Re: [Matplotlib-users] 'bug' in labelling axes for data with small variation?

[Darren D. <dd...@co...>]

oops, I just noticed a bug, the first script I posted wont run. This updated script 
worked for me with a fresh 0.72.1 installation. Sorry about the error.

Darren

from matplotlib import *
rc('font',size='smaller')
rc('tick',labelsize='smaller')
from matplotlib.ticker import ScalarFormatter, LinearLocator
import math
from matplotlib.numerix import absolute, average

from pylab import *

class ScalarFormatterScientific(ScalarFormatter):
    """
    Tick location is a plain old number.  If useOffset==True and the data range
    <1e-4* the data average, then an offset will be determined such that the
    tick labels are meaningful. Scientific notation is used for data < 1e-4 or 
    data >= 1e4. Scientific notation is presented once for each axis, in the 
    last ticklabel.
    """
    def __init__(self, useOffset=True):
        """
        useOffset allows plotting small data ranges with large offsets:
        for example: [1+1e-9,1+2e-9,1+3e-9]
        """
        self._useOffset = useOffset
        self.offset = 0
        self.orderOfMagnitude = 0
        self.format = None
        
    def set_locs(self, locs):
        self.locs = locs
        self._set_offset()
        self._set_orderOfMagnitude()
        self._set_format()
        
    def _set_offset(self):
        # offset of 20,001 is 20,000, for example
        if self._useOffset:
            ave_loc = average(self.locs)
            std_loc = std(self.locs)
            if ave_loc: # dont want to take log10(0)
                ave_oom = math.floor(math.log10(absolute(ave_loc)))
                if std_loc/math.fabs(ave_loc) < 1e-4: # four sig-figs
                    # add 1e-15 because of floating point precision, fixes conversion
                    self.offset = int(ave_loc/10**ave_oom+1e-15)*10**ave_oom
        else: self.offset = 0
        
    def _set_orderOfMagnitude(self):
        # if scientific notation is to be used, find the appropriate exponent
        # if using an offset, find the OOM after applying the offset
        locs = array(self.locs)-self.offset
        ave_loc_abs = average(absolute(locs))
        oom = math.floor(math.log10(ave_loc_abs))
        # need to special-case for range of 0-1e-5
        if oom <= 0 and std(locs) < 1e-4:#10**(2*oom):
            self.orderOfMagnitude = oom
        elif oom <=0 and oom >= -5:
            pass
        elif math.fabs(oom) >= 4:
            self.orderOfMagnitude = oom
                
    def _set_format(self):
        # set the format string to format all the ticklabels
        locs = (array(self.locs,'d')-self.offset) / \
                10**self.orderOfMagnitude+1e-15
        sigfigs = [len(str('%1.4f'% loc).split('.')[1].rstrip('0')) \
                   for loc in locs]
        sigfigs.sort()
        self.format = '%1.' + str(sigfigs[-1]) + 'f'
                
    def pprint_val(self, x, d):
        # d is no longer necessary, x is the tick location.
        xp = (x-self.offset)/10**self.orderOfMagnitude
        if x==self.locs[-1] and (self.orderOfMagnitude or self.offset):
            offsetStr = ''
            sciNotStr = ''
            xp = self.format % xp
            if self.offset: 
                p = '%1.e+'% self.offset
                offsetStr = self._formatSciNotation(p)
            if self.orderOfMagnitude: 
                p = 'x%1.e'% 10**self.orderOfMagnitude
                sciNotStr = self._formatSciNotation(p)
            return ''.join((offsetStr,xp,sciNotStr[2:]))
        elif xp==0: return '%d'% xp
        else: return self.format % xp
            
    def _formatSciNotation(self,s):
        # transform 1e+004 into 1e4, for example
        tup = s.split('e')
        mantissa = tup[0]
        sign = tup[1][0].replace('+', '')
        exponent = tup[1][1:].lstrip('0')
        return '%se%s%s' %(mantissa, sign, exponent)
        

figure(1,figsize=(6,6))
ax1 = axes([.2,.74,.75,.2])
ax1.plot(arange(11)*5e2)
ax1.yaxis.set_major_formatter(ScalarFormatterScientific())
ax1.xaxis.set_visible(False)
ax1.set_title('BIG NUMBERS',fontsize=14)

ax2 = axes([.2,.51,.75,.2])
ax2.plot(arange(11)*1e4)
ax2.yaxis.set_major_formatter(ScalarFormatterScientific())
ax2.text(1,6e4,'y=1e4*x')
ax2.xaxis.set_visible(False)

ax3 = axes([.2,.28,.75,.2])
ax3.plot(arange(11)*1e4+1e10)
ax3.yaxis.set_major_formatter(ScalarFormatterScientific())
ax3.text(1,6e4+1e10,'y=1e4*x+1e10')
ax3.xaxis.set_visible(False)

ax4 = axes([.2,.05,.75,.2])
ax4.plot(arange(11)*1e4+1e10)
ax4.yaxis.set_major_formatter(ScalarFormatterScientific(useOffset=False))
ax4.text(1,1e10+6e4,'y=1e4*x+1e10, no offset')


figure(2,figsize=(6,6))
ax1 = axes([.225,.74,.75,.2])
ax1.plot(arange(11)*1e-4)
ax1.yaxis.set_major_formatter(ScalarFormatterScientific())
ax1.xaxis.set_visible(False)
ax1.set_title('small numbers',fontsize=8)

ax2 = axes([.225,.51,.75,.2])
ax2.plot(arange(11)*1e-5)
ax2.yaxis.set_major_formatter(ScalarFormatterScientific())
ax2.text(1,6e-5,'y=1e-5*x')
ax2.xaxis.set_visible(False)

ax3 = axes([.225,.28,.75,.2])
ax3.plot(arange(11)*1e-10+1e-5)
ax3.yaxis.set_major_formatter(ScalarFormatterScientific())
ax3.text(1,1e-5+6e-10,'y=1e-10*x+1e-5')
ax3.xaxis.set_visible(False)

ax4 = axes([.225,.05,.75,.2])
ax4.plot(arange(11)*1e-10+1e-5)
ax4.yaxis.set_major_formatter(ScalarFormatterScientific(useOffset=False))
ax4.text(1,1e-5+6e-10,'y=1e-10*x+1e-5, no offset')
show()