An instance of this class encapsulates data about a cromulent isomorphism $HX(a_H) \to PX(a_P)$ for some specific numerical values of $a_H$ and $a_P$
Field: a_H::numericThis should be set by the set_a_H method.
Field: a_P::numericThis will be calculated by the find_p1 method, and should not be set directly.
Field: v_HS::tableAs in Definition defn-schwarz-phi
Field: v_PS::tableAs in Definition defn-schwarz-phi
Field: c_HS::tableAs in Definition defn-schwarz-phi
Field: c_PS::tableAs in Definition defn-schwarz-phi
Field: psiAs in Definition defn-schwarz-phi. This is set up so that if X is an instance of the present class, the required syntax is X["psi"](z).
Field: psi_invAs in Definition defn-schwarz-phi, with the same kind of syntax as for psi
Field: phiAs in Definition defn-schwarz-phi, with the same kind of syntax as for psi
Field: phi_invAs in Definition defn-schwarz-phi, with the same kind of syntax as for psi
Field: samples::list(CC0)This is a list of points lying in $\psi^{-1}((C_3\cup C_5)\cap F_{16})$. These should be sent by $p_1$ to the unit circle, and the find_p1 method will try to choose the coefficients of $p_1$ to make this true. This should be set by the make_samples method.
Field: num_samples::posint = 200Number of sample points. This should be significantly larger than the poly_deg field. It should be set by the make_samples method.
Field: errs::listThe list of differences $|p_1(z)|^2-1$, as $z$ runs through the sample points.
Field: err::RR0The maximum absolute value of the above errors.
Field: poly_deg::posint = 20Number of degrees of freedom when choosing $p_1$. It should be set by the set_poly_deg method.
Field: a::list(RR0)This is a list of coefficients (of length equal to poly_deg) which determines the approximating function $p_1$. In more detail, we have $p_1=p_{10}+a_1p_{11}(z)+a_2p_{12}(z)+a_3p_{13}(z)+(sum_{i>3}a_iz^{2*i-8})p_{14}(z)$ for certain fixed functions $p_{1k}(z)$.
Field: p1A rational function of $z$ which approximates the map $p_1\:\Delta\to\C$.
Field: p1_seriesA Taylor series for $p_1$.
Field: p10An auxiliary polynomial.
Field: p11An auxiliary polynomial.
Field: p12An auxiliary polynomial.
Field: p13An auxiliary rational function.
Field: p14An auxiliary polynomial.
Field: p1_invA polynomial approximation to the compositional inverse of $p_1$.
Field: S_p1_invA polynomial approximation to the schwarzian derivative of $p_1^{-1}$.
Field: dA constant such that the schwarzian derivative of $p_1^{-1}$ is S0_p1_inv + d * S1_p1_inv
Field: schwarzian_errs::listA list of differences between the coefficients of $S(p_1^{-1})$ and S0_p1_inv + d * S1_p1_inv
Field: m_seriesA Taylor series for the function $m(z)$ such that $\omega_0=m(z) dz$.
Field: p_seriesA Taylor series for $p(z)$.
Field: mp_seriesA Taylor series for $m(z)p(z)$.
Method: set_a_H(a::RR1)::RR1Set the a_H field and perform associated bookkeeping.
Set the a_P field and perform associated bookkeeping. Normally one should only use the set_a_H method directly; then other code will calculate an appropriate value for a_P and call the set_a_P method.
Set the poly_deg field and perform associated bookkeeping.
Truncate or extend the a field to ensure that it has the right length.
Set the auxiliary functions p11 to p15. These are all odd polynomials with real coefficients and vanishing derivatives at $\psi^{-1}(v_0)$ and $\psi^{-1}(v_{11})$. The polynomials p11 and p12 vanish at $\psi^{-1}(v_0)$ and $\psi^{-1}(v_3)$, and take the values $1$ and $i$ respectively at $\psi^{-1}(v_{11})$. The polynomial p13 sends $\psi^{-1}(v_i)$ to $\phi(v_i)$ for $i\in\{0,3,6,11\}$, whereas p14 sends all these points to zero. The polynomials p11, p12 and p13 have degree $13$, whereas p14 has degree $15$, with linear term $z$. These properties charecterise the polynomials uniquely.
This calculates the function $p=\phi^{-1}\circ p_1\circ\psi$
This also calculates $p(z)$, but it uses the equivariance properties of $p_1$ so we only need to calculate $p_1(w)$ when $w$ is small
This calculates the function $m(z)$ such that $p^*(\omega_0)=m(z) dz$
This also calculates $m(z)$, but it uses the equivariance properties of $p_1$ so we only need to calculate $p_1(w)$ when $w$ is small
This finds a power series approximation to $m(z)$
This finds a power series approximation to $m(z)p(z)$
This finds a power series approximation to $p(z)$
Calculate a list of sample points. We have used equally spaced points, but Chebyshev spacing might be better.
This method searches for a polynomial p1 of the required form, which sends the sample points as close as possible to the unit circle.
This sets the fields p1_inv, S_p1_inv and d based on the p1 field.
Generates a plot of p1(F16), which should just be the first quadrant of the unit disc
Generates a plot of the behaviour of $p_1$ near $v_{11}$
This generates a plot showing the errors stored in the errs field.
This generates a plot showing the logs of the absolute values of the coefficients in the a field, which determine the approximating function $p_1$
This generates a plot showing the logs of the absolute values of the coefficients in the Taylor expansion of $p_1(z)$
This generates a plot showing the logs of the absolute values of the coefficients in the Taylor expansion of $p_1^{-1}(z)$
This generates a plot showing the logs of the absolute values of the errors stored in the schwarzian_errs field.
This generates a plot showing the curve $m(r e^{it})$, where $r$ is the radius argument.
This generates a tikzpicture environment showing the curve $m(r e^{it})$, where $r$ is the radius argument.