Commit3101e00

committed

LogNorm.autoscale ignores nonpositive values; closes 2953069

svn path=/trunk/matplotlib/; revision=8348

1 parent9226ef5 commit3101e00Copy full SHA for 3101e00

File tree

+20

-0

lines changed

+20

-0

lines changed

Lines changed: 20 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -850,6 +850,8 @@ def __call__(self, value, clip=None):`
`850`	`850`	`vtype='scalar'`
`851`	`851`	`val=ma.array([value]).astype(np.float)`
`852`	`852`
	`853`	`+val=ma.masked_less_equal(val,0,copy=False)`
	`854`	`+`
`853`	`855`	`self.autoscale_None(val)`
`854`	`856`	`vmin,vmax=self.vmin,self.vmax`
`855`	`857`	`ifvmin>vmax:`
`@@ -879,6 +881,24 @@ def inverse(self, value):`
`879`	`881`	`else:`
`880`	`882`	`returnvmin*pow((vmax/vmin),value)`
`881`	`883`
	`884`	`+defautoscale(self,A):`
	`885`	`+'''`
	`886`	`+ Set vmin, vmax to min, max of A.`
	`887`	`+ '''`
	`888`	`+A=ma.masked_less_equal(A,0,copy=False)`
	`889`	`+self.vmin=ma.min(A)`
	`890`	`+self.vmax=ma.max(A)`
	`891`	`+`
	`892`	`+defautoscale_None(self,A):`
	`893`	`+' autoscale only None-valued vmin or vmax'`
	`894`	`+ifself.vminisnotNoneandself.vmaxisnotNone:`
	`895`	`+return`
	`896`	`+A=ma.masked_less_equal(A,0,copy=False)`
	`897`	`+ifself.vminisNone:`
	`898`	`+self.vmin=ma.min(A)`
	`899`	`+ifself.vmaxisNone:`
	`900`	`+self.vmax=ma.max(A)`
	`901`	`+`
`882`	`902`	`classBoundaryNorm(Normalize):`
`883`	`903`	`'''`
`884`	`904`	`Generate a colormap index based on discrete intervals.`

Comments

(0)