def pr2a(file_prefix=None):
lfunc = lorenz.lorenz(16, 45, 4)
ts, xxs = rungekutta.rk4(lfunc, 0.0, numpy.array([-13.0, -12.0, 52.0], dtype=numpy.float64), 0.0001, 300000)
xs = xxs.transpose()[:, 0]
data = numpy.array(zip(xs, ts), dtype=numpy.float64)
ms = tispy.mutual("-D", 16000, input=data)
tau = first_min(ms)
ws = tispy.delay("-d", int(tau), "-m", 7, input=data)
x0 = numpy.array([-35, -35], dtype=numpy.float64)
zs = numpy.array(zip(ws[100000:, 0], ws[100000:, 5]), dtype=numpy.float64)
d_cap = find_loglog_slope(zs, x0, file_prefix=suffixed(file_prefix, "_2a"))
print "Lorenz\tembed\td_cap = {0:.6f}".format(d_cap)
def pr2a(file_prefix=None):
lfunc = lorenz.lorenz(16, 45, 4)
ts, xxs = rungekutta.rk4(
lfunc, 0.0, numpy.array([-13.0, -12.0, 52.0], dtype=numpy.float64),
0.0001, 300000)
xs = xxs.transpose()[:, 0]
data = numpy.array(zip(xs, ts), dtype=numpy.float64)
ms = tispy.mutual('-D', 16000, input=data)
tau = first_min(ms)
ws = tispy.delay('-d', int(tau), '-m', 7, input=data)
x0 = numpy.array([-35, -35], dtype=numpy.float64)
zs = numpy.array(zip(ws[100000:, 0], ws[100000:, 5]), dtype=numpy.float64)
d_cap = find_loglog_slope(zs, x0, file_prefix=suffixed(file_prefix, '_2a'))
print 'Lorenz\tembed\td_cap = {0:.6f}'.format(d_cap)
def extrema():
lfunc = lorenz.lorenz(16, 45, 4)
ts, xxs = rungekutta.rk4(lfunc, 0.0, numpy.array([-13.0, -12.0, 52.0], dtype=numpy.float64), 0.0001, 300000)
xs = xxs.transpose()[:, 0]
data = numpy.array(zip(xs, ts), dtype=numpy.float64)
ms = tispy.mutual("-D", 16000, input=data)
tau = first_min(ms)
print "Tau: {0:.6f}".format(tau)
ws = tispy.delay("-d", int(tau), "-m", 7, input=data)
zs = ws[100000:, :]
mins = numpy.empty(7, dtype=numpy.float64)
maxs = numpy.empty(7, dtype=numpy.float64)
for i in xrange(7):
mins[i] = min(zs[:, i])
maxs[i] = max(zs[:, i])
print "Mins: {0}".format(mins)
print "Maxs: {0}".format(maxs)
def extrema():
lfunc = lorenz.lorenz(16, 45, 4)
ts, xxs = rungekutta.rk4(
lfunc, 0.0, numpy.array([-13.0, -12.0, 52.0], dtype=numpy.float64),
0.0001, 300000)
xs = xxs.transpose()[:, 0]
data = numpy.array(zip(xs, ts), dtype=numpy.float64)
ms = tispy.mutual('-D', 16000, input=data)
tau = first_min(ms)
print 'Tau: {0:.6f}'.format(tau)
ws = tispy.delay('-d', int(tau), '-m', 7, input=data)
zs = ws[100000:, :]
mins = numpy.empty(7, dtype=numpy.float64)
maxs = numpy.empty(7, dtype=numpy.float64)
for i in xrange(7):
mins[i] = min(zs[:, i])
maxs[i] = max(zs[:, i])
print 'Mins: {0}'.format(mins)
print 'Maxs: {0}'.format(maxs)
