> Why would the integration fail in the current release? It fails in master(dev version) too. It might be a problem with the integral module.
> I'm using the latest release (1.6.2), where `ContinuousRV` does not have a `check` argument. I see, maybe `check` argument will also come with the next release. Since, we ensure CI checks pass before merge, you may try using `master`(dev version) directly. The following steps can be helpful for installing the dev version. I have tried them on Linux. See https://docs.sympy.org/dev/install.html for more details. 1. git clone https://github.com/sympy/sympy 2. cd /path/to/sympy/sympy 3. python3 setup.py develop This way you will be able to do your task without much delay. Thank you and apologies for inconveniences. On Sun, Oct 11, 2020 at 10:23 PM [email protected] <[email protected]> wrote: > It seems you're working with the dev version. I'm using the latest > release (1.6.2), where `ContinuousRV` does not have a `check` argument. > Why would the integration fail in the current release? > > Thanks for the feedback, > -- > Seb > > > On Sunday, October 11, 2020 at 10:47:58 AM UTC-5 czgdp1807 wrote: > >> Hi, >> >> Try using the following, >> >> X = ContinuousRV(x, pdf, set=Interval(-oo, -_ETA), check=False) >> >> The keyword argument `check=True` in your case and hence the PDF is >> integrated for validation which fails. You can avoid that check by setting >> it to `False`. In the next release, it would be by default, `False`. See, >> https://github.com/sympy/sympy/pull/20120 and hence your code worked on >> the development version. >> >> On Sun, Oct 11, 2020 at 9:09 PM Gagandeep Singh (B17CS021) < >> [email protected]> wrote: >> >>> IPython console for SymPy 1.7.dev (Python 3.6.9-64-bit) (ground types: >>> python) >>> >>> These commands were executed: >>> >>> from __future__ import division >>> >>> from sympy import * >>> >>> x, y, z, t = symbols('x y z t') >>> >>> k, m, n = symbols('k m n', integer=True) >>> >>> f, g, h = symbols('f g h', cls=Function) >>> >>> init_printing() >>> >>> Documentation can be found at https://docs.sympy.org/dev >>> >>> >>> In [1]: from sympy.stats import ContinuousRV >>> >>> In [2]: from sympy import Lambda, log, Pow, exp, symbols, Interval, oo >>> >>> In [3]: _BETA = 10.56 >>> >>> In [5]: _ETA = -90 >>> >>> In [6]: _ALPHA = 3.11 >>> >>> In [7]: x, beta, alpha, eta = symbols("x, beta, alpha, eta") >>> >>> In [8]: log_weibull_pdf = ((beta / (alpha * (1 - x - eta))) * >>> ...: (Pow(log(1 - x - eta) / alpha, beta - 1)) * >>> ...: (exp(-Pow(log(1 - x - eta) / alpha, beta)))) >>> >>> In [9]: log_weibull_pdf.subs({beta: _BETA, >>> ...: alpha: _ALPHA, >>> ...: eta: _ETA} >>> ...: >>> ...: >>> ...: >>> ...: >>> ...: ) >>> Out[9]: >>> 10.56 >>> >>> -6.25821230086363e-6⋅log (91 - x) 9.56 >>> >>> 6.60867218971199e-5⋅ℯ ⋅log (91 - >>> x) >>> >>> ────────────────────────────────────────────────────────────────────────── >>> 91 - x >>> >>> >>> In [10]: pdf = _ >>> >>> In [11]: X = ContinuousRV(x, pdf, set=Interval(-oo, -_ETA)) >>> >>> In [12]: X >>> Out[12]: x >>> >>> In [14]: from sympy.stats import density >>> >>> In [15]: density(X)(y) >>> Out[15]: >>> ⎧ 10.56 >>> >>> ⎪ -6.25821230086363e-6⋅log (91 - y) 9.56 >>> >>> ⎪6.60867218971199e-5⋅ℯ ⋅log (91 - >>> y) >>> ⎨────────────────────────────────────────────────────────────────────────── >>> f >>> ⎪ 91 - y >>> >>> ⎪ >>> >>> ⎩ 0 >>> >>> >>> >>> >>> >>> or y ≥ -∞ ∧ y ≤ 90 >>> >>> >>> otherwise >>> >>> Is the above what you were trying to do? >>> >>> On Sun, Oct 11, 2020 at 8:55 PM [email protected] <[email protected]> >>> wrote: >>> >>>> Here is my attempt with ContinuousRV: >>>> >>>> from sympy.stats import ContinuousRV >>>> from sympy import Lambda, log, Pow, exp, symbols, Interval, oo >>>> >>>> # Parameters >>>> _BETA = 10.56 >>>> _ETA = -90 >>>> _ALPHA = 3.11 >>>> >>>> x, beta, alpha, eta = symbols("x, beta, alpha, eta") >>>> >>>> log_weibull_pdf = ((beta / (alpha * (1 - x - eta))) * >>>> (Pow(log(1 - x - eta) / alpha, beta - 1)) * >>>> (exp(-Pow(log(1 - x - eta) / alpha, beta)))) >>>> X = ContinuousRV(x, log_weibull_pdf.subs({beta: _BETA, >>>> alpha: _ALPHA, >>>> eta: _ETA}), >>>> set=Interval(-oo, -_ETA)) >>>> >>>> which fails with: >>>> >>>> ValueError: x**w where w is irrational is not defined for negative x >>>> >>>> -- >>>> Seb >>>> >>>> >>>> On Sunday, October 11, 2020 at 1:51:16 AM UTC-5 czgdp1807 wrote: >>>> >>>>> Hi, >>>>> >>>>> I think for creating RVs with custom distributions, one can use, >>>>> ContinuousRV, DiscreteRV Or FiniteRV depending on the type of >>>>> distribution. You can take a look at >>>>> https://docs.sympy.org/latest/modules/stats.html#examples >>>>> Note that the PDF/PMF should be a SymPy object. >>>>> >>>>> With Regards, >>>>> Gagandeep Singh >>>>> Github - https://github.com/czgdp1807 >>>>> LinkedIn - https://www.linkedin.com/in/czgdp1807 >>>>> >>>>> On Sun, 11 Oct, 2020, 3:45 AM [email protected], <[email protected]> >>>>> wrote: >>>>> >>>>>> Hello, >>>>>> >>>>>> I'm trying to set up a custom distribution with the following >>>>>> function describing its PDF: >>>>>> >>>>>> def pdf(x, beta, alpha, eta): >>>>>> t0 = beta / (alpha * (1 - x - eta)) >>>>>> t1 = pow(np.log(1 - x - eta) / alpha, beta - 1) >>>>>> t2 = np.exp(-pow(np.log(1 - x - eta) / alpha, beta)) >>>>>> return t0 * t1 * t2 >>>>>> >>>>>> It's a particular parameterization of the Log-Weibull distribution, >>>>>> with beta and alpha being the shape and scale parameters, respectively, >>>>>> and >>>>>> eta acts as a shift parameter representing the upper bound of the sample >>>>>> space, which is then defined as -inf < x < eta. I'm interested in >>>>>> drawing >>>>>> random variates, computing the above PDF, and CDF. >>>>>> >>>>>> I have limited experience with sympy, and none with sympy.stats, but >>>>>> it seems as if what I need is sympy.stats.ContinuousDistributionHandmade. >>>>>> However, I'd appreciate any pointers. >>>>>> >>>>>> Thanks, >>>>>> -- >>>>>> Seb >>>>>> >>>>>> -- >>>>>> You received this message because you are subscribed to the Google >>>>>> Groups "sympy" group. >>>>>> To unsubscribe from this group and stop receiving emails from it, >>>>>> send an email to [email protected]. >>>>>> To view this discussion on the web visit >>>>>> https://groups.google.com/d/msgid/sympy/8f73147b-7032-464d-b95c-a1b68537c1a7n%40googlegroups.com >>>>>> <https://groups.google.com/d/msgid/sympy/8f73147b-7032-464d-b95c-a1b68537c1a7n%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>> . >>>>>> >>>>> -- >>>> You received this message because you are subscribed to the Google >>>> Groups "sympy" group. >>>> To unsubscribe from this group and stop receiving emails from it, send >>>> an email to [email protected]. >>>> To view this discussion on the web visit >>>> https://groups.google.com/d/msgid/sympy/16120812-5243-4f41-869e-7d03288dfb97n%40googlegroups.com >>>> <https://groups.google.com/d/msgid/sympy/16120812-5243-4f41-869e-7d03288dfb97n%40googlegroups.com?utm_medium=email&utm_source=footer> >>>> . >>>> >>> >>> >>> -- >>> With regards, >>> Gagandeep Singh >>> Github - https://github.com/czgdp1807/ >>> Linkedin - https://www.linkedin.com/in/czgdp1807/ >>> <https://www.linkedin.com/in/gdp1/> >>> >> >> >> -- >> With regards, >> Gagandeep Singh >> Github - https://github.com/czgdp1807/ >> Linkedin - https://www.linkedin.com/in/czgdp1807/ >> <https://www.linkedin.com/in/gdp1/> >> > -- > You received this message because you are subscribed to the Google Groups > "sympy" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To view this discussion on the web visit > https://groups.google.com/d/msgid/sympy/4f6cd660-20e1-4fce-9f58-30ff3a65e505n%40googlegroups.com > <https://groups.google.com/d/msgid/sympy/4f6cd660-20e1-4fce-9f58-30ff3a65e505n%40googlegroups.com?utm_medium=email&utm_source=footer> > . > -- With regards, Gagandeep Singh Github - https://github.com/czgdp1807/ Linkedin - https://www.linkedin.com/in/czgdp1807/ <https://www.linkedin.com/in/gdp1/> -- You received this message because you are subscribed to the Google Groups "sympy" group. 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