Approximation of square root of sum of two squared terms












0














I have the following equation



$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}$. I want to get rid of square-root and find an approximation which contains only $x_a,x_n,y_a,y_n$ (there should not be any other non-linear operator in the approximation). Can anyone help me in this matter and guide me to the right direction?



$x_n <x_a, y_n<y_a, y_a<x_a$ and $x_a,x_n,y_a,y_n in[-1,1]$. However, $y_n$ is not always less than $x_n$.










share|cite|improve this question
























  • $x_a+y_a-x_n-y_n$ is an approximation, albeit not a good one (though it is good when $x_a-x_ngg y_a-y_n$ or $x_a-x_nll y_a-y_n$)
    – Hagen von Eitzen
    Nov 24 at 21:29










  • Would you accept the approximation $1/2?$ If not what are your requirements for the goodness of approximation?
    – gammatester
    Nov 24 at 21:32












  • @HagenvonEitzen I have modified my question a bit and add a new condition. I think under that condition, your suggested approximation might work. What do you think?
    – Muhammad Usman
    Nov 24 at 21:48












  • @gammatester My requirement is that approximated value should lie in between $in [0.9-1]$
    – Muhammad Usman
    Nov 24 at 21:51










  • Then why not use $0.95?$ Again: how accurate should the approximation be?
    – gammatester
    Nov 24 at 21:53


















0














I have the following equation



$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}$. I want to get rid of square-root and find an approximation which contains only $x_a,x_n,y_a,y_n$ (there should not be any other non-linear operator in the approximation). Can anyone help me in this matter and guide me to the right direction?



$x_n <x_a, y_n<y_a, y_a<x_a$ and $x_a,x_n,y_a,y_n in[-1,1]$. However, $y_n$ is not always less than $x_n$.










share|cite|improve this question
























  • $x_a+y_a-x_n-y_n$ is an approximation, albeit not a good one (though it is good when $x_a-x_ngg y_a-y_n$ or $x_a-x_nll y_a-y_n$)
    – Hagen von Eitzen
    Nov 24 at 21:29










  • Would you accept the approximation $1/2?$ If not what are your requirements for the goodness of approximation?
    – gammatester
    Nov 24 at 21:32












  • @HagenvonEitzen I have modified my question a bit and add a new condition. I think under that condition, your suggested approximation might work. What do you think?
    – Muhammad Usman
    Nov 24 at 21:48












  • @gammatester My requirement is that approximated value should lie in between $in [0.9-1]$
    – Muhammad Usman
    Nov 24 at 21:51










  • Then why not use $0.95?$ Again: how accurate should the approximation be?
    – gammatester
    Nov 24 at 21:53
















0












0








0







I have the following equation



$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}$. I want to get rid of square-root and find an approximation which contains only $x_a,x_n,y_a,y_n$ (there should not be any other non-linear operator in the approximation). Can anyone help me in this matter and guide me to the right direction?



$x_n <x_a, y_n<y_a, y_a<x_a$ and $x_a,x_n,y_a,y_n in[-1,1]$. However, $y_n$ is not always less than $x_n$.










share|cite|improve this question















I have the following equation



$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}$. I want to get rid of square-root and find an approximation which contains only $x_a,x_n,y_a,y_n$ (there should not be any other non-linear operator in the approximation). Can anyone help me in this matter and guide me to the right direction?



$x_n <x_a, y_n<y_a, y_a<x_a$ and $x_a,x_n,y_a,y_n in[-1,1]$. However, $y_n$ is not always less than $x_n$.







real-analysis approximation radicals






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Nov 24 at 22:11

























asked Nov 24 at 21:26









Muhammad Usman

136




136












  • $x_a+y_a-x_n-y_n$ is an approximation, albeit not a good one (though it is good when $x_a-x_ngg y_a-y_n$ or $x_a-x_nll y_a-y_n$)
    – Hagen von Eitzen
    Nov 24 at 21:29










  • Would you accept the approximation $1/2?$ If not what are your requirements for the goodness of approximation?
    – gammatester
    Nov 24 at 21:32












  • @HagenvonEitzen I have modified my question a bit and add a new condition. I think under that condition, your suggested approximation might work. What do you think?
    – Muhammad Usman
    Nov 24 at 21:48












  • @gammatester My requirement is that approximated value should lie in between $in [0.9-1]$
    – Muhammad Usman
    Nov 24 at 21:51










  • Then why not use $0.95?$ Again: how accurate should the approximation be?
    – gammatester
    Nov 24 at 21:53




















  • $x_a+y_a-x_n-y_n$ is an approximation, albeit not a good one (though it is good when $x_a-x_ngg y_a-y_n$ or $x_a-x_nll y_a-y_n$)
    – Hagen von Eitzen
    Nov 24 at 21:29










  • Would you accept the approximation $1/2?$ If not what are your requirements for the goodness of approximation?
    – gammatester
    Nov 24 at 21:32












  • @HagenvonEitzen I have modified my question a bit and add a new condition. I think under that condition, your suggested approximation might work. What do you think?
    – Muhammad Usman
    Nov 24 at 21:48












  • @gammatester My requirement is that approximated value should lie in between $in [0.9-1]$
    – Muhammad Usman
    Nov 24 at 21:51










  • Then why not use $0.95?$ Again: how accurate should the approximation be?
    – gammatester
    Nov 24 at 21:53


















$x_a+y_a-x_n-y_n$ is an approximation, albeit not a good one (though it is good when $x_a-x_ngg y_a-y_n$ or $x_a-x_nll y_a-y_n$)
– Hagen von Eitzen
Nov 24 at 21:29




$x_a+y_a-x_n-y_n$ is an approximation, albeit not a good one (though it is good when $x_a-x_ngg y_a-y_n$ or $x_a-x_nll y_a-y_n$)
– Hagen von Eitzen
Nov 24 at 21:29












Would you accept the approximation $1/2?$ If not what are your requirements for the goodness of approximation?
– gammatester
Nov 24 at 21:32






Would you accept the approximation $1/2?$ If not what are your requirements for the goodness of approximation?
– gammatester
Nov 24 at 21:32














@HagenvonEitzen I have modified my question a bit and add a new condition. I think under that condition, your suggested approximation might work. What do you think?
– Muhammad Usman
Nov 24 at 21:48






@HagenvonEitzen I have modified my question a bit and add a new condition. I think under that condition, your suggested approximation might work. What do you think?
– Muhammad Usman
Nov 24 at 21:48














@gammatester My requirement is that approximated value should lie in between $in [0.9-1]$
– Muhammad Usman
Nov 24 at 21:51




@gammatester My requirement is that approximated value should lie in between $in [0.9-1]$
– Muhammad Usman
Nov 24 at 21:51












Then why not use $0.95?$ Again: how accurate should the approximation be?
– gammatester
Nov 24 at 21:53






Then why not use $0.95?$ Again: how accurate should the approximation be?
– gammatester
Nov 24 at 21:53












3 Answers
3






active

oldest

votes


















0














Let $vec{r}=<x_n,y_n>$, $vec{r_0}=<x_a,y_a>$



$d^2=(vec{r}-vec{r_0})^2$



$d=sqrt{r_n^2+ r_0^2-2 vec{r_n} cdot vec{r_0}}$



From here, I Think there are several options.



With some tweaking, I think you can expand with legendre polynomials.



There's also a vector version of Taylor Series applicable.:



$f(x,y)=f(x_0,y_0)+nabla f cdotvec{ds}+...$






share|cite|improve this answer































    0














    You are not very explicit about the kind of function you allow, nor the desired accuracy.



    Your expression (Euclidean distance between two points) is essentially the square root of



    $$(x_a-x_n)^2+(y_a-y_n)^2$$



    which only uses the elementary operations. So you can focus on just the square root function, for arguments between $0$ and $8$.



    If you can hack into the floating-point representation, you can transform the value to a number between $1$ and $2$ and an integer power of $2$. Then the square root will be the square root of the number times two to a half-integer power, i.e. an integer or an integer times $sqrt2$.



    The square root function is very smooth and simple, and even a linear approximation could do ! There are numerous options such as parabolic or cubic interpolation or approximation.



    enter image description here





    Another approach is by considering the largest of $|x_a-x_n|,|y_a-y_n|$ (e.g. $x$) and write



    $$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}=|x_a-x_n|sqrt{1+left(frac{y_a-y_n}{x_a-x_n}right)^2}.$$



    Now you only have to approximate $sqrt{1+t^2}$ in the range $[0,1]$.



    enter image description here



    (Or $sqrt{1+t}$ if you can afford to square $t$ explicitly, giving the same curve as above.)





    Last but not least, you may consider the wonderful Moller-Morisson algorithm that only uses the four basic operations as has an excellent convergence speed. https://blogs.mathworks.com/images/cleve/moler_morrison.pdf






    share|cite|improve this answer































      0














      Starting from Yves Daoust's answer.



      A good approximation of $sqrt{1+t^2}$ could be obtained using the simplest Padé approximant of it (built at $t=0$). This would be
      $$sqrt{1+t^2}sim frac {4+3t^2}{4+t^2}$$ If more accuracy is required, we can minimize
      $$Phi=int_0^1 left(sqrt{t^2+1}-frac{1+a t^2}{1+b t^2}right)^2 , dt$$ which has a (very nasty) expression. Numerically, $a= 0.689417$ and $b=0.195385$ corresponding to $Phi=8.45times 10^{-8}$ while using $a=frac 34$ and $b=frac 14$ would give $Phi=1.88 times 10^{-5}$.






      share|cite|improve this answer





















        Your Answer





        StackExchange.ifUsing("editor", function () {
        return StackExchange.using("mathjaxEditing", function () {
        StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
        StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
        });
        });
        }, "mathjax-editing");

        StackExchange.ready(function() {
        var channelOptions = {
        tags: "".split(" "),
        id: "69"
        };
        initTagRenderer("".split(" "), "".split(" "), channelOptions);

        StackExchange.using("externalEditor", function() {
        // Have to fire editor after snippets, if snippets enabled
        if (StackExchange.settings.snippets.snippetsEnabled) {
        StackExchange.using("snippets", function() {
        createEditor();
        });
        }
        else {
        createEditor();
        }
        });

        function createEditor() {
        StackExchange.prepareEditor({
        heartbeatType: 'answer',
        autoActivateHeartbeat: false,
        convertImagesToLinks: true,
        noModals: true,
        showLowRepImageUploadWarning: true,
        reputationToPostImages: 10,
        bindNavPrevention: true,
        postfix: "",
        imageUploader: {
        brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
        contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
        allowUrls: true
        },
        noCode: true, onDemand: true,
        discardSelector: ".discard-answer"
        ,immediatelyShowMarkdownHelp:true
        });


        }
        });














        draft saved

        draft discarded


















        StackExchange.ready(
        function () {
        StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3012104%2fapproximation-of-square-root-of-sum-of-two-squared-terms%23new-answer', 'question_page');
        }
        );

        Post as a guest















        Required, but never shown

























        3 Answers
        3






        active

        oldest

        votes








        3 Answers
        3






        active

        oldest

        votes









        active

        oldest

        votes






        active

        oldest

        votes









        0














        Let $vec{r}=<x_n,y_n>$, $vec{r_0}=<x_a,y_a>$



        $d^2=(vec{r}-vec{r_0})^2$



        $d=sqrt{r_n^2+ r_0^2-2 vec{r_n} cdot vec{r_0}}$



        From here, I Think there are several options.



        With some tweaking, I think you can expand with legendre polynomials.



        There's also a vector version of Taylor Series applicable.:



        $f(x,y)=f(x_0,y_0)+nabla f cdotvec{ds}+...$






        share|cite|improve this answer




























          0














          Let $vec{r}=<x_n,y_n>$, $vec{r_0}=<x_a,y_a>$



          $d^2=(vec{r}-vec{r_0})^2$



          $d=sqrt{r_n^2+ r_0^2-2 vec{r_n} cdot vec{r_0}}$



          From here, I Think there are several options.



          With some tweaking, I think you can expand with legendre polynomials.



          There's also a vector version of Taylor Series applicable.:



          $f(x,y)=f(x_0,y_0)+nabla f cdotvec{ds}+...$






          share|cite|improve this answer


























            0












            0








            0






            Let $vec{r}=<x_n,y_n>$, $vec{r_0}=<x_a,y_a>$



            $d^2=(vec{r}-vec{r_0})^2$



            $d=sqrt{r_n^2+ r_0^2-2 vec{r_n} cdot vec{r_0}}$



            From here, I Think there are several options.



            With some tweaking, I think you can expand with legendre polynomials.



            There's also a vector version of Taylor Series applicable.:



            $f(x,y)=f(x_0,y_0)+nabla f cdotvec{ds}+...$






            share|cite|improve this answer














            Let $vec{r}=<x_n,y_n>$, $vec{r_0}=<x_a,y_a>$



            $d^2=(vec{r}-vec{r_0})^2$



            $d=sqrt{r_n^2+ r_0^2-2 vec{r_n} cdot vec{r_0}}$



            From here, I Think there are several options.



            With some tweaking, I think you can expand with legendre polynomials.



            There's also a vector version of Taylor Series applicable.:



            $f(x,y)=f(x_0,y_0)+nabla f cdotvec{ds}+...$







            share|cite|improve this answer














            share|cite|improve this answer



            share|cite|improve this answer








            edited Nov 24 at 22:31

























            answered Nov 24 at 22:21









            TurlocTheRed

            838311




            838311























                0














                You are not very explicit about the kind of function you allow, nor the desired accuracy.



                Your expression (Euclidean distance between two points) is essentially the square root of



                $$(x_a-x_n)^2+(y_a-y_n)^2$$



                which only uses the elementary operations. So you can focus on just the square root function, for arguments between $0$ and $8$.



                If you can hack into the floating-point representation, you can transform the value to a number between $1$ and $2$ and an integer power of $2$. Then the square root will be the square root of the number times two to a half-integer power, i.e. an integer or an integer times $sqrt2$.



                The square root function is very smooth and simple, and even a linear approximation could do ! There are numerous options such as parabolic or cubic interpolation or approximation.



                enter image description here





                Another approach is by considering the largest of $|x_a-x_n|,|y_a-y_n|$ (e.g. $x$) and write



                $$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}=|x_a-x_n|sqrt{1+left(frac{y_a-y_n}{x_a-x_n}right)^2}.$$



                Now you only have to approximate $sqrt{1+t^2}$ in the range $[0,1]$.



                enter image description here



                (Or $sqrt{1+t}$ if you can afford to square $t$ explicitly, giving the same curve as above.)





                Last but not least, you may consider the wonderful Moller-Morisson algorithm that only uses the four basic operations as has an excellent convergence speed. https://blogs.mathworks.com/images/cleve/moler_morrison.pdf






                share|cite|improve this answer




























                  0














                  You are not very explicit about the kind of function you allow, nor the desired accuracy.



                  Your expression (Euclidean distance between two points) is essentially the square root of



                  $$(x_a-x_n)^2+(y_a-y_n)^2$$



                  which only uses the elementary operations. So you can focus on just the square root function, for arguments between $0$ and $8$.



                  If you can hack into the floating-point representation, you can transform the value to a number between $1$ and $2$ and an integer power of $2$. Then the square root will be the square root of the number times two to a half-integer power, i.e. an integer or an integer times $sqrt2$.



                  The square root function is very smooth and simple, and even a linear approximation could do ! There are numerous options such as parabolic or cubic interpolation or approximation.



                  enter image description here





                  Another approach is by considering the largest of $|x_a-x_n|,|y_a-y_n|$ (e.g. $x$) and write



                  $$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}=|x_a-x_n|sqrt{1+left(frac{y_a-y_n}{x_a-x_n}right)^2}.$$



                  Now you only have to approximate $sqrt{1+t^2}$ in the range $[0,1]$.



                  enter image description here



                  (Or $sqrt{1+t}$ if you can afford to square $t$ explicitly, giving the same curve as above.)





                  Last but not least, you may consider the wonderful Moller-Morisson algorithm that only uses the four basic operations as has an excellent convergence speed. https://blogs.mathworks.com/images/cleve/moler_morrison.pdf






                  share|cite|improve this answer


























                    0












                    0








                    0






                    You are not very explicit about the kind of function you allow, nor the desired accuracy.



                    Your expression (Euclidean distance between two points) is essentially the square root of



                    $$(x_a-x_n)^2+(y_a-y_n)^2$$



                    which only uses the elementary operations. So you can focus on just the square root function, for arguments between $0$ and $8$.



                    If you can hack into the floating-point representation, you can transform the value to a number between $1$ and $2$ and an integer power of $2$. Then the square root will be the square root of the number times two to a half-integer power, i.e. an integer or an integer times $sqrt2$.



                    The square root function is very smooth and simple, and even a linear approximation could do ! There are numerous options such as parabolic or cubic interpolation or approximation.



                    enter image description here





                    Another approach is by considering the largest of $|x_a-x_n|,|y_a-y_n|$ (e.g. $x$) and write



                    $$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}=|x_a-x_n|sqrt{1+left(frac{y_a-y_n}{x_a-x_n}right)^2}.$$



                    Now you only have to approximate $sqrt{1+t^2}$ in the range $[0,1]$.



                    enter image description here



                    (Or $sqrt{1+t}$ if you can afford to square $t$ explicitly, giving the same curve as above.)





                    Last but not least, you may consider the wonderful Moller-Morisson algorithm that only uses the four basic operations as has an excellent convergence speed. https://blogs.mathworks.com/images/cleve/moler_morrison.pdf






                    share|cite|improve this answer














                    You are not very explicit about the kind of function you allow, nor the desired accuracy.



                    Your expression (Euclidean distance between two points) is essentially the square root of



                    $$(x_a-x_n)^2+(y_a-y_n)^2$$



                    which only uses the elementary operations. So you can focus on just the square root function, for arguments between $0$ and $8$.



                    If you can hack into the floating-point representation, you can transform the value to a number between $1$ and $2$ and an integer power of $2$. Then the square root will be the square root of the number times two to a half-integer power, i.e. an integer or an integer times $sqrt2$.



                    The square root function is very smooth and simple, and even a linear approximation could do ! There are numerous options such as parabolic or cubic interpolation or approximation.



                    enter image description here





                    Another approach is by considering the largest of $|x_a-x_n|,|y_a-y_n|$ (e.g. $x$) and write



                    $$sqrt{(x_a-x_n)^2+(y_a-y_n)^2}=|x_a-x_n|sqrt{1+left(frac{y_a-y_n}{x_a-x_n}right)^2}.$$



                    Now you only have to approximate $sqrt{1+t^2}$ in the range $[0,1]$.



                    enter image description here



                    (Or $sqrt{1+t}$ if you can afford to square $t$ explicitly, giving the same curve as above.)





                    Last but not least, you may consider the wonderful Moller-Morisson algorithm that only uses the four basic operations as has an excellent convergence speed. https://blogs.mathworks.com/images/cleve/moler_morrison.pdf







                    share|cite|improve this answer














                    share|cite|improve this answer



                    share|cite|improve this answer








                    edited Nov 24 at 23:34

























                    answered Nov 24 at 23:17









                    Yves Daoust

                    124k671221




                    124k671221























                        0














                        Starting from Yves Daoust's answer.



                        A good approximation of $sqrt{1+t^2}$ could be obtained using the simplest Padé approximant of it (built at $t=0$). This would be
                        $$sqrt{1+t^2}sim frac {4+3t^2}{4+t^2}$$ If more accuracy is required, we can minimize
                        $$Phi=int_0^1 left(sqrt{t^2+1}-frac{1+a t^2}{1+b t^2}right)^2 , dt$$ which has a (very nasty) expression. Numerically, $a= 0.689417$ and $b=0.195385$ corresponding to $Phi=8.45times 10^{-8}$ while using $a=frac 34$ and $b=frac 14$ would give $Phi=1.88 times 10^{-5}$.






                        share|cite|improve this answer


























                          0














                          Starting from Yves Daoust's answer.



                          A good approximation of $sqrt{1+t^2}$ could be obtained using the simplest Padé approximant of it (built at $t=0$). This would be
                          $$sqrt{1+t^2}sim frac {4+3t^2}{4+t^2}$$ If more accuracy is required, we can minimize
                          $$Phi=int_0^1 left(sqrt{t^2+1}-frac{1+a t^2}{1+b t^2}right)^2 , dt$$ which has a (very nasty) expression. Numerically, $a= 0.689417$ and $b=0.195385$ corresponding to $Phi=8.45times 10^{-8}$ while using $a=frac 34$ and $b=frac 14$ would give $Phi=1.88 times 10^{-5}$.






                          share|cite|improve this answer
























                            0












                            0








                            0






                            Starting from Yves Daoust's answer.



                            A good approximation of $sqrt{1+t^2}$ could be obtained using the simplest Padé approximant of it (built at $t=0$). This would be
                            $$sqrt{1+t^2}sim frac {4+3t^2}{4+t^2}$$ If more accuracy is required, we can minimize
                            $$Phi=int_0^1 left(sqrt{t^2+1}-frac{1+a t^2}{1+b t^2}right)^2 , dt$$ which has a (very nasty) expression. Numerically, $a= 0.689417$ and $b=0.195385$ corresponding to $Phi=8.45times 10^{-8}$ while using $a=frac 34$ and $b=frac 14$ would give $Phi=1.88 times 10^{-5}$.






                            share|cite|improve this answer












                            Starting from Yves Daoust's answer.



                            A good approximation of $sqrt{1+t^2}$ could be obtained using the simplest Padé approximant of it (built at $t=0$). This would be
                            $$sqrt{1+t^2}sim frac {4+3t^2}{4+t^2}$$ If more accuracy is required, we can minimize
                            $$Phi=int_0^1 left(sqrt{t^2+1}-frac{1+a t^2}{1+b t^2}right)^2 , dt$$ which has a (very nasty) expression. Numerically, $a= 0.689417$ and $b=0.195385$ corresponding to $Phi=8.45times 10^{-8}$ while using $a=frac 34$ and $b=frac 14$ would give $Phi=1.88 times 10^{-5}$.







                            share|cite|improve this answer












                            share|cite|improve this answer



                            share|cite|improve this answer










                            answered Nov 25 at 6:05









                            Claude Leibovici

                            119k1157132




                            119k1157132






























                                draft saved

                                draft discarded




















































                                Thanks for contributing an answer to Mathematics Stack Exchange!


                                • Please be sure to answer the question. Provide details and share your research!

                                But avoid



                                • Asking for help, clarification, or responding to other answers.

                                • Making statements based on opinion; back them up with references or personal experience.


                                Use MathJax to format equations. MathJax reference.


                                To learn more, see our tips on writing great answers.





                                Some of your past answers have not been well-received, and you're in danger of being blocked from answering.


                                Please pay close attention to the following guidance:


                                • Please be sure to answer the question. Provide details and share your research!

                                But avoid



                                • Asking for help, clarification, or responding to other answers.

                                • Making statements based on opinion; back them up with references or personal experience.


                                To learn more, see our tips on writing great answers.




                                draft saved


                                draft discarded














                                StackExchange.ready(
                                function () {
                                StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3012104%2fapproximation-of-square-root-of-sum-of-two-squared-terms%23new-answer', 'question_page');
                                }
                                );

                                Post as a guest















                                Required, but never shown





















































                                Required, but never shown














                                Required, but never shown












                                Required, but never shown







                                Required, but never shown

































                                Required, but never shown














                                Required, but never shown












                                Required, but never shown







                                Required, but never shown







                                Popular posts from this blog

                                Plaza Victoria

                                Puebla de Zaragoza

                                Musa