CODEWITHSUNDEEP
pythonpython-2.7
Anirban De
Anirban De

Reputation: 9

Python Code unable to execute in Windows

My python code was running successfully in Ubuntu 14.04; but when I went to run in Windows Platform, it throws me into error. The Code: 

import pymc

with open("days1.txt") as f:
    dataset = map(float, f)

a = pymc.Uniform('a', lower=0, upper=1500000, value=70, doc='Weibull alpha parameter')

b = pymc.Uniform('b', lower=0, upper=1500000, value=70, doc='Weibull beta parameter')

like = pymc.Weibull('like', alpha=a, beta=b, value=dataset, observed=True)

if __name__=='__main__':

    import pylab
    M = pymc.MCMC([a,b,like])
    M.sample(10000,5000,2)
    pymc.Matplot.plot(a)
    pymc.Matplot.plot(b)
    M.summary()
    M.write_csv("parameters1.csv")

The error: 

C:\Python35-32>python.exe "E:\TCS\Desktop\EarlyWarning\JLR\Data\EJ327000AB\Scrip
ts\Screen 7\Check Python - 1\weibullEstimationOutData - 1.py"
Traceback (most recent call last):
  File "C:\Python35-32\lib\site-packages\pymc\PyMCObjects.py", line 742, in __in
it__
    self._value = np.array(value, dtype=dtype)
TypeError: float() argument must be a string or a number, not 'map'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "E:\TCS\Desktop\EarlyWarning\JLR\Data\EJ327000AB\Scripts\Screen 7\Check P
ython - 1\weibullEstimationOutData - 1.py", line 8, in <module>
    like = pymc.Weibull('like', alpha=a, beta=b, value=dataset, observed=True)
  AttributeError: 'TypeError' object has no attribute 'message'

Kindly Help. Thanks in Advance

Upvotes: 0

Views: 152

Answers (1)

Daniel
Daniel

Reputation: 42778

You are using Python 2 with Ubuntu, but Python 3 with Windows. Install Python 2 for Windows, or port your code to Python 3

import pylab
import pymc

with open("days1.txt") as f:
    dataset = list(map(float, f))

a = pymc.Uniform('a', lower=0, upper=1500000, value=70, doc='Weibull alpha parameter')

b = pymc.Uniform('b', lower=0, upper=1500000, value=70, doc='Weibull beta parameter')

like = pymc.Weibull('like', alpha=a, beta=b, value=dataset, observed=True)

if __name__=='__main__':
    M = pymc.MCMC([a,b,like])
    M.sample(10000,5000,2)
    pymc.Matplot.plot(a)
    pymc.Matplot.plot(b)
    M.summary()
    M.write_csv("parameters1.csv")

Upvotes: 2

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