Robert wrote:
> Hi,
>
> I find a useful code snippet on link:
>
> http://stackoverflow.com/questions/25126444/logistic-regression-in-pymc/34400966#34400966
>
> but it has error on plot function. The error message is as following:
> ---------
> %run "C:\Users\rj\pyprj\logic_regression0.py"
> [-----------------100%-----------------] 10000 of 10000 complete in 12.6
> [ secPlotting beta0
> Plotting tau
> Plotting betaSalad
> Plotting sigma
>
---------------------------------------------------------------------------
> UnboundLocalError Traceback (most recent call
> last) C:\Users\pyprj\logic_regression0.py in <module>()
> 34 #m.sample(100000, 50000, 50)
> 35 m.sample(10000, 5000, 50)
> ---> 36 pm.Matplot.plot(m)
> 37 import matplotlib.pyplot as plt
> 38 #plt.plot(m)
>
> C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-
> packages\pymc\Matplot.pyc in wrapper(pymc_obj, *args, **kwargs)
> 339 if args:
> 340 name = '%s_%s' % (args[0],
> variable.__name__)
> --> 341 f(data, name, *args, **kwargs)
> 342 return
> 343 except AttributeError:
>
> C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-
packages\pymc\Matplot.pyc
> in plot(data, name, format, suffix, path, common_scale, datarange, new,
> last, rows, num, fontmap, verbose)
> 453 num=num * 2,
> 454 last=last,
> --> 455 fontmap=fontmap)
> 456
> 457 if last:
>
> C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-
packages\pymc\Matplot.pyc
> in wrapper(pymc_obj, *args, **kwargs)
> 375
> 376 # If others fail, assume that raw data is passed
> --> 377 f(pymc_obj, *args, **kwargs)
> 378
> 379 wrapper.__doc__ = f.__doc__
>
> C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-
packages\pymc\Matplot.pyc
> in histogram(data, name, bins, datarange, format, suffix, path, rows,
> columns, num, last, fontmap, verbose)
> 576
> 577 # Generate histogram
> --> 578 hist(data.tolist(), bins, histtype='stepfilled')
> 579
> 580 xlim(datarange)
>
> C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-
packages\matplotlib\pyplot.py
> in hist(x, bins, range, normed, weights, cumulative, bottom, histtype,
> align, orientation, rwidth, log, color, label, stacked, hold, data,
> **kwargs)
> 2956 histtype=histtype, align=align,
> orientation=orientation,
> 2957 rwidth=rwidth, log=log, color=color,
> label=label,
> -> 2958 stacked=stacked, data=data, **kwargs)
> 2959 finally:
> 2960 ax.hold(washold)
>
> C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-
packages\matplotlib\__init__.py
> in inner(ax, *args, **kwargs)
> 1809 warnings.warn(msg % (label_namer,
> func.__name__),
> 1810 RuntimeWarning, stacklevel=2)
> -> 1811 return func(ax, *args, **kwargs)
> 1812 pre_doc = inner.__doc__
> 1813 if pre_doc is None:
>
> C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-
packages\matplotlib\axes\_axes.py
> in hist(self, x, bins, range, normed, weights, cumulative, bottom,
> histtype, align, orientation, rwidth, log, color, label, stacked,
> **kwargs)
> 6192 ymin = np.amin(m[m != 0])
> 6193 # filter out the 0 height bins
> -> 6194 ymin = max(ymin*0.9, minimum) if not input_empty
> else minimum
> 6195 ymin = min(ymin0, ymin)
> 6196 self.dataLim.intervaly = (ymin, ymax)
>
> UnboundLocalError: local variable 'ymin' referenced before assignment
> /////////////
>
> I have no clue at all on debug it. Could you help me?
To me that looks like a bug in matplotlib. ymin is not properly initialised
before the loop
"""
for m in n:
if np.sum(m) > 0: # make sure there are counts
ymin = np.amin(m[m != 0])
# filter out the 0 height bins
ymin = max(ymin*0.9, minimum) if not input_empty else
minimum
"""
so if for there aren't any m with np.sum(m) > 0 (i. e. all bins are empty)
you get the error. Here's a made-up example for illustration:
>>> def last_positive_item(items):
... for item in items:
... if item > 0:
... last = item
... return last
...
As long as you pass at least one positive item everything seems OK:
>>> last_positive_item([1, 2, -3, 3])
3
But if you don't you get the error:
>>> last_positive_item([-1, -2, -3, 0])
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 5, in last_positive_item
UnboundLocalError: local variable 'last' referenced before assignment
Please file a bug report if there isn't one already.
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