diff --git a/pywafo/src/wafo/misc.py b/pywafo/src/wafo/misc.py index db5df41..af3c57d 100644 --- a/pywafo/src/wafo/misc.py +++ b/pywafo/src/wafo/misc.py @@ -6,14 +6,15 @@ from __future__ import division import sys import numpy as np -from numpy import (abs, amax, any, logical_and, arange, linspace, atleast_1d, - array, asarray, broadcast_arrays, ceil, floor, frexp, hypot, - sqrt, arctan2, sin, cos, exp, log, mod, diff, empty_like, - finfo, inf, pi, interp, isnan, isscalar, zeros, ones, +from numpy import (abs, amax, any, logical_and, arange, linspace, atleast_1d, + array, asarray, broadcast_arrays, ceil, floor, frexp, hypot, + sqrt, arctan2, sin, cos, exp, log, mod, diff, empty_like, + finfo, inf, pi, interp, isnan, isscalar, zeros, ones, r_, sign, unique, hstack, vstack, nonzero, where, extract) from scipy.special import gammaln import types import warnings +from wafo import plotbackend try: import wafo.c_library as clib @@ -26,7 +27,7 @@ __all__ = ['JITImport', 'DotDict', 'Bunch', 'printf', 'sub_dict_select', 'parse_kwargs', 'ecross', 'findtc', 'findtp', 'findcross', 'findextrema', 'findrfc', 'rfcfilter', 'common_shape', 'argsreduce', 'stirlerr', 'getshipchar', 'betaloge', 'gravity', 'nextpow2', - 'discretize', 'pol2cart', 'cart2pol', 'ndgrid', 'meshgrid'] + 'discretize', 'pol2cart', 'cart2pol', 'ndgrid', 'meshgrid', 'histgrm'] class JITImport(object): ''' @@ -246,7 +247,7 @@ def _findcross(xn): n = len(xn) iz, = (xn == 0).nonzero() - if len(iz)>0: + if len(iz) > 0: # Trick to avoid turning points on the crossinglevel. if iz[0] == 0: if len(iz) == n: @@ -254,15 +255,15 @@ def _findcross(xn): return zeros(0, dtype=np.int) diz = diff(iz) - if len(diz)>0 and (diz>1).any(): + if len(diz) > 0 and (diz > 1).any(): ix = iz[(diz > 1).argmax()] else: ix = iz[-1] #x(ix) is a up crossing if x(1:ix) = v and x(ix+1) > v. #x(ix) is a downcrossing if x(1:ix) = v and x(ix+1) < v. - xn[0:ix+1] = -xn[ix + 1] - iz = iz[ix+1::] + xn[0:ix + 1] = -xn[ix + 1] + iz = iz[ix + 1::] for ix in iz.tolist(): xn[ix] = xn[ix - 1] @@ -1400,7 +1401,7 @@ def discretize(fun, a, b, tol=0.005, n=5): err = 0.5 * amax(abs((y00 - y) / (abs(y00 + y) + tiny))) return x, y -def discretize2(fun, a,b,tol=0.005, n=5): +def discretize2(fun, a, b, tol=0.005, n=5): ''' Automatic adaptive discretization of function @@ -1432,23 +1433,23 @@ def discretize2(fun, a,b,tol=0.005, n=5): ''' tiny = floatinfo.tiny - n += (mod(n,2)==0) # make sure n is odd + n += (mod(n, 2) == 0) # make sure n is odd x = linspace(a, b, n) fx = fun(x) - n2 = (n-1)/2 - erri = hstack( (zeros((n2,1)), ones((n2,1)) )).ravel() + n2 = (n - 1) / 2 + erri = hstack((zeros((n2, 1)), ones((n2, 1)))).ravel() err = erri.max() err0 = inf #while (err != err0 and err > tol and n < nmax): for j in range(50): - if err!=err0 and np.any(erri > tol): + if err != err0 and np.any(erri > tol): err0 = err # find top errors - I, = where(erri>tol) + I, = where(erri > tol) # double the sample rate in intervals with the most error - y = (vstack(((x[I]+x[I-1])/2, (x[I+1]+x[I])/2)).T).ravel() + y = (vstack(((x[I] + x[I - 1]) / 2, (x[I + 1] + x[I]) / 2)).T).ravel() fy = fun(y) fy0 = interp(y, x, fx) @@ -1456,12 +1457,12 @@ def discretize2(fun, a,b,tol=0.005, n=5): err = erri.max() - x = hstack((x,y)) + x = hstack((x, y)) I = x.argsort() x = x[I] - erri = hstack((zeros(len(fx)),erri))[I] - fx = hstack((fx,fy))[I] + erri = hstack((zeros(len(fx)), erri))[I] + fx = hstack((fx, fy))[I] else: break @@ -1488,7 +1489,7 @@ def pol2cart(theta, rho, z=None): if z is None: return x, y else: - return x,y,z + return x, y, z def cart2pol(x, y, z=None): @@ -1507,7 +1508,7 @@ def cart2pol(x, y, z=None): ''' t, r = arctan2(y, x), hypot(x, y) if z is None: - return t,r + return t, r else: return t, r, z @@ -1849,9 +1850,69 @@ def tranproc(x, f, x0, *xi): warnings.warn('Transformation of derivatives of order>4 not supported.') return y #y0,y1,y2,y3,y4 - +def histgrm(data, n=None, odd=False, scale=False, lintype='b-'): + '''HISTGRM Plot histogram + + CALL: binwidth = histgrm(x,N,odd,scale) + binwidth = the width of each bin + + Parameters + ----------- + x = the data + n = approximate number of bins wanted + (default depending on length(x)) + odd = placement of bins (0 or 1) (default 0) + scale = argument for scaling (default 0) + scale = 1 yields the area 1 under the histogram + lintype : specify color and lintype, see PLOT for possibilities. + + Example: + R=rndgumb(2,2,1,100); + histgrm(R,20,0,1) + hold on + x=linspace(-3,16,200); + plot(x,pdfgumb(x,2,2),'r') + hold off + ''' + + x = np.atleast_1d(data) + if n is None: + n = np.ceil(4 * np.sqrt(np.sqrt(len(x)))) + + mn = x.min() + mx = x.max() + d = (mx - mn) / n * 2 + e = np.floor(np.log(d) / np.log(10)); + m = np.floor(d / 10 ** e) + if m > 5: + m = 5 + elif m > 2: + m = 2 + + d = m * 10 ** e + mn = (np.floor(mn / d) - 1) * d - odd * d / 2 + mx = (np.ceil(mx / d) + 1) * d + odd * d / 2 + limits = np.arange(mn, mx, d) + + + + bin, limits = np.histogram(data, bins=limits, normed=scale) #, new=True) + limits.shape = (-1, 1) + xx = limits.repeat(3, axis=1) + xx.shape = (-1,) + xx = xx[1:-1] + bin.shape = (-1, 1) + yy = bin.repeat(3, axis=1) + #yy[0,0] = 0.0 # pdf + yy[:, 0] = 0.0 # histogram + yy.shape = (-1,) + yy = np.hstack((yy, 0.0)) + plotbackend.plotbackend.plot(xx, yy, lintype, limits, limits * 0) + binwidth = d + return binwidth + def _test_find_cross(): - t = findcross([0, 0, 1, -1, 1],0) + t = findcross([0, 0, 1, -1, 1], 0) def _test_common_shape(): @@ -1936,8 +1997,8 @@ def _test_discretize(): def _test_discretize2(): import numpy as np import pylab as plb - x,y = discretize2(np.cos,0,np.pi) - t = plb.plot(x,y) + x, y = discretize2(np.cos, 0, np.pi) + t = plb.plot(x, y) plb.show() plb.close('all') diff --git a/pywafo/src/wafo/objects.py b/pywafo/src/wafo/objects.py index 2323fcf..31a264f 100644 --- a/pywafo/src/wafo/objects.py +++ b/pywafo/src/wafo/objects.py @@ -895,7 +895,7 @@ class TimeSeries(WafoData): """ fs = 1. / (2 * self.sampling_period()) S, f = psd(self.data.ravel(), Fs=fs, *args, **kwargs) - fact = 2.0 * pi + fact = 2 * 2.0 * pi w = fact * f return _wafospec.SpecData1D(S / fact, w) def trdata(self, method='nonlinear', **options):