examples/usersguide/int_save.py


########################################################
#
# Copyright (c) 2003-2010 by University of Queensland
# Earth Systems Science Computational Center (ESSCC)
# http://www.uq.edu.au/esscc
#
# Primary Business: Queensland, Australia
# Licensed under the Open Software License version 3.0
# http://www.opensource.org/licenses/osl-3.0.php
#
########################################################

__copyright__="""Copyright (c) 2003-2010 by University of Queensland
Earth Systems Science Computational Center (ESSCC)
http://www.uq.edu.au/esscc
Primary Business: Queensland, Australia"""
__license__="""Licensed under the Open Software License version 3.0
http://www.opensource.org/licenses/osl-3.0.php"""
__url__="https://launchpad.net/escript-finley"


# This example demonstrates both interpolation and saving data in CSV format

from esys.escript import saveDataCSV, sup, interpolateTable
import numpy
from esys.finley import Rectangle

n=4     #Change this to whatever you like
r=Rectangle(n,n)
x=r.getX()
x0=x[0]
x1=x[1]    #we'll use this later
toobig=100  #An exception will be thrown if interpolation produces a value larger than this

#First one dimensional interpolation

#In this example we will interpolate a sine curve
#The values we take from the domain will range from 0 to 1 (inclusive)

sine_table=[0, 0.70710678118654746, 1, 0.70710678118654746, 0, -0.70710678118654746, -1, -0.70710678118654746, 0]

numslices=len(sine_table)-1

minval=0
maxval=1

step=sup(maxval-minval)/numslices   #The width of the gap between entries in the table

result=interpolateTable(sine_table, x0, minval, step, toobig)

#Now we save the input and output for comparison

saveDataCSV("1d.csv", inp=x0, out=result)

#Now 2D interpolation

#This time the sine curve will be at full height along the x (ie x0) axis.
#Its amplitude will decrease to a flat line along x1=1.1

#Interpolate works with numpy arrays so we'll use them
st=numpy.array(sine_table)

table=[st, 0.5*st, 0*st ]   #Note that this table is 2D

#The y dimension should be the outer the dimension of the table
result2=interpolateTable(table, x, (minval,0), (0.55, step), toobig)
saveDataCSV("2d.csv",inp0=x0, inp2=x1, out=result2)
1
2	########################################################
3	#
4	# Copyright (c) 2003-2010 by University of Queensland
5	# Earth Systems Science Computational Center (ESSCC)
6	# http://www.uq.edu.au/esscc
7	#
8	# Primary Business: Queensland, Australia
9	# Licensed under the Open Software License version 3.0
10	# http://www.opensource.org/licenses/osl-3.0.php
11	#
12	########################################################
13
14	__copyright__="""Copyright (c) 2003-2010 by University of Queensland
15	Earth Systems Science Computational Center (ESSCC)
16	http://www.uq.edu.au/esscc
17	Primary Business: Queensland, Australia"""
18	__license__="""Licensed under the Open Software License version 3.0
19	http://www.opensource.org/licenses/osl-3.0.php"""
20	__url__="https://launchpad.net/escript-finley"
21
22
23
24	# This example demonstrates both interpolation and saving data in CSV format
25
26	from esys.escript import saveDataCSV, sup, interpolateTable
27	import numpy
28	from esys.finley import Rectangle
29
30	n=4 #Change this to whatever you like
31	r=Rectangle(n,n)
32	x=r.getX()
33	x0=x[0]
34	x1=x[1] #we'll use this later
35	toobig=100 #An exception will be thrown if interpolation produces a value larger than this
36
37	#First one dimensional interpolation
38
39	#In this example we will interpolate a sine curve
40	#The values we take from the domain will range from 0 to 1 (inclusive)
41
42	sine_table=[0, 0.70710678118654746, 1, 0.70710678118654746, 0, -0.70710678118654746, -1, -0.70710678118654746, 0]
43
44	numslices=len(sine_table)-1
45
46	minval=0
47	maxval=1
48
49	step=sup(maxval-minval)/numslices #The width of the gap between entries in the table
50
51	result=interpolateTable(sine_table, x0, minval, step, toobig)
52
53	#Now we save the input and output for comparison
54
55	saveDataCSV("1d.csv", inp=x0, out=result)
56
57	#Now 2D interpolation
58
59	#This time the sine curve will be at full height along the x (ie x0) axis.
60	#Its amplitude will decrease to a flat line along x1=1.1
61
62	#Interpolate works with numpy arrays so we'll use them
63	st=numpy.array(sine_table)
64
65	table=[st, 0.5st, 0st ] #Note that this table is 2D
66
67	#The y dimension should be the outer the dimension of the table
68	result2=interpolateTable(table, x, (minval,0), (0.55, step), toobig)
69	saveDataCSV("2d.csv",inp0=x0, inp2=x1, out=result2)