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I have a five period of data with their probabilities and I would like to simulate it with 20000 times with the Poisson distribution, I want the x-axis start from 0-1, I tried but I stock with that my code here: And is there any way to code it easy than what I did

import numpy import matplotlib.pyplot import pylab import numpy as np from pylab import * data = [] inventory = 0 for j in range(4000): totalOrder= 0 totalProduction = 0 for i in range (5): # calculate order mean = 105 order = np.random.gamma(mean, 20000) totalOrder = totalOrder+order # calculate production production = numpy.random.choice([80, 100, 130, 150], p = [0.2, 0.50 ,0.20, 0.1]) totalProduction = totalProduction + production # calcculate new inventory inventory = inventory + production - order if inventory < 0: inventory = 0 # calculate fill rate for last 5 orders fr = float(totalProduction) / float(totalOrder) if fr > 1: fr = 1 # append FR to dataset data.append(fr) grid(True) xlabel('Fill Rate') ylabel('Density') title('Simulate the system for 20000 week') matplotlib.pyplot.hist(data, normed = True) pylab.show()
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  • Does this code work? If not, what does it do? Errors (provide traceback)? Unexpected outputs (provide inputs and expected and actual outputs)? Commented Apr 24, 2014 at 12:15
  • Yes it works the code but I need the X axis start from 0-1, It appears another number when I want to plot, I want the X axis start from 0 - 1. Commented Apr 24, 2014 at 13:02

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You'll want to use matplotlib's set_xlim method for the axes. Have a look at some of their examples, this one for example, to understand better what you can do with the module.

For your code, you'll need to add:

ax = plt.gca() ax.set_xlim(0,1)

As for some optimizations, I see that you're adding the same module just under different aliases (e.g., you have numpy and its alias np imported, which are also imported by pylab). It tells me you don't have a lot of experience with the language yet. As you continue to learn, you'll eventually reduce all those imports to just a few, e.g.

import numpy as np import matplotlib.pyplot as plt

and you'll call the correct functions belonging to these namespaces (e.g. plt.show(), rather than pylab.show - pylab is no more than a thin veil over a package of numpy and matplotlib.

There are a few more optimizations you could make to your code (e.g. vectorizing the loop), but given your current level, I think this would make it too complex. Besides, the loop does make it more explicit what you're doing.

Maybe just one tip: in python, when you want to update a variable that is numeric (int, float, ...), you could just do:

inventory += production - order

It saves you from typing inventory again and thus less chances of errors in the future if you want to make changes to your code.

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@user3462393, then please consider "accepting" the answer, which is the usual way questions on SO get resolved.

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