401 lines
14 KiB
Python
401 lines
14 KiB
Python
from .plot_interval import PlotInterval
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from .plot_object import PlotObject
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from .util import parse_option_string
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from sympy.core.symbol import Symbol
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from sympy.core.sympify import sympify
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from sympy.geometry.entity import GeometryEntity
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from sympy.utilities.iterables import is_sequence
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class PlotMode(PlotObject):
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"""
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Grandparent class for plotting
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modes. Serves as interface for
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registration, lookup, and init
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of modes.
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To create a new plot mode,
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inherit from PlotModeBase
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or one of its children, such
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as PlotSurface or PlotCurve.
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"""
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## Class-level attributes
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## used to register and lookup
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## plot modes. See PlotModeBase
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## for descriptions and usage.
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i_vars, d_vars = '', ''
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intervals = []
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aliases = []
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is_default = False
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## Draw is the only method here which
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## is meant to be overridden in child
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## classes, and PlotModeBase provides
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## a base implementation.
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def draw(self):
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raise NotImplementedError()
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## Everything else in this file has to
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## do with registration and retrieval
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## of plot modes. This is where I've
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## hidden much of the ugliness of automatic
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## plot mode divination...
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## Plot mode registry data structures
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_mode_alias_list = []
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_mode_map = {
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1: {1: {}, 2: {}},
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2: {1: {}, 2: {}},
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3: {1: {}, 2: {}},
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} # [d][i][alias_str]: class
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_mode_default_map = {
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1: {},
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2: {},
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3: {},
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} # [d][i]: class
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_i_var_max, _d_var_max = 2, 3
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def __new__(cls, *args, **kwargs):
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"""
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This is the function which interprets
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arguments given to Plot.__init__ and
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Plot.__setattr__. Returns an initialized
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instance of the appropriate child class.
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"""
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newargs, newkwargs = PlotMode._extract_options(args, kwargs)
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mode_arg = newkwargs.get('mode', '')
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# Interpret the arguments
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d_vars, intervals = PlotMode._interpret_args(newargs)
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i_vars = PlotMode._find_i_vars(d_vars, intervals)
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i, d = max([len(i_vars), len(intervals)]), len(d_vars)
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# Find the appropriate mode
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subcls = PlotMode._get_mode(mode_arg, i, d)
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# Create the object
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o = object.__new__(subcls)
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# Do some setup for the mode instance
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o.d_vars = d_vars
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o._fill_i_vars(i_vars)
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o._fill_intervals(intervals)
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o.options = newkwargs
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return o
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@staticmethod
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def _get_mode(mode_arg, i_var_count, d_var_count):
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"""
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Tries to return an appropriate mode class.
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Intended to be called only by __new__.
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mode_arg
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Can be a string or a class. If it is a
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PlotMode subclass, it is simply returned.
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If it is a string, it can an alias for
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a mode or an empty string. In the latter
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case, we try to find a default mode for
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the i_var_count and d_var_count.
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i_var_count
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The number of independent variables
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needed to evaluate the d_vars.
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d_var_count
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The number of dependent variables;
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usually the number of functions to
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be evaluated in plotting.
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For example, a Cartesian function y = f(x) has
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one i_var (x) and one d_var (y). A parametric
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form x,y,z = f(u,v), f(u,v), f(u,v) has two
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two i_vars (u,v) and three d_vars (x,y,z).
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"""
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# if the mode_arg is simply a PlotMode class,
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# check that the mode supports the numbers
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# of independent and dependent vars, then
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# return it
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try:
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m = None
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if issubclass(mode_arg, PlotMode):
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m = mode_arg
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except TypeError:
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pass
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if m:
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if not m._was_initialized:
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raise ValueError(("To use unregistered plot mode %s "
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"you must first call %s._init_mode().")
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% (m.__name__, m.__name__))
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if d_var_count != m.d_var_count:
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raise ValueError(("%s can only plot functions "
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"with %i dependent variables.")
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% (m.__name__,
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m.d_var_count))
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if i_var_count > m.i_var_count:
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raise ValueError(("%s cannot plot functions "
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"with more than %i independent "
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"variables.")
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% (m.__name__,
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m.i_var_count))
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return m
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# If it is a string, there are two possibilities.
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if isinstance(mode_arg, str):
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i, d = i_var_count, d_var_count
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if i > PlotMode._i_var_max:
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raise ValueError(var_count_error(True, True))
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if d > PlotMode._d_var_max:
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raise ValueError(var_count_error(False, True))
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# If the string is '', try to find a suitable
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# default mode
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if not mode_arg:
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return PlotMode._get_default_mode(i, d)
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# Otherwise, interpret the string as a mode
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# alias (e.g. 'cartesian', 'parametric', etc)
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else:
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return PlotMode._get_aliased_mode(mode_arg, i, d)
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else:
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raise ValueError("PlotMode argument must be "
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"a class or a string")
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@staticmethod
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def _get_default_mode(i, d, i_vars=-1):
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if i_vars == -1:
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i_vars = i
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try:
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return PlotMode._mode_default_map[d][i]
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except KeyError:
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# Keep looking for modes in higher i var counts
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# which support the given d var count until we
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# reach the max i_var count.
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if i < PlotMode._i_var_max:
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return PlotMode._get_default_mode(i + 1, d, i_vars)
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else:
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raise ValueError(("Couldn't find a default mode "
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"for %i independent and %i "
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"dependent variables.") % (i_vars, d))
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@staticmethod
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def _get_aliased_mode(alias, i, d, i_vars=-1):
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if i_vars == -1:
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i_vars = i
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if alias not in PlotMode._mode_alias_list:
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raise ValueError(("Couldn't find a mode called"
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" %s. Known modes: %s.")
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% (alias, ", ".join(PlotMode._mode_alias_list)))
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try:
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return PlotMode._mode_map[d][i][alias]
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except TypeError:
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# Keep looking for modes in higher i var counts
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# which support the given d var count and alias
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# until we reach the max i_var count.
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if i < PlotMode._i_var_max:
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return PlotMode._get_aliased_mode(alias, i + 1, d, i_vars)
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else:
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raise ValueError(("Couldn't find a %s mode "
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"for %i independent and %i "
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"dependent variables.")
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% (alias, i_vars, d))
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@classmethod
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def _register(cls):
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"""
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Called once for each user-usable plot mode.
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For Cartesian2D, it is invoked after the
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class definition: Cartesian2D._register()
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"""
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name = cls.__name__
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cls._init_mode()
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try:
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i, d = cls.i_var_count, cls.d_var_count
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# Add the mode to _mode_map under all
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# given aliases
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for a in cls.aliases:
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if a not in PlotMode._mode_alias_list:
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# Also track valid aliases, so
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# we can quickly know when given
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# an invalid one in _get_mode.
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PlotMode._mode_alias_list.append(a)
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PlotMode._mode_map[d][i][a] = cls
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if cls.is_default:
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# If this mode was marked as the
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# default for this d,i combination,
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# also set that.
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PlotMode._mode_default_map[d][i] = cls
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except Exception as e:
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raise RuntimeError(("Failed to register "
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"plot mode %s. Reason: %s")
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% (name, (str(e))))
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@classmethod
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def _init_mode(cls):
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"""
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Initializes the plot mode based on
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the 'mode-specific parameters' above.
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Only intended to be called by
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PlotMode._register(). To use a mode without
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registering it, you can directly call
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ModeSubclass._init_mode().
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"""
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def symbols_list(symbol_str):
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return [Symbol(s) for s in symbol_str]
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# Convert the vars strs into
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# lists of symbols.
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cls.i_vars = symbols_list(cls.i_vars)
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cls.d_vars = symbols_list(cls.d_vars)
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# Var count is used often, calculate
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# it once here
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cls.i_var_count = len(cls.i_vars)
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cls.d_var_count = len(cls.d_vars)
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if cls.i_var_count > PlotMode._i_var_max:
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raise ValueError(var_count_error(True, False))
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if cls.d_var_count > PlotMode._d_var_max:
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raise ValueError(var_count_error(False, False))
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# Try to use first alias as primary_alias
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if len(cls.aliases) > 0:
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cls.primary_alias = cls.aliases[0]
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else:
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cls.primary_alias = cls.__name__
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di = cls.intervals
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if len(di) != cls.i_var_count:
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raise ValueError("Plot mode must provide a "
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"default interval for each i_var.")
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for i in range(cls.i_var_count):
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# default intervals must be given [min,max,steps]
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# (no var, but they must be in the same order as i_vars)
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if len(di[i]) != 3:
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raise ValueError("length should be equal to 3")
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# Initialize an incomplete interval,
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# to later be filled with a var when
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# the mode is instantiated.
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di[i] = PlotInterval(None, *di[i])
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# To prevent people from using modes
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# without these required fields set up.
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cls._was_initialized = True
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_was_initialized = False
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## Initializer Helper Methods
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@staticmethod
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def _find_i_vars(functions, intervals):
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i_vars = []
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# First, collect i_vars in the
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# order they are given in any
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# intervals.
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for i in intervals:
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if i.v is None:
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continue
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elif i.v in i_vars:
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raise ValueError(("Multiple intervals given "
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"for %s.") % (str(i.v)))
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i_vars.append(i.v)
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# Then, find any remaining
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# i_vars in given functions
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# (aka d_vars)
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for f in functions:
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for a in f.free_symbols:
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if a not in i_vars:
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i_vars.append(a)
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return i_vars
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def _fill_i_vars(self, i_vars):
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# copy default i_vars
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self.i_vars = [Symbol(str(i)) for i in self.i_vars]
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# replace with given i_vars
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for i in range(len(i_vars)):
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self.i_vars[i] = i_vars[i]
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def _fill_intervals(self, intervals):
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# copy default intervals
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self.intervals = [PlotInterval(i) for i in self.intervals]
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# track i_vars used so far
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v_used = []
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# fill copy of default
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# intervals with given info
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for i in range(len(intervals)):
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self.intervals[i].fill_from(intervals[i])
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if self.intervals[i].v is not None:
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v_used.append(self.intervals[i].v)
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# Find any orphan intervals and
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# assign them i_vars
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for i in range(len(self.intervals)):
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if self.intervals[i].v is None:
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u = [v for v in self.i_vars if v not in v_used]
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if len(u) == 0:
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raise ValueError("length should not be equal to 0")
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self.intervals[i].v = u[0]
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v_used.append(u[0])
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@staticmethod
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def _interpret_args(args):
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interval_wrong_order = "PlotInterval %s was given before any function(s)."
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interpret_error = "Could not interpret %s as a function or interval."
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functions, intervals = [], []
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if isinstance(args[0], GeometryEntity):
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for coords in list(args[0].arbitrary_point()):
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functions.append(coords)
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intervals.append(PlotInterval.try_parse(args[0].plot_interval()))
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else:
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for a in args:
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i = PlotInterval.try_parse(a)
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if i is not None:
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if len(functions) == 0:
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raise ValueError(interval_wrong_order % (str(i)))
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else:
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intervals.append(i)
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else:
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if is_sequence(a, include=str):
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raise ValueError(interpret_error % (str(a)))
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try:
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f = sympify(a)
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functions.append(f)
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except TypeError:
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raise ValueError(interpret_error % str(a))
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return functions, intervals
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@staticmethod
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def _extract_options(args, kwargs):
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newkwargs, newargs = {}, []
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for a in args:
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if isinstance(a, str):
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newkwargs = dict(newkwargs, **parse_option_string(a))
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else:
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newargs.append(a)
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newkwargs = dict(newkwargs, **kwargs)
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return newargs, newkwargs
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def var_count_error(is_independent, is_plotting):
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"""
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Used to format an error message which differs
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slightly in 4 places.
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"""
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if is_plotting:
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v = "Plotting"
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else:
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v = "Registering plot modes"
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if is_independent:
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n, s = PlotMode._i_var_max, "independent"
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else:
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n, s = PlotMode._d_var_max, "dependent"
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return ("%s with more than %i %s variables "
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"is not supported.") % (v, n, s)
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