/usr/share/pyshared/gvbmod/dispositions.py is in gvb 1.2.1-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | # GVB - a GTK+/GNOME vibrations simulator
#
# Copyright (C) 2008 Pietro Battiston
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#Give startup dispositions of the points
from scipy import array, zeros, sin, cos, pi, concatenate, ones, prod, sqrt
from scipy.linalg import norm
from gvbi18n import _
def disposition(shape, type_descriptor):
# print "shape", shape
if len(shape) in dispositions and type_descriptor in dispositions[len(shape)]:
return dispositions_dict[len(shape)][type_descriptor](shape)
else:
print "type not found:", type_descriptor
return zeros(shape)
waveforms_dict = { #hl=half wave lenght, cen=centering (from 0 to 1), x is between 1 (not 0) and wl-1
'square': (lambda hl, ce, t: 1)
,
'triangular': (lambda hl, ce, t: min(float(t)/ce, float(hl-t)/(1-ce))/hl )
,
'sinusoidal': (lambda hl, ce, t: sin(min(float(t)/(2*ce), float(hl-t)/(2*(1-ce))) * pi/hl) )
,
'peak': (lambda hl, ce, t: max((abs(hl*ce-t),0),(.5,1))[1] )
}
waveforms = ['sinusoidal', 'triangular', 'square', 'peak']
def waveformer_1d((n,), waveform, lenght, shift, wavelenght, fase_angle, height, centering, rule = None):
singlewave = array([waveforms_dict[waveform](wavelenght/2+1, centering, t) for t in range (1,wavelenght/2+1)])
doublewave = concatenate([singlewave, zeros(1), -1*singlewave])*height
fase = wavelenght * fase_angle/360
calculated = doublewave
while len(calculated) < lenght+fase:
calculated = concatenate([calculated, array([0]), doublewave])
# print "stopped extending:", len(calculated)
calculated = calculated[fase:lenght+fase]
# print "calculated clipped:", len(calculated)
wave_clip = lenght - max(0, shift + lenght - n)
zeros_before = shift-(lenght-wave_clip)
zeros_after = n - (shift + wave_clip)
wave_final = concatenate([ calculated[wave_clip:], zeros(zeros_before), calculated[:wave_clip], zeros(zeros_after) ])
# print "first trunk:", calculated[wave_clip:]
# print "fase:", fase, "wave_clipped:", wave_clip
return wave_final
def waveformer_2d((n1,n2), *args):
wave1 = waveformer_1d((n1,), *args[:7])
wave2 = waveformer_1d((n2,), *args[7:14])
rules = {'sum' : sum, 'prod' : prod, 'max' : max, 'min': min}
rule = rules[args[14]]
# print "rule:", rule
#FIXME: really not efficient... should someway use scipy.
wave_final = array( [[rule([wave1[i], wave2[j]]) for i in range(n1)] for j in range(n2)] )
# print "max final:", max ([max(i) for i in wave_final])
return wave_final
waveformer = {1: waveformer_1d, 2: waveformer_2d}
dispositions_1d={ #Dispositions are created combining waveformers and/or other dispositions
'flat': zeros
,
# 'sin': (lambda (n,): array([sin(t*pi*2/(n+1)) for t in range(1,n+1)]))
'sin': (lambda shape: waveformer_1d(shape, 'sinusoidal', shape[0], 0, shape[0], 0, 1, .5 ) )
,
# 'half sin': (lambda (n,): array([sin(t*pi/(n+1)) for t in range(1,n+1)]))
'half sin': (lambda shape: waveformer_1d(shape, 'sinusoidal', shape[0], 0, 2*shape[0]+1, 0, 1, .5 ) )
,
# 'picked': (lambda (n,): array([float(2*min(t, n-t+1))/n for t in range(1,n+1) ]))
'picked': (lambda shape: waveformer_1d(shape, 'triangular', shape[0], 0, 2*shape[0]+1, 0, 1, .5 ) )
,
'triangular signal': (lambda (n,): concatenate([ disposition((n/4,), 'picked'), disposition((n-n/4,), 'flat') ]))
,
'sinusoidal signal': (lambda (n,): concatenate([ disposition((n/4,), 'sin'), disposition((n-n/4,), 'flat') ]))
,
# 'picked lateral': (lambda (n,): array([float(min(float(2*t)/n, float(n-t+1)/n)) for t in range(1,n+1) ]))
'picked lateral': (lambda shape: waveformer_1d(shape, 'triangular', shape[0], 0, 2*shape[0]+1, 0, 1, .25 ) )
,
'opposite triangulars': (lambda (n,): concatenate([ disposition((n/4,), 'picked'), disposition((n-n/4-n/4,), 'flat'), disposition((n/4,), 'picked') ]))
,
'opposite sinusoidals': (lambda (n,): concatenate([ disposition((n/4,), 'sin'), disposition((n-n/4-n/4,), 'flat'), disposition((n/4,), 'sin') ]))
,
'square': ones
,
'square signal': (lambda (n,): concatenate([ disposition((n/4,), 'square'), disposition((n-n/4,), 'flat') ]))
,
# 'discontinuous peak': (lambda (n,): concatenate([ disposition((n/2,), 'flat'), [1], disposition((n-n/2-1,), 'flat') ]))
'discontinuous peak': (lambda shape: waveformer_1d(shape, 'peak', shape[0], 0, 2*shape[0]+1, 0, 1, .5 ) )
,
'cos (shifted)': (lambda shape: waveformer_1d(shape, 'sinusoidal', shape[0], 0, shape[0], 270, 1, .5) + ones(shape) )
}
dispositions_2d={
'flat': zeros
,
# 'picked': (lambda (n,m): array([array([float(2*min(t, m-t+1))/n for t in range(1,m+1) ])*float(2*min(j, n-j+1))/n for j in range(1,n+1)]))
'picked': (lambda shape: waveformer_2d(shape, 'triangular', shape[0], 0, 2*shape[0]+1, 0, .5, .5, 'triangular', shape[0], 0, 2*shape[0]+1, 0, .5, .5 , 'sum' ) )
,
'sin': (lambda shape: waveformer_2d(shape, 'sinusoidal', shape[0], 0, shape[0], 0, 1, .5, 'sinusoidal', shape[0], 0, shape[0], 0, 1, .5 , 'prod' ) )
,
'half sin': (lambda shape: waveformer_2d(shape, 'sinusoidal', shape[0], 0, 2*shape[0]+1, 0, .5, .5, 'sinusoidal', shape[0], 0, 2*shape[0]+1, 0, .5, .5 , 'sum' ) )
,
'pond': (lambda (n,m): array([[(lambda x,y,r : -.1*cos(10*pi*norm([x,y])/r) * max(1-norm([x,y])/r, 0) ) (i-float(m)/2, j-float(n)/2, float(min(m,n))/2) for i in range(1,m+1) ] for j in range(1,n+1)]))
,
'waterfall': (lambda (n,m): array([[(lambda x,y : 1 if norm([x,y]) < min(m,n)/10 else 0)(i-float(m)/2, j-float(n)/2) for i in range(1,m+1) ] for j in range(1,n+1)]))
,
'gut': (lambda (n,m): array([[(lambda x,y,r : -1-cos(8*pi*norm([x,y])/r) if norm([x,y]) < r/8 else 0) (i-float(m)/2, j-float(n)/2, float(min(m,n))) for i in range(1,m+1) ] for j in range(1,n+1)]))
}
dispositions_dict={1:dispositions_1d, 2:dispositions_2d}
dispositions={}
for dim in [1,2]:
keys=dispositions_dict[dim].keys()
keys.sort()
dispositions[dim]=keys
dummy_list_for_gettext=[_('flat'), _('sin'), _('half sin'), _('picked'), _('triangular signal'), _('sinusoidal signal'), _('picked lateral'), _('opposite triangulars'), _('picked'), _('opposite sinusoidals'), _('square'), _('square signal'), _('discontinuous peak'), _('cos (shifted)'), _('pond'), _('waterfall'), _('gut'), _('peak'), _('sinusoidal') ]
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