Computation of piece-wise linear hat functions












4














I have a discretized 3D surface for which I want to compute piece-wise linear hat functions. I assumed these functions are of the following form:



$$phi = ax + by + cz + d$$



with the property of $phi_i(x_j) = delta_{ij}$.



For a general 3D surface, the number of neighbors for each vertex is different, ranging from 3 to 6 or even more. For example, in the figure below, 3D vertex $i$ has 6 neighbors. This means:



$$
phi_{17}(x_{17}) = ax_{17} + by_{17} + cz_{17} + d_{17} = 1,\
phi_{17}(x_{11}) = ax_{11} + by_{11} + cz_{11} + d_{11} = 0,\
phi_{17}(x_{12}) = ax_{12} + by_{12} + cz_{12} + d_{12} = 0,\
phi_{17}(x_{13}) = ax_{13} + by_{13} + cz_{13} + d_{13} = 0,\
phi_{17}(x_{14}) = ax_{14} + by_{14} + cz_{14} + d_{14} = 0,\
phi_{17}(x_{15}) = ax_{15} + by_{15} + cz_{15} + d_{15} = 0,\
phi_{17}(x_{16}) = ax_{16} + by_{16} + cz_{16} + d_{16} = 0.\
$$



enter image description here



The system of equations for vertex 17 is overdetermined (7 equations and 4 unknowns) and not necessarily lead to a set of coefficients, $(a, b, c, d)$, that satisfy $phi_i(x_j) = delta_{ij}$.



I was wondering how piece-wise linear hat functions should be computed for such surfaces to guarantee the hat function is $1$ at vertex $i$ and $0$ at all other vertices.










share|cite|improve this question




















  • 2




    Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
    – Korf
    Oct 24 at 15:52












  • I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
    – AFP
    Oct 25 at 6:54








  • 2




    What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
    – Korf
    Oct 25 at 16:00
















4














I have a discretized 3D surface for which I want to compute piece-wise linear hat functions. I assumed these functions are of the following form:



$$phi = ax + by + cz + d$$



with the property of $phi_i(x_j) = delta_{ij}$.



For a general 3D surface, the number of neighbors for each vertex is different, ranging from 3 to 6 or even more. For example, in the figure below, 3D vertex $i$ has 6 neighbors. This means:



$$
phi_{17}(x_{17}) = ax_{17} + by_{17} + cz_{17} + d_{17} = 1,\
phi_{17}(x_{11}) = ax_{11} + by_{11} + cz_{11} + d_{11} = 0,\
phi_{17}(x_{12}) = ax_{12} + by_{12} + cz_{12} + d_{12} = 0,\
phi_{17}(x_{13}) = ax_{13} + by_{13} + cz_{13} + d_{13} = 0,\
phi_{17}(x_{14}) = ax_{14} + by_{14} + cz_{14} + d_{14} = 0,\
phi_{17}(x_{15}) = ax_{15} + by_{15} + cz_{15} + d_{15} = 0,\
phi_{17}(x_{16}) = ax_{16} + by_{16} + cz_{16} + d_{16} = 0.\
$$



enter image description here



The system of equations for vertex 17 is overdetermined (7 equations and 4 unknowns) and not necessarily lead to a set of coefficients, $(a, b, c, d)$, that satisfy $phi_i(x_j) = delta_{ij}$.



I was wondering how piece-wise linear hat functions should be computed for such surfaces to guarantee the hat function is $1$ at vertex $i$ and $0$ at all other vertices.










share|cite|improve this question




















  • 2




    Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
    – Korf
    Oct 24 at 15:52












  • I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
    – AFP
    Oct 25 at 6:54








  • 2




    What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
    – Korf
    Oct 25 at 16:00














4












4








4


0





I have a discretized 3D surface for which I want to compute piece-wise linear hat functions. I assumed these functions are of the following form:



$$phi = ax + by + cz + d$$



with the property of $phi_i(x_j) = delta_{ij}$.



For a general 3D surface, the number of neighbors for each vertex is different, ranging from 3 to 6 or even more. For example, in the figure below, 3D vertex $i$ has 6 neighbors. This means:



$$
phi_{17}(x_{17}) = ax_{17} + by_{17} + cz_{17} + d_{17} = 1,\
phi_{17}(x_{11}) = ax_{11} + by_{11} + cz_{11} + d_{11} = 0,\
phi_{17}(x_{12}) = ax_{12} + by_{12} + cz_{12} + d_{12} = 0,\
phi_{17}(x_{13}) = ax_{13} + by_{13} + cz_{13} + d_{13} = 0,\
phi_{17}(x_{14}) = ax_{14} + by_{14} + cz_{14} + d_{14} = 0,\
phi_{17}(x_{15}) = ax_{15} + by_{15} + cz_{15} + d_{15} = 0,\
phi_{17}(x_{16}) = ax_{16} + by_{16} + cz_{16} + d_{16} = 0.\
$$



enter image description here



The system of equations for vertex 17 is overdetermined (7 equations and 4 unknowns) and not necessarily lead to a set of coefficients, $(a, b, c, d)$, that satisfy $phi_i(x_j) = delta_{ij}$.



I was wondering how piece-wise linear hat functions should be computed for such surfaces to guarantee the hat function is $1$ at vertex $i$ and $0$ at all other vertices.










share|cite|improve this question















I have a discretized 3D surface for which I want to compute piece-wise linear hat functions. I assumed these functions are of the following form:



$$phi = ax + by + cz + d$$



with the property of $phi_i(x_j) = delta_{ij}$.



For a general 3D surface, the number of neighbors for each vertex is different, ranging from 3 to 6 or even more. For example, in the figure below, 3D vertex $i$ has 6 neighbors. This means:



$$
phi_{17}(x_{17}) = ax_{17} + by_{17} + cz_{17} + d_{17} = 1,\
phi_{17}(x_{11}) = ax_{11} + by_{11} + cz_{11} + d_{11} = 0,\
phi_{17}(x_{12}) = ax_{12} + by_{12} + cz_{12} + d_{12} = 0,\
phi_{17}(x_{13}) = ax_{13} + by_{13} + cz_{13} + d_{13} = 0,\
phi_{17}(x_{14}) = ax_{14} + by_{14} + cz_{14} + d_{14} = 0,\
phi_{17}(x_{15}) = ax_{15} + by_{15} + cz_{15} + d_{15} = 0,\
phi_{17}(x_{16}) = ax_{16} + by_{16} + cz_{16} + d_{16} = 0.\
$$



enter image description here



The system of equations for vertex 17 is overdetermined (7 equations and 4 unknowns) and not necessarily lead to a set of coefficients, $(a, b, c, d)$, that satisfy $phi_i(x_j) = delta_{ij}$.



I was wondering how piece-wise linear hat functions should be computed for such surfaces to guarantee the hat function is $1$ at vertex $i$ and $0$ at all other vertices.







finite-element-method piecewise-continuity






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share|cite|improve this question













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edited Oct 24 at 7:34

























asked Oct 24 at 7:10









AFP

225111




225111








  • 2




    Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
    – Korf
    Oct 24 at 15:52












  • I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
    – AFP
    Oct 25 at 6:54








  • 2




    What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
    – Korf
    Oct 25 at 16:00














  • 2




    Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
    – Korf
    Oct 24 at 15:52












  • I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
    – AFP
    Oct 25 at 6:54








  • 2




    What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
    – Korf
    Oct 25 at 16:00








2




2




Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
– Korf
Oct 24 at 15:52






Your expression for $phi$ holds only on a single triangle. The parameters $a, b, c, d$ can and will be different on each triangle since the function is only piecewise $P1$. So the problem with overdetermination is not really there. Also the surface is effectively 2D which means that there should be only 3 parameters for the hat function.
– Korf
Oct 24 at 15:52














I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
– AFP
Oct 25 at 6:54






I am actually trying to understand gradient computation that is described here: libigl.github.io/tutorial/#gradient. I want to find the operator $boldsymbol{G}$ in $nabla f approx mathbf{G},mathbf{f}$. Could you please let me know of your thoughts?
– AFP
Oct 25 at 6:54






2




2




What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
– Korf
Oct 25 at 16:00




What the tutorial describes is pretty much standard stuff and the tutorial itself says that $G_i = sumlimits_{i=1}^n nabla phi_i(mathbf{x})$ where $G_i$ is the row/column of $G$ and all information needed for the computation comes from the mesh. So I am afraid I am only able to suggest to read some introduction into finite element method relevant to your field.
– Korf
Oct 25 at 16:00










1 Answer
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oldest

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1














First define one triangle and interpolations as follows:
$$
begin{bmatrix} x \ y \ z end{bmatrix} =
begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
$$

And quite in general:
$$
phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
$$

From this reference we infer that:
$$
begin{cases}
xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
end{cases}
$$

Where $Delta$ is twice the area of a triangle.

The Finite Element shape functions thus are, still for one triangle:
$$
N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
$$
$$
x = N_1x_1+N_2x_2+N_3x_3 \
y = N_1y_1+N_2y_2+N_3y_3 \
z = N_1z_1+N_2z_2+N_3z_3 \
phi = N_1phi_1+N_2phi_2+N_3phi_3
$$

Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:




  1. $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$

  2. $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$

  3. $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$

  4. $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$

  5. $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$

  6. $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$






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    1 Answer
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    1 Answer
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    active

    oldest

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    active

    oldest

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    1














    First define one triangle and interpolations as follows:
    $$
    begin{bmatrix} x \ y \ z end{bmatrix} =
    begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
    begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
    begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
    qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
    $$

    And quite in general:
    $$
    phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
    $$

    From this reference we infer that:
    $$
    begin{cases}
    xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
    eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
    end{cases}
    $$

    Where $Delta$ is twice the area of a triangle.

    The Finite Element shape functions thus are, still for one triangle:
    $$
    N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
    $$
    $$
    x = N_1x_1+N_2x_2+N_3x_3 \
    y = N_1y_1+N_2y_2+N_3y_3 \
    z = N_1z_1+N_2z_2+N_3z_3 \
    phi = N_1phi_1+N_2phi_2+N_3phi_3
    $$

    Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:




    1. $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$

    2. $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$

    3. $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$

    4. $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$

    5. $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$

    6. $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$






    share|cite|improve this answer


























      1














      First define one triangle and interpolations as follows:
      $$
      begin{bmatrix} x \ y \ z end{bmatrix} =
      begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
      begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
      begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
      qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
      $$

      And quite in general:
      $$
      phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
      $$

      From this reference we infer that:
      $$
      begin{cases}
      xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
      eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
      end{cases}
      $$

      Where $Delta$ is twice the area of a triangle.

      The Finite Element shape functions thus are, still for one triangle:
      $$
      N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
      $$
      $$
      x = N_1x_1+N_2x_2+N_3x_3 \
      y = N_1y_1+N_2y_2+N_3y_3 \
      z = N_1z_1+N_2z_2+N_3z_3 \
      phi = N_1phi_1+N_2phi_2+N_3phi_3
      $$

      Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:




      1. $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$

      2. $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$

      3. $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$

      4. $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$

      5. $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$

      6. $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$






      share|cite|improve this answer
























        1












        1








        1






        First define one triangle and interpolations as follows:
        $$
        begin{bmatrix} x \ y \ z end{bmatrix} =
        begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
        begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
        begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
        qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
        $$

        And quite in general:
        $$
        phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
        $$

        From this reference we infer that:
        $$
        begin{cases}
        xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
        eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
        end{cases}
        $$

        Where $Delta$ is twice the area of a triangle.

        The Finite Element shape functions thus are, still for one triangle:
        $$
        N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
        $$
        $$
        x = N_1x_1+N_2x_2+N_3x_3 \
        y = N_1y_1+N_2y_2+N_3y_3 \
        z = N_1z_1+N_2z_2+N_3z_3 \
        phi = N_1phi_1+N_2phi_2+N_3phi_3
        $$

        Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:




        1. $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$

        2. $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$

        3. $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$

        4. $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$

        5. $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$

        6. $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$






        share|cite|improve this answer












        First define one triangle and interpolations as follows:
        $$
        begin{bmatrix} x \ y \ z end{bmatrix} =
        begin{bmatrix} x_1 \ y_1 \ z_1 end{bmatrix} +
        begin{bmatrix} x_2-x_1 \ y_2-y_1 \ z_2-z_1 end{bmatrix} xi +
        begin{bmatrix} x_3-x_1 \ y_3-y_1 \ z_3-z_1end{bmatrix} eta
        qquad mbox{with:} quad begin{cases} xi > 0 \ eta > 0 \ xi+eta < 1 end{cases}
        $$

        And quite in general:
        $$
        phi = phi_1 + (phi_2-phi_1),xi + (phi_3-phi_1),eta
        $$

        From this reference we infer that:
        $$
        begin{cases}
        xi = [ (y_3 - y_1).(x - x_1) - (x_3 - x_1).(y - y_1) ] / Delta \
        eta = [ (x_2 - x_1).(y - y_1) - (y_2 - y_1).(x - x_1) ] / Delta
        end{cases}
        $$

        Where $Delta$ is twice the area of a triangle.

        The Finite Element shape functions thus are, still for one triangle:
        $$
        N_1 = 1-xi-eta quad ; quad N_2 = xi quad ; quad N_3 = eta
        $$
        $$
        x = N_1x_1+N_2x_2+N_3x_3 \
        y = N_1y_1+N_2y_2+N_3y_3 \
        z = N_1z_1+N_2z_2+N_3z_3 \
        phi = N_1phi_1+N_2phi_2+N_3phi_3
        $$

        Now specify for the 6 triangles in you mesh and you're done, for $,xi = eta = 0,$ eventually:




        1. $(1)rightarrow(17) ;,; (2)rightarrow(11) ;,; (3)rightarrow(12)$

        2. $(1)rightarrow(17) ;,; (2)rightarrow(12) ;,; (3)rightarrow(13)$

        3. $(1)rightarrow(17) ;,; (2)rightarrow(13) ;,; (3)rightarrow(14)$

        4. $(1)rightarrow(17) ;,; (2)rightarrow(14) ;,; (3)rightarrow(15)$

        5. $(1)rightarrow(17) ;,; (2)rightarrow(15) ;,; (3)rightarrow(16)$

        6. $(1)rightarrow(17) ;,; (2)rightarrow(16) ;,; (3)rightarrow(11)$







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        answered Nov 18 at 15:19









        Han de Bruijn

        12.1k22361




        12.1k22361






























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