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pywafo
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made code python 3 compatible:

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Replaced xrange with range
Replaced map with list comprehension
master
Per A Brodtkorb 9 years ago
parent c903426235
commit cef998d962
10 changed files with 55 additions and 54 deletions
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29
wafo/fig.py
Unescape Escape View File

@ -1,11 +1,11 @@
'''
Module FIG
------------
Module for manipulating windows/figures created using
pylab or enthought.mayavi.mlab on the windows platform.
'''
Module FIG
------------
Module for manipulating windows/figures created using
pylab or enthought.mayavi.mlab on the windows platform.
Figure manipulation involves
maximization, minimization, hiding, closing, stacking or tiling.
Figure manipulation involves
maximization, minimization, hiding, closing, stacking or tiling.
This module assumes that the figures are uniquely numbered in the following way:
Figure 1
@ -21,7 +21,7 @@ Example
-------
>>> import pylab as p
>>> import wafo.fig as fig
>>> for ix in range(6):
>>> for ix in range(6):
... f = p.figure(ix)
>>> fig.stack('all')
>>> fig.stack(1,2)
@ -538,7 +538,7 @@ def stack(*figs):
#% Location (1,1) is at bottom left corner
#
#print('Screensz = ',screenpos)
for iy in xrange(numfigs):
for iy in range(numfigs):
pos = list(GetWindowRect(wnds[iy]))
pos[3] -= pos[1]
pos[2] -= pos[0]
@ -621,7 +621,7 @@ def tile(*figs, **kwds):
#% 3 - Window horizontal size
#% 4 - Window vertical size
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
hspc = 10 # Horisontal space.
topspc = 20; # Space above top figure.
medspc = 10; # Space between figures.
@ -639,10 +639,10 @@ def tile(*figs, **kwds):
#% Put the figures where they belong.
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
idx = 0
for unused_ix in xrange(nlayers):
for row in xrange(nv):
for col in xrange(nh):
if (row) * nh + col < nfigspertile :
for unused_ix in range(nlayers):
for row in range(nv):
for col in range(nh):
if (row) * nh + col < nfigspertile :
if idx < nfigs:
figlft = int(screenpos[0] + (col + 1) * hspc + col * figwid)
figtop = int(screenpos[1] + topspc + row * (fighgt + medspc))
@ -654,6 +654,7 @@ def tile(*figs, **kwds):
#figure(figs[idx]); # Raise figure.
idx += 1
def cycle(*figs, **kwds):
''' Cycle through figure windows.

34
wafo/integrate.py
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@ -255,7 +255,7 @@ def romberg(fun, a, b, releps=1e-3, abseps=1e-3):
# [res,abserr,epstab,newflg] = dea(newflg,Ih4,abserr,epstab)
two = 1
one = 0
for i in xrange(1, tableLimit):
for i in range(1, tableLimit):
h *= 0.5
Un5 = np.sum(fun(a + np.arange(1, 2 * ipower, 2) * h)) * h
@ -265,7 +265,7 @@ def romberg(fun, a, b, releps=1e-3, abseps=1e-3):
fp[i] = 4 * fp[i - 1]
# Richardson extrapolation
for k in xrange(i):
for k in range(i):
rom[two, k + 1] = rom[two, k] + \
(rom[two, k] - rom[one, k]) / (fp[k] - 1)
@ -354,12 +354,12 @@ def h_roots(n, method='newton'):
L = zeros((3, len(z)))
k0 = 0
kp1 = 1
for _its in xrange(max_iter):
for _its in range(max_iter):
# Newtons method carried out simultaneously on the roots.
L[k0, :] = 0
L[kp1, :] = PIM4
for j in xrange(1, n + 1):
for j in range(1, n + 1):
# Loop up the recurrence relation to get the Hermite
# polynomials evaluated at z.
km1 = k0
@ -454,13 +454,13 @@ def j_roots(n, alpha, beta, method='newton'):
L = zeros((3, len(z)))
k0 = 0
kp1 = 1
for _its in xrange(max_iter):
for _its in range(max_iter):
# Newton's method carried out simultaneously on the roots.
tmp = 2 + alfbet
L[k0, :] = 1
L[kp1, :] = (alpha - beta + tmp * z) / 2
for j in xrange(2, n + 1):
for j in range(2, n + 1):
# Loop up the recurrence relation to get the Jacobi
# polynomials evaluated at z.
km1 = k0
@ -565,12 +565,12 @@ def la_roots(n, alpha=0, method='newton'):
k0 = 0
kp1 = 1
k = slice(len(z))
for _its in xrange(max_iter):
for _its in range(max_iter):
# Newton's method carried out simultaneously on the roots.
L[k0, k] = 0.
L[kp1, k] = 1.
for jj in xrange(1, n + 1):
for jj in range(1, n + 1):
# Loop up the recurrence relation to get the Laguerre
# polynomials evaluated at z.
km1 = k0
@ -683,11 +683,11 @@ def p_roots(n, method='newton', a=-1, b=1):
k = slice(m)
k0 = 0
kp1 = 1
for _ix in xrange(max_iter):
for _ix in range(max_iter):
L[k0, k] = 1
L[kp1, k] = xo[k]
for jj in xrange(2, n + 1):
for jj in range(2, n + 1):
km1 = k0
k0 = kp1
kp1 = np.mod(k0 + 1, 3)
@ -712,10 +712,10 @@ def p_roots(n, method='newton', a=-1, b=1):
e1 = n * (n + 1)
for _j in xrange(2):
for _j in range(2):
pkm1 = 1
pk = xo
for k in xrange(2, n + 1):
for k in range(2, n + 1):
t1 = xo * pk
pkp1 = t1 - pkm1 - (t1 - pkm1) / k + t1
pkm1 = pk
@ -1008,7 +1008,7 @@ class _Gaussq(object):
def _initialize(self, wfun, a, b, args):
args = np.broadcast_arrays(*np.atleast_1d(a, b, *args))
a_shape = args[0].shape
args = map(lambda x: np.reshape(x, (-1, 1)), args)
args = [np.reshape(x, (-1, 1)) for x in args]
A, B = args[:2]
args = args[2:]
if wfun in [2, 3]:
@ -1036,7 +1036,7 @@ class _Gaussq(object):
k = np.arange(nk)
opts = (nk, dtype)
val, val_old, abserr = zeros(*opts), ones(*opts), zeros(*opts)
for i in xrange(max_iter):
for i in range(max_iter):
xn, w = self._points_and_weights(gn, wfun, alpha, beta)
x = (xn + shift) * jacob[k, :] + A[k, :]
@ -1181,7 +1181,7 @@ def quadgr(fun, a, b, abseps=1e-5, max_iter=17):
Q0[0] = hh * np.sum(wq * fun(x), axis=0)
# Successive bisection of intervals
for k in xrange(1, max_iter):
for k in range(1, max_iter):
# Interval bisection
hh = hh / 2
@ -1312,7 +1312,7 @@ def qdemo(f, a, b, kmax=9, plot_error=False):
# try various approximations
methods = [trapz, simps, boole, ]
for k in xrange(kmax):
for k in range(kmax):
n = 2 ** (k + 1) + 1
neval[k] = n
x = np.linspace(a, b, n)
@ -1365,7 +1365,7 @@ def qdemo(f, a, b, kmax=9, plot_error=False):
data.append(vals_dic[name])
data.append(err_dic[name])
data = np.vstack(tuple(data)).T
for k in xrange(kmax):
for k in range(kmax):
tmp = data[k].tolist()
print(''.join(fi % t for fi, t in zip(formats, tmp)))
if plot_error:

6
wafo/interpolate.py
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@ -322,7 +322,7 @@ class PPform(object):
dx = xx - self.breaks.take(indxs)
v = pp[0, indxs]
for i in xrange(1, self.order):
for i in range(1, self.order):
v = dx * v + pp[i, indxs]
values = v
@ -409,7 +409,7 @@ class PPform(object):
vv = xs * cof[0, index]
k = self.order
for i in xrange(1, k):
for i in range(1, k):
vv = xs * (vv + cof[i, index])
cof[-1] = np.hstack((0, vv)).cumsum()
@ -419,7 +419,7 @@ class PPform(object):
# def fromspline(self, xk, cvals, order, fill=0.0):
# N = len(xk) - 1
# sivals = np.empty((order + 1, N), dtype=float)
# for m in xrange(order, -1, -1):
# for m in range(order, -1, -1):
# fact = spec.gamma(m + 1)
# res = _fitpack._bspleval(xk[:-1], xk, cvals, order, m)
# res /= fact

4
wafo/kdetools.py
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@ -3172,10 +3172,10 @@ def gridcount(data, X, y=1):
# fact1 = fact1(ones(n,1),:);
bt0 = [0, 0]
X1 = X.ravel()
for ir in xrange(2 ** (d - 1)):
for ir in range(2 ** (d - 1)):
bt0[0] = np.reshape(bitget(ir, np.arange(d)), (d, -1))
bt0[1] = 1 - bt0[0]
for ix in xrange(2):
for ix in range(2):
one = np.mod(ix, 2)
two = np.mod(ix + 1, 2)
# Convert to linear index

6
wafo/misc.py
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@ -1069,7 +1069,7 @@ def findrfc(tp, h=0.0, method='clib'):
if clib is None or method not in ('clib'):
ind = zeros(n, dtype=np.int)
NC = np.int(NC)
for i in xrange(NC):
for i in range(NC):
Tmi = Tstart + 2 * i
Tpl = Tstart + 2 * i + 2
xminus = y[2 * i]
@ -1557,7 +1557,7 @@ def findtc(x_in, v=None, kind=None):
first_is_down_crossing = (x[v_ind[0]] > x[v_ind[0] + 1])
if first_is_down_crossing:
for i in xrange(n_tc):
for i in range(n_tc):
# trough
j = 2 * i
ind[j] = x[v_ind[j] + 1:v_ind[j + 1] + 1].argmin()
@ -1569,7 +1569,7 @@ def findtc(x_in, v=None, kind=None):
ind[n_c - 2] = x[v_ind[n_c - 2] + 1:v_ind[n_c - 1]].argmin()
else: # the first is a up-crossing
for i in xrange(n_tc):
for i in range(n_tc):
# crest
j = 2 * i
ind[j] = x[v_ind[j] + 1:v_ind[j + 1] + 1].argmax()

10
wafo/objects.py
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@ -318,7 +318,7 @@ class LevelCrossings(PlotData):
ff = [f[0], ]
tt = [t[0], ]
for i in xrange(1, n):
for i in range(1, n):
if f[i] > ff[-1]:
ff.append(f[i])
tt.append(t[i])
@ -741,7 +741,7 @@ class CyclePairs(PlotData):
n = extremes.shape[1]
extr = zeros((4, n))
extr[:, 0] = extremes[:, 0]
for i in xrange(1, n):
for i in range(1, n):
if extremes[0, i] == extr[0, ii]:
extr[1:4, ii] = extr[1:4, ii] + extremes[1:4, i]
else:
@ -1563,7 +1563,7 @@ class TimeSeries(PlotData):
>>> import wafo.objects as wo
>>> x = wd.sea()
>>> ts = wo.mat2timeseries(x)
>>> for i in xrange(-3,4):
>>> for i in range(-3,4):
... S, H = ts.wave_height_steepness(method=i)
... print(S[:2],H[:2])
(array([ 0.01186982, 0.04852534]), array([ 0.69, 0.86]))
@ -2207,10 +2207,10 @@ class TimeSeries(PlotData):
plot = plotbackend.plot
subplot = plotbackend.subplot
figs = []
for unused_iz in xrange(nfig):
for unused_iz in range(nfig):
figs.append(plotbackend.figure())
plotbackend.title('Surface elevation from mean water level (MWL).')
for ix in xrange(nsub):
for ix in range(nsub):
if nsub > 1:
subplot(nsub, 1, ix)
h_scale = array([tn[ind[0]], tn[ind[-1]]])

12
wafo/polynomial.py
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@ -961,7 +961,7 @@ def cheb2poly(ck, a=-1, b=1):
y2 = 2. * y
# Clenshaw recurence
for ix in xrange(n - 1):
for ix in range(n - 1):
tmp = b_Nmi
b_Nmi = polymul(y2, b_Nmi) # polynomial multiplication
nb = len(b_Nmip1)
@ -1327,7 +1327,7 @@ def _chebval(x, ck, kind=1):
b_Nmip1 = b_Nmi.copy() # b_(N-i+1)
x2 = 2 * x
# Clenshaw reccurence
for ix in xrange(n - 1):
for ix in range(n - 1):
tmp = b_Nmi
b_Nmi = x2 * b_Nmi - b_Nmip1 + ck[ix]
b_Nmip1 = tmp
@ -1444,7 +1444,7 @@ def chebder(ck, a=-1, b=1):
cder = zeros(n, dtype=asarray(ck).dtype)
cder[0] = 2 * n * ck[0]
cder[1] = 2 * (n - 1) * ck[1]
for j in xrange(2, n):
for j in range(2, n):
cder[j] = cder[j - 2] + 2 * (n - j) * ck[j]
return cder * 2. / (b - a) # Normalize to the interval b-a.
@ -1837,17 +1837,17 @@ def padefitlsq(fun, m, k, a=-1, b=1, trace=False, x=None, end_points=True):
mad = 0
u = zeros((npt, ncof))
for ix in xrange(MAXIT):
for ix in range(MAXIT):
# Set up design matrix for least squares fit.
pow1 = wt
bb = pow1 * (fs + abs(mad) * sign(ee))
for jx in xrange(m + 1):
for jx in range(m + 1):
u[:, jx] = pow1
pow1 = pow1 * x
pow1 = -bb
for jx in xrange(m + 1, ncof):
for jx in range(m + 1, ncof):
pow1 = pow1 * x
u[:, jx] = pow1

4
wafo/stats/estimation.py
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@ -253,7 +253,7 @@ class Profile(object):
for size, step in ((-1, -1), (pvec.size, 1)):
phatfree = phatfree0.copy()
for ix in xrange(k1, size, step):
for ix in range(k1, size, step):
Lmax, phatfree = self._profile_optimum(phatfree, pvec[ix])
self.data[ix] = Lmax
if self.data[ix] < self.alpha_cross_level:
@ -728,7 +728,7 @@ class FitDistribution(rv_frozen):
LL = nnlf(theta, data)
H = zeros((num_par, num_par)) # Hessian matrix
theta = tuple(theta)
for ix in xrange(num_par):
for ix in range(num_par):
sparam = list(theta)
sparam[ix] = theta[ix] + delta
fp = nnlf(sparam, data)

2
wafo/transform/estimation.py
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@ -104,7 +104,7 @@ class TransformEstimator(object):
x = tr.args
mean = tr.mean
sigma = tr.sigma
for ix in xrange(5):
for ix in range(5):
dy = np.diff(tr.data)
if (dy <= 0).any():
dy[dy > 0] = eps

2
wafo/win32_utils.py
Unescape Escape View File

@ -250,7 +250,7 @@ if __name__ == '__main__':
ErrorDlg('This is an example of an error message')
wb = Waitbar('Waitbar example')
# wb2 = Waitbar2('Waitbar example')
for i in xrange(20):
for i in range(20):
print(wb.update(i * 5))
# wb2.update(i)
sleep(0.1)

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