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_polybase.py
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""" Abstract base class for the various polynomial Classes. The ABCPolyBase class provides the methods needed to implement the common API for the various polynomial classes. It operates as a mixin, but uses the abc module from the stdlib, hence it is only available for Python >= 2.6. """ import abc import numbers import numpy as np from . import polyutils as pu __all__ = ['ABCPolyBase'] class ABCPolyBase(abc.ABC): """An abstract base class for immutable series classes. ABCPolyBase provides the standard Python numerical methods '+', '-', '*', '//', '%', 'divmod', '**', and '()' along with the methods listed below. .. versionadded:: 1.9.0 Parameters ---------- coef : array_like Series coefficients in order of increasing degree, i.e., ``(1, 2, 3)`` gives ``1*P_0(x) + 2*P_1(x) + 3*P_2(x)``, where ``P_i`` is the basis polynomials of degree ``i``. domain : (2,) array_like, optional Domain to use. The interval ``[domain[0], domain[1]]`` is mapped to the interval ``[window[0], window[1]]`` by shifting and scaling. The default value is the derived class domain. window : (2,) array_like, optional Window, see domain for its use. The default value is the derived class window. Attributes ---------- coef : (N,) ndarray Series coefficients in order of increasing degree. domain : (2,) ndarray Domain that is mapped to window. window : (2,) ndarray Window that domain is mapped to. Class Attributes ---------------- maxpower : int Maximum power allowed, i.e., the largest number ``n`` such that ``p(x)**n`` is allowed. This is to limit runaway polynomial size. domain : (2,) ndarray Default domain of the class. window : (2,) ndarray Default window of the class. """ # Not hashable __hash__ = None # Opt out of numpy ufuncs and Python ops with ndarray subclasses. __array_ufunc__ = None # Limit runaway size. T_n^m has degree n*m maxpower = 100 @property @abc.abstractmethod def domain(self): pass @property @abc.abstractmethod def window(self): pass @property @abc.abstractmethod def nickname(self): pass @property @abc.abstractmethod def basis_name(self): pass @staticmethod @abc.abstractmethod def _add(c1, c2): pass @staticmethod @abc.abstractmethod def _sub(c1, c2): pass @staticmethod @abc.abstractmethod def _mul(c1, c2): pass @staticmethod @abc.abstractmethod def _div(c1, c2): pass @staticmethod @abc.abstractmethod def _pow(c, pow, maxpower=None): pass @staticmethod @abc.abstractmethod def _val(x, c): pass @staticmethod @abc.abstractmethod def _int(c, m, k, lbnd, scl): pass @staticmethod @abc.abstractmethod def _der(c, m, scl): pass @staticmethod @abc.abstractmethod def _fit(x, y, deg, rcond, full): pass @staticmethod @abc.abstractmethod def _line(off, scl): pass @staticmethod @abc.abstractmethod def _roots(c): pass @staticmethod @abc.abstractmethod def _fromroots(r): pass def has_samecoef(self, other): """Check if coefficients match. .. versionadded:: 1.6.0 Parameters ---------- other : class instance The other class must have the ``coef`` attribute. Returns ------- bool : boolean True if the coefficients are the same, False otherwise. """ if len(self.coef) != len(other.coef): return False elif not np.all(self.coef == other.coef): return False else: return True def has_samedomain(self, other): """Check if domains match. .. versionadded:: 1.6.0 Parameters ---------- other : class instance The other class must have the ``domain`` attribute. Returns ------- bool : boolean True if the domains are the same, False otherwise. """ return np.all(self.domain == other.domain) def has_samewindow(self, other): """Check if windows match. .. versionadded:: 1.6.0 Parameters ---------- other : class instance The other class must have the ``window`` attribute. Returns ------- bool : boolean True if the windows are the same, False otherwise. """ return np.all(self.window == other.window) def has_sametype(self, other): """Check if types match. .. versionadded:: 1.7.0 Parameters ---------- other : object Class instance. Returns ------- bool : boolean True if other is same class as self """ return isinstance(other, self.__class__) def _get_coefficients(self, other): """Interpret other as polynomial coefficients. The `other` argument is checked to see if it is of the same class as self with identical domain and window. If so, return its coefficients, otherwise return `other`. .. versionadded:: 1.9.0 Parameters ---------- other : anything Object to be checked. Returns ------- coef The coefficients of`other` if it is a compatible instance, of ABCPolyBase, otherwise `other`. Raises ------ TypeError When `other` is an incompatible instance of ABCPolyBase. """ if isinstance(other, ABCPolyBase): if not isinstance(other, self.__class__): raise TypeError("Polynomial types differ") elif not np.all(self.domain == other.domain): raise TypeError("Domains differ") elif not np.all(self.window == other.window): raise TypeError("Windows differ") return other.coef return other def __init__(self, coef, domain=None, window=None): [coef] = pu.as_series([coef], trim=False) self.coef = coef if domain is not None: [domain] = pu.as_series([domain], trim=False) if len(domain) != 2: raise ValueError("Domain has wrong number of elements.") self.domain = domain if window is not None: [window] = pu.as_series([window], trim=False) if len(window) != 2: raise ValueError("Window has wrong number of elements.") self.window = window def __repr__(self): coef = repr(self.coef)[6:-1] domain = repr(self.domain)[6:-1] window = repr(self.window)[6:-1] name = self.__class__.__name__ return f"{name}({coef}, domain={domain}, window={window})" def __str__(self): coef = str(self.coef) name = self.nickname return f"{name}({coef})" @classmethod def _repr_latex_term(cls, i, arg_str, needs_parens): if cls.basis_name is None: raise NotImplementedError( "Subclasses must define either a basis name, or override " "_repr_latex_term(i, arg_str, needs_parens)") # since we always add parens, we don't care if the expression needs them return f"{{{cls.basis_name}}}_{{{i}}}({arg_str})" @staticmethod def _repr_latex_scalar(x): # TODO: we're stuck with disabling math formatting until we handle # exponents in this function return r'\text{{{}}}'.format(x) def _repr_latex_(self): # get the scaled argument string to the basis functions off, scale = self.mapparms() if off == 0 and scale == 1: term = 'x' needs_parens = False elif scale == 1: term = f"{self._repr_latex_scalar(off)} + x" needs_parens = True elif off == 0: term = f"{self._repr_latex_scalar(scale)}x" needs_parens = True else: term = ( f"{self._repr_latex_scalar(off)} + " f"{self._repr_latex_scalar(scale)}x" ) needs_parens = True mute = r"\color{{LightGray}}{{{}}}".format parts = [] for i, c in enumerate(self.coef): # prevent duplication of + and - signs if i == 0: coef_str = f"{self._repr_latex_scalar(c)}" elif not isinstance(c, numbers.Real): coef_str = f" + ({self._repr_latex_scalar(c)})" elif not np.signbit(c): coef_str = f" + {self._repr_latex_scalar(c)}" else: coef_str = f" - {self._repr_latex_scalar(-c)}" # produce the string for the term term_str = self._repr_latex_term(i, term, needs_parens) if term_str == '1': part = coef_str else: part = rf"{coef_str}\,{term_str}" if c == 0: part = mute(part) parts.append(part) if parts: body = ''.join(parts) else: # in case somehow there are no coefficients at all body = '0' return rf"$x \mapsto {body}$" # Pickle and copy def __getstate__(self): ret = self.__dict__.copy() ret['coef'] = self.coef.copy() ret['domain'] = self.domain.copy() ret['window'] = self.window.copy() return ret def __setstate__(self, dict): self.__dict__ = dict # Call def __call__(self, arg): off, scl = pu.mapparms(self.domain, self.window) arg = off + scl*arg return self._val(arg, self.coef) def __iter__(self): return iter(self.coef) def __len__(self): return len(self.coef) # Numeric properties. def __neg__(self): return self.__class__(-self.coef, self.domain, self.window) def __pos__(self): return self def __add__(self, other): othercoef = self._get_coefficients(other) try: coef = self._add(self.coef, othercoef) except Exception: return NotImplemented return self.__class__(coef, self.domain, self.window) def __sub__(self, other): othercoef = self._get_coefficients(other) try: coef = self._sub(self.coef, othercoef) except Exception: return NotImplemented return self.__class__(coef, self.domain, self.window) def __mul__(self, other): othercoef = self._get_coefficients(other) try: coef = self._mul(self.coef, othercoef) except Exception: return NotImplemented return self.__class__(coef, self.domain, self.window) def __truediv__(self, other): # there is no true divide if the rhs is not a Number, although it # could return the first n elements of an infinite series. # It is hard to see where n would come from, though. if not isinstance(other, numbers.Number) or isinstance(other, bool): raise TypeError( f"unsupported types for true division: " f"'{type(self)}', '{type(other)}'" ) return self.__floordiv__(other) def __floordiv__(self, other): res = self.__divmod__(other) if res is NotImplemented: return res return res[0] def __mod__(self, other): res = self.__divmod__(other) if res is NotImplemented: return res return res[1] def __divmod__(self, other): othercoef = self._get_coefficients(other) try: quo, rem = self._div(self.coef, othercoef) except ZeroDivisionError as e: raise e except Exception: return NotImplemented quo = self.__class__(quo, self.domain, self.window) rem = self.__class__(rem, self.domain, self.window) return quo, rem def __pow__(self, other): coef = self._pow(self.coef, other, maxpower=self.maxpower) res = self.__class__(coef, self.domain, self.window) return res def __radd__(self, other): try: coef = self._add(other, self.coef) except Exception: return NotImplemented return self.__class__(coef, self.domain, self.window) def __rsub__(self, other): try: coef = self._sub(other, self.coef) except Exception: return NotImplemented return self.__class__(coef, self.domain, self.window) def __rmul__(self, other): try: coef = self._mul(other, self.coef) except Exception: return NotImplemented return self.__class__(coef, self.domain, self.window) def __rdiv__(self, other): # set to __floordiv__ /. return self.__rfloordiv__(other) def __rtruediv__(self, other): # An instance of ABCPolyBase is not considered a # Number. return NotImplemented def __rfloordiv__(self, other): res = self.__rdivmod__(other) if res is NotImplemented: return res return res[0] def __rmod__(self, other): res = self.__rdivmod__(other) if res is NotImplemented: return res return res[1] def __rdivmod__(self, other): try: quo, rem = self._div(other, self.coef) except ZeroDivisionError as e: raise e except Exception: return NotImplemented quo = self.__class__(quo, self.domain, self.window) rem = self.__class__(rem, self.domain, self.window) return quo, rem def __eq__(self, other): res = (isinstance(other, self.__class__) and np.all(self.domain == other.domain) and np.all(self.window == other.window) and (self.coef.shape == other.coef.shape) and np.all(self.coef == other.coef)) return res def __ne__(self, other): return not self.__eq__(other) # # Extra methods. # def copy(self): """Return a copy. Returns ------- new_series : series Copy of self. """ return self.__class__(self.coef, self.domain, self.window) def degree(self): """The degree of the series. .. versionadded:: 1.5.0 Returns ------- degree : int Degree of the series, one less than the number of coefficients. """ return len(self) - 1 def cutdeg(self, deg): """Truncate series to the given degree. Reduce the degree of the series to `deg` by discarding the high order terms. If `deg` is greater than the current degree a copy of the current series is returned. This can be useful in least squares where the coefficients of the high degree terms may be very small. .. versionadded:: 1.5.0 Parameters ---------- deg : non-negative int The series is reduced to degree `deg` by discarding the high order terms. The value of `deg` must be a non-negative integer. Returns ------- new_series : series New instance of series with reduced degree. """ return self.truncate(deg + 1) def trim(self, tol=0): """Remove trailing coefficients Remove trailing coefficients until a coefficient is reached whose absolute value greater than `tol` or the beginning of the series is reached. If all the coefficients would be removed the series is set to ``[0]``. A new series instance is returned with the new coefficients. The current instance remains unchanged. Parameters ---------- tol : non-negative number. All trailing coefficients less than `tol` will be removed. Returns ------- new_series : series Contains the new set of coefficients. """ coef = pu.trimcoef(self.coef, tol) return self.__class__(coef, self.domain, self.window) def truncate(self, size): """Truncate series to length `size`. Reduce the series to length `size` by discarding the high degree terms. The value of `size` must be a positive integer. This can be useful in least squares where the coefficients of the high degree terms may be very small. Parameters ---------- size : positive int The series is reduced to length `size` by discarding the high degree terms. The value of `size` must be a positive integer. Returns ------- new_series : series New instance of series with truncated coefficients. """ isize = int(size) if isize != size or isize < 1: raise ValueError("size must be a positive integer") if isize >= len(self.coef): coef = self.coef else: coef = self.coef[:isize] return self.__class__(coef, self.domain, self.window) def convert(self, domain=None, kind=None, window=None): """Convert series to a different kind and/or domain and/or window. Parameters ---------- domain : array_like, optional The domain of the converted series. If the value is None, the default domain of `kind` is used. kind : class, optional The polynomial series type class to which the current instance should be converted. If kind is None, then the class of the current instance is used. window : array_like, optional The window of the converted series. If the value is None, the default window of `kind` is used. Returns ------- new_series : series The returned class can be of different type than the current instance and/or have a different domain and/or different window. Notes ----- Conversion between domains and class types can result in numerically ill defined series. Examples -------- """ if kind is None: kind = self.__class__ if domain is None: domain = kind.domain if window is None: window = kind.window return self(kind.identity(domain, window=window)) def mapparms(self): """Return the mapping parameters. The returned values define a linear map ``off + scl*x`` that is applied to the input arguments before the series is evaluated. The map depends on the ``domain`` and ``window``; if the current ``domain`` is equal to the ``window`` the resulting map is the identity. If the coefficients of the series instance are to be used by themselves outside this class, then the linear function must be substituted for the ``x`` in the standard representation of the base polynomials. Returns ------- off, scl : float or complex The mapping function is defined by ``off + scl*x``. Notes ----- If the current domain is the interval ``[l1, r1]`` and the window is ``[l2, r2]``, then the linear mapping function ``L`` is defined by the equations:: L(l1) = l2 L(r1) = r2 """ return pu.mapparms(self.domain, self.window) def integ(self, m=1, k=[], lbnd=None): """Integrate. Return a series instance that is the definite integral of the current series. Parameters ---------- m : non-negative int The number of integrations to perform. k : array_like Integration constants. The first constant is applied to the first integration, the second to the second, and so on. The list of values must less than or equal to `m` in length and any missing values are set to zero. lbnd : Scalar The lower bound of the definite integral. Returns ------- new_series : series A new series representing the integral. The domain is the same as the domain of the integrated series. """ off, scl = self.mapparms() if lbnd is None: lbnd = 0 else: lbnd = off + scl*lbnd coef = self._int(self.coef, m, k, lbnd, 1./scl) return self.__class__(coef, self.domain, self.window) def deriv(self, m=1): """Differentiate. Return a series instance of that is the derivative of the current series. Parameters ---------- m : non-negative int Find the derivative of order `m`. Returns ------- new_series : series A new series representing the derivative. The domain is the same as the domain of the differentiated series. """ off, scl = self.mapparms() coef = self._der(self.coef, m, scl) return self.__class__(coef, self.domain, self.window) def roots(self): """Return the roots of the series polynomial. Compute the roots for the series. Note that the accuracy of the roots decrease the further outside the domain they lie. Returns ------- roots : ndarray Array containing the roots of the series. """ roots = self._roots(self.coef) return pu.mapdomain(roots, self.window, self.domain) def linspace(self, n=100, domain=None): """Return x, y values at equally spaced points in domain. Returns the x, y values at `n` linearly spaced points across the domain. Here y is the value of the polynomial at the points x. By default the domain is the same as that of the series instance. This method is intended mostly as a plotting aid. .. versionadded:: 1.5.0 Parameters ---------- n : int, optional Number of point pairs to return. The default value is 100. domain : {None, array_like}, optional If not None, the specified domain is used instead of that of the calling instance. It should be of the form ``[beg,end]``. The default is None which case the class domain is used. Returns ------- x, y : ndarray x is equal to linspace(self.domain[0], self.domain[1], n) and y is the series evaluated at element of x. """ if domain is None: domain = self.domain x = np.linspace(domain[0], domain[1], n) y = self(x) return x, y @classmethod def fit(cls, x, y, deg, domain=None, rcond=None, full=False, w=None, window=None): """Least squares fit to data. Return a series instance that is the least squares fit to the data `y` sampled at `x`. The domain of the returned instance can be specified and this will often result in a superior fit with less chance of ill conditioning. Parameters ---------- x : array_like, shape (M,) x-coordinates of the M sample points ``(x[i], y[i])``. y : array_like, shape (M,) or (M, K) y-coordinates of the sample points. Several data sets of sample points sharing the same x-coordinates can be fitted at once by passing in a 2D-array that contains one dataset per column. deg : int or 1-D array_like Degree(s) of the fitting polynomials. If `deg` is a single integer all terms up to and including the `deg`'th term are included in the fit. For NumPy versions >= 1.11.0 a list of integers specifying the degrees of the terms to include may be used instead. domain : {None, [beg, end], []}, optional Domain to use for the returned series. If ``None``, then a minimal domain that covers the points `x` is chosen. If ``[]`` the class domain is used. The default value was the class domain in NumPy 1.4 and ``None`` in later versions. The ``[]`` option was added in numpy 1.5.0. rcond : float, optional Relative condition number of the fit. Singular values smaller than this relative to the largest singular value will be ignored. The default value is len(x)*eps, where eps is the relative precision of the float type, about 2e-16 in most cases. full : bool, optional Switch determining nature of return value. When it is False (the default) just the coefficients are returned, when True diagnostic information from the singular value decomposition is also returned. w : array_like, shape (M,), optional Weights. If not None the contribution of each point ``(x[i],y[i])`` to the fit is weighted by `w[i]`. Ideally the weights are chosen so that the errors of the products ``w[i]*y[i]`` all have the same variance. The default value is None. .. versionadded:: 1.5.0 window : {[beg, end]}, optional Window to use for the returned series. The default value is the default class domain .. versionadded:: 1.6.0 Returns ------- new_series : series A series that represents the least squares fit to the data and has the domain and window specified in the call. If the coefficients for the unscaled and unshifted basis polynomials are of interest, do ``new_series.convert().coef``. [resid, rank, sv, rcond] : list These values are only returned if `full` = True resid -- sum of squared residuals of the least squares fit rank -- the numerical rank of the scaled Vandermonde matrix sv -- singular values of the scaled Vandermonde matrix rcond -- value of `rcond`. For more details, see `linalg.lstsq`. """ if domain is None: domain = pu.getdomain(x) elif type(domain) is list and len(domain) == 0: domain = cls.domain if window is None: window = cls.window xnew = pu.mapdomain(x, domain, window) res = cls._fit(xnew, y, deg, w=w, rcond=rcond, full=full) if full: [coef, status] = res return cls(coef, domain=domain, window=window), status else: coef = res return cls(coef, domain=domain, window=window) @classmethod def fromroots(cls, roots, domain=[], window=None): """Return series instance that has the specified roots. Returns a series representing the product ``(x - r[0])*(x - r[1])*...*(x - r[n-1])``, where ``r`` is a list of roots. Parameters ---------- roots : array_like List of roots. domain : {[], None, array_like}, optional Domain for the resulting series. If None the domain is the interval from the smallest root to the largest. If [] the domain is the class domain. The default is []. window : {None, array_like}, optional Window for the returned series. If None the class window is used. The default is None. Returns ------- new_series : series Series with the specified roots. """ [roots] = pu.as_series([roots], trim=False) if domain is None: domain = pu.getdomain(roots) elif type(domain) is list and len(domain) == 0: domain = cls.domain if window is None: window = cls.window deg = len(roots) off, scl = pu.mapparms(domain, window) rnew = off + scl*roots coef = cls._fromroots(rnew) / scl**deg return cls(coef, domain=domain, window=window) @classmethod def identity(cls, domain=None, window=None): """Identity function. If ``p`` is the returned series, then ``p(x) == x`` for all values of x. Parameters ---------- domain : {None, array_like}, optional If given, the array must be of the form ``[beg, end]``, where ``beg`` and ``end`` are the endpoints of the domain. If None is given then the class domain is used. The default is None. window : {None, array_like}, optional If given, the resulting array must be if the form ``[beg, end]``, where ``beg`` and ``end`` are the endpoints of the window. If None is given then the class window is used. The default is None. Returns ------- new_series : series Series of representing the identity. """ if domain is None: domain = cls.domain if window is None: window = cls.window off, scl = pu.mapparms(window, domain) coef = cls._line(off, scl) return cls(coef, domain, window) @classmethod def basis(cls, deg, domain=None, window=None): """Series basis polynomial of degree `deg`. Returns the series representing the basis polynomial of degree `deg`. .. versionadded:: 1.7.0 Parameters ---------- deg : int Degree of the basis polynomial for the series. Must be >= 0. domain : {None, array_like}, optional If given, the array must be of the form ``[beg, end]``, where ``beg`` and ``end`` are the endpoints of the domain. If None is given then the class domain is used. The default is None. window : {None, array_like}, optional If given, the resulting array must be if the form ``[beg, end]``, where ``beg`` and ``end`` are the endpoints of the window. If None is given then the class window is used. The default is None. Returns ------- new_series : series A series with the coefficient of the `deg` term set to one and all others zero. """ if domain is None: domain = cls.domain if window is None: window = cls.window ideg = int(deg) if ideg != deg or ideg < 0: raise ValueError("deg must be non-negative integer") return cls([0]*ideg + [1], domain, window) @classmethod def cast(cls, series, domain=None, window=None): """Convert series to series of this class. The `series` is expected to be an instance of some polynomial series of one of the types supported by by the numpy.polynomial module, but could be some other class that supports the convert method. .. versionadded:: 1.7.0 Parameters ---------- series : series The series instance to be converted. domain : {None, array_like}, optional If given, the array must be of the form ``[beg, end]``, where ``beg`` and ``end`` are the endpoints of the domain. If None is given then the class domain is used. The default is None. window : {None, array_like}, optional If given, the resulting array must be if the form ``[beg, end]``, where ``beg`` and ``end`` are the endpoints of the window. If None is given then the class window is used. The default is None. Returns ------- new_series : series A series of the same kind as the calling class and equal to `series` when evaluated. See Also -------- convert : similar instance method """ if domain is None: domain = cls.domain if window is None: window = cls.window return series.convert(domain, cls, window)