Projects/laydi
Projects
/
laydi
Archived
7
0
Fork 0

Addded automatic bin selection in histogram plot

This commit is contained in:
Arnar Flatberg 2007-08-04 10:37:22 +00:00
parent 3f7215bc35
commit 72e300c95e
1 changed files with 13 additions and 2 deletions

View File

@ -575,7 +575,8 @@ class HistogramPlot(Plot):
# Set default paramteters
if not kw.has_key('bins'):
kw['bins'] = 20
kw['bins'] = self._get_binsize()
print kw['bins']
# Initial draw
self.axes.grid(False)
@ -598,7 +599,7 @@ class HistogramPlot(Plot):
self._toolbar.freeze_button.set_sensitive(False)
self._toolbar.set_mode_sensitive('select', False)
self._toolbar.set_mode_sensitive('lassoselect', False)
def rectangle_select_callback(self, x1, y1, x2, y2, key):
if self.current_dim == None: return
# make (x1, y1) the lower left corner
@ -653,6 +654,16 @@ class HistogramPlot(Plot):
patch.set_facecolor((r,g,b,1))
self.canvas.draw()
def _get_binsize(self, min_bins=2, max_bins=100):
""" Automatic bin selection, as described by Shimazaki."""
bin_vec = scipy.arange(min_bins, max_bins, 1)
D = self._data.ptp()/bin_vec
cost = scipy.empty((bin_vec.shape[0],), 'f')
for i, bins in enumerate(bin_vec):
count, lims = scipy.histogram(self._data, bins)
cost[i] = (2*count.mean() - count.var())/(D[i]**2)
best_bin_size = bin_vec[scipy.argmin(cost)]
return best_bin_size
class BarPlot(Plot):
"""Bar plot.