Finished base functionality for plotting probability spaces. #1
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…s for plotting of box plots as of now.
…curves when plotted.
…continuous distributions to be plotted.
symbulate/probability_space.py
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| @@ -26,6 +33,28 @@ def sim(self, n): | |||
| """ | |||
| return Results(self.draw() for _ in range(n)) | |||
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| def plot(self, type = None, alpha = None, xlim = None, **kwargs): | |||
| if (self.pf == None): | |||
| raise Exception("Probabiltiy Space is not supported for plotting probability distribution.") | |||
symbulate/probability_space.py
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| if (self.pf == None): | ||
| raise Exception("Probabiltiy Space is not supported for plotting probability distribution.") | ||
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| if (xlim == None): # if no limits for x-axis are specified, then use the default from plt |
symbulate/distributions.py
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| from .probability_space import ProbabilitySpace | ||
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| # Helper function for combinations | ||
| def ncr(n, r): |
symbulate/distributions.py
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| @@ -93,7 +136,15 @@ class NegativeBinomial(ProbabilitySpace): | |||
| def __init__(self, r, p): | |||
| self.r = r | |||
| self.p = p | |||
| self.discrete = True | |||
| self.pf = lambda x: ncr(x-1, r-1)*((1-p)**(x-r))*(p**r) | |||
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Use Scipy's pmf, but add r before plugging into formula.
symbulate/probability_space.py
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| """ | ||
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| def __init__(self, draw): | ||
| def __init__(self, draw, pf = None, discrete = False): |
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Instead of adding pf and discrete to ProbabilitySpace class, create a Distribution subclass with these kwargs, and all the distributions will be instances of that. Only Distribution supports plotting, not ProbabilitySpace. I think you can revert probability_space.py to how it was.
…tion class with basic functionality.
symbulate/distributions.py
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| def plot(self, type = None, alpha = None, xlim = None, **kwargs): | ||
| if (xlim == None): # if no limits for x-axis are specified, then use the default from plt |
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Can you make these style changes throughout the file?
symbulate/distributions.py
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| self.discrete = discrete | ||
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| self.xlim = [ |
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This should be a tuple rather than a list.
symbulate/distributions.py
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| ] | ||
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| def plot(self, type = None, alpha = None, xlim = None, **kwargs): | ||
| if xlim is None: # if no limits for x-axis are specified, then use the default from plt |
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xlower, xupper = xlim if xlim is not None else self.xlim
symbulate/distributions.py
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| if self.discrete: | ||
| xlower = int(xlower) | ||
| xupper = int(xupper) | ||
| xvals = list(np.arange(xlower, xupper+1, 1)) |
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Is there any reason you're casting this to a list instead of keeping it as a Numpy array?
Also, don't include the step when it's equal to 1. So just np.arange(xlower, xupper+1)
symbulate/distributions.py
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| else: | ||
| xvals = list(np.linspace(xlower, xupper, 100)) | ||
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| yvals = list(map(self.pdf, xvals)) |
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Can you use vectorization here? You should be able to just do self.pdf(xvals), right?
symbulate/probability_space.py
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| pf (function): A function giving the exact probability | ||
| density (if continuous) or mass (if discrete) from the probability space | ||
| for a given input. | ||
| discrete (boolean): Describes if the probability space is discrete or not. |
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This addition should probably be reverted? Could you revert all changes to probability_space.py?
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