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Quad definite integral with infinite limit


Limiting floats to two decimal pointshow to call python scipy quad with array inputsPython Numerical Integration for Volume of RegionCustom distribution in scipy with pdf givenHow to use tplquad?Integration of a bessel function in python: subdivision issue“TypeError” message while performing quad integration method of scipy.integrate with mpmath functionsscipy quadrature integration accuracy warning and nan difference valuesRunning Tensorflow undefined symbol: PyClass_TypeError executing rnn model . How to fix it?













2















I am trying to solve the following:
enter image description here



where, g is a constant, and mu = 0, but I am getting a warning and the result is not quite what is supposed to be.



Here is the code:



%matplotlib inline
from scipy.integrate import quad
from numpy import arange
from numpy import pi
import matplotlib.pyplot as plt
import numpy as np

###Parameters

ms = 100. ## m
ggX = 2. ## g

def Integrand(E, T, m_dm):
return ((ggX/(2*(np.pi**2)))*E*(E**2-m_dm**2)**(1/2))/(np.exp(E/T)-1)

def Integrate_E(T,m_dm):
'''
Integrate over E given T and ms
'''
return quad(Integrand, m_dm, np.inf, args=(T,m_dm))[0]

TT = np.logspace(-10,15,100)
nn =[Integrate_E(T,ms) for T in (TT)]

plt.loglog(TT, nn)
plt.grid(True)


This is the result I am obtaining:



/home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The algorithm does not converge. Roundoff error is detected
in the extrapolation table. It is assumed that the requested tolerance
cannot be achieved, and that the returned result (if full_output = 1) is
the best which can be obtained.
warnings.warn(msg, IntegrationWarning)
/home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The integral is probably divergent, or slowly convergent.
warnings.warn(msg, IntegrationWarning)
/home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The maximum number of subdivisions (50) has been achieved.
If increasing the limit yields no improvement it is advised to analyze
the integrand in order to determine the difficulties. If the position of a
local difficulty can be determined (singularity, discontinuity) one will
probably gain from splitting up the interval and calling the integrator
on the subranges. Perhaps a special-purpose integrator should be used.
warnings.warn(msg, IntegrationWarning)


And the plot gives:



enter image description here



For values of T greater than 1e4 is where the problem begins. It should keep almost constant after this value, but you can see the horrible peaks it shows.
I tried modifying the epsabs and the epsrel but it did not worked. I tried to split the integration limits, and apparently from E = m to 1e4 it works fine, but when it integrates from E = 1e5 to infinity is where again appear problems.



When I print the results of the integral, it gives absurd values for nn (It can go from 5.454320597790705e+17 to -3085930898.2363224). I don't know what else to do. Thanks in advance!










share|improve this question


























    2















    I am trying to solve the following:
    enter image description here



    where, g is a constant, and mu = 0, but I am getting a warning and the result is not quite what is supposed to be.



    Here is the code:



    %matplotlib inline
    from scipy.integrate import quad
    from numpy import arange
    from numpy import pi
    import matplotlib.pyplot as plt
    import numpy as np

    ###Parameters

    ms = 100. ## m
    ggX = 2. ## g

    def Integrand(E, T, m_dm):
    return ((ggX/(2*(np.pi**2)))*E*(E**2-m_dm**2)**(1/2))/(np.exp(E/T)-1)

    def Integrate_E(T,m_dm):
    '''
    Integrate over E given T and ms
    '''
    return quad(Integrand, m_dm, np.inf, args=(T,m_dm))[0]

    TT = np.logspace(-10,15,100)
    nn =[Integrate_E(T,ms) for T in (TT)]

    plt.loglog(TT, nn)
    plt.grid(True)


    This is the result I am obtaining:



    /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The algorithm does not converge. Roundoff error is detected
    in the extrapolation table. It is assumed that the requested tolerance
    cannot be achieved, and that the returned result (if full_output = 1) is
    the best which can be obtained.
    warnings.warn(msg, IntegrationWarning)
    /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The integral is probably divergent, or slowly convergent.
    warnings.warn(msg, IntegrationWarning)
    /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The maximum number of subdivisions (50) has been achieved.
    If increasing the limit yields no improvement it is advised to analyze
    the integrand in order to determine the difficulties. If the position of a
    local difficulty can be determined (singularity, discontinuity) one will
    probably gain from splitting up the interval and calling the integrator
    on the subranges. Perhaps a special-purpose integrator should be used.
    warnings.warn(msg, IntegrationWarning)


    And the plot gives:



    enter image description here



    For values of T greater than 1e4 is where the problem begins. It should keep almost constant after this value, but you can see the horrible peaks it shows.
    I tried modifying the epsabs and the epsrel but it did not worked. I tried to split the integration limits, and apparently from E = m to 1e4 it works fine, but when it integrates from E = 1e5 to infinity is where again appear problems.



    When I print the results of the integral, it gives absurd values for nn (It can go from 5.454320597790705e+17 to -3085930898.2363224). I don't know what else to do. Thanks in advance!










    share|improve this question
























      2












      2








      2








      I am trying to solve the following:
      enter image description here



      where, g is a constant, and mu = 0, but I am getting a warning and the result is not quite what is supposed to be.



      Here is the code:



      %matplotlib inline
      from scipy.integrate import quad
      from numpy import arange
      from numpy import pi
      import matplotlib.pyplot as plt
      import numpy as np

      ###Parameters

      ms = 100. ## m
      ggX = 2. ## g

      def Integrand(E, T, m_dm):
      return ((ggX/(2*(np.pi**2)))*E*(E**2-m_dm**2)**(1/2))/(np.exp(E/T)-1)

      def Integrate_E(T,m_dm):
      '''
      Integrate over E given T and ms
      '''
      return quad(Integrand, m_dm, np.inf, args=(T,m_dm))[0]

      TT = np.logspace(-10,15,100)
      nn =[Integrate_E(T,ms) for T in (TT)]

      plt.loglog(TT, nn)
      plt.grid(True)


      This is the result I am obtaining:



      /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The algorithm does not converge. Roundoff error is detected
      in the extrapolation table. It is assumed that the requested tolerance
      cannot be achieved, and that the returned result (if full_output = 1) is
      the best which can be obtained.
      warnings.warn(msg, IntegrationWarning)
      /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The integral is probably divergent, or slowly convergent.
      warnings.warn(msg, IntegrationWarning)
      /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The maximum number of subdivisions (50) has been achieved.
      If increasing the limit yields no improvement it is advised to analyze
      the integrand in order to determine the difficulties. If the position of a
      local difficulty can be determined (singularity, discontinuity) one will
      probably gain from splitting up the interval and calling the integrator
      on the subranges. Perhaps a special-purpose integrator should be used.
      warnings.warn(msg, IntegrationWarning)


      And the plot gives:



      enter image description here



      For values of T greater than 1e4 is where the problem begins. It should keep almost constant after this value, but you can see the horrible peaks it shows.
      I tried modifying the epsabs and the epsrel but it did not worked. I tried to split the integration limits, and apparently from E = m to 1e4 it works fine, but when it integrates from E = 1e5 to infinity is where again appear problems.



      When I print the results of the integral, it gives absurd values for nn (It can go from 5.454320597790705e+17 to -3085930898.2363224). I don't know what else to do. Thanks in advance!










      share|improve this question














      I am trying to solve the following:
      enter image description here



      where, g is a constant, and mu = 0, but I am getting a warning and the result is not quite what is supposed to be.



      Here is the code:



      %matplotlib inline
      from scipy.integrate import quad
      from numpy import arange
      from numpy import pi
      import matplotlib.pyplot as plt
      import numpy as np

      ###Parameters

      ms = 100. ## m
      ggX = 2. ## g

      def Integrand(E, T, m_dm):
      return ((ggX/(2*(np.pi**2)))*E*(E**2-m_dm**2)**(1/2))/(np.exp(E/T)-1)

      def Integrate_E(T,m_dm):
      '''
      Integrate over E given T and ms
      '''
      return quad(Integrand, m_dm, np.inf, args=(T,m_dm))[0]

      TT = np.logspace(-10,15,100)
      nn =[Integrate_E(T,ms) for T in (TT)]

      plt.loglog(TT, nn)
      plt.grid(True)


      This is the result I am obtaining:



      /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The algorithm does not converge. Roundoff error is detected
      in the extrapolation table. It is assumed that the requested tolerance
      cannot be achieved, and that the returned result (if full_output = 1) is
      the best which can be obtained.
      warnings.warn(msg, IntegrationWarning)
      /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The integral is probably divergent, or slowly convergent.
      warnings.warn(msg, IntegrationWarning)
      /home/vcti/anaconda3/lib/python3.7/site-packages/scipy/integrate/quadpack.py:385: IntegrationWarning: The maximum number of subdivisions (50) has been achieved.
      If increasing the limit yields no improvement it is advised to analyze
      the integrand in order to determine the difficulties. If the position of a
      local difficulty can be determined (singularity, discontinuity) one will
      probably gain from splitting up the interval and calling the integrator
      on the subranges. Perhaps a special-purpose integrator should be used.
      warnings.warn(msg, IntegrationWarning)


      And the plot gives:



      enter image description here



      For values of T greater than 1e4 is where the problem begins. It should keep almost constant after this value, but you can see the horrible peaks it shows.
      I tried modifying the epsabs and the epsrel but it did not worked. I tried to split the integration limits, and apparently from E = m to 1e4 it works fine, but when it integrates from E = 1e5 to infinity is where again appear problems.



      When I print the results of the integral, it gives absurd values for nn (It can go from 5.454320597790705e+17 to -3085930898.2363224). I don't know what else to do. Thanks in advance!







      python integration quad






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Mar 7 at 22:49









      Ah77Ah77

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