@@ -4921,11 +4921,10 @@ def make_iterable(x):
49214921 if orientation == 'vertical' :
49224922 self ._process_unit_info (xdata = left , ydata = height , kwargs = kwargs )
49234923 if log :
4924- self .set_yscale ('log' )
4924+ self .set_yscale ('log' , nonposy = 'clip' )
49254925 # size width and bottom according to length of left
49264926 if _bottom is None :
49274927 if self .get_yscale () == 'log' :
4928- bottom = [1e-100 ]
49294928 adjust_ylim = True
49304929 else :
49314930 bottom = [0 ]
@@ -4937,11 +4936,10 @@ def make_iterable(x):
49374936 elif orientation == 'horizontal' :
49384937 self ._process_unit_info (xdata = width , ydata = bottom , kwargs = kwargs )
49394938 if log :
4940- self .set_xscale ('log' )
4939+ self .set_xscale ('log' , nonposx = 'clip' )
49414940 # size left and height according to length of bottom
49424941 if _left is None :
49434942 if self .get_xscale () == 'log' :
4944- left = [1e-100 ]
49454943 adjust_xlim = True
49464944 else :
49474945 left = [0 ]
@@ -8218,6 +8216,11 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
82188216 raise ValueError (
82198217 "orientation kwarg %s is not recognized" % orientation )
82208218
8219+ if kwargs .get ('width' ) is not None :
8220+ raise mplDeprecation (
8221+ 'hist now uses the rwidth to give relative width '
8222+ 'and not absolute width' )
8223+
82218224 if histtype == 'barstacked' and not stacked :
82228225 stacked = True
82238226
@@ -8233,9 +8236,9 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
82338236 else :
82348237 raise ValueError ("x must be 1D or 2D" )
82358238 if x .shape [1 ] < x .shape [0 ]:
8236- warnings .warn ('2D hist input should be nsamples x '
8237- ' nvariables;\n this looks transposed '
8238- ' (shape is %d x %d)'% x .shape [::- 1 ])
8239+ warnings .warn (
8240+ '2D hist input should be nsamples x nvariables;\n '
8241+ 'this looks transposed (shape is %d x %d)'% x .shape [::- 1 ])
82398242 else :
82408243 # multiple hist with data of different length
82418244 x = [np .asarray (xi ) for xi in x ]
@@ -8270,7 +8273,7 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
82708273 raise ValueError (
82718274 'weights should have the same shape as x' )
82728275 else :
8273- w = [None ] * nx
8276+ w = [None ]* nx
82748277
82758278 # Save autoscale state for later restoration; turn autoscaling
82768279 # off so we can do it all a single time at the end, instead
@@ -8285,7 +8288,7 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
82858288
82868289 # Check whether bins or range are given explicitly. In that
82878290 # case use those values for autoscaling.
8288- binsgiven = (cbook .iterable (bins ) or bin_range != None )
8291+ binsgiven = (cbook .iterable (bins ) or bin_range is not None )
82898292
82908293 # If bins are not specified either explicitly or via range,
82918294 # we need to figure out the range required for all datasets,
@@ -8304,16 +8307,13 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
83048307 hist_kwargs = dict (range = bin_range )
83058308
83068309 n = []
8307- mlast = None
8308- # reversed order is necessary so when stacking histogram, first
8309- # dataset is on top if histogram isn't stacked, this doesn't make any
8310- # difference
8311- for i in reversed (xrange (nx )):
8310+ mlast = bottom
8311+ for i in xrange (nx ):
83128312 # this will automatically overwrite bins,
83138313 # so that each histogram uses the same bins
83148314 m , bins = np .histogram (x [i ], bins , weights = w [i ], ** hist_kwargs )
83158315 if mlast is None :
8316- mlast = np .zeros (len (bins ) - 1 , m .dtype )
8316+ mlast = np .zeros (len (bins )- 1 , m .dtype )
83178317 if normed :
83188318 db = np .diff (bins )
83198319 m = (m .astype (float ) / db ) / m .sum ()
@@ -8322,8 +8322,6 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
83228322 mlast [:] = m
83238323 n .append (m )
83248324
8325-
8326-
83278325 if cumulative :
83288326 slc = slice (None )
83298327 if cbook .is_numlike (cumulative ) and cumulative < 0 :
@@ -8334,8 +8332,6 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
83348332 else :
83358333 n = [m [slc ].cumsum ()[slc ] for m in n ]
83368334
8337- n .reverse () # put them back in the right order
8338-
83398335 patches = []
83408336
83418337 if histtype .startswith ('bar' ):
@@ -8349,21 +8345,20 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
83498345 dr = 1.0
83508346
83518347 if histtype == 'bar' and not stacked :
8352- width = dr * totwidth / nx
8348+ width = dr * totwidth / nx
83538349 dw = width
83548350
83558351 if nx > 1 :
8356- boffset = - 0.5 * dr * totwidth * (1.0 - 1.0 / nx )
8352+ boffset = - 0.5 * dr * totwidth * (1.0 - 1.0 / nx )
83578353 else :
83588354 boffset = 0.0
83598355 stacked = False
83608356 elif histtype == 'barstacked' or stacked :
8361- width = dr * totwidth
8357+ width = dr * totwidth
83628358 boffset , dw = 0.0 , 0.0
83638359
83648360 if align == 'mid' or align == 'edge' :
8365- boffset += 0.5 * totwidth
8366-
8361+ boffset += 0.5 * totwidth
83678362 elif align == 'right' :
83688363 boffset += totwidth
83698364
@@ -8373,31 +8368,34 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
83738368 _barfunc = self .bar
83748369
83758370 for m , c in zip (n , color ):
8376- patch = _barfunc (bins [:- 1 ] + boffset , m , width ,
8371+ if bottom is None :
8372+ bottom = np .zeros (len (m ), np .float )
8373+ if stacked :
8374+ height = m - bottom
8375+ else :
8376+ height = m
8377+ patch = _barfunc (bins [:- 1 ]+ boffset , height , width ,
83778378 align = 'center' , log = log ,
83788379 color = c , bottom = bottom )
83798380 patches .append (patch )
8381+ if stacked :
8382+ bottom [:] = m
83808383 boffset += dw
83818384
83828385 elif histtype .startswith ('step' ):
8383- x = np .zeros (2 * len (bins ), np .float )
8384- y = np .zeros (2 * len (bins ), np .float )
8385-
8386- x [0 ::2 ], x [1 ::2 ] = bins , bins
8387-
8388- minimum = np .min (n )
8386+ # these define the perimeter of the polygon
8387+ x = np .zeros (4 * len (bins ) - 3 , np .float )
8388+ y = np .zeros (4 * len (bins ) - 3 , np .float )
83898389
8390- if align == 'left' or align == 'center' :
8391- x -= 0.5 * (bins [1 ] - bins [0 ])
8392- elif align == 'right' :
8393- x += 0.5 * (bins [1 ] - bins [0 ])
8390+ x [0 :2 * len (bins )- 1 :2 ], x [1 :2 * len (bins )- 1 :2 ] = bins , bins [:- 1 ]
8391+ x [2 * len (bins )- 1 :] = x [1 :2 * len (bins )- 1 ][::- 1 ]
83948392
83958393 if log :
83968394 if orientation == 'horizontal' :
8397- self .set_xscale ('log' )
8395+ self .set_xscale ('log' , nonposx = 'clip' )
83988396 logbase = self .xaxis ._scale .base
83998397 else : # orientation == 'vertical'
8400- self .set_yscale ('log' )
8398+ self .set_yscale ('log' , nonposy = 'clip' )
84018399 logbase = self .yaxis ._scale .base
84028400
84038401 # Setting a minimum of 0 results in problems for log plots
@@ -8407,47 +8405,71 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
84078405 ndata = np .array (n )
84088406 minimum = (np .min (ndata [ndata > 0 ])) / logbase
84098407 else :
8410- # For non-normed data, set the min to log base, again so
8411- # that there is 1 full tick-label unit for the lowest bin
8408+ # For non-normed data, set the min to log base,
8409+ # again so that there is 1 full tick-label unit
8410+ # for the lowest bin
84128411 minimum = 1.0 / logbase
84138412
84148413 y [0 ], y [- 1 ] = minimum , minimum
84158414 else :
84168415 minimum = np .min (bins )
84178416
8417+ if align == 'left' or align == 'center' :
8418+ x -= 0.5 * (bins [1 ]- bins [0 ])
8419+ elif align == 'right' :
8420+ x += 0.5 * (bins [1 ]- bins [0 ])
8421+
84188422 # If fill kwarg is set, it will be passed to the patch collection,
84198423 # overriding this
84208424 fill = (histtype == 'stepfilled' )
84218425
8422- for m , c in zip (n , color ):
8423- y [1 :- 1 :2 ], y [2 ::2 ] = m , m
8426+ xvals , yvals = [], []
8427+ for m in n :
8428+ # starting point for drawing polygon
8429+ y [0 ] = y [- 1 ]
8430+ # top of the previous polygon becomes the bottom
8431+ y [2 * len (bins )- 1 :] = y [1 :2 * len (bins )- 1 ][::- 1 ]
8432+ # set the top of this polygon
8433+ y [1 :2 * len (bins )- 1 :2 ], y [2 :2 * len (bins ):2 ] = m , m
84248434 if log :
84258435 y [y < minimum ] = minimum
84268436 if orientation == 'horizontal' :
84278437 x , y = y , x
84288438
8439+ xvals .append (x .copy ())
8440+ yvals .append (y .copy ())
8441+
8442+ # add patches in reverse order so that when stacking,
8443+ # items lower in the stack are plottted on top of
8444+ # items higher in the stack
8445+ for x , y , c in reversed (zip (xvals , yvals , color )):
84298446 if fill :
84308447 patches .append (self .fill (x , y ,
8431- closed = False , facecolor = c ))
8448+ closed = False ,
8449+ facecolor = c ))
84328450 else :
84338451 patches .append (self .fill (x , y ,
8434- closed = False , edgecolor = c , fill = False ))
8452+ closed = False , edgecolor = c ,
8453+ fill = False ))
8454+
8455+ # we return patches, so put it back in the expected order
8456+ patches .reverse ()
84358457
84368458 # adopted from adjust_x/ylim part of the bar method
84378459 if orientation == 'horizontal' :
8438- xmin0 = max (_saved_bounds [0 ] * 0.9 , minimum )
8460+ xmin0 = max (_saved_bounds [0 ]* 0.9 , minimum )
84398461 xmax = self .dataLim .intervalx [1 ]
84408462 for m in n :
8441- xmin = np .amin (m [m != 0 ]) # filter out the 0 height bins
8442- xmin = max (xmin * 0.9 , minimum )
8463+ xmin = np .amin (m [m != 0 ]) # filter out the 0 height bins
8464+ xmin = max (xmin * 0.9 , minimum )
84438465 xmin = min (xmin0 , xmin )
84448466 self .dataLim .intervalx = (xmin , xmax )
84458467 elif orientation == 'vertical' :
8446- ymin0 = max (_saved_bounds [1 ] * 0.9 , minimum )
8468+ ymin0 = max (_saved_bounds [1 ]* 0.9 , minimum )
84478469 ymax = self .dataLim .intervaly [1 ]
84488470 for m in n :
8449- ymin = np .amin (m [m != 0 ]) # filter out the 0 height bins
8450- ymin = max (ymin * 0.9 , minimum )
8471+ ymin = np .amin (m [m != 0 ]) # filter out the 0 height bins
8472+ ymin = max (ymin * 0.9 , minimum )
84518473 ymin = min (ymin0 , ymin )
84528474 self .dataLim .intervaly = (ymin , ymax )
84538475
@@ -8458,8 +8480,8 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
84588480 elif is_sequence_of_strings (label ):
84598481 labels = list (label )
84608482 else :
8461- raise ValueError ('invalid label: must be string or sequence of '
8462- ' strings'
8483+ raise ValueError (
8484+ 'invalid label: must be string or sequence of strings'
84638485
84648486 if len (labels ) < nx :
84658487 labels += [None ] * (nx - len (labels ))
@@ -8479,11 +8501,11 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
84798501
84808502 if binsgiven :
84818503 if orientation == 'vertical' :
8482- self .update_datalim ([( bins [ 0 ], 0 ), ( bins [ - 1 ], 0 )],
8483- updatey = False )
8504+ self .update_datalim (
8505+ [( bins [ 0 ], 0 ), ( bins [ - 1 ], 0 )], updatey = False )
84848506 else :
8485- self .update_datalim ([( 0 , bins [ 0 ]), ( 0 , bins [ - 1 ])],
8486- updatex = False )
8507+ self .update_datalim (
8508+ [( 0 , bins [ 0 ]), ( 0 , bins [ - 1 ])], updatex = False )
84878509
84888510 self .set_autoscalex_on (_saved_autoscalex )
84898511 self .set_autoscaley_on (_saved_autoscaley )
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