I think you may be right. So we will need to implement mpmath as a
backend for this to work.

Aaron Meurer

On Tue, May 12, 2015 at 2:54 PM, Peter Brady <[email protected]> wrote:
> From the post:
>
>>  Initially the idea was to implement it in mpmath, but due to speed
>> concerns, the interval arithmetic module was completely implemented in
>> numpy. The interval arithmetic is not completely accurate as it uses
>> floating points, but it was sufficient for plotting.
>
>
> Perhaps since the y-bounds are [k:k+17] where k is 524 digit number, double
> precision arithmetic simply won't cut it.  Note that I haven't looked at the
> actually plotting routines to check, I'm just going off the above quote.
>
> On Tuesday, May 12, 2015 at 1:40:24 PM UTC-6, Aaron Meurer wrote:
>>
>> Ideally implitic_plot should be able to do it. The plot comes from a
>> paper whose algorithm was implemented in a GSoC project
>>
>> https://github.com/sympy/sympy/wiki/GSoC-2012-Report-Bharath-M-R:-Implicit-plotting.
>>
>> Aaron Meurer
>>
>> On Tue, May 12, 2015 at 12:45 PM, Sumith 1896 <[email protected]> wrote:
>> > Is there a need for an issue to be opened?
>> >
>> >
>> > On Tue, May 12, 2015 at 10:59 PM Peter Brady <[email protected]> wrote:
>> >>
>> >> Just tried:
>> >>
>> >> In [1]: from sympy import *
>> >>
>> >> In [3]: x,y = symbols("x y")
>> >>
>> >> In [11]: rhs =
>> >> floor(Mod(floor(y/17)*2**(-17*floor(x)-Mod(floor(y),17)),2))
>> >>
>> >> In [14]: s = "960 939 379 918 958 884 971 672 962 127 852 754 715 004
>> >> 339
>> >> 660 129 306 651 505 519 271 702 802 395 266 424 689 642 842 174 350 718
>> >> 121
>> >> 267 153 782 770 623 355 993 237 280 874 144 307 891 325 963 941 337 723
>> >> 487
>> >> 857 735 749 823 926 629 715 517 173 716 995 165 232 890 538 221 612 403
>> >> 238
>> >> 855 866 184 013 235 585 136 048 828 693 337 902 491 454 229 288 667 081
>> >> 096
>> >> 184 496 091 705 183 454 067 827 731 551 705 405 381 627 380 967 602 565
>> >> 625
>> >> 016 981 482 083 418 783 163 849 115 590 225 610 003 652 351 370 343 874
>> >> 461
>> >> 848 378 737 238 198 224 849 863 465 033 159 410 054 974 700 593 138 339
>> >> 226
>> >> 497 249 461 751 545 728 366 702 369 745 461 014 655 997 933 798 537 483
>> >> 143
>> >> 786 841 806 593 422 227 898 388 722 980 000 748 404 719".replace(" ",
>> >> "")
>> >>
>> >> In [16]: k = S(s)
>> >>
>> >> In [17]: plot_
>> >> plot_backends  plot_implicit
>> >>
>> >> In [17]: plot_implicit(S(1/2) < rhs, (x, 0, 106), (y, k, k+17))
>> >> /home/ptb/gitrepos/sympy/sympy/plotting/plot_implicit.py:84:
>> >> UserWarning:
>> >> Adaptive meshing could not be applied to the expression. Using uniform
>> >> meshing.
>> >>   warnings.warn("Adaptive meshing could not be applied to the"
>> >>
>> >> I then got a lot of errors that started with:
>> >>
>> >>
>> >>
>> >> ---------------------------------------------------------------------------
>> >> ValueError                                Traceback (most recent call
>> >> last)
>> >> /home/ptb/gitrepos/sympy/sympy/plotting/experimental_lambdify.py in
>> >> __call__(self, *args)
>> >>     118             temp_args = (np.array(a, dtype=np.complex) for a in
>> >> args)
>> >> --> 119             results = self.vector_func(*temp_args)
>> >>     120             results = np.ma.masked_where(
>> >>
>> >> <string> in <lambda>(x0, x1)
>> >>
>> >> and ended with
>> >>
>> >> /home/ptb/gitrepos/sympy/sympy/sets/sets.py in __new__(cls, *args,
>> >> **kwargs)
>> >>    1684         evaluate = kwargs.get('evaluate', global_evaluate[0])
>> >>    1685         if evaluate:
>> >> -> 1686             args = list(map(sympify, args))
>> >>    1687
>> >>    1688             if len(args) == 0:
>> >>
>> >> RuntimeError: maximum recursion depth exceeded
>> >>
>> >>
>> >> On Tuesday, May 12, 2015 at 11:22:14 AM UTC-6, Ondřej Čertík wrote:
>> >>>
>> >>> On Tue, May 12, 2015 at 10:00 AM, Sumith 1896 <[email protected]>
>> >>> wrote:
>> >>> > Hi there,
>> >>> > I just happened to come across this very interesting formula known
>> >>> > as
>> >>> > Tupper’s self-referential formula.
>> >>> > The wiki article says that is a formula defined by Jeff Tupper that,
>> >>> > when graphed in two dimensions at a very specific location in the
>> >>> > plane, can
>> >>> > be “programmed” to visually reproduce the formula itself.
>> >>> > Matlab is capable to plot this. It was very interesting to see the
>> >>> > plot.
>> >>> > Is our plotting module capable to plot this?
>> >>> > If yes, could you say how?
>> >>>
>> >>>
>> >>> Good question, we should be able to do it. I found more info about
>> >>> this:
>> >>>
>> >>>
>> >>>
>> >>> http://www.quora.com/How-did-Jeff-Tupper-come-up-with-his-%E2%80%9Cself-referential%E2%80%9D-formula
>> >>>
>> >>> With some other examples.
>> >>>
>> >>> Ondrej
>> >>
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