[X",
" # Y]",
" data = np.array(rows, dtype=\"double\")",
" assert (data.shape[0], data.shape[1]) == (grid.shape[0]*2, grid.shape[1]), \\",
" \"Expected shape of data:{} , got {}\".format((grid.shape[0]*2, grid.shape[1]), (data.shape[0], data.shape[1]))",
" X, Y = data[:grid.shape[0],:], data[grid.shape[0]:,:]",
" grid.X, grid.Y = X, Y ",
" return grid",
" ",
"grid = Grid.fromfile('fijn1.grd')",
"",
"print grid.shape",
"print grid.X.shape",
"print grid.Y.shape",
"print grid.properties"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(153, 129)",
"(153, 129)",
"(153, 129)",
"{'Coordinate System': 'Cartesian', 'xori': 0.0, 'alfori': 0.0, 'yori': 0.0}"
]
}
],
"prompt_number": 91
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"X, Y = readxbgrid(xname=\"x2.grd\", yname=\"y2.grd\")"
],
"language": "python",
"outputs": [],
"prompt_number": 17
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"assert X.shape == Y.shape, \"{} not equal to {}\".format(X.shape, Y.shape)",
"plt.pcolormesh(X,Y,X)"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 18,
"text": [
"<matplotlib.collections.QuadMesh at 0x106229810>"
]
},
{
"output_type": "display_data",
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nO/H6xx9/bO655574V2e7urqm3d+mTZuM3+83N998s7nzzjvNuXPn0u5vJh05\ncsQUFxebpUuXmj179lyROY0x5h//+IcpLS01paWlZvny5fG533//fVNWVpbyK4aTXbfpuO+++8wN\nN9xg8vLyjMfjMc8++2xaPWTyzy65p8bGxqw/n44fP24cDocpLS2Nf9Xy6NGjWb1WqXo6cuRIVq/V\nm2++aVauXGlKS0uN3+83P/jBD4wx6T2vZ7qnK3Wd0ropDwDwf8us+hgKADA7ERYAACvCAgBgRVgA\nAKwICwCAFWEBALD6/wwydpcazaqSAAAAAElFTkSuQmCC\n"
}
],
"prompt_number": 18
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a = \"3 3 2\""
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 37,
"text": [
"array([3, 3, 2])"
]
}
],
"prompt_number": 37
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"outputs": [
{
"ename": "UnpicklingError",
"evalue": "invalid load key, '3'.",
"output_type": "pyerr",
"traceback": [
"---------------------------------------------------------------------------\nUnpicklingError Traceback (most recent call last)",
"/Users/fedorbaart/Documents/checkouts/xcoast/tests/zandmotor_5years_morphotide/<ipython-input-20-b3be03afae85> in <module>()\n----> 1 np.loads(a)\n",
"UnpicklingError: invalid load key, '3'."
]
}
],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": true,
"input": [],
"language": "python",
"outputs": [],
"prompt_number": " "
}
]
}
]
}