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Updated docs in header

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master
Per A Brodtkorb 9 years ago
parent 4f90672e6a
commit 796a5e6d8b
1 changed files with 85 additions and 105 deletions
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wafo/containers.py
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@ -1,7 +1,7 @@
from __future__ import absolute_import from __future__ import absolute_import
import warnings import warnings
from wafo.graphutil import cltext from wafo.graphutil import cltext
from wafo.plotbackend import plotbackend from wafo.plotbackend import plotbackend as plt
from time import gmtime, strftime from time import gmtime, strftime
import numpy as np import numpy as np
from scipy.integrate.quadrature import cumtrapz # @UnresolvedImport from scipy.integrate.quadrature import cumtrapz # @UnresolvedImport
@ -20,14 +20,6 @@ def empty_copy(obj):
return newcopy return newcopy
def _set_seed(iseed):
if iseed is not None:
try:
np.random.set_state(iseed)
except:
np.random.seed(iseed)
def now(): def now():
''' '''
Return current date and time as a string Return current date and time as a string
@ -60,20 +52,22 @@ class PlotData(object):
Example Example
------- -------
>>> import numpy as np >>> import numpy as np
>>> x = np.arange(-2, 2, 0.2) >>> x = np.linspace(0, np.pi, 9)
# Plot 2 objects in one call # Plot 2 objects in one call
>>> d2 = PlotData(np.sin(x), x, xlab='x', ylab='sin', title='sinus') >>> d2 = PlotData(np.sin(x), x, xlab='x', ylab='sin', title='sinus',
... plot_args=['r.'])
h = d2.plot() >>> h = d2.plot()
h1 = d2() >>> h1 = d2()
Plot with confidence interval # Plot with confidence interval
>>> d3 = PlotData(np.sin(x), x) >>> d3 = PlotData(np.sin(x), x)
>>> d3.children = [PlotData(np.vstack([np.sin(x)*0.9, np.sin(x)*1.2]).T,x)] >>> d3.children = [PlotData(np.vstack([np.sin(x)*0.9,
>>> d3.plot_args_children=[':r'] ... np.sin(x)*1.2]).T, x)]
>>> d3.plot_args_children = [':r']
h = d3.plot() >>> h = d3.plot()
''' '''
@ -82,7 +76,7 @@ class PlotData(object):
self.args = args self.args = args
self.date = now() self.date = now()
self.plotter = kwds.pop('plotter', None) self.plotter = kwds.pop('plotter', None)
self.children = None self.children = kwds.pop('children', None)
self.plot_args_children = kwds.pop('plot_args_children', []) self.plot_args_children = kwds.pop('plot_args_children', [])
self.plot_kwds_children = kwds.pop('plot_kwds_children', {}) self.plot_kwds_children = kwds.pop('plot_kwds_children', {})
self.plot_args = kwds.pop('plot_args', []) self.plot_args = kwds.pop('plot_args', [])
@ -133,8 +127,10 @@ class PlotData(object):
... plot_args=['r.']) ... plot_args=['r.'])
>>> di = PlotData(d.eval_points(xi), xi) >>> di = PlotData(d.eval_points(xi), xi)
hi = di.plot() >>> hi = di.plot()
h = d.plot() >>> h = d.plot()
>>> di.to_cdf()
See also See also
-------- --------
@ -154,16 +150,15 @@ class PlotData(object):
warnings.warn(msg) warnings.warn(msg)
else: else:
xi = np.meshgrid(*self.args) xi = np.meshgrid(*self.args)
return interpolate.griddata( return interpolate.griddata(xi, self.data.ravel(), points,
xi, self.data.ravel(), points, **options) **options)
else: # One dimensional data # One dimensional data
return interpolate.griddata( return interpolate.griddata(self.args, self.data, points, **options)
self.args, self.data, points, **options)
def to_cdf(self): def to_cdf(self):
if isinstance(self.args, (list, tuple)): # Multidimensional data if isinstance(self.args, (list, tuple)): # Multidimensional data
raise NotImplementedError('integration for ndim>1 not implemented') raise NotImplementedError('integration for ndim>1 not implemented')
cdf = np.hstack((0, integrate.cumtrapz(self.data, self.args))) cdf = np.hstack((0, cumtrapz(self.data, self.args)))
return PlotData(cdf, np.copy(self.args), xlab='x', ylab='F(x)') return PlotData(cdf, np.copy(self.args), xlab='x', ylab='F(x)')
def integrate(self, a=None, b=None, **kwds): def integrate(self, a=None, b=None, **kwds):
@ -182,40 +177,27 @@ class PlotData(object):
fun = getattr(integrate, method) fun = getattr(integrate, method)
if isinstance(self.args, (list, tuple)): # Multidimensional data if isinstance(self.args, (list, tuple)): # Multidimensional data
raise NotImplementedError('integration for ndim>1 not implemented') raise NotImplementedError('integration for ndim>1 not implemented')
# ndim = len(self.args) # One dimensional data
# if ndim < 2: return_ci = kwds.pop('return_ci', False)
# msg = '''Unable to determine plotter-type, because x = self.args
# len(self.args)<2. if a is None:
# If the data is 1D, then self.args should be a vector! a = x[0]
# If the data is 2D, then length(self.args) should be 2. if b is None:
# If the data is 3D, then length(self.args) should be 3. b = x[-1]
# Unless you fix this, the plot methods will not work!''' ix = np.flatnonzero((a < x) & (x < b))
# warnings.warn(msg) xi = np.hstack((a, x.take(ix), b))
# else: fi = np.hstack((self.eval_points(a), self.data.take(ix),
# return interpolate.griddata(self.args, self.data.ravel(), **kwds) self.eval_points(b)))
else: # One dimensional data res = fun(fi, xi, **kwds)
return_ci = kwds.pop('return_ci', False) if return_ci:
x = self.args return np.hstack(
if a is None: (res, fun(self.dataCI[ix, :].T, xi[1:-1], **kwds)))
a = x[0] return res
if b is None:
b = x[-1]
ix = np.flatnonzero((a < x) & (x < b))
xi = np.hstack((a, x.take(ix), b))
fi = np.hstack(
(self.eval_points(a),
self.data.take(ix),
self.eval_points(b)))
res = fun(fi, xi, **kwds)
if return_ci:
return np.hstack(
(res, fun(self.dataCI[ix, :].T, xi[1:-1], **kwds)))
return res
def plot(self, *args, **kwds): def plot(self, *args, **kwds):
axis = kwds.pop('axis', None) axis = kwds.pop('axis', None)
if axis is None: if axis is None:
axis = plotbackend.gca() axis = plt.gca()
tmp = None tmp = None
default_plotflag = self.plot_kwds.get('plotflag', None) default_plotflag = self.plot_kwds.get('plotflag', None)
plotflag = kwds.get('plotflag', default_plotflag) plotflag = kwds.get('plotflag', default_plotflag)
@ -294,7 +276,7 @@ class AxisLabels:
def labelfig(self, axis=None): def labelfig(self, axis=None):
if axis is None: if axis is None:
axis = plotbackend.gca() axis = plt.gca()
try: try:
h = [] h = []
for fun, txt in zip( for fun, txt in zip(
@ -335,19 +317,19 @@ class Plotter_1d(object):
if plotmethod is None: if plotmethod is None:
plotmethod = 'plot' plotmethod = 'plot'
self.plotmethod = plotmethod self.plotmethod = plotmethod
self.plotbackend = plotbackend # self.plotbackend = plotbackend
# try: # try:
# self.plotfun = getattr(plotbackend, plotmethod) # self.plotfun = getattr(plotbackend, plotmethod)
# except: # except:
# pass # pass
def show(self, *args, **kwds): def show(self, *args, **kwds):
plotbackend.show(*args, **kwds) plt.show(*args, **kwds)
def plot(self, wdata, *args, **kwds): def plot(self, wdata, *args, **kwds):
axis = kwds.pop('axis', None) axis = kwds.pop('axis', None)
if axis is None: if axis is None:
axis = plotbackend.gca() axis = plt.gca()
plotflag = kwds.pop('plotflag', False) plotflag = kwds.pop('plotflag', False)
if plotflag: if plotflag:
h1 = self._plot(axis, plotflag, wdata, *args, **kwds) h1 = self._plot(axis, plotflag, wdata, *args, **kwds)
@ -377,7 +359,7 @@ class Plotter_1d(object):
def plot1d(axis, args, data, dataCI, plotflag, *varargin, **kwds): def plot1d(axis, args, data, dataCI, plotflag, *varargin, **kwds):
plottype = np.mod(plotflag, 10) plottype = np.mod(plotflag, 10)
if plottype == 0: # % No plotting if plottype == 0: # No plotting
return [] return []
elif plottype == 1: elif plottype == 1:
H = axis.plot(args, data, *varargin, **kwds) H = axis.plot(args, data, *varargin, **kwds)
@ -386,18 +368,10 @@ def plot1d(axis, args, data, dataCI, plotflag, *varargin, **kwds):
elif plottype == 3: elif plottype == 3:
H = axis.stem(args, data, *varargin, **kwds) H = axis.stem(args, data, *varargin, **kwds)
elif plottype == 4: elif plottype == 4:
H = axis.errorbar( H = axis.errorbar(args, data,
args, yerr=[dataCI[:, 0] - data,
data, dataCI[:, 1] - data],
yerr=[ *varargin, **kwds)
dataCI[
:,
0] - data,
dataCI[
:,
1] - data],
*varargin,
**kwds)
elif plottype == 5: elif plottype == 5:
H = axis.bar(args, data, *varargin, **kwds) H = axis.bar(args, data, *varargin, **kwds)
elif plottype == 6: elif plottype == 6:
@ -408,10 +382,8 @@ def plot1d(axis, args, data, dataCI, plotflag, *varargin, **kwds):
H = axis.fill_between(args, data, *varargin, **kwds) H = axis.fill_between(args, data, *varargin, **kwds)
elif plottype == 7: elif plottype == 7:
H = axis.plot(args, data, *varargin, **kwds) H = axis.plot(args, data, *varargin, **kwds)
H = axis.fill_between( H = axis.fill_between(args, dataCI[:, 0], dataCI[:, 1],
args, dataCI[ alpha=0.2, color='r')
:, 0], dataCI[
:, 1], alpha=0.2, color='r')
scale = plotscale(plotflag) scale = plotscale(plotflag)
logXscale = 'x' in scale logXscale = 'x' in scale
@ -467,16 +439,32 @@ def plotscale(plotflag):
if (mod(floor(scaleId/10),10)>0) : Log scale on y-axis. if (mod(floor(scaleId/10),10)>0) : Log scale on y-axis.
if (mod(floor(scaleId/100),10)>0) : Log scale on z-axis. if (mod(floor(scaleId/100),10)>0) : Log scale on z-axis.
scale = string defining plotscale valid options are: scale = string defining plotscale valid options are:
'linear', 'xlog', 'ylog', 'xylog', 'zlog', 'xzlog', 'linear', 'xlog', 'ylog', 'xylog', 'zlog', 'xzlog',
'yzlog', 'xyzlog' 'yzlog', 'xyzlog'
Example Examples
plotscale(100) % xlog --------
plotscale(200) % xlog >>> for i in range(7):
plotscale(1000) % ylog ... plotscale(i*100)
'linear'
See also plotscale 'xlog'
'ylog'
'xylog'
'zlog'
'xzlog'
'yzlog'
>>> plotscale(100)
'xlog'
>>> plotscale(1000)
'ylog'
>>> plotscale(10000)
'zlog'
See also
---------
plotscale
''' '''
scaleId = plotflag // 100 scaleId = plotflag // 100
if scaleId > 7: if scaleId > 7:
@ -485,15 +473,8 @@ def plotscale(plotflag):
logZscaleId = (np.mod(scaleId // 100, 10) > 0) * 4 logZscaleId = (np.mod(scaleId // 100, 10) > 0) * 4
scaleId = logYscaleId + logXscaleId + logZscaleId scaleId = logYscaleId + logXscaleId + logZscaleId
scales = [ scales = ['linear', 'xlog', 'ylog', 'xylog', 'zlog', 'xzlog',
'linear', 'yzlog', 'xyzlog']
'xlog',
'ylog',
'xylog',
'zlog',
'xzlog',
'yzlog',
'xyzlog']
return scales[scaleId] return scales[scaleId]
@ -593,7 +574,7 @@ def plot2d(axis, wdata, plotflag, *args, **kwds):
elif plotflag == 10: elif plotflag == 10:
h = axis.contourf(*args1, **kwds) h = axis.contourf(*args1, **kwds)
axis.clabel(h) axis.clabel(h)
plotbackend.colorbar(h) plt.colorbar(h)
else: else:
raise ValueError('unknown option for plotflag') raise ValueError('unknown option for plotflag')
# if any(plotflag==(2:5)) # if any(plotflag==(2:5))
@ -603,16 +584,19 @@ def plot2d(axis, wdata, plotflag, *args, **kwds):
def test_plotdata(): def test_plotdata():
plotbackend.ioff() plt.ioff()
x = np.arange(-2, 2, 0.4) x = np.linspace(0, np.pi, 9)
xi = np.arange(-2, 2, 0.1) xi = np.linspace(0, np.pi, 4*9)
d = PlotData(np.sin(x), x, xlab='x', ylab='sin', title='sinus', d = PlotData(np.sin(x)/2, x, xlab='x', ylab='sin', title='sinus',
plot_args=['r.']) plot_args=['r.'])
di = PlotData(d.eval_points(xi, method='cubic'), xi) di = PlotData(d.eval_points(xi, method='cubic'), xi)
unused_hi = di.plot() unused_hi = di.plot()
unused_h = d.plot() unused_h = d.plot()
d.show() f = di.to_cdf()
for i in range(4):
_ = f.plot(plotflag=i)
d.show('hold')
def test_docstrings(): def test_docstrings():
@ -621,10 +605,6 @@ def test_docstrings():
doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE) doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
def main():
pass
if __name__ == '__main__': if __name__ == '__main__':
test_docstrings() #test_docstrings()
# test_plotdata() test_plotdata()
# main()

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