/[escript]/trunk/modellib/py_src/input.py
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Contents of /trunk/modellib/py_src/input.py

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Revision 147 - (show annotations)
Fri Aug 12 01:45:47 2005 UTC (17 years, 7 months ago) by jgs
Original Path: trunk/esys2/modellib/py_src/input.py
File MIME type: text/x-python
File size: 9066 byte(s)
erge of development branch dev-02 back to main trunk on 2005-08-12

1 # $Id$
2 from escript.escript import *
3 from escript.modelframe import Model
4 from math import log
5
6 class Sequencer(Model):
7 """@brief runs through time until t_end is reached.
8
9 @param t_end (in) - model is terminate when t_end is passed (default Model.UNDEF_DT)
10 @param dt_max (in) - maximum time step size (default Model.UNDEF_DT)
11 @param t (out) - current time
12
13 """
14 def __init__(self,debug=False):
15 Model.__init__(self,debug=debug)
16 self.declareParameter(t=0., \
17 t_end=Model.UNDEF_DT, \
18 dt_max=Model.UNDEF_DT)
19
20 def doInitialization(self):
21 self.__t_old=self.t
22
23 def doStepPreprocessing(self,dt):
24 self.t=self.__t_old+dt
25
26 def doStepPostprocessing(self,dt):
27 self.__t_old=self.t
28
29 def finalize(self):
30 """true when t has reached t_end"""
31 return self.t>=self.t_end
32
33 def getSafeTimeStepSize(self,dt):
34 """returns dt_max"""
35 return self.dt_max
36
37 class GausseanProfile(Model):
38 """@brief generates a gaussean profile at center x_c, width width and height A over a domain
39
40 @param domain (in) - domain
41 @param x_c (in) - center of the Gaussean profile (default [0.,0.,0.])
42 @param A (in) - height of the profile. A maybe a vector. (default 1.)
43 @param width (in) - width of the profile (default 0.1)
44 @param r (in) - radius of the circle (default = 0)
45 @param out (callable) - profile
46
47
48 In the case that the spatial dimension is two, The third component of x_c is dropped
49 """
50 def __init__(self,debug=False):
51 Model.__init__(self,debug=debug)
52 self.declareParameter(domain=None,
53 x_c=numarray.zeros([3]),
54 A=1.,
55 width=0.1,
56 r=0)
57
58 def out(self):
59 x=self.domain.getX()
60 dim=self.domain.getDim()
61 l=length(x-self.x_c[:dim])
62 m=(l-self.r).whereNegative()
63 return (m+(1.-m)*exp(-log(2.)*(l/self.width)**2))*self.A
64
65 class InterpolateOverBox(Model):
66 """
67 @brief returns values at each time. The values are defined through given values at time node.
68
69 @param domain (in) - domain
70 @param left_bottom_front (in) - coordinates of left,bottom,front corner of the box
71 @param right_top_back (in) - coordinates of the right, top, back corner of the box
72 @param value_left_bottom_front (in) - value at left,bottom,front corner
73 @param value_right_bottom_front (in) - value at right, bottom, front corner
74 @param value_left_top_front (in) - value at left,top,front corner
75 @param value_right_top_front (in) - value at right,top,front corner
76 @param value_left_bottom_back (in) - value at left,bottom,back corner
77 @param value_right_bottom_back (in) - value at right,bottom,back corner
78 @param value_left_top_back (in) - value at left,top,back corner
79 @param value_right_top_back (in) - value at right,top,back corner
80 @param out (callable) - values at doamin locations by bilinear interpolation. for two dimensional domains back values are ignored.
81
82 """
83
84 def __init__(self,debug=False):
85 Model.__init__(self,debug=debug)
86 self.declareParameter(domain=None,
87 left_bottom_front=[0.,0.,0.],
88 right_top_back=[1.,1.,1.],
89 value_left_bottom_front=0.,
90 value_right_bottom_front=0.,
91 value_left_top_front=0.,
92 value_right_top_front=0.,
93 value_left_bottom_back=0.,
94 value_right_bottom_back=0.,
95 value_left_top_back=0.,
96 value_right_top_back=0.)
97
98
99 def out(self):
100 x=self.domain.getX()
101 if self.domain.getDim()==2:
102 f_right=(x[0]-self.left_bottom_front[0])/(self.right_top_back[0]-self.left_bottom_front[0])
103 f_left=1.-f_right
104 f_top=(x[1]-self.left_bottom_front[1])/(self.right_top_back[1]-self.left_bottom_front[1])
105 f_bottom=1.-f_top
106 out=self.value_left_bottom_front * f_left * f_bottom \
107 +self.value_right_bottom_front* f_right * f_bottom \
108 +self.value_left_top_front * f_left * f_top \
109 +self.value_right_top_front * f_right * f_top
110
111 else:
112 f_right=(x[0]-self.left_bottom_front[0])/(self.right_top_back[0]-self.left_bottom_front[0])
113 f_left=1.-f_right
114 f_top=(x[1]-self.left_bottom_front[1])/(self.right_top_back[1]-self.left_bottom_front[1])
115 f_bottom=1.-f_top
116 f_back=(x[2]-self.left_bottom_front[1])/(self.right_top_back[2]-self.left_bottom_front[2])
117 f_front=1.-f_back
118 out=self.value_left_bottom_front * f_left * f_bottom * f_front \
119 +self.value_right_bottom_front* f_right * f_bottom * f_front \
120 +self.value_left_top_front * f_left * f_top * f_front \
121 +self.value_right_top_front * f_right * f_top * f_front \
122 +self.value_left_bottom_back * f_left * f_bottom * f_back \
123 +self.value_right_bottom_back * f_right * f_bottom * f_back \
124 +self.value_left_top_back * f_left * f_top * f_back \
125 +self.value_right_top_back * f_right * f_top * f_back
126 return out
127
128
129 class InterpolatedTimeProfile(Model):
130 """@brief returns values at each time. The values are defined through given values at time node.
131
132 value[i] defines the value at time nodes[i]. Between nodes linear interpolation is used.
133 for time t<nodes[0] value[0] is used and for t>nodes[l] values[l] is used where l=len(nodes)-1.
134
135
136 @param t (in) - current time
137 @param node (in) - list of time nodes
138 @param values (in) - list of values at time nodes
139 @param out (callable) - current value
140
141
142 """
143
144 def __init__(self,debug=False):
145 Model.__init__(self,debug=debug)
146 self.declareParameter(t=0., \
147 nodes=[0.,1.],\
148 values=[1.,1.])
149 def out(self):
150 l=len(self.nodes)-1
151 t=self.t
152 if t<=self.nodes[0]:
153 return self.values[0]
154 else:
155 for i in range(1,l):
156 if t<self.nodes[i]:
157 m=(self.values[i-1]-self.values[i])/(self.nodes[i-1]-self.nodes[i])
158 return m*(t-self.nodes[i-1])+self.values[i-1]
159 return self.values[l]
160
161 class LinearCombination(Model):
162 """@brief returns a linear combination of the f0*v0+f1*v1+f2*v2+f3*v3+f4*v4
163
164 @param f0 (in) numerical object or None (default: None)
165 @param v0 (in) numerical object or None (default: None)
166 @param f1 (in) numerical object or None (default: None)
167 @param v1 (in) numerical object or None (default: None)
168 @param f2 (in) numerical object or None (default: None)
169 @param v2 (in) numerical object or None (default: None)
170 @param f3 (in) numerical object or None (default: None)
171 @param v3 (in) numerical object or None (default: None)
172 @param f4 (in) numerical object or None (default: None)
173 @param v4 (in) numerical object or None (default: None)
174 @param out (callable) - current value
175
176
177 """
178 def __init__(self,debug=False):
179 Model.__init__(self,debug=debug)
180 self.declareParameter(f0=None, \
181 v0=None, \
182 f1=None, \
183 v1=None, \
184 f2=None, \
185 v2=None, \
186 f3=None, \
187 v3=None, \
188 f4=None, \
189 v4=None)
190 def out(self):
191 if not self.f0==None and not self.v0==None:
192 fv0=self.f0*self.v0
193 else:
194 fv0=None
195
196 if not self.f1==None and not self.v1==None:
197 fv1=self.f1*self.v1
198 else:
199 fv1=None
200
201 if not self.f2==None and not self.v2==None:
202 fv2=f2*v2
203 else:
204 fv2=None
205
206 if not self.f3==None and not self.v3==None:
207 fv3=self.f3*self.v3
208 else:
209 fv3=None
210
211 if not self.f4==None and not self.v4==None:
212 fv4=self.f4*self.v4
213 else:
214 fv4=None
215
216 if fv0==None:
217 out=0.
218 else:
219 out=fv0
220 if not fv1==None: out+=fv1
221 if not fv2==None: out+=fv2
222 if not fv3==None: out+=fv3
223 return out

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