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pythonProject/.venv/Lib/site-packages/sympy/plotting/experimental_lambdify.py

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+""" rewrite of lambdify - This stuff is not stable at all.
+
+It is for internal use in the new plotting module.
+It may (will! see the Q'n'A in the source) be rewritten.
+
+It's completely self contained. Especially it does not use lambdarepr.
+
+It does not aim to replace the current lambdify. Most importantly it will never
+ever support anything else than SymPy expressions (no Matrices, dictionaries
+and so on).
+"""
+
+
+import re
+from sympy.core.numbers import (I, NumberSymbol, oo, zoo)
+from sympy.core.symbol import Symbol
+from sympy.utilities.iterables import numbered_symbols
+
+#  We parse the expression string into a tree that identifies functions. Then
+# we translate the names of the functions and we translate also some strings
+# that are not names of functions (all this according to translation
+# dictionaries).
+#  If the translation goes to another module (like numpy) the
+# module is imported and 'func' is translated to 'module.func'.
+#  If a function can not be translated, the inner nodes of that part of the
+# tree are not translated. So if we have Integral(sqrt(x)), sqrt is not
+# translated to np.sqrt and the Integral does not crash.
+#  A namespace for all this is generated by crawling the (func, args) tree of
+# the expression. The creation of this namespace involves many ugly
+# workarounds.
+#  The namespace consists of all the names needed for the SymPy expression and
+# all the name of modules used for translation. Those modules are imported only
+# as a name (import numpy as np) in order to keep the namespace small and
+# manageable.
+
+#  Please, if there is a bug, do not try to fix it here! Rewrite this by using
+# the method proposed in the last Q'n'A below. That way the new function will
+# work just as well, be just as simple, but it wont need any new workarounds.
+#  If you insist on fixing it here, look at the workarounds in the function
+# sympy_expression_namespace and in lambdify.
+
+# Q: Why are you not using Python abstract syntax tree?
+# A: Because it is more complicated and not much more powerful in this case.
+
+# Q: What if I have Symbol('sin') or g=Function('f')?
+# A: You will break the algorithm. We should use srepr to defend against this?
+#  The problem with Symbol('sin') is that it will be printed as 'sin'. The
+# parser will distinguish it from the function 'sin' because functions are
+# detected thanks to the opening parenthesis, but the lambda expression won't
+# understand the difference if we have also the sin function.
+# The solution (complicated) is to use srepr and maybe ast.
+#  The problem with the g=Function('f') is that it will be printed as 'f' but in
+# the global namespace we have only 'g'. But as the same printer is used in the
+# constructor of the namespace there will be no problem.
+
+# Q: What if some of the printers are not printing as expected?
+# A: The algorithm wont work. You must use srepr for those cases. But even
+# srepr may not print well. All problems with printers should be considered
+# bugs.
+
+# Q: What about _imp_ functions?
+# A: Those are taken care for by evalf. A special case treatment will work
+# faster but it's not worth the code complexity.
+
+# Q: Will ast fix all possible problems?
+# A: No. You will always have to use some printer. Even srepr may not work in
+# some cases. But if the printer does not work, that should be considered a
+# bug.
+
+# Q: Is there same way to fix all possible problems?
+# A: Probably by constructing our strings ourself by traversing the (func,
+# args) tree and creating the namespace at the same time. That actually sounds
+# good.
+
+from sympy.external import import_module
+import warnings
+
+#TODO debugging output
+
+
+class vectorized_lambdify:
+    """ Return a sufficiently smart, vectorized and lambdified function.
+
+    Returns only reals.
+
+    Explanation
+    ===========
+
+    This function uses experimental_lambdify to created a lambdified
+    expression ready to be used with numpy. Many of the functions in SymPy
+    are not implemented in numpy so in some cases we resort to Python cmath or
+    even to evalf.
+
+    The following translations are tried:
+      only numpy complex
+      - on errors raised by SymPy trying to work with ndarray:
+          only Python cmath and then vectorize complex128
+
+    When using Python cmath there is no need for evalf or float/complex
+    because Python cmath calls those.
+
+    This function never tries to mix numpy directly with evalf because numpy
+    does not understand SymPy Float. If this is needed one can use the
+    float_wrap_evalf/complex_wrap_evalf options of experimental_lambdify or
+    better one can be explicit about the dtypes that numpy works with.
+    Check numpy bug http://projects.scipy.org/numpy/ticket/1013 to know what
+    types of errors to expect.
+    """
+    def __init__(self, args, expr):
+        self.args = args
+        self.expr = expr
+        self.np = import_module('numpy')
+
+        self.lambda_func_1 = experimental_lambdify(
+            args, expr, use_np=True)
+        self.vector_func_1 = self.lambda_func_1
+
+        self.lambda_func_2 = experimental_lambdify(
+            args, expr, use_python_cmath=True)
+        self.vector_func_2 = self.np.vectorize(
+            self.lambda_func_2, otypes=[complex])
+
+        self.vector_func = self.vector_func_1
+        self.failure = False
+
+    def __call__(self, *args):
+        np = self.np
+
+        try:
+            temp_args = (np.array(a, dtype=complex) for a in args)
+            results = self.vector_func(*temp_args)
+            results = np.ma.masked_where(
+                np.abs(results.imag) > 1e-7 * np.abs(results),
+                results.real, copy=False)
+            return results
+        except ValueError:
+            if self.failure:
+                raise
+
+            self.failure = True
+            self.vector_func = self.vector_func_2
+            warnings.warn(
+                'The evaluation of the expression is problematic. '
+                'We are trying a failback method that may still work. '
+                'Please report this as a bug.')
+            return self.__call__(*args)
+
+
+class lambdify:
+    """Returns the lambdified function.
+
+    Explanation
+    ===========
+
+    This function uses experimental_lambdify to create a lambdified
+    expression. It uses cmath to lambdify the expression. If the function
+    is not implemented in Python cmath, Python cmath calls evalf on those
+    functions.
+    """
+
+    def __init__(self, args, expr):
+        self.args = args
+        self.expr = expr
+        self.lambda_func_1 = experimental_lambdify(
+            args, expr, use_python_cmath=True, use_evalf=True)
+        self.lambda_func_2 = experimental_lambdify(
+            args, expr, use_python_math=True, use_evalf=True)
+        self.lambda_func_3 = experimental_lambdify(
+            args, expr, use_evalf=True, complex_wrap_evalf=True)
+        self.lambda_func = self.lambda_func_1
+        self.failure = False
+
+    def __call__(self, args):
+        try:
+            #The result can be sympy.Float. Hence wrap it with complex type.
+            result = complex(self.lambda_func(args))
+            if abs(result.imag) > 1e-7 * abs(result):
+                return None
+            return result.real
+        except (ZeroDivisionError, OverflowError):
+            return None
+        except TypeError as e:
+            if self.failure:
+                raise e
+
+            if self.lambda_func == self.lambda_func_1:
+                self.lambda_func = self.lambda_func_2
+                return self.__call__(args)
+
+            self.failure = True
+            self.lambda_func = self.lambda_func_3
+            warnings.warn(
+                'The evaluation of the expression is problematic. '
+                'We are trying a failback method that may still work. '
+                'Please report this as a bug.', stacklevel=2)
+            return self.__call__(args)
+
+
+def experimental_lambdify(*args, **kwargs):
+    l = Lambdifier(*args, **kwargs)
+    return l
+
+
+class Lambdifier:
+    def __init__(self, args, expr, print_lambda=False, use_evalf=False,
+                 float_wrap_evalf=False, complex_wrap_evalf=False,
+                 use_np=False, use_python_math=False, use_python_cmath=False,
+                 use_interval=False):
+
+        self.print_lambda = print_lambda
+        self.use_evalf = use_evalf
+        self.float_wrap_evalf = float_wrap_evalf
+        self.complex_wrap_evalf = complex_wrap_evalf
+        self.use_np = use_np
+        self.use_python_math = use_python_math
+        self.use_python_cmath = use_python_cmath
+        self.use_interval = use_interval
+
+        # Constructing the argument string
+        # - check
+        if not all(isinstance(a, Symbol) for a in args):
+            raise ValueError('The arguments must be Symbols.')
+        # - use numbered symbols
+        syms = numbered_symbols(exclude=expr.free_symbols)
+        newargs = [next(syms) for _ in args]
+        expr = expr.xreplace(dict(zip(args, newargs)))
+        argstr = ', '.join([str(a) for a in newargs])
+        del syms, newargs, args
+
+        # Constructing the translation dictionaries and making the translation
+        self.dict_str = self.get_dict_str()
+        self.dict_fun = self.get_dict_fun()
+        exprstr = str(expr)
+        newexpr = self.tree2str_translate(self.str2tree(exprstr))
+
+        # Constructing the namespaces
+        namespace = {}
+        namespace.update(self.sympy_atoms_namespace(expr))
+        namespace.update(self.sympy_expression_namespace(expr))
+        # XXX Workaround
+        # Ugly workaround because Pow(a,Half) prints as sqrt(a)
+        # and sympy_expression_namespace can not catch it.
+        from sympy.functions.elementary.miscellaneous import sqrt
+        namespace.update({'sqrt': sqrt})
+        namespace.update({'Eq': lambda x, y: x == y})
+        namespace.update({'Ne': lambda x, y: x != y})
+        # End workaround.
+        if use_python_math:
+            namespace.update({'math': __import__('math')})
+        if use_python_cmath:
+            namespace.update({'cmath': __import__('cmath')})
+        if use_np:
+            try:
+                namespace.update({'np': __import__('numpy')})
+            except ImportError:
+                raise ImportError(
+                    'experimental_lambdify failed to import numpy.')
+        if use_interval:
+            namespace.update({'imath': __import__(
+                'sympy.plotting.intervalmath', fromlist=['intervalmath'])})
+            namespace.update({'math': __import__('math')})
+
+        # Construct the lambda
+        if self.print_lambda:
+            print(newexpr)
+        eval_str = 'lambda %s : ( %s )' % (argstr, newexpr)
+        self.eval_str = eval_str
+        exec("MYNEWLAMBDA = %s" % eval_str, namespace)
+        self.lambda_func = namespace['MYNEWLAMBDA']
+
+    def __call__(self, *args, **kwargs):
+        return self.lambda_func(*args, **kwargs)
+
+
+    ##############################################################################
+    # Dicts for translating from SymPy to other modules
+    ##############################################################################
+    ###
+    # builtins
+    ###
+    # Functions with different names in builtins
+    builtin_functions_different = {
+        'Min': 'min',
+        'Max': 'max',
+        'Abs': 'abs',
+    }
+
+    # Strings that should be translated
+    builtin_not_functions = {
+        'I': '1j',
+#        'oo': '1e400',
+    }
+
+    ###
+    # numpy
+    ###
+
+    # Functions that are the same in numpy
+    numpy_functions_same = [
+        'sin', 'cos', 'tan', 'sinh', 'cosh', 'tanh', 'exp', 'log',
+        'sqrt', 'floor', 'conjugate', 'sign',
+    ]
+
+    # Functions with different names in numpy
+    numpy_functions_different = {
+        "acos": "arccos",
+        "acosh": "arccosh",
+        "arg": "angle",
+        "asin": "arcsin",
+        "asinh": "arcsinh",
+        "atan": "arctan",
+        "atan2": "arctan2",
+        "atanh": "arctanh",
+        "ceiling": "ceil",
+        "im": "imag",
+        "ln": "log",
+        "Max": "amax",
+        "Min": "amin",
+        "re": "real",
+        "Abs": "abs",
+    }
+
+    # Strings that should be translated
+    numpy_not_functions = {
+        'pi': 'np.pi',
+        'oo': 'np.inf',
+        'E': 'np.e',
+    }
+
+    ###
+    # Python math
+    ###
+
+    # Functions that are the same in math
+    math_functions_same = [
+        'sin', 'cos', 'tan', 'asin', 'acos', 'atan', 'atan2',
+        'sinh', 'cosh', 'tanh', 'asinh', 'acosh', 'atanh',
+        'exp', 'log', 'erf', 'sqrt', 'floor', 'factorial', 'gamma',
+    ]
+
+    # Functions with different names in math
+    math_functions_different = {
+        'ceiling': 'ceil',
+        'ln': 'log',
+        'loggamma': 'lgamma'
+    }
+
+    # Strings that should be translated
+    math_not_functions = {
+        'pi': 'math.pi',
+        'E': 'math.e',
+    }
+
+    ###
+    # Python cmath
+    ###
+
+    # Functions that are the same in cmath
+    cmath_functions_same = [
+        'sin', 'cos', 'tan', 'asin', 'acos', 'atan',
+        'sinh', 'cosh', 'tanh', 'asinh', 'acosh', 'atanh',
+        'exp', 'log', 'sqrt',
+    ]
+
+    # Functions with different names in cmath
+    cmath_functions_different = {
+        'ln': 'log',
+        'arg': 'phase',
+    }
+
+    # Strings that should be translated
+    cmath_not_functions = {
+        'pi': 'cmath.pi',
+        'E': 'cmath.e',
+    }
+
+    ###
+    # intervalmath
+    ###
+
+    interval_not_functions = {
+        'pi': 'math.pi',
+        'E': 'math.e'
+    }
+
+    interval_functions_same = [
+        'sin', 'cos', 'exp', 'tan', 'atan', 'log',
+        'sqrt', 'cosh', 'sinh', 'tanh', 'floor',
+        'acos', 'asin', 'acosh', 'asinh', 'atanh',
+        'Abs', 'And', 'Or'
+    ]
+
+    interval_functions_different = {
+        'Min': 'imin',
+        'Max': 'imax',
+        'ceiling': 'ceil',
+
+    }
+
+    ###
+    # mpmath, etc
+    ###
+    #TODO
+
+    ###
+    # Create the final ordered tuples of dictionaries
+    ###
+
+    # For strings
+    def get_dict_str(self):
+        dict_str = dict(self.builtin_not_functions)
+        if self.use_np:
+            dict_str.update(self.numpy_not_functions)
+        if self.use_python_math:
+            dict_str.update(self.math_not_functions)
+        if self.use_python_cmath:
+            dict_str.update(self.cmath_not_functions)
+        if self.use_interval:
+            dict_str.update(self.interval_not_functions)
+        return dict_str
+
+    # For functions
+    def get_dict_fun(self):
+        dict_fun = dict(self.builtin_functions_different)
+        if self.use_np:
+            for s in self.numpy_functions_same:
+                dict_fun[s] = 'np.' + s
+            for k, v in self.numpy_functions_different.items():
+                dict_fun[k] = 'np.' + v
+        if self.use_python_math:
+            for s in self.math_functions_same:
+                dict_fun[s] = 'math.' + s
+            for k, v in self.math_functions_different.items():
+                dict_fun[k] = 'math.' + v
+        if self.use_python_cmath:
+            for s in self.cmath_functions_same:
+                dict_fun[s] = 'cmath.' + s
+            for k, v in self.cmath_functions_different.items():
+                dict_fun[k] = 'cmath.' + v
+        if self.use_interval:
+            for s in self.interval_functions_same:
+                dict_fun[s] = 'imath.' + s
+            for k, v in self.interval_functions_different.items():
+                dict_fun[k] = 'imath.' + v
+        return dict_fun
+
+    ##############################################################################
+    # The translator functions, tree parsers, etc.
+    ##############################################################################
+
+    def str2tree(self, exprstr):
+        """Converts an expression string to a tree.
+
+        Explanation
+        ===========
+
+        Functions are represented by ('func_name(', tree_of_arguments).
+        Other expressions are (head_string, mid_tree, tail_str).
+        Expressions that do not contain functions are directly returned.
+
+        Examples
+        ========
+
+        >>> from sympy.abc import x, y, z
+        >>> from sympy import Integral, sin
+        >>> from sympy.plotting.experimental_lambdify import Lambdifier
+        >>> str2tree = Lambdifier([x], x).str2tree
+
+        >>> str2tree(str(Integral(x, (x, 1, y))))
+        ('', ('Integral(', 'x, (x, 1, y)'), ')')
+        >>> str2tree(str(x+y))
+        'x + y'
+        >>> str2tree(str(x+y*sin(z)+1))
+        ('x + y*', ('sin(', 'z'), ') + 1')
+        >>> str2tree('sin(y*(y + 1.1) + (sin(y)))')
+        ('', ('sin(', ('y*(y + 1.1) + (', ('sin(', 'y'), '))')), ')')
+        """
+        #matches the first 'function_name('
+        first_par = re.search(r'(\w+\()', exprstr)
+        if first_par is None:
+            return exprstr
+        else:
+            start = first_par.start()
+            end = first_par.end()
+            head = exprstr[:start]
+            func = exprstr[start:end]
+            tail = exprstr[end:]
+            count = 0
+            for i, c in enumerate(tail):
+                if c == '(':
+                    count += 1
+                elif c == ')':
+                    count -= 1
+                if count == -1:
+                    break
+            func_tail = self.str2tree(tail[:i])
+            tail = self.str2tree(tail[i:])
+            return (head, (func, func_tail), tail)
+
+    @classmethod
+    def tree2str(cls, tree):
+        """Converts a tree to string without translations.
+
+        Examples
+        ========
+
+        >>> from sympy.abc import x, y, z
+        >>> from sympy import sin
+        >>> from sympy.plotting.experimental_lambdify import Lambdifier
+        >>> str2tree = Lambdifier([x], x).str2tree
+        >>> tree2str = Lambdifier([x], x).tree2str
+
+        >>> tree2str(str2tree(str(x+y*sin(z)+1)))
+        'x + y*sin(z) + 1'
+        """
+        if isinstance(tree, str):
+            return tree
+        else:
+            return ''.join(map(cls.tree2str, tree))
+
+    def tree2str_translate(self, tree):
+        """Converts a tree to string with translations.
+
+        Explanation
+        ===========
+
+        Function names are translated by translate_func.
+        Other strings are translated by translate_str.
+        """
+        if isinstance(tree, str):
+            return self.translate_str(tree)
+        elif isinstance(tree, tuple) and len(tree) == 2:
+            return self.translate_func(tree[0][:-1], tree[1])
+        else:
+            return ''.join([self.tree2str_translate(t) for t in tree])
+
+    def translate_str(self, estr):
+        """Translate substrings of estr using in order the dictionaries in
+        dict_tuple_str."""
+        for pattern, repl in self.dict_str.items():
+                estr = re.sub(pattern, repl, estr)
+        return estr
+
+    def translate_func(self, func_name, argtree):
+        """Translate function names and the tree of arguments.
+
+        Explanation
+        ===========
+
+        If the function name is not in the dictionaries of dict_tuple_fun then the
+        function is surrounded by a float((...).evalf()).
+
+        The use of float is necessary as np.<function>(sympy.Float(..)) raises an
+        error."""
+        if func_name in self.dict_fun:
+            new_name = self.dict_fun[func_name]
+            argstr = self.tree2str_translate(argtree)
+            return new_name + '(' + argstr
+        elif func_name in ['Eq', 'Ne']:
+            op = {'Eq': '==', 'Ne': '!='}
+            return "(lambda x, y: x {} y)({}".format(op[func_name], self.tree2str_translate(argtree))
+        else:
+            template = '(%s(%s)).evalf(' if self.use_evalf else '%s(%s'
+            if self.float_wrap_evalf:
+                template = 'float(%s)' % template
+            elif self.complex_wrap_evalf:
+                template = 'complex(%s)' % template
+
+            # Wrapping should only happen on the outermost expression, which
+            # is the only thing we know will be a number.
+            float_wrap_evalf = self.float_wrap_evalf
+            complex_wrap_evalf = self.complex_wrap_evalf
+            self.float_wrap_evalf = False
+            self.complex_wrap_evalf = False
+            ret =  template % (func_name, self.tree2str_translate(argtree))
+            self.float_wrap_evalf = float_wrap_evalf
+            self.complex_wrap_evalf = complex_wrap_evalf
+            return ret
+
+    ##############################################################################
+    # The namespace constructors
+    ##############################################################################
+
+    @classmethod
+    def sympy_expression_namespace(cls, expr):
+        """Traverses the (func, args) tree of an expression and creates a SymPy
+        namespace. All other modules are imported only as a module name. That way
+        the namespace is not polluted and rests quite small. It probably causes much
+        more variable lookups and so it takes more time, but there are no tests on
+        that for the moment."""
+        if expr is None:
+            return {}
+        else:
+            funcname = str(expr.func)
+            # XXX Workaround
+            # Here we add an ugly workaround because str(func(x))
+            # is not always the same as str(func). Eg
+            # >>> str(Integral(x))
+            # "Integral(x)"
+            # >>> str(Integral)
+            # "<class 'sympy.integrals.integrals.Integral'>"
+            # >>> str(sqrt(x))
+            # "sqrt(x)"
+            # >>> str(sqrt)
+            # "<function sqrt at 0x3d92de8>"
+            # >>> str(sin(x))
+            # "sin(x)"
+            # >>> str(sin)
+            # "sin"
+            # Either one of those can be used but not all at the same time.
+            # The code considers the sin example as the right one.
+            regexlist = [
+                r'<class \'sympy[\w.]*?.([\w]*)\'>$',
+                # the example Integral
+                r'<function ([\w]*) at 0x[\w]*>$',    # the example sqrt
+            ]
+            for r in regexlist:
+                m = re.match(r, funcname)
+                if m is not None:
+                    funcname = m.groups()[0]
+            # End of the workaround
+            # XXX debug: print funcname
+            args_dict = {}
+            for a in expr.args:
+                if (isinstance(a, (Symbol, NumberSymbol)) or a in [I, zoo, oo]):
+                    continue
+                else:
+                    args_dict.update(cls.sympy_expression_namespace(a))
+            args_dict.update({funcname: expr.func})
+            return args_dict
+
+    @staticmethod
+    def sympy_atoms_namespace(expr):
+        """For no real reason this function is separated from
+        sympy_expression_namespace. It can be moved to it."""
+        atoms = expr.atoms(Symbol, NumberSymbol, I, zoo, oo)
+        d = {}
+        for a in atoms:
+            # XXX debug: print 'atom:' + str(a)
+            d[str(a)] = a
+        return d

pythonProject/.venv/Lib/site-packages/sympy/plotting/plot.py

@@ -0,0 +1,1234 @@
+"""Plotting module for SymPy.
+
+A plot is represented by the ``Plot`` class that contains a reference to the
+backend and a list of the data series to be plotted. The data series are
+instances of classes meant to simplify getting points and meshes from SymPy
+expressions. ``plot_backends`` is a dictionary with all the backends.
+
+This module gives only the essential. For all the fancy stuff use directly
+the backend. You can get the backend wrapper for every plot from the
+``_backend`` attribute. Moreover the data series classes have various useful
+methods like ``get_points``, ``get_meshes``, etc, that may
+be useful if you wish to use another plotting library.
+
+Especially if you need publication ready graphs and this module is not enough
+for you - just get the ``_backend`` attribute and add whatever you want
+directly to it. In the case of matplotlib (the common way to graph data in
+python) just copy ``_backend.fig`` which is the figure and ``_backend.ax``
+which is the axis and work on them as you would on any other matplotlib object.
+
+Simplicity of code takes much greater importance than performance. Do not use it
+if you care at all about performance. A new backend instance is initialized
+every time you call ``show()`` and the old one is left to the garbage collector.
+"""
+
+from sympy.concrete.summations import Sum
+from sympy.core.containers import Tuple
+from sympy.core.expr import Expr
+from sympy.core.function import Function, AppliedUndef
+from sympy.core.symbol import (Dummy, Symbol, Wild)
+from sympy.external import import_module
+from sympy.functions import sign
+from sympy.plotting.backends.base_backend import Plot
+from sympy.plotting.backends.matplotlibbackend import MatplotlibBackend
+from sympy.plotting.backends.textbackend import TextBackend
+from sympy.plotting.series import (
+    LineOver1DRangeSeries, Parametric2DLineSeries, Parametric3DLineSeries,
+    ParametricSurfaceSeries, SurfaceOver2DRangeSeries, ContourSeries)
+from sympy.plotting.utils import _check_arguments, _plot_sympify
+from sympy.tensor.indexed import Indexed
+# to maintain back-compatibility
+from sympy.plotting.plotgrid import PlotGrid # noqa: F401
+from sympy.plotting.series import BaseSeries # noqa: F401
+from sympy.plotting.series import Line2DBaseSeries # noqa: F401
+from sympy.plotting.series import Line3DBaseSeries # noqa: F401
+from sympy.plotting.series import SurfaceBaseSeries # noqa: F401
+from sympy.plotting.series import List2DSeries # noqa: F401
+from sympy.plotting.series import GenericDataSeries # noqa: F401
+from sympy.plotting.series import centers_of_faces # noqa: F401
+from sympy.plotting.series import centers_of_segments # noqa: F401
+from sympy.plotting.series import flat # noqa: F401
+from sympy.plotting.backends.base_backend import unset_show # noqa: F401
+from sympy.plotting.backends.matplotlibbackend import _matplotlib_list # noqa: F401
+from sympy.plotting.textplot import textplot # noqa: F401
+
+
+__doctest_requires__ = {
+    ('plot3d',
+     'plot3d_parametric_line',
+     'plot3d_parametric_surface',
+     'plot_parametric'): ['matplotlib'],
+    # XXX: The plot doctest possibly should not require matplotlib. It fails at
+    # plot(x**2, (x, -5, 5)) which should be fine for text backend.
+    ('plot',): ['matplotlib'],
+}
+
+
+def _process_summations(sum_bound, *args):
+    """Substitute oo (infinity) in the lower/upper bounds of a summation with
+    some integer number.
+
+    Parameters
+    ==========
+
+    sum_bound : int
+        oo will be substituted with this integer number.
+    *args : list/tuple
+        pre-processed arguments of the form (expr, range, ...)
+
+    Notes
+    =====
+    Let's consider the following summation: ``Sum(1 / x**2, (x, 1, oo))``.
+    The current implementation of lambdify (SymPy 1.12 at the time of
+    writing this) will create something of this form:
+    ``sum(1 / x**2 for x in range(1, INF))``
+    The problem is that ``type(INF)`` is float, while ``range`` requires
+    integers: the evaluation fails.
+    Instead of modifying ``lambdify`` (which requires a deep knowledge), just
+    replace it with some integer number.
+    """
+    def new_bound(t, bound):
+        if (not t.is_number) or t.is_finite:
+            return t
+        if sign(t) >= 0:
+            return bound
+        return -bound
+
+    args = list(args)
+    expr = args[0]
+
+    # select summations whose lower/upper bound is infinity
+    w = Wild("w", properties=[
+        lambda t: isinstance(t, Sum),
+        lambda t: any((not a[1].is_finite) or (not a[2].is_finite) for i, a in enumerate(t.args) if i > 0)
+    ])
+
+    for t in list(expr.find(w)):
+        sums_args = list(t.args)
+        for i, a in enumerate(sums_args):
+            if i > 0:
+                sums_args[i] = (a[0], new_bound(a[1], sum_bound),
+                    new_bound(a[2], sum_bound))
+        s = Sum(*sums_args)
+        expr = expr.subs(t, s)
+    args[0] = expr
+    return args
+
+
+def _build_line_series(*args, **kwargs):
+    """Loop over the provided arguments and create the necessary line series.
+    """
+    series = []
+    sum_bound = int(kwargs.get("sum_bound", 1000))
+    for arg in args:
+        expr, r, label, rendering_kw = arg
+        kw = kwargs.copy()
+        if rendering_kw is not None:
+            kw["rendering_kw"] = rendering_kw
+        # TODO: _process_piecewise check goes here
+        if not callable(expr):
+            arg = _process_summations(sum_bound, *arg)
+        series.append(LineOver1DRangeSeries(*arg[:-1], **kw))
+    return series
+
+
+def _create_series(series_type, plot_expr, **kwargs):
+    """Extract the rendering_kw dictionary from the provided arguments and
+    create an appropriate data series.
+    """
+    series = []
+    for args in plot_expr:
+        kw = kwargs.copy()
+        if args[-1] is not None:
+            kw["rendering_kw"] = args[-1]
+        series.append(series_type(*args[:-1], **kw))
+    return series
+
+
+def _set_labels(series, labels, rendering_kw):
+    """Apply the `label` and `rendering_kw` keyword arguments to the series.
+    """
+    if not isinstance(labels, (list, tuple)):
+        labels = [labels]
+    if len(labels) > 0:
+        if len(labels) == 1 and len(series) > 1:
+            # if one label is provided and multiple series are being plotted,
+            # set the same label to all data series. It maintains
+            # back-compatibility
+            labels *= len(series)
+        if len(series) != len(labels):
+            raise ValueError("The number of labels must be equal to the "
+                "number of expressions being plotted.\nReceived "
+                f"{len(series)} expressions and {len(labels)} labels")
+
+        for s, l in zip(series, labels):
+            s.label = l
+
+    if rendering_kw:
+        if isinstance(rendering_kw, dict):
+            rendering_kw = [rendering_kw]
+        if len(rendering_kw) == 1:
+            rendering_kw *= len(series)
+        elif len(series) != len(rendering_kw):
+            raise ValueError("The number of rendering dictionaries must be "
+                "equal to the number of expressions being plotted.\nReceived "
+                f"{len(series)} expressions and {len(labels)} labels")
+        for s, r in zip(series, rendering_kw):
+            s.rendering_kw = r
+
+
+def plot_factory(*args, **kwargs):
+    backend = kwargs.pop("backend", "default")
+    if isinstance(backend, str):
+        if backend == "default":
+            matplotlib = import_module('matplotlib',
+                min_module_version='1.1.0', catch=(RuntimeError,))
+            if matplotlib:
+                return MatplotlibBackend(*args, **kwargs)
+            return TextBackend(*args, **kwargs)
+        return plot_backends[backend](*args, **kwargs)
+    elif (type(backend) == type) and issubclass(backend, Plot):
+        return backend(*args, **kwargs)
+    else:
+        raise TypeError("backend must be either a string or a subclass of ``Plot``.")
+
+
+plot_backends = {
+    'matplotlib': MatplotlibBackend,
+    'text': TextBackend,
+}
+
+
+####New API for plotting module ####
+
+# TODO: Add color arrays for plots.
+# TODO: Add more plotting options for 3d plots.
+# TODO: Adaptive sampling for 3D plots.
+
+def plot(*args, show=True, **kwargs):
+    """Plots a function of a single variable as a curve.
+
+    Parameters
+    ==========
+
+    args :
+        The first argument is the expression representing the function
+        of single variable to be plotted.
+
+        The last argument is a 3-tuple denoting the range of the free
+        variable. e.g. ``(x, 0, 5)``
+
+        Typical usage examples are in the following:
+
+        - Plotting a single expression with a single range.
+            ``plot(expr, range, **kwargs)``
+        - Plotting a single expression with the default range (-10, 10).
+            ``plot(expr, **kwargs)``
+        - Plotting multiple expressions with a single range.
+            ``plot(expr1, expr2, ..., range, **kwargs)``
+        - Plotting multiple expressions with multiple ranges.
+            ``plot((expr1, range1), (expr2, range2), ..., **kwargs)``
+
+        It is best practice to specify range explicitly because default
+        range may change in the future if a more advanced default range
+        detection algorithm is implemented.
+
+    show : bool, optional
+        The default value is set to ``True``. Set show to ``False`` and
+        the function will not display the plot. The returned instance of
+        the ``Plot`` class can then be used to save or display the plot
+        by calling the ``save()`` and ``show()`` methods respectively.
+
+    line_color : string, or float, or function, optional
+        Specifies the color for the plot.
+        See ``Plot`` to see how to set color for the plots.
+        Note that by setting ``line_color``, it would be applied simultaneously
+        to all the series.
+
+    title : str, optional
+        Title of the plot. It is set to the latex representation of
+        the expression, if the plot has only one expression.
+
+    label : str, optional
+        The label of the expression in the plot. It will be used when
+        called with ``legend``. Default is the name of the expression.
+        e.g. ``sin(x)``
+
+    xlabel : str or expression, optional
+        Label for the x-axis.
+
+    ylabel : str or expression, optional
+        Label for the y-axis.
+
+    xscale : 'linear' or 'log', optional
+        Sets the scaling of the x-axis.
+
+    yscale : 'linear' or 'log', optional
+        Sets the scaling of the y-axis.
+
+    axis_center : (float, float), optional
+        Tuple of two floats denoting the coordinates of the center or
+        {'center', 'auto'}
+
+    xlim : (float, float), optional
+        Denotes the x-axis limits, ``(min, max)```.
+
+    ylim : (float, float), optional
+        Denotes the y-axis limits, ``(min, max)```.
+
+    annotations : list, optional
+        A list of dictionaries specifying the type of annotation
+        required. The keys in the dictionary should be equivalent
+        to the arguments of the :external:mod:`matplotlib`'s
+        :external:meth:`~matplotlib.axes.Axes.annotate` method.
+
+    markers : list, optional
+        A list of dictionaries specifying the type the markers required.
+        The keys in the dictionary should be equivalent to the arguments
+        of the :external:mod:`matplotlib`'s :external:func:`~matplotlib.pyplot.plot()` function
+        along with the marker related keyworded arguments.
+
+    rectangles : list, optional
+        A list of dictionaries specifying the dimensions of the
+        rectangles to be plotted. The keys in the dictionary should be
+        equivalent to the arguments of the :external:mod:`matplotlib`'s
+        :external:class:`~matplotlib.patches.Rectangle` class.
+
+    fill : dict, optional
+        A dictionary specifying the type of color filling required in
+        the plot. The keys in the dictionary should be equivalent to the
+        arguments of the :external:mod:`matplotlib`'s
+        :external:meth:`~matplotlib.axes.Axes.fill_between` method.
+
+    adaptive : bool, optional
+        The default value is set to ``True``. Set adaptive to ``False``
+        and specify ``n`` if uniform sampling is required.
+
+        The plotting uses an adaptive algorithm which samples
+        recursively to accurately plot. The adaptive algorithm uses a
+        random point near the midpoint of two points that has to be
+        further sampled. Hence the same plots can appear slightly
+        different.
+
+    depth : int, optional
+        Recursion depth of the adaptive algorithm. A depth of value
+        `n` samples a maximum of `2^{n}` points.
+
+        If the ``adaptive`` flag is set to ``False``, this will be
+        ignored.
+
+    n : int, optional
+        Used when the ``adaptive`` is set to ``False``. The function
+        is uniformly sampled at ``n`` number of points. If the ``adaptive``
+        flag is set to ``True``, this will be ignored.
+        This keyword argument replaces ``nb_of_points``, which should be
+        considered deprecated.
+
+    size : (float, float), optional
+        A tuple in the form (width, height) in inches to specify the size of
+        the overall figure. The default value is set to ``None``, meaning
+        the size will be set by the default backend.
+
+    Examples
+    ========
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> from sympy import symbols
+       >>> from sympy.plotting import plot
+       >>> x = symbols('x')
+
+    Single Plot
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot(x**2, (x, -5, 5))
+       Plot object containing:
+       [0]: cartesian line: x**2 for x over (-5.0, 5.0)
+
+    Multiple plots with single range.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot(x, x**2, x**3, (x, -5, 5))
+       Plot object containing:
+       [0]: cartesian line: x for x over (-5.0, 5.0)
+       [1]: cartesian line: x**2 for x over (-5.0, 5.0)
+       [2]: cartesian line: x**3 for x over (-5.0, 5.0)
+
+    Multiple plots with different ranges.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot((x**2, (x, -6, 6)), (x, (x, -5, 5)))
+       Plot object containing:
+       [0]: cartesian line: x**2 for x over (-6.0, 6.0)
+       [1]: cartesian line: x for x over (-5.0, 5.0)
+
+    No adaptive sampling.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot(x**2, adaptive=False, n=400)
+       Plot object containing:
+       [0]: cartesian line: x**2 for x over (-10.0, 10.0)
+
+    See Also
+    ========
+
+    Plot, LineOver1DRangeSeries
+
+    """
+    args = _plot_sympify(args)
+    plot_expr = _check_arguments(args, 1, 1, **kwargs)
+    params = kwargs.get("params", None)
+    free = set()
+    for p in plot_expr:
+        if not isinstance(p[1][0], str):
+            free |= {p[1][0]}
+        else:
+            free |= {Symbol(p[1][0])}
+    if params:
+        free = free.difference(params.keys())
+    x = free.pop() if free else Symbol("x")
+    kwargs.setdefault('xlabel', x)
+    kwargs.setdefault('ylabel', Function('f')(x))
+
+    labels = kwargs.pop("label", [])
+    rendering_kw = kwargs.pop("rendering_kw", None)
+    series = _build_line_series(*plot_expr, **kwargs)
+    _set_labels(series, labels, rendering_kw)
+
+    plots = plot_factory(*series, **kwargs)
+    if show:
+        plots.show()
+    return plots
+
+
+def plot_parametric(*args, show=True, **kwargs):
+    """
+    Plots a 2D parametric curve.
+
+    Parameters
+    ==========
+
+    args
+        Common specifications are:
+
+        - Plotting a single parametric curve with a range
+            ``plot_parametric((expr_x, expr_y), range)``
+        - Plotting multiple parametric curves with the same range
+            ``plot_parametric((expr_x, expr_y), ..., range)``
+        - Plotting multiple parametric curves with different ranges
+            ``plot_parametric((expr_x, expr_y, range), ...)``
+
+        ``expr_x`` is the expression representing $x$ component of the
+        parametric function.
+
+        ``expr_y`` is the expression representing $y$ component of the
+        parametric function.
+
+        ``range`` is a 3-tuple denoting the parameter symbol, start and
+        stop. For example, ``(u, 0, 5)``.
+
+        If the range is not specified, then a default range of (-10, 10)
+        is used.
+
+        However, if the arguments are specified as
+        ``(expr_x, expr_y, range), ...``, you must specify the ranges
+        for each expressions manually.
+
+        Default range may change in the future if a more advanced
+        algorithm is implemented.
+
+    adaptive : bool, optional
+        Specifies whether to use the adaptive sampling or not.
+
+        The default value is set to ``True``. Set adaptive to ``False``
+        and specify ``n`` if uniform sampling is required.
+
+    depth :  int, optional
+        The recursion depth of the adaptive algorithm. A depth of
+        value $n$ samples a maximum of $2^n$ points.
+
+    n : int, optional
+        Used when the ``adaptive`` flag is set to ``False``. Specifies the
+        number of the points used for the uniform sampling.
+        This keyword argument replaces ``nb_of_points``, which should be
+        considered deprecated.
+
+    line_color : string, or float, or function, optional
+        Specifies the color for the plot.
+        See ``Plot`` to see how to set color for the plots.
+        Note that by setting ``line_color``, it would be applied simultaneously
+        to all the series.
+
+    label : str, optional
+        The label of the expression in the plot. It will be used when
+        called with ``legend``. Default is the name of the expression.
+        e.g. ``sin(x)``
+
+    xlabel : str, optional
+        Label for the x-axis.
+
+    ylabel : str, optional
+        Label for the y-axis.
+
+    xscale : 'linear' or 'log', optional
+        Sets the scaling of the x-axis.
+
+    yscale : 'linear' or 'log', optional
+        Sets the scaling of the y-axis.
+
+    axis_center : (float, float), optional
+        Tuple of two floats denoting the coordinates of the center or
+        {'center', 'auto'}
+
+    xlim : (float, float), optional
+        Denotes the x-axis limits, ``(min, max)```.
+
+    ylim : (float, float), optional
+        Denotes the y-axis limits, ``(min, max)```.
+
+    size : (float, float), optional
+        A tuple in the form (width, height) in inches to specify the size of
+        the overall figure. The default value is set to ``None``, meaning
+        the size will be set by the default backend.
+
+    Examples
+    ========
+
+    .. plot::
+       :context: reset
+       :format: doctest
+       :include-source: True
+
+       >>> from sympy import plot_parametric, symbols, cos, sin
+       >>> u = symbols('u')
+
+    A parametric plot with a single expression:
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot_parametric((cos(u), sin(u)), (u, -5, 5))
+       Plot object containing:
+       [0]: parametric cartesian line: (cos(u), sin(u)) for u over (-5.0, 5.0)
+
+    A parametric plot with multiple expressions with the same range:
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot_parametric((cos(u), sin(u)), (u, cos(u)), (u, -10, 10))
+       Plot object containing:
+       [0]: parametric cartesian line: (cos(u), sin(u)) for u over (-10.0, 10.0)
+       [1]: parametric cartesian line: (u, cos(u)) for u over (-10.0, 10.0)
+
+    A parametric plot with multiple expressions with different ranges
+    for each curve:
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot_parametric((cos(u), sin(u), (u, -5, 5)),
+       ...     (cos(u), u, (u, -5, 5)))
+       Plot object containing:
+       [0]: parametric cartesian line: (cos(u), sin(u)) for u over (-5.0, 5.0)
+       [1]: parametric cartesian line: (cos(u), u) for u over (-5.0, 5.0)
+
+    Notes
+    =====
+
+    The plotting uses an adaptive algorithm which samples recursively to
+    accurately plot the curve. The adaptive algorithm uses a random point
+    near the midpoint of two points that has to be further sampled.
+    Hence, repeating the same plot command can give slightly different
+    results because of the random sampling.
+
+    If there are multiple plots, then the same optional arguments are
+    applied to all the plots drawn in the same canvas. If you want to
+    set these options separately, you can index the returned ``Plot``
+    object and set it.
+
+    For example, when you specify ``line_color`` once, it would be
+    applied simultaneously to both series.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+        >>> from sympy import pi
+        >>> expr1 = (u, cos(2*pi*u)/2 + 1/2)
+        >>> expr2 = (u, sin(2*pi*u)/2 + 1/2)
+        >>> p = plot_parametric(expr1, expr2, (u, 0, 1), line_color='blue')
+
+    If you want to specify the line color for the specific series, you
+    should index each item and apply the property manually.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+        >>> p[0].line_color = 'red'
+        >>> p.show()
+
+    See Also
+    ========
+
+    Plot, Parametric2DLineSeries
+    """
+    args = _plot_sympify(args)
+    plot_expr = _check_arguments(args, 2, 1, **kwargs)
+
+    labels = kwargs.pop("label", [])
+    rendering_kw = kwargs.pop("rendering_kw", None)
+    series = _create_series(Parametric2DLineSeries, plot_expr, **kwargs)
+    _set_labels(series, labels, rendering_kw)
+
+    plots = plot_factory(*series, **kwargs)
+    if show:
+        plots.show()
+    return plots
+
+
+def plot3d_parametric_line(*args, show=True, **kwargs):
+    """
+    Plots a 3D parametric line plot.
+
+    Usage
+    =====
+
+    Single plot:
+
+    ``plot3d_parametric_line(expr_x, expr_y, expr_z, range, **kwargs)``
+
+    If the range is not specified, then a default range of (-10, 10) is used.
+
+    Multiple plots.
+
+    ``plot3d_parametric_line((expr_x, expr_y, expr_z, range), ..., **kwargs)``
+
+    Ranges have to be specified for every expression.
+
+    Default range may change in the future if a more advanced default range
+    detection algorithm is implemented.
+
+    Arguments
+    =========
+
+    expr_x : Expression representing the function along x.
+
+    expr_y : Expression representing the function along y.
+
+    expr_z : Expression representing the function along z.
+
+    range : (:class:`~.Symbol`, float, float)
+        A 3-tuple denoting the range of the parameter variable, e.g., (u, 0, 5).
+
+    Keyword Arguments
+    =================
+
+    Arguments for ``Parametric3DLineSeries`` class.
+
+    n : int
+        The range is uniformly sampled at ``n`` number of points.
+        This keyword argument replaces ``nb_of_points``, which should be
+        considered deprecated.
+
+    Aesthetics:
+
+    line_color : string, or float, or function, optional
+        Specifies the color for the plot.
+        See ``Plot`` to see how to set color for the plots.
+        Note that by setting ``line_color``, it would be applied simultaneously
+        to all the series.
+
+    label : str
+        The label to the plot. It will be used when called with ``legend=True``
+        to denote the function with the given label in the plot.
+
+    If there are multiple plots, then the same series arguments are applied to
+    all the plots. If you want to set these options separately, you can index
+    the returned ``Plot`` object and set it.
+
+    Arguments for ``Plot`` class.
+
+    title : str
+        Title of the plot.
+
+    size : (float, float), optional
+        A tuple in the form (width, height) in inches to specify the size of
+        the overall figure. The default value is set to ``None``, meaning
+        the size will be set by the default backend.
+
+    Examples
+    ========
+
+    .. plot::
+       :context: reset
+       :format: doctest
+       :include-source: True
+
+       >>> from sympy import symbols, cos, sin
+       >>> from sympy.plotting import plot3d_parametric_line
+       >>> u = symbols('u')
+
+    Single plot.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot3d_parametric_line(cos(u), sin(u), u, (u, -5, 5))
+       Plot object containing:
+       [0]: 3D parametric cartesian line: (cos(u), sin(u), u) for u over (-5.0, 5.0)
+
+
+    Multiple plots.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot3d_parametric_line((cos(u), sin(u), u, (u, -5, 5)),
+       ...     (sin(u), u**2, u, (u, -5, 5)))
+       Plot object containing:
+       [0]: 3D parametric cartesian line: (cos(u), sin(u), u) for u over (-5.0, 5.0)
+       [1]: 3D parametric cartesian line: (sin(u), u**2, u) for u over (-5.0, 5.0)
+
+
+    See Also
+    ========
+
+    Plot, Parametric3DLineSeries
+
+    """
+    args = _plot_sympify(args)
+    plot_expr = _check_arguments(args, 3, 1, **kwargs)
+    kwargs.setdefault("xlabel", "x")
+    kwargs.setdefault("ylabel", "y")
+    kwargs.setdefault("zlabel", "z")
+
+    labels = kwargs.pop("label", [])
+    rendering_kw = kwargs.pop("rendering_kw", None)
+    series = _create_series(Parametric3DLineSeries, plot_expr, **kwargs)
+    _set_labels(series, labels, rendering_kw)
+
+    plots = plot_factory(*series, **kwargs)
+    if show:
+        plots.show()
+    return plots
+
+
+def _plot3d_plot_contour_helper(Series, *args, **kwargs):
+    """plot3d and plot_contour are structurally identical. Let's reduce
+    code repetition.
+    """
+    # NOTE: if this import would be at the top-module level, it would trigger
+    # SymPy's optional-dependencies tests to fail.
+    from sympy.vector import BaseScalar
+
+    args = _plot_sympify(args)
+    plot_expr = _check_arguments(args, 1, 2, **kwargs)
+
+    free_x = set()
+    free_y = set()
+    _types = (Symbol, BaseScalar, Indexed, AppliedUndef)
+    for p in plot_expr:
+        free_x |= {p[1][0]} if isinstance(p[1][0], _types) else {Symbol(p[1][0])}
+        free_y |= {p[2][0]} if isinstance(p[2][0], _types) else {Symbol(p[2][0])}
+    x = free_x.pop() if free_x else Symbol("x")
+    y = free_y.pop() if free_y else Symbol("y")
+    kwargs.setdefault("xlabel", x)
+    kwargs.setdefault("ylabel", y)
+    kwargs.setdefault("zlabel", Function('f')(x, y))
+
+    # if a polar discretization is requested and automatic labelling has ben
+    # applied, hide the labels on the x-y axis.
+    if kwargs.get("is_polar", False):
+        if callable(kwargs["xlabel"]):
+            kwargs["xlabel"] = ""
+        if callable(kwargs["ylabel"]):
+            kwargs["ylabel"] = ""
+
+    labels = kwargs.pop("label", [])
+    rendering_kw = kwargs.pop("rendering_kw", None)
+    series = _create_series(Series, plot_expr, **kwargs)
+    _set_labels(series, labels, rendering_kw)
+    plots = plot_factory(*series, **kwargs)
+    if kwargs.get("show", True):
+        plots.show()
+    return plots
+
+
+def plot3d(*args, show=True, **kwargs):
+    """
+    Plots a 3D surface plot.
+
+    Usage
+    =====
+
+    Single plot
+
+    ``plot3d(expr, range_x, range_y, **kwargs)``
+
+    If the ranges are not specified, then a default range of (-10, 10) is used.
+
+    Multiple plot with the same range.
+
+    ``plot3d(expr1, expr2, range_x, range_y, **kwargs)``
+
+    If the ranges are not specified, then a default range of (-10, 10) is used.
+
+    Multiple plots with different ranges.
+
+    ``plot3d((expr1, range_x, range_y), (expr2, range_x, range_y), ..., **kwargs)``
+
+    Ranges have to be specified for every expression.
+
+    Default range may change in the future if a more advanced default range
+    detection algorithm is implemented.
+
+    Arguments
+    =========
+
+    expr : Expression representing the function along x.
+
+    range_x : (:class:`~.Symbol`, float, float)
+        A 3-tuple denoting the range of the x variable, e.g. (x, 0, 5).
+
+    range_y : (:class:`~.Symbol`, float, float)
+        A 3-tuple denoting the range of the y variable, e.g. (y, 0, 5).
+
+    Keyword Arguments
+    =================
+
+    Arguments for ``SurfaceOver2DRangeSeries`` class:
+
+    n1 : int
+        The x range is sampled uniformly at ``n1`` of points.
+        This keyword argument replaces ``nb_of_points_x``, which should be
+        considered deprecated.
+
+    n2 : int
+        The y range is sampled uniformly at ``n2`` of points.
+        This keyword argument replaces ``nb_of_points_y``, which should be
+        considered deprecated.
+
+    Aesthetics:
+
+    surface_color : Function which returns a float
+        Specifies the color for the surface of the plot.
+        See :class:`~.Plot` for more details.
+
+    If there are multiple plots, then the same series arguments are applied to
+    all the plots. If you want to set these options separately, you can index
+    the returned ``Plot`` object and set it.
+
+    Arguments for ``Plot`` class:
+
+    title : str
+        Title of the plot.
+
+    size : (float, float), optional
+        A tuple in the form (width, height) in inches to specify the size of the
+        overall figure. The default value is set to ``None``, meaning the size will
+        be set by the default backend.
+
+    Examples
+    ========
+
+    .. plot::
+       :context: reset
+       :format: doctest
+       :include-source: True
+
+       >>> from sympy import symbols
+       >>> from sympy.plotting import plot3d
+       >>> x, y = symbols('x y')
+
+    Single plot
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot3d(x*y, (x, -5, 5), (y, -5, 5))
+       Plot object containing:
+       [0]: cartesian surface: x*y for x over (-5.0, 5.0) and y over (-5.0, 5.0)
+
+
+    Multiple plots with same range
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot3d(x*y, -x*y, (x, -5, 5), (y, -5, 5))
+       Plot object containing:
+       [0]: cartesian surface: x*y for x over (-5.0, 5.0) and y over (-5.0, 5.0)
+       [1]: cartesian surface: -x*y for x over (-5.0, 5.0) and y over (-5.0, 5.0)
+
+
+    Multiple plots with different ranges.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot3d((x**2 + y**2, (x, -5, 5), (y, -5, 5)),
+       ...     (x*y, (x, -3, 3), (y, -3, 3)))
+       Plot object containing:
+       [0]: cartesian surface: x**2 + y**2 for x over (-5.0, 5.0) and y over (-5.0, 5.0)
+       [1]: cartesian surface: x*y for x over (-3.0, 3.0) and y over (-3.0, 3.0)
+
+
+    See Also
+    ========
+
+    Plot, SurfaceOver2DRangeSeries
+
+    """
+    kwargs.setdefault("show", show)
+    return _plot3d_plot_contour_helper(
+        SurfaceOver2DRangeSeries, *args, **kwargs)
+
+
+def plot3d_parametric_surface(*args, show=True, **kwargs):
+    """
+    Plots a 3D parametric surface plot.
+
+    Explanation
+    ===========
+
+    Single plot.
+
+    ``plot3d_parametric_surface(expr_x, expr_y, expr_z, range_u, range_v, **kwargs)``
+
+    If the ranges is not specified, then a default range of (-10, 10) is used.
+
+    Multiple plots.
+
+    ``plot3d_parametric_surface((expr_x, expr_y, expr_z, range_u, range_v), ..., **kwargs)``
+
+    Ranges have to be specified for every expression.
+
+    Default range may change in the future if a more advanced default range
+    detection algorithm is implemented.
+
+    Arguments
+    =========
+
+    expr_x : Expression representing the function along ``x``.
+
+    expr_y : Expression representing the function along ``y``.
+
+    expr_z : Expression representing the function along ``z``.
+
+    range_u : (:class:`~.Symbol`, float, float)
+        A 3-tuple denoting the range of the u variable, e.g. (u, 0, 5).
+
+    range_v : (:class:`~.Symbol`, float, float)
+        A 3-tuple denoting the range of the v variable, e.g. (v, 0, 5).
+
+    Keyword Arguments
+    =================
+
+    Arguments for ``ParametricSurfaceSeries`` class:
+
+    n1 : int
+        The ``u`` range is sampled uniformly at ``n1`` of points.
+        This keyword argument replaces ``nb_of_points_u``, which should be
+        considered deprecated.
+
+    n2 : int
+        The ``v`` range is sampled uniformly at ``n2`` of points.
+        This keyword argument replaces ``nb_of_points_v``, which should be
+        considered deprecated.
+
+    Aesthetics:
+
+    surface_color : Function which returns a float
+        Specifies the color for the surface of the plot. See
+        :class:`~Plot` for more details.
+
+    If there are multiple plots, then the same series arguments are applied for
+    all the plots. If you want to set these options separately, you can index
+    the returned ``Plot`` object and set it.
+
+
+    Arguments for ``Plot`` class:
+
+    title : str
+        Title of the plot.
+
+    size : (float, float), optional
+        A tuple in the form (width, height) in inches to specify the size of the
+        overall figure. The default value is set to ``None``, meaning the size will
+        be set by the default backend.
+
+    Examples
+    ========
+
+    .. plot::
+       :context: reset
+       :format: doctest
+       :include-source: True
+
+       >>> from sympy import symbols, cos, sin
+       >>> from sympy.plotting import plot3d_parametric_surface
+       >>> u, v = symbols('u v')
+
+    Single plot.
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+       >>> plot3d_parametric_surface(cos(u + v), sin(u - v), u - v,
+       ...     (u, -5, 5), (v, -5, 5))
+       Plot object containing:
+       [0]: parametric cartesian surface: (cos(u + v), sin(u - v), u - v) for u over (-5.0, 5.0) and v over (-5.0, 5.0)
+
+
+    See Also
+    ========
+
+    Plot, ParametricSurfaceSeries
+
+    """
+
+    args = _plot_sympify(args)
+    plot_expr = _check_arguments(args, 3, 2, **kwargs)
+    kwargs.setdefault("xlabel", "x")
+    kwargs.setdefault("ylabel", "y")
+    kwargs.setdefault("zlabel", "z")
+
+    labels = kwargs.pop("label", [])
+    rendering_kw = kwargs.pop("rendering_kw", None)
+    series = _create_series(ParametricSurfaceSeries, plot_expr, **kwargs)
+    _set_labels(series, labels, rendering_kw)
+
+    plots = plot_factory(*series, **kwargs)
+    if show:
+        plots.show()
+    return plots
+
+def plot_contour(*args, show=True, **kwargs):
+    """
+    Draws contour plot of a function
+
+    Usage
+    =====
+
+    Single plot
+
+    ``plot_contour(expr, range_x, range_y, **kwargs)``
+
+    If the ranges are not specified, then a default range of (-10, 10) is used.
+
+    Multiple plot with the same range.
+
+    ``plot_contour(expr1, expr2, range_x, range_y, **kwargs)``
+
+    If the ranges are not specified, then a default range of (-10, 10) is used.
+
+    Multiple plots with different ranges.
+
+    ``plot_contour((expr1, range_x, range_y), (expr2, range_x, range_y), ..., **kwargs)``
+
+    Ranges have to be specified for every expression.
+
+    Default range may change in the future if a more advanced default range
+    detection algorithm is implemented.
+
+    Arguments
+    =========
+
+    expr : Expression representing the function along x.
+
+    range_x : (:class:`Symbol`, float, float)
+        A 3-tuple denoting the range of the x variable, e.g. (x, 0, 5).
+
+    range_y : (:class:`Symbol`, float, float)
+        A 3-tuple denoting the range of the y variable, e.g. (y, 0, 5).
+
+    Keyword Arguments
+    =================
+
+    Arguments for ``ContourSeries`` class:
+
+    n1 : int
+        The x range is sampled uniformly at ``n1`` of points.
+        This keyword argument replaces ``nb_of_points_x``, which should be
+        considered deprecated.
+
+    n2 : int
+        The y range is sampled uniformly at ``n2`` of points.
+        This keyword argument replaces ``nb_of_points_y``, which should be
+        considered deprecated.
+
+    Aesthetics:
+
+    surface_color : Function which returns a float
+        Specifies the color for the surface of the plot. See
+        :class:`sympy.plotting.Plot` for more details.
+
+    If there are multiple plots, then the same series arguments are applied to
+    all the plots. If you want to set these options separately, you can index
+    the returned ``Plot`` object and set it.
+
+    Arguments for ``Plot`` class:
+
+    title : str
+        Title of the plot.
+
+    size : (float, float), optional
+        A tuple in the form (width, height) in inches to specify the size of
+        the overall figure. The default value is set to ``None``, meaning
+        the size will be set by the default backend.
+
+    See Also
+    ========
+
+    Plot, ContourSeries
+
+    """
+    kwargs.setdefault("show", show)
+    return _plot3d_plot_contour_helper(ContourSeries, *args, **kwargs)
+
+
+def check_arguments(args, expr_len, nb_of_free_symbols):
+    """
+    Checks the arguments and converts into tuples of the
+    form (exprs, ranges).
+
+    Examples
+    ========
+
+    .. plot::
+       :context: reset
+       :format: doctest
+       :include-source: True
+
+       >>> from sympy import cos, sin, symbols
+       >>> from sympy.plotting.plot import check_arguments
+       >>> x = symbols('x')
+       >>> check_arguments([cos(x), sin(x)], 2, 1)
+           [(cos(x), sin(x), (x, -10, 10))]
+
+       >>> check_arguments([x, x**2], 1, 1)
+           [(x, (x, -10, 10)), (x**2, (x, -10, 10))]
+    """
+    if not args:
+        return []
+    if expr_len > 1 and isinstance(args[0], Expr):
+        # Multiple expressions same range.
+        # The arguments are tuples when the expression length is
+        # greater than 1.
+        if len(args) < expr_len:
+            raise ValueError("len(args) should not be less than expr_len")
+        for i in range(len(args)):
+            if isinstance(args[i], Tuple):
+                break
+        else:
+            i = len(args) + 1
+
+        exprs = Tuple(*args[:i])
+        free_symbols = list(set().union(*[e.free_symbols for e in exprs]))
+        if len(args) == expr_len + nb_of_free_symbols:
+            #Ranges given
+            plots = [exprs + Tuple(*args[expr_len:])]
+        else:
+            default_range = Tuple(-10, 10)
+            ranges = []
+            for symbol in free_symbols:
+                ranges.append(Tuple(symbol) + default_range)
+
+            for i in range(len(free_symbols) - nb_of_free_symbols):
+                ranges.append(Tuple(Dummy()) + default_range)
+            plots = [exprs + Tuple(*ranges)]
+        return plots
+
+    if isinstance(args[0], Expr) or (isinstance(args[0], Tuple) and
+                                     len(args[0]) == expr_len and
+                                     expr_len != 3):
+        # Cannot handle expressions with number of expression = 3. It is
+        # not possible to differentiate between expressions and ranges.
+        #Series of plots with same range
+        for i in range(len(args)):
+            if isinstance(args[i], Tuple) and len(args[i]) != expr_len:
+                break
+            if not isinstance(args[i], Tuple):
+                args[i] = Tuple(args[i])
+        else:
+            i = len(args) + 1
+
+        exprs = args[:i]
+        assert all(isinstance(e, Expr) for expr in exprs for e in expr)
+        free_symbols = list(set().union(*[e.free_symbols for expr in exprs
+                                        for e in expr]))
+
+        if len(free_symbols) > nb_of_free_symbols:
+            raise ValueError("The number of free_symbols in the expression "
+                             "is greater than %d" % nb_of_free_symbols)
+        if len(args) == i + nb_of_free_symbols and isinstance(args[i], Tuple):
+            ranges = Tuple(*list(args[
+                           i:i + nb_of_free_symbols]))
+            plots = [expr + ranges for expr in exprs]
+            return plots
+        else:
+            # Use default ranges.
+            default_range = Tuple(-10, 10)
+            ranges = []
+            for symbol in free_symbols:
+                ranges.append(Tuple(symbol) + default_range)
+
+            for i in range(nb_of_free_symbols - len(free_symbols)):
+                ranges.append(Tuple(Dummy()) + default_range)
+            ranges = Tuple(*ranges)
+            plots = [expr + ranges for expr in exprs]
+            return plots
+
+    elif isinstance(args[0], Tuple) and len(args[0]) == expr_len + nb_of_free_symbols:
+        # Multiple plots with different ranges.
+        for arg in args:
+            for i in range(expr_len):
+                if not isinstance(arg[i], Expr):
+                    raise ValueError("Expected an expression, given %s" %
+                                     str(arg[i]))
+            for i in range(nb_of_free_symbols):
+                if not len(arg[i + expr_len]) == 3:
+                    raise ValueError("The ranges should be a tuple of "
+                                     "length 3, got %s" % str(arg[i + expr_len]))
+        return args

pythonProject/.venv/Lib/site-packages/sympy/plotting/plotgrid.py

@@ -0,0 +1,188 @@
+
+from sympy.external import import_module
+import sympy.plotting.backends.base_backend as base_backend
+
+
+# N.B.
+# When changing the minimum module version for matplotlib, please change
+# the same in the `SymPyDocTestFinder`` in `sympy/testing/runtests.py`
+
+
+__doctest_requires__ = {
+    ("PlotGrid",): ["matplotlib"],
+}
+
+
+class PlotGrid:
+    """This class helps to plot subplots from already created SymPy plots
+    in a single figure.
+
+    Examples
+    ========
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+        >>> from sympy import symbols
+        >>> from sympy.plotting import plot, plot3d, PlotGrid
+        >>> x, y = symbols('x, y')
+        >>> p1 = plot(x, x**2, x**3, (x, -5, 5))
+        >>> p2 = plot((x**2, (x, -6, 6)), (x, (x, -5, 5)))
+        >>> p3 = plot(x**3, (x, -5, 5))
+        >>> p4 = plot3d(x*y, (x, -5, 5), (y, -5, 5))
+
+    Plotting vertically in a single line:
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+        >>> PlotGrid(2, 1, p1, p2)
+        PlotGrid object containing:
+        Plot[0]:Plot object containing:
+        [0]: cartesian line: x for x over (-5.0, 5.0)
+        [1]: cartesian line: x**2 for x over (-5.0, 5.0)
+        [2]: cartesian line: x**3 for x over (-5.0, 5.0)
+        Plot[1]:Plot object containing:
+        [0]: cartesian line: x**2 for x over (-6.0, 6.0)
+        [1]: cartesian line: x for x over (-5.0, 5.0)
+
+    Plotting horizontally in a single line:
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+        >>> PlotGrid(1, 3, p2, p3, p4)
+        PlotGrid object containing:
+        Plot[0]:Plot object containing:
+        [0]: cartesian line: x**2 for x over (-6.0, 6.0)
+        [1]: cartesian line: x for x over (-5.0, 5.0)
+        Plot[1]:Plot object containing:
+        [0]: cartesian line: x**3 for x over (-5.0, 5.0)
+        Plot[2]:Plot object containing:
+        [0]: cartesian surface: x*y for x over (-5.0, 5.0) and y over (-5.0, 5.0)
+
+    Plotting in a grid form:
+
+    .. plot::
+       :context: close-figs
+       :format: doctest
+       :include-source: True
+
+        >>> PlotGrid(2, 2, p1, p2, p3, p4)
+        PlotGrid object containing:
+        Plot[0]:Plot object containing:
+        [0]: cartesian line: x for x over (-5.0, 5.0)
+        [1]: cartesian line: x**2 for x over (-5.0, 5.0)
+        [2]: cartesian line: x**3 for x over (-5.0, 5.0)
+        Plot[1]:Plot object containing:
+        [0]: cartesian line: x**2 for x over (-6.0, 6.0)
+        [1]: cartesian line: x for x over (-5.0, 5.0)
+        Plot[2]:Plot object containing:
+        [0]: cartesian line: x**3 for x over (-5.0, 5.0)
+        Plot[3]:Plot object containing:
+        [0]: cartesian surface: x*y for x over (-5.0, 5.0) and y over (-5.0, 5.0)
+
+    """
+    def __init__(self, nrows, ncolumns, *args, show=True, size=None, **kwargs):
+        """
+        Parameters
+        ==========
+
+        nrows :
+            The number of rows that should be in the grid of the
+            required subplot.
+        ncolumns :
+            The number of columns that should be in the grid
+            of the required subplot.
+
+        nrows and ncolumns together define the required grid.
+
+        Arguments
+        =========
+
+        A list of predefined plot objects entered in a row-wise sequence
+        i.e. plot objects which are to be in the top row of the required
+        grid are written first, then the second row objects and so on
+
+        Keyword arguments
+        =================
+
+        show : Boolean
+            The default value is set to ``True``. Set show to ``False`` and
+            the function will not display the subplot. The returned instance
+            of the ``PlotGrid`` class can then be used to save or display the
+            plot by calling the ``save()`` and ``show()`` methods
+            respectively.
+        size : (float, float), optional
+            A tuple in the form (width, height) in inches to specify the size of
+            the overall figure. The default value is set to ``None``, meaning
+            the size will be set by the default backend.
+        """
+        self.matplotlib = import_module('matplotlib',
+            import_kwargs={'fromlist': ['pyplot', 'cm', 'collections']},
+            min_module_version='1.1.0', catch=(RuntimeError,))
+        self.nrows = nrows
+        self.ncolumns = ncolumns
+        self._series = []
+        self._fig = None
+        self.args = args
+        for arg in args:
+            self._series.append(arg._series)
+        self.size = size
+        if show and self.matplotlib:
+            self.show()
+
+    def _create_figure(self):
+        gs = self.matplotlib.gridspec.GridSpec(self.nrows, self.ncolumns)
+        mapping = {}
+        c = 0
+        for i in range(self.nrows):
+            for j in range(self.ncolumns):
+                if c < len(self.args):
+                    mapping[gs[i, j]] = self.args[c]
+                c += 1
+
+        kw = {} if not self.size else {"figsize": self.size}
+        self._fig = self.matplotlib.pyplot.figure(**kw)
+        for spec, p in mapping.items():
+            kw = ({"projection": "3d"} if (len(p._series) > 0 and
+                p._series[0].is_3D) else {})
+            cur_ax = self._fig.add_subplot(spec, **kw)
+            p._plotgrid_fig = self._fig
+            p._plotgrid_ax = cur_ax
+            p.process_series()
+
+    @property
+    def fig(self):
+        if not self._fig:
+            self._create_figure()
+        return self._fig
+
+    @property
+    def _backend(self):
+        return self
+
+    def close(self):
+        self.matplotlib.pyplot.close(self.fig)
+
+    def show(self):
+        if base_backend._show:
+            self.fig.tight_layout()
+            self.matplotlib.pyplot.show()
+        else:
+            self.close()
+
+    def save(self, path):
+        self.fig.savefig(path)
+
+    def __str__(self):
+        plot_strs = [('Plot[%d]:' % i) + str(plot)
+                      for i, plot in enumerate(self.args)]
+
+        return 'PlotGrid object containing:\n' + '\n'.join(plot_strs)