import numpy as np
import matplotlib
import matplotlib.pyplot as plt


class MyLogFormatter(matplotlib.ticker.LogFormatter):
    def __call__(self, x, pos=None):
        e = np.floor(np.log10(x))
        m = x/(10**e)
        if x < 0.01:
            return '%de%d' % (round(m), e)
        elif x < 1:
            return '%.2f' % x
        elif x < 10:
            return '%.1f' % x
        elif x < 1000:
            return '%.0f' % x
        else:
            return '%de%d' % (round(m), e)
    @staticmethod
    def ticks(xmin, xmax):
        ndecades = np.ceil(np.log10(xmax/xmin))
        if ndecades > 6:
            mantissas = [1]
        elif ndecades > 3:
            mantissas = [1,3]
        else:
            mantissas = [1,2,5]
        roundnumbers = (10**np.arange(np.floor(np.log10(xmin)), np.ceil(np.log10(xmax)))*np.atleast_2d(mantissas).T).T.flatten()
        return np.hstack((xmin, [x for x in roundnumbers if xmin*1.25 < x < 0.8*xmax], xmax))        

data = 0
for k in xrange(4):
    data += np.random.randint(6, size=100000)
    
count,edges = np.histogram(data,10)
x = 100 * (1.1 ** edges)

fig = plt.figure(figsize=(8,6))
ax = fig.add_subplot(1,1,1,xscale='log')
ax.bar(x[:-1], count, width=x[1:] - x[:-1], color='red',edgecolor='black',align='edge')
xmin = min(x)
xmax = max(x)
LF = MyLogFormatter(labelOnlyBase=False)
ax.set_xticks(LF.ticks(xmin, xmax))
ax.xaxis.set_major_formatter(LF)