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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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158
wafo/containers.py
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@ -1,7 +1,7 @@
from __future__ import absolute_import
import warnings
from wafo.graphutil import cltext
from wafo.plotbackend import plotbackend
from wafo.plotbackend import plotbackend as plt
from time import gmtime, strftime
import numpy as np
from scipy.integrate.quadrature import cumtrapz # @UnresolvedImport
@ -20,14 +20,6 @@ def empty_copy(obj):
return newcopy
def _set_seed(iseed):
if iseed is not None:
try:
np.random.set_state(iseed)
except:
np.random.seed(iseed)
def now():
'''
Return current date and time as a string
@ -60,20 +52,22 @@ class PlotData(object):
Example
-------
>>> import numpy as np
>>> x = np.arange(-2, 2, 0.2)
>>> x = np.linspace(0, np.pi, 9)
# 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()
h1 = d2()
>>> h = d2.plot()
>>> h1 = d2()
Plot with confidence interval
# Plot with confidence interval
>>> d3 = PlotData(np.sin(x), x)
>>> d3.children = [PlotData(np.vstack([np.sin(x)*0.9, np.sin(x)*1.2]).T,x)]
>>> d3.plot_args_children=[':r']
>>> d3.children = [PlotData(np.vstack([np.sin(x)*0.9,
... 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.date = now()
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_kwds_children = kwds.pop('plot_kwds_children', {})
self.plot_args = kwds.pop('plot_args', [])
@ -133,8 +127,10 @@ class PlotData(object):
... plot_args=['r.'])
>>> di = PlotData(d.eval_points(xi), xi)
hi = di.plot()
h = d.plot()
>>> hi = di.plot()
>>> h = d.plot()
>>> di.to_cdf()
See also
--------
@ -154,16 +150,15 @@ class PlotData(object):
warnings.warn(msg)
else:
xi = np.meshgrid(*self.args)
return interpolate.griddata(
xi, self.data.ravel(), points, **options)
else: # One dimensional data
return interpolate.griddata(
self.args, self.data, points, **options)
return interpolate.griddata(xi, self.data.ravel(), points,
**options)
# One dimensional data
return interpolate.griddata(self.args, self.data, points, **options)
def to_cdf(self):
if isinstance(self.args, (list, tuple)): # Multidimensional data
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)')
def integrate(self, a=None, b=None, **kwds):
@ -182,18 +177,7 @@ class PlotData(object):
fun = getattr(integrate, method)
if isinstance(self.args, (list, tuple)): # Multidimensional data
raise NotImplementedError('integration for ndim>1 not implemented')
# ndim = len(self.args)
# if ndim < 2:
# msg = '''Unable to determine plotter-type, because
# len(self.args)<2.
# If the data is 1D, then self.args should be a vector!
# If the data is 2D, then length(self.args) should be 2.
# If the data is 3D, then length(self.args) should be 3.
# Unless you fix this, the plot methods will not work!'''
# warnings.warn(msg)
# else:
# return interpolate.griddata(self.args, self.data.ravel(), **kwds)
else: # One dimensional data
# One dimensional data
return_ci = kwds.pop('return_ci', False)
x = self.args
if a is None:
@ -202,9 +186,7 @@ class PlotData(object):
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),
fi = np.hstack((self.eval_points(a), self.data.take(ix),
self.eval_points(b)))
res = fun(fi, xi, **kwds)
if return_ci:
@ -215,7 +197,7 @@ class PlotData(object):
def plot(self, *args, **kwds):
axis = kwds.pop('axis', None)
if axis is None:
axis = plotbackend.gca()
axis = plt.gca()
tmp = None
default_plotflag = self.plot_kwds.get('plotflag', None)
plotflag = kwds.get('plotflag', default_plotflag)
@ -294,7 +276,7 @@ class AxisLabels:
def labelfig(self, axis=None):
if axis is None:
axis = plotbackend.gca()
axis = plt.gca()
try:
h = []
for fun, txt in zip(
@ -335,19 +317,19 @@ class Plotter_1d(object):
if plotmethod is None:
plotmethod = 'plot'
self.plotmethod = plotmethod
self.plotbackend = plotbackend
# self.plotbackend = plotbackend
# try:
# self.plotfun = getattr(plotbackend, plotmethod)
# except:
# pass
def show(self, *args, **kwds):
plotbackend.show(*args, **kwds)
plt.show(*args, **kwds)
def plot(self, wdata, *args, **kwds):
axis = kwds.pop('axis', None)
if axis is None:
axis = plotbackend.gca()
axis = plt.gca()
plotflag = kwds.pop('plotflag', False)
if plotflag:
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):
plottype = np.mod(plotflag, 10)
if plottype == 0: # % No plotting
if plottype == 0: # No plotting
return []
elif plottype == 1:
H = axis.plot(args, data, *varargin, **kwds)
@ -386,18 +368,10 @@ def plot1d(axis, args, data, dataCI, plotflag, *varargin, **kwds):
elif plottype == 3:
H = axis.stem(args, data, *varargin, **kwds)
elif plottype == 4:
H = axis.errorbar(
args,
data,
yerr=[
dataCI[
:,
0] - data,
dataCI[
:,
1] - data],
*varargin,
**kwds)
H = axis.errorbar(args, data,
yerr=[dataCI[:, 0] - data,
dataCI[:, 1] - data],
*varargin, **kwds)
elif plottype == 5:
H = axis.bar(args, data, *varargin, **kwds)
elif plottype == 6:
@ -408,10 +382,8 @@ def plot1d(axis, args, data, dataCI, plotflag, *varargin, **kwds):
H = axis.fill_between(args, data, *varargin, **kwds)
elif plottype == 7:
H = axis.plot(args, data, *varargin, **kwds)
H = axis.fill_between(
args, dataCI[
:, 0], dataCI[
:, 1], alpha=0.2, color='r')
H = axis.fill_between(args, dataCI[:, 0], dataCI[:, 1],
alpha=0.2, color='r')
scale = plotscale(plotflag)
logXscale = 'x' in scale
@ -471,12 +443,28 @@ def plotscale(plotflag):
'linear', 'xlog', 'ylog', 'xylog', 'zlog', 'xzlog',
'yzlog', 'xyzlog'
Example
plotscale(100) % xlog
plotscale(200) % xlog
plotscale(1000) % ylog
Examples
--------
>>> for i in range(7):
... plotscale(i*100)
'linear'
'xlog'
'ylog'
'xylog'
'zlog'
'xzlog'
'yzlog'
>>> plotscale(100)
'xlog'
>>> plotscale(1000)
'ylog'
>>> plotscale(10000)
'zlog'
See also plotscale
See also
---------
plotscale
'''
scaleId = plotflag // 100
if scaleId > 7:
@ -485,15 +473,8 @@ def plotscale(plotflag):
logZscaleId = (np.mod(scaleId // 100, 10) > 0) * 4
scaleId = logYscaleId + logXscaleId + logZscaleId
scales = [
'linear',
'xlog',
'ylog',
'xylog',
'zlog',
'xzlog',
'yzlog',
'xyzlog']
scales = ['linear', 'xlog', 'ylog', 'xylog', 'zlog', 'xzlog',
'yzlog', 'xyzlog']
return scales[scaleId]
@ -593,7 +574,7 @@ def plot2d(axis, wdata, plotflag, *args, **kwds):
elif plotflag == 10:
h = axis.contourf(*args1, **kwds)
axis.clabel(h)
plotbackend.colorbar(h)
plt.colorbar(h)
else:
raise ValueError('unknown option for plotflag')
# if any(plotflag==(2:5))
@ -603,16 +584,19 @@ def plot2d(axis, wdata, plotflag, *args, **kwds):
def test_plotdata():
plotbackend.ioff()
x = np.arange(-2, 2, 0.4)
xi = np.arange(-2, 2, 0.1)
plt.ioff()
x = np.linspace(0, np.pi, 9)
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.'])
di = PlotData(d.eval_points(xi, method='cubic'), xi)
unused_hi = di.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():
@ -621,10 +605,6 @@ def test_docstrings():
doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
def main():
pass
if __name__ == '__main__':
test_docstrings()
# test_plotdata()
# main()
#test_docstrings()
test_plotdata()

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