def arrow(x0,y0,x1,y1,color=0,ang=45.0,height=6,width=1.5,lc=None):
"""Draw an arrow.
Description:
Draw an arrow from (x0,y0) to (x1,y1) in the current coordinate system.
Inputs:
x0, y0 -- The beginning point.
x1, y1 -- Then ending point.
color -- The color of the arrowhead. Number represents an index
in the current palette or a negative number or a spelled
out basic color.
lc -- The color of the line (same as color by default).
ang -- The angle of the arrowhead.
height -- The height of the arrowhead in points.
width -- The width of the arrow line in points.
"""
if lc is None:
lc = color
if type(lc) is types.StringType:
lc = _colornum[lc]
if type(color) is types.StringType:
color = _colornum[color]
vp = gist.viewport()
plotlims = gist.limits()
gist.limits(plotlims)
conv_factorx = (vp[1]-vp[0]) / (plotlims[1]-plotlims[0])
conv_factory = (vp[3]-vp[2]) / (plotlims[3]-plotlims[2])
ang = ang*pi/180
height = height*points
hypot = height / cos(ang)
difx = (x1 - x0) * conv_factorx
dify = (y1 - y0) * conv_factory
theta = arctan2(dify,difx) + pi
tha = theta + ang
thb = theta - ang
x1a = x1 + hypot*cos(tha) / conv_factorx
x1b = x1 + hypot*cos(thb) / conv_factorx
y1a = y1 + hypot*sin(tha) / conv_factory
y1b = y1 + hypot*sin(thb) / conv_factory
gist.pldj([x0],[y0],[x1],[y1],color=lc,width=width)
gist.plfp(array([color],'B'),[y1,y1a,y1b],[x1,x1a,x1b],[3])
return
def __init__(self, numPoints, k):
"""numPoints: number of approximation points; k: number of basis functions [2,...,numPoints]"""
self.numPoints = numPoints
self.k = k
## assert k > 1, "Error TrigonomerticBasis: k <= 1"
assert k <= numPoints, "Error TrigonomerticBasis: k > numPoints"
# evaluate trigonometric basis functions on the given number of points from [-pi,pi]
self.x = Numeric.arange(-1*math.pi, math.pi+0.0000001, 2*math.pi/(numPoints-1))
self.y = Numeric.ones((k, numPoints), Numeric.Float)
for kk in range(1, k, 2):
## print "kk, cos %ix" % ((kk+1)/2.)
self.y[kk] = MLab.cos(self.x*(kk+1)/2)
for kk in range(2, k, 2):
## print "kk, sin %ix" % (kk/2.)
self.y[kk] = MLab.sin(self.x*kk/2)
# approx. matrix
self.Ainv = LinearAlgebra.inverse(Numeric.matrixmultiply(self.y, Numeric.transpose(self.y)))
self.yyTinvy = Numeric.matrixmultiply(LinearAlgebra.inverse(Numeric.matrixmultiply(self.y, Numeric.transpose(self.y))), self.y)
def __init__(self, numPoints, k):
"""numPoints: number of approximation points; k: number of basis functions [2,...,numPoints]"""
self.numPoints = numPoints
self.k = k
## assert k > 1, "Error TrigonomerticBasis: k <= 1"
assert k <= numPoints, "Error TrigonomerticBasis: k > numPoints"
# evaluate trigonometric basis functions on the given number of points from [-pi,pi]
self.x = Numeric.arange(-1 * math.pi, math.pi + 0.0000001,
2 * math.pi / (numPoints - 1))
self.y = Numeric.ones((k, numPoints), Numeric.Float)
for kk in range(1, k, 2):
## print "kk, cos %ix" % ((kk+1)/2.)
self.y[kk] = MLab.cos(self.x * (kk + 1) / 2)
for kk in range(2, k, 2):
## print "kk, sin %ix" % (kk/2.)
self.y[kk] = MLab.sin(self.x * kk / 2)
# approx. matrix
self.Ainv = LinearAlgebra.inverse(
Numeric.matrixmultiply(self.y, Numeric.transpose(self.y)))
self.yyTinvy = Numeric.matrixmultiply(
LinearAlgebra.inverse(
Numeric.matrixmultiply(self.y, Numeric.transpose(self.y))),
self.y)