# Source code for sympy.categories.diagram_drawing

r"""
This module contains the functionality to arrange the nodes of a
diagram on an abstract grid, and then to produce a graphical
representation of the grid.

The currently supported back-ends are Xy-pic [Xypic].

Layout Algorithm
================

This section provides an overview of the algorithms implemented in
:class:DiagramGrid to lay out diagrams.

The first step of the algorithm is the removal composite and identity
morphisms which do not have properties in the supplied diagram.  The
premises and conclusions of the diagram are then merged.

The generic layout algorithm begins with the construction of the
"skeleton" of the diagram.  The skeleton is an undirected graph which
has the objects of the diagram as vertices and has an (undirected)
edge between each pair of objects between which there exist morphisms.
The direction of the morphisms does not matter at this stage.  The
skeleton also includes an edge between each pair of vertices A and
C such that there exists an object B which is connected via
a morphism to A, and via a morphism to C.

The skeleton constructed in this way has the property that every
object is a vertex of a triangle formed by three edges of the
skeleton.  This property lies at the base of the generic layout
algorithm.

After the skeleton has been constructed, the algorithm lists all
triangles which can be formed.  Note that some triangles will not have
all edges corresponding to morphisms which will actually be drawn.
Triangles which have only one edge or less which will actually be
drawn are immediately discarded.

The list of triangles is sorted according to the number of edges which
correspond to morphisms, then the triangle with the least number of such
edges is selected.  One of such edges is picked and the corresponding
objects are placed horizontally, on a grid.  This edge is recorded to
be in the fringe.  The algorithm then finds a "welding" of a triangle
to the fringe.  A welding is an edge in the fringe where a triangle
could be attached.  If the algorithm succeeds in finding such a
welding, it adds to the grid that vertex of the triangle which was not
yet included in any edge in the fringe and records the two new edges in
the fringe.  This process continues iteratively until all objects of
the diagram has been placed or until no more weldings can be found.

An edge is only removed from the fringe when a welding to this edge
has been found, and there is no room around this edge to place
another vertex.

When no more weldings can be found, but there are still triangles
left, the algorithm searches for a possibility of attaching one of the
remaining triangles to the existing structure by a vertex.  If such a
possibility is found, the corresponding edge of the found triangle is
placed in the found space and the iterative process of welding
triangles restarts.

When logical groups are supplied, each of these groups is laid out
independently.  Then a diagram is constructed in which groups are
objects and any two logical groups between which there exist morphisms
are connected via a morphism.  This diagram is laid out.  Finally,
the grid which includes all objects of the initial diagram is
constructed by replacing the cells which contain logical groups with
the corresponding laid out grids, and by correspondingly expanding the
rows and columns.

The sequential layout algorithm begins by constructing the
underlying undirected graph defined by the morphisms obtained after
simplifying premises and conclusions and merging them (see above).
The vertex with the minimal degree is then picked up and depth-first
search is started from it.  All objects which are located at distance
n from the root in the depth-first search tree, are positioned in
the n-th column of the resulting grid.  The sequential layout will
therefore attempt to lay the objects out along a line.

References
==========

[Xypic] http://xy-pic.sourceforge.net/

"""
from __future__ import print_function, division

from sympy.core import Dict, Symbol
from sympy.sets import FiniteSet
from sympy.categories import (CompositeMorphism, IdentityMorphism,
NamedMorphism, Diagram)
from sympy.utilities import default_sort_key
from itertools import chain
from sympy.core.compatibility import iterable, range
from sympy.printing import latex
from sympy.utilities.decorator import doctest_depends_on

class _GrowableGrid(object):
"""
Holds a growable grid of objects.

It is possible to append or prepend a row or a column to the grid
using the corresponding methods.  Prepending rows or columns has
the effect of changing the coordinates of the already existing
elements.

This class currently represents a naive implementation of the
functionality with little attempt at optimisation.
"""
def __init__(self, width, height):
self._width = width
self._height = height

self._array = [[None for j in range(width)] for i in range(height)]

@property
def width(self):
return self._width

@property
def height(self):
return self._height

def __getitem__(self, i_j):
"""
Returns the element located at in the i-th line and j-th
column.
"""
i, j = i_j
return self._array[i][j]

def __setitem__(self, i_j, newvalue):
"""
Sets the element located at in the i-th line and j-th
column.
"""
i, j = i_j
self._array[i][j] = newvalue

def append_row(self):
"""
Appends an empty row to the grid.
"""
self._height += 1
self._array.append([None for j in range(self._width)])

def append_column(self):
"""
Appends an empty column to the grid.
"""
self._width += 1
for i in range(self._height):
self._array[i].append(None)

def prepend_row(self):
"""
Prepends the grid with an empty row.
"""
self._height += 1
self._array.insert(0, [None for j in range(self._width)])

def prepend_column(self):
"""
Prepends the grid with an empty column.
"""
self._width += 1
for i in range(self._height):
self._array[i].insert(0, None)

[docs]class DiagramGrid(object): r""" Constructs and holds the fitting of the diagram into a grid. The mission of this class is to analyse the structure of the supplied diagram and to place its objects on a grid such that, when the objects and the morphisms are actually drawn, the diagram would be "readable", in the sense that there will not be many intersections of moprhisms. This class does not perform any actual drawing. It does strive nevertheless to offer sufficient metadata to draw a diagram. Consider the following simple diagram. >>> from sympy.categories import Object, NamedMorphism >>> from sympy.categories import Diagram, DiagramGrid >>> from sympy import pprint >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g]) The simplest way to have a diagram laid out is the following: >>> grid = DiagramGrid(diagram) >>> (grid.width, grid.height) (2, 2) >>> pprint(grid) A B <BLANKLINE> C Sometimes one sees the diagram as consisting of logical groups. One can advise DiagramGrid as to such groups by employing the groups keyword argument. Consider the following diagram: >>> D = Object("D") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> h = NamedMorphism(D, A, "h") >>> k = NamedMorphism(D, B, "k") >>> diagram = Diagram([f, g, h, k]) Lay it out with generic layout: >>> grid = DiagramGrid(diagram) >>> pprint(grid) A B D <BLANKLINE> C Now, we can group the objects A and D to have them near one another: >>> grid = DiagramGrid(diagram, groups=[[A, D], B, C]) >>> pprint(grid) B C <BLANKLINE> A D Note how the positioning of the other objects changes. Further indications can be supplied to the constructor of :class:DiagramGrid using keyword arguments. The currently supported hints are explained in the following paragraphs. :class:DiagramGrid does not automatically guess which layout would suit the supplied diagram better. Consider, for example, the following linear diagram: >>> E = Object("E") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> h = NamedMorphism(C, D, "h") >>> i = NamedMorphism(D, E, "i") >>> diagram = Diagram([f, g, h, i]) When laid out with the generic layout, it does not get to look linear: >>> grid = DiagramGrid(diagram) >>> pprint(grid) A B <BLANKLINE> C D <BLANKLINE> E To get it laid out in a line, use layout="sequential": >>> grid = DiagramGrid(diagram, layout="sequential") >>> pprint(grid) A B C D E One may sometimes need to transpose the resulting layout. While this can always be done by hand, :class:DiagramGrid provides a hint for that purpose: >>> grid = DiagramGrid(diagram, layout="sequential", transpose=True) >>> pprint(grid) A <BLANKLINE> B <BLANKLINE> C <BLANKLINE> D <BLANKLINE> E Separate hints can also be provided for each group. For an example, refer to tests/test_drawing.py, and see the different ways in which the five lemma [FiveLemma] can be laid out. See Also ======== Diagram References ========== [FiveLemma] http://en.wikipedia.org/wiki/Five_lemma """ @staticmethod def _simplify_morphisms(morphisms): """ Given a dictionary mapping morphisms to their properties, returns a new dictionary in which there are no morphisms which do not have properties, and which are compositions of other morphisms included in the dictionary. Identities are dropped as well. """ newmorphisms = {} for morphism, props in morphisms.items(): if isinstance(morphism, CompositeMorphism) and not props: continue elif isinstance(morphism, IdentityMorphism): continue else: newmorphisms[morphism] = props return newmorphisms @staticmethod def _merge_premises_conclusions(premises, conclusions): """ Given two dictionaries of morphisms and their properties, produces a single dictionary which includes elements from both dictionaries. If a morphism has some properties in premises and also in conclusions, the properties in conclusions take priority. """ return dict(chain(premises.items(), conclusions.items())) @staticmethod def _juxtapose_edges(edge1, edge2): """ If edge1 and edge2 have precisely one common endpoint, returns an edge which would form a triangle with edge1 and edge2. If edge1 and edge2 don't have a common endpoint, returns None. If edge1 and edge are the same edge, returns None. """ intersection = edge1 & edge2 if len(intersection) != 1: # The edges either have no common points or are equal. return None # The edges have a common endpoint. Extract the different # endpoints and set up the new edge. return (edge1 - intersection) | (edge2 - intersection) @staticmethod def _add_edge_append(dictionary, edge, elem): """ If edge is not in dictionary, adds edge to the dictionary and sets its value to [elem]. Otherwise appends elem to the value of existing entry. Note that edges are undirected, thus (A, B) = (B, A). """ if edge in dictionary: dictionary[edge].append(elem) else: dictionary[edge] = [elem] @staticmethod def _build_skeleton(morphisms): """ Creates a dictionary which maps edges to corresponding morphisms. Thus for a morphism f:A\rightarrow B, the edge (A, B) will be associated with f. This function also adds to the list those edges which are formed by juxtaposition of two edges already in the list. These new edges are not associated with any morphism and are only added to assure that the diagram can be decomposed into triangles. """ edges = {} # Create edges for morphisms. for morphism in morphisms: DiagramGrid._add_edge_append( edges, frozenset([morphism.domain, morphism.codomain]), morphism) # Create new edges by juxtaposing existing edges. edges1 = dict(edges) for w in edges1: for v in edges1: wv = DiagramGrid._juxtapose_edges(w, v) if wv and wv not in edges: edges[wv] = [] return edges @staticmethod def _list_triangles(edges): """ Builds the set of triangles formed by the supplied edges. The triangles are arbitrary and need not be commutative. A triangle is a set that contains all three of its sides. """ triangles = set() for w in edges: for v in edges: wv = DiagramGrid._juxtapose_edges(w, v) if wv and wv in edges: triangles.add(frozenset([w, v, wv])) return triangles @staticmethod def _drop_redundant_triangles(triangles, skeleton): """ Returns a list which contains only those triangles who have morphisms associated with at least two edges. """ return [tri for tri in triangles if len([e for e in tri if skeleton[e]]) >= 2] @staticmethod def _morphism_length(morphism): """ Returns the length of a morphism. The length of a morphism is the number of components it consists of. A non-composite morphism is of length 1. """ if isinstance(morphism, CompositeMorphism): return len(morphism.components) else: return 1 @staticmethod def _compute_triangle_min_sizes(triangles, edges): r""" Returns a dictionary mapping triangles to their minimal sizes. The minimal size of a triangle is the sum of maximal lengths of morphisms associated to the sides of the triangle. The length of a morphism is the number of components it consists of. A non-composite morphism is of length 1. Sorting triangles by this metric attempts to address two aspects of layout. For triangles with only simple morphisms in the edge, this assures that triangles with all three edges visible will get typeset after triangles with less visible edges, which sometimes minimises the necessity in diagonal arrows. For triangles with composite morphisms in the edges, this assures that objects connected with shorter morphisms will be laid out first, resulting the visual proximity of those objects which are connected by shorter morphisms. """ triangle_sizes = {} for triangle in triangles: size = 0 for e in triangle: morphisms = edges[e] if morphisms: size += max(DiagramGrid._morphism_length(m) for m in morphisms) triangle_sizes[triangle] = size return triangle_sizes @staticmethod def _triangle_objects(triangle): """ Given a triangle, returns the objects included in it. """ # A triangle is a frozenset of three two-element frozensets # (the edges). This chains the three edges together and # creates a frozenset from the iterator, thus producing a # frozenset of objects of the triangle. return frozenset(chain(*tuple(triangle))) @staticmethod def _other_vertex(triangle, edge): """ Given a triangle and an edge of it, returns the vertex which opposes the edge. """ # This gets the set of objects of the triangle and then # subtracts the set of objects employed in edge to get the # vertex opposite to edge. return list(DiagramGrid._triangle_objects(triangle) - set(edge))[0] @staticmethod def _empty_point(pt, grid): """ Checks if the cell at coordinates pt is either empty or out of the bounds of the grid. """ if (pt[0] < 0) or (pt[1] < 0) or \ (pt[0] >= grid.height) or (pt[1] >= grid.width): return True return grid[pt] is None @staticmethod def _put_object(coords, obj, grid, fringe): """ Places an object at the coordinate cords in grid, growing the grid and updating fringe, if necessary. Returns (0, 0) if no row or column has been prepended, (1, 0) if a row was prepended, (0, 1) if a column was prepended and (1, 1) if both a column and a row were prepended. """ (i, j) = coords offset = (0, 0) if i == -1: grid.prepend_row() i = 0 offset = (1, 0) for k in range(len(fringe)): ((i1, j1), (i2, j2)) = fringe[k] fringe[k] = ((i1 + 1, j1), (i2 + 1, j2)) elif i == grid.height: grid.append_row() if j == -1: j = 0 offset = (offset[0], 1) grid.prepend_column() for k in range(len(fringe)): ((i1, j1), (i2, j2)) = fringe[k] fringe[k] = ((i1, j1 + 1), (i2, j2 + 1)) elif j == grid.width: grid.append_column() grid[i, j] = obj return offset @staticmethod def _choose_target_cell(pt1, pt2, edge, obj, skeleton, grid): """ Given two points, pt1 and pt2, and the welding edge edge, chooses one of the two points to place the opposing vertex obj of the triangle. If neither of this points fits, returns None. """ pt1_empty = DiagramGrid._empty_point(pt1, grid) pt2_empty = DiagramGrid._empty_point(pt2, grid) if pt1_empty and pt2_empty: # Both cells are empty. Of these two, choose that cell # which will assure that a visible edge of the triangle # will be drawn perpendicularly to the current welding # edge. A = grid[edge[0]] B = grid[edge[1]] if skeleton.get(frozenset([A, obj])): return pt1 else: return pt2 if pt1_empty: return pt1 elif pt2_empty: return pt2 else: return None @staticmethod def _find_triangle_to_weld(triangles, fringe, grid): """ Finds, if possible, a triangle and an edge in the fringe to which the triangle could be attached. Returns the tuple containing the triangle and the index of the corresponding edge in the fringe. This function relies on the fact that objects are unique in the diagram. """ for triangle in triangles: for (a, b) in fringe: if frozenset([grid[a], grid[b]]) in triangle: return (triangle, (a, b)) return None @staticmethod def _weld_triangle(tri, welding_edge, fringe, grid, skeleton): """ If possible, welds the triangle tri to fringe and returns False. If this method encounters a degenerate situation in the fringe and corrects it such that a restart of the search is required, it returns True (which means that a restart in finding triangle weldings is required). A degenerate situation is a situation when an edge listed in the fringe does not belong to the visual boundary of the diagram. """ a, b = welding_edge target_cell = None obj = DiagramGrid._other_vertex(tri, (grid[a], grid[b])) # We now have a triangle and an edge where it can be welded to # the fringe. Decide where to place the other vertex of the # triangle and check for degenerate situations en route. if (abs(a[0] - b[0]) == 1) and (abs(a[1] - b[1]) == 1): # A diagonal edge. target_cell = (a[0], b[1]) if grid[target_cell]: # That cell is already occupied. target_cell = (b[0], a[1]) if grid[target_cell]: # Degenerate situation, this edge is not # on the actual fringe. Correct the # fringe and go on. fringe.remove((a, b)) return True elif a[0] == b[0]: # A horizontal edge. We first attempt to build the # triangle in the downward direction. down_left = a[0] + 1, a[1] down_right = a[0] + 1, b[1] target_cell = DiagramGrid._choose_target_cell( down_left, down_right, (a, b), obj, skeleton, grid) if not target_cell: # No room below this edge. Check above. up_left = a[0] - 1, a[1] up_right = a[0] - 1, b[1] target_cell = DiagramGrid._choose_target_cell( up_left, up_right, (a, b), obj, skeleton, grid) if not target_cell: # This edge is not in the fringe, remove it # and restart. fringe.remove((a, b)) return True elif a[1] == b[1]: # A vertical edge. We will attempt to place the other # vertex of the triangle to the right of this edge. right_up = a[0], a[1] + 1 right_down = b[0], a[1] + 1 target_cell = DiagramGrid._choose_target_cell( right_up, right_down, (a, b), obj, skeleton, grid) if not target_cell: # No room to the left. See what's to the right. left_up = a[0], a[1] - 1 left_down = b[0], a[1] - 1 target_cell = DiagramGrid._choose_target_cell( left_up, left_down, (a, b), obj, skeleton, grid) if not target_cell: # This edge is not in the fringe, remove it # and restart. fringe.remove((a, b)) return True # We now know where to place the other vertex of the # triangle. offset = DiagramGrid._put_object(target_cell, obj, grid, fringe) # Take care of the displacement of coordinates if a row or # a column was prepended. target_cell = (target_cell[0] + offset[0], target_cell[1] + offset[1]) a = (a[0] + offset[0], a[1] + offset[1]) b = (b[0] + offset[0], b[1] + offset[1]) fringe.extend([(a, target_cell), (b, target_cell)]) # No restart is required. return False @staticmethod def _triangle_key(tri, triangle_sizes): """ Returns a key for the supplied triangle. It should be the same independently of the hash randomisation. """ objects = sorted( DiagramGrid._triangle_objects(tri), key=default_sort_key) return (triangle_sizes[tri], default_sort_key(objects)) @staticmethod def _pick_root_edge(tri, skeleton): """ For a given triangle always picks the same root edge. The root edge is the edge that will be placed first on the grid. """ candidates = [sorted(e, key=default_sort_key) for e in tri if skeleton[e]] sorted_candidates = sorted(candidates, key=default_sort_key) # Don't forget to assure the proper ordering of the vertices # in this edge. return tuple(sorted(sorted_candidates[0], key=default_sort_key)) @staticmethod def _drop_irrelevant_triangles(triangles, placed_objects): """ Returns only those triangles whose set of objects is not completely included in placed_objects. """ return [tri for tri in triangles if not placed_objects.issuperset( DiagramGrid._triangle_objects(tri))] @staticmethod def _grow_pseudopod(triangles, fringe, grid, skeleton, placed_objects): """ Starting from an object in the existing structure on the grid, adds an edge to which a triangle from triangles could be welded. If this method has found a way to do so, it returns the object it has just added. This method should be applied when _weld_triangle cannot find weldings any more. """ for i in range(grid.height): for j in range(grid.width): obj = grid[i, j] if not obj: continue # Here we need to choose a triangle which has only # obj in common with the existing structure. The # situations when this is not possible should be # handled elsewhere. def good_triangle(tri): objs = DiagramGrid._triangle_objects(tri) return obj in objs and \ placed_objects & (objs - {obj}) == set() tris = [tri for tri in triangles if good_triangle(tri)] if not tris: # This object is not interesting. continue # Pick the "simplest" of the triangles which could be # attached. Remember that the list of triangles is # sorted according to their "simplicity" (see # _compute_triangle_min_sizes for the metric). # # Note that tris are sequentially built from # triangles, so we don't have to worry about hash # randomisation. tri = tris[0] # We have found a triangle which could be attached to # the existing structure by a vertex. candidates = sorted([e for e in tri if skeleton[e]], key=lambda e: FiniteSet(*e).sort_key()) edges = [e for e in candidates if obj in e] # Note that a meaningful edge (i.e., and edge that is # associated with a morphism) containing obj # always exists. That's because all triangles are # guaranteed to have at least two meaningful edges. # See _drop_redundant_triangles. # Get the object at the other end of the edge. edge = edges[0] other_obj = tuple(edge - frozenset([obj]))[0] # Now check for free directions. When checking for # free directions, prefer the horizontal and vertical # directions. neighbours = [(i - 1, j), (i, j + 1), (i + 1, j), (i, j - 1), (i - 1, j - 1), (i - 1, j + 1), (i + 1, j - 1), (i + 1, j + 1)] for pt in neighbours: if DiagramGrid._empty_point(pt, grid): # We have a found a place to grow the # pseudopod into. offset = DiagramGrid._put_object( pt, other_obj, grid, fringe) i += offset[0] j += offset[1] pt = (pt[0] + offset[0], pt[1] + offset[1]) fringe.append(((i, j), pt)) return other_obj # This diagram is actually cooler that I can handle. Fail cowardly. return None @staticmethod def _handle_groups(diagram, groups, merged_morphisms, hints): """ Given the slightly preprocessed morphisms of the diagram, produces a grid laid out according to groups. If a group has hints, it is laid out with those hints only, without any influence from hints. Otherwise, it is laid out with hints. """ def lay_out_group(group, local_hints): """ If group is a set of objects, uses a DiagramGrid to lay it out and returns the grid. Otherwise returns the object (i.e., group). If local_hints is not empty, it is supplied to DiagramGrid as the dictionary of hints. Otherwise, the hints argument of _handle_groups is used. """ if isinstance(group, FiniteSet): # Set up the corresponding object-to-group # mappings. for obj in group: obj_groups[obj] = group # Lay out the current group. if local_hints: groups_grids[group] = DiagramGrid( diagram.subdiagram_from_objects(group), **local_hints) else: groups_grids[group] = DiagramGrid( diagram.subdiagram_from_objects(group), **hints) else: obj_groups[group] = group def group_to_finiteset(group): """ Converts group to a :class:FiniteSet if it is an iterable. """ if iterable(group): return FiniteSet(*group) else: return group obj_groups = {} groups_grids = {} # We would like to support various containers to represent # groups. To achieve that, before laying each group out, it # should be converted to a FiniteSet, because that is what the # following code expects. if isinstance(groups, dict) or isinstance(groups, Dict): finiteset_groups = {} for group, local_hints in groups.items(): finiteset_group = group_to_finiteset(group) finiteset_groups[finiteset_group] = local_hints lay_out_group(group, local_hints) groups = finiteset_groups else: finiteset_groups = [] for group in groups: finiteset_group = group_to_finiteset(group) finiteset_groups.append(finiteset_group) lay_out_group(finiteset_group, None) groups = finiteset_groups new_morphisms = [] for morphism in merged_morphisms: dom = obj_groups[morphism.domain] cod = obj_groups[morphism.codomain] # Note that we are not really interested in morphisms # which do not employ two different groups, because # these do not influence the layout. if dom != cod: # These are essentially unnamed morphisms; they are # not going to mess in the final layout. By giving # them the same names, we avoid unnecessary # duplicates. new_morphisms.append(NamedMorphism(dom, cod, "dummy")) # Lay out the new diagram. Since these are dummy morphisms, # properties and conclusions are irrelevant. top_grid = DiagramGrid(Diagram(new_morphisms)) # We now have to substitute the groups with the corresponding # grids, laid out at the beginning of this function. Compute # the size of each row and column in the grid, so that all # nested grids fit. def group_size(group): """ For the supplied group (or object, eventually), returns the size of the cell that will hold this group (object). """ if group in groups_grids: grid = groups_grids[group] return (grid.height, grid.width) else: return (1, 1) row_heights = [max(group_size(top_grid[i, j])[0] for j in range(top_grid.width)) for i in range(top_grid.height)] column_widths = [max(group_size(top_grid[i, j])[1] for i in range(top_grid.height)) for j in range(top_grid.width)] grid = _GrowableGrid(sum(column_widths), sum(row_heights)) real_row = 0 real_column = 0 for logical_row in range(top_grid.height): for logical_column in range(top_grid.width): obj = top_grid[logical_row, logical_column] if obj in groups_grids: # This is a group. Copy the corresponding grid in # place. local_grid = groups_grids[obj] for i in range(local_grid.height): for j in range(local_grid.width): grid[real_row + i, real_column + j] = local_grid[i, j] else: # This is an object. Just put it there. grid[real_row, real_column] = obj real_column += column_widths[logical_column] real_column = 0 real_row += row_heights[logical_row] return grid @staticmethod def _generic_layout(diagram, merged_morphisms): """ Produces the generic layout for the supplied diagram. """ all_objects = set(diagram.objects) if len(all_objects) == 1: # There only one object in the diagram, just put in on 1x1 # grid. grid = _GrowableGrid(1, 1) grid[0, 0] = tuple(all_objects)[0] return grid skeleton = DiagramGrid._build_skeleton(merged_morphisms) grid = _GrowableGrid(2, 1) if len(skeleton) == 1: # This diagram contains only one morphism. Draw it # horizontally. objects = sorted(all_objects, key=default_sort_key) grid[0, 0] = objects[0] grid[0, 1] = objects[1] return grid triangles = DiagramGrid._list_triangles(skeleton) triangles = DiagramGrid._drop_redundant_triangles(triangles, skeleton) triangle_sizes = DiagramGrid._compute_triangle_min_sizes( triangles, skeleton) triangles = sorted(triangles, key=lambda tri: DiagramGrid._triangle_key(tri, triangle_sizes)) # Place the first edge on the grid. root_edge = DiagramGrid._pick_root_edge(triangles[0], skeleton) grid[0, 0], grid[0, 1] = root_edge fringe = [((0, 0), (0, 1))] # Record which objects we now have on the grid. placed_objects = set(root_edge) while placed_objects != all_objects: welding = DiagramGrid._find_triangle_to_weld( triangles, fringe, grid) if welding: (triangle, welding_edge) = welding restart_required = DiagramGrid._weld_triangle( triangle, welding_edge, fringe, grid, skeleton) if restart_required: continue placed_objects.update( DiagramGrid._triangle_objects(triangle)) else: # No more weldings found. Try to attach triangles by # vertices. new_obj = DiagramGrid._grow_pseudopod( triangles, fringe, grid, skeleton, placed_objects) if not new_obj: # No more triangles can be attached, not even by # the edge. We will set up a new diagram out of # what has been left, laid it out independently, # and then attach it to this one. remaining_objects = all_objects - placed_objects remaining_diagram = diagram.subdiagram_from_objects( FiniteSet(*remaining_objects)) remaining_grid = DiagramGrid(remaining_diagram) # Now, let's glue remaining_grid to grid. final_width = grid.width + remaining_grid.width final_height = max(grid.height, remaining_grid.height) final_grid = _GrowableGrid(final_width, final_height) for i in range(grid.width): for j in range(grid.height): final_grid[i, j] = grid[i, j] start_j = grid.width for i in range(remaining_grid.height): for j in range(remaining_grid.width): final_grid[i, start_j + j] = remaining_grid[i, j] return final_grid placed_objects.add(new_obj) triangles = DiagramGrid._drop_irrelevant_triangles( triangles, placed_objects) return grid @staticmethod def _get_undirected_graph(objects, merged_morphisms): """ Given the objects and the relevant morphisms of a diagram, returns the adjacency lists of the underlying undirected graph. """ adjlists = {} for obj in objects: adjlists[obj] = [] for morphism in merged_morphisms: adjlists[morphism.domain].append(morphism.codomain) adjlists[morphism.codomain].append(morphism.domain) # Assure that the objects in the adjacency list are always in # the same order. for obj in adjlists.keys(): adjlists[obj].sort(key=default_sort_key) return adjlists @staticmethod def _sequential_layout(diagram, merged_morphisms): r""" Lays out the diagram in "sequential" layout. This method will attempt to produce a result as close to a line as possible. For linear diagrams, the result will actually be a line. """ objects = diagram.objects sorted_objects = sorted(objects, key=default_sort_key) # Set up the adjacency lists of the underlying undirected # graph of merged_morphisms. adjlists = DiagramGrid._get_undirected_graph(objects, merged_morphisms) # Find an object with the minimal degree. This is going to be # the root. root = sorted_objects[0] mindegree = len(adjlists[root]) for obj in sorted_objects: current_degree = len(adjlists[obj]) if current_degree < mindegree: root = obj mindegree = current_degree grid = _GrowableGrid(1, 1) grid[0, 0] = root placed_objects = {root} def place_objects(pt, placed_objects): """ Does depth-first search in the underlying graph of the diagram and places the objects en route. """ # We will start placing new objects from here. new_pt = (pt[0], pt[1] + 1) for adjacent_obj in adjlists[grid[pt]]: if adjacent_obj in placed_objects: # This object has already been placed. continue DiagramGrid._put_object(new_pt, adjacent_obj, grid, []) placed_objects.add(adjacent_obj) placed_objects.update(place_objects(new_pt, placed_objects)) new_pt = (new_pt[0] + 1, new_pt[1]) return placed_objects place_objects((0, 0), placed_objects) return grid @staticmethod def _drop_inessential_morphisms(merged_morphisms): r""" Removes those morphisms which should appear in the diagram, but which have no relevance to object layout. Currently this removes "loop" morphisms: the non-identity morphisms with the same domains and codomains. """ morphisms = [m for m in merged_morphisms if m.domain != m.codomain] return morphisms @staticmethod def _get_connected_components(objects, merged_morphisms): """ Given a container of morphisms, returns a list of connected components formed by these morphisms. A connected component is represented by a diagram consisting of the corresponding morphisms. """ component_index = {} for o in objects: component_index[o] = None # Get the underlying undirected graph of the diagram. adjlist = DiagramGrid._get_undirected_graph(objects, merged_morphisms) def traverse_component(object, current_index): """ Does a depth-first search traversal of the component containing object. """ component_index[object] = current_index for o in adjlist[object]: if component_index[o] is None: traverse_component(o, current_index) # Traverse all components. current_index = 0 for o in adjlist: if component_index[o] is None: traverse_component(o, current_index) current_index += 1 # List the objects of the components. component_objects = [[] for i in range(current_index)] for o, idx in component_index.items(): component_objects[idx].append(o) # Finally, list the morphisms belonging to each component. # # Note: If some objects are isolated, they will not get any # morphisms at this stage, and since the layout algorithm # relies, we are essentially going to lose this object. # Therefore, check if there are isolated objects and, for each # of them, provide the trivial identity morphism. It will get # discarded later, but the object will be there. component_morphisms = [] for component in component_objects: current_morphisms = {} for m in merged_morphisms: if (m.domain in component) and (m.codomain in component): current_morphisms[m] = merged_morphisms[m] if len(component) == 1: # Let's add an identity morphism, for the sake of # surely having morphisms in this component. current_morphisms[IdentityMorphism(component[0])] = FiniteSet() component_morphisms.append(Diagram(current_morphisms)) return component_morphisms def __init__(self, diagram, groups=None, **hints): premises = DiagramGrid._simplify_morphisms(diagram.premises) conclusions = DiagramGrid._simplify_morphisms(diagram.conclusions) all_merged_morphisms = DiagramGrid._merge_premises_conclusions( premises, conclusions) merged_morphisms = DiagramGrid._drop_inessential_morphisms( all_merged_morphisms) # Store the merged morphisms for later use. self._morphisms = all_merged_morphisms components = DiagramGrid._get_connected_components( diagram.objects, all_merged_morphisms) if groups and (groups != diagram.objects): # Lay out the diagram according to the groups. self._grid = DiagramGrid._handle_groups( diagram, groups, merged_morphisms, hints) elif len(components) > 1: # Note that we check for connectedness _before_ checking # the layout hints because the layout strategies don't # know how to deal with disconnected diagrams. # The diagram is disconnected. Lay out the components # independently. grids = [] # Sort the components to eventually get the grids arranged # in a fixed, hash-independent order. components = sorted(components, key=default_sort_key) for component in components: grid = DiagramGrid(component, **hints) grids.append(grid) # Throw the grids together, in a line. total_width = sum(g.width for g in grids) total_height = max(g.height for g in grids) grid = _GrowableGrid(total_width, total_height) start_j = 0 for g in grids: for i in range(g.height): for j in range(g.width): grid[i, start_j + j] = g[i, j] start_j += g.width self._grid = grid elif "layout" in hints: if hints["layout"] == "sequential": self._grid = DiagramGrid._sequential_layout( diagram, merged_morphisms) else: self._grid = DiagramGrid._generic_layout(diagram, merged_morphisms) if hints.get("transpose"): # Transpose the resulting grid. grid = _GrowableGrid(self._grid.height, self._grid.width) for i in range(self._grid.height): for j in range(self._grid.width): grid[j, i] = self._grid[i, j] self._grid = grid @property def width(self): """ Returns the number of columns in this diagram layout. Examples ======== >>> from sympy.categories import Object, NamedMorphism >>> from sympy.categories import Diagram, DiagramGrid >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g]) >>> grid = DiagramGrid(diagram) >>> grid.width 2 """ return self._grid.width @property def height(self): """ Returns the number of rows in this diagram layout. Examples ======== >>> from sympy.categories import Object, NamedMorphism >>> from sympy.categories import Diagram, DiagramGrid >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g]) >>> grid = DiagramGrid(diagram) >>> grid.height 2 """ return self._grid.height def __getitem__(self, i_j): """ Returns the object placed in the row i and column j. The indices are 0-based. Examples ======== >>> from sympy.categories import Object, NamedMorphism >>> from sympy.categories import Diagram, DiagramGrid >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g]) >>> grid = DiagramGrid(diagram) >>> (grid[0, 0], grid[0, 1]) (Object("A"), Object("B")) >>> (grid[1, 0], grid[1, 1]) (None, Object("C")) """ i, j = i_j return self._grid[i, j] @property def morphisms(self): """ Returns those morphisms (and their properties) which are sufficiently meaningful to be drawn. Examples ======== >>> from sympy.categories import Object, NamedMorphism >>> from sympy.categories import Diagram, DiagramGrid >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g]) >>> grid = DiagramGrid(diagram) >>> grid.morphisms {NamedMorphism(Object("A"), Object("B"), "f"): EmptySet(), NamedMorphism(Object("B"), Object("C"), "g"): EmptySet()} """ return self._morphisms def __str__(self): """ Produces a string representation of this class. This method returns a string representation of the underlying list of lists of objects. Examples ======== >>> from sympy.categories import Object, NamedMorphism >>> from sympy.categories import Diagram, DiagramGrid >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g]) >>> grid = DiagramGrid(diagram) >>> print(grid) [[Object("A"), Object("B")], [None, Object("C")]] """ return repr(self._grid._array)
[docs]class ArrowStringDescription(object): r""" Stores the information necessary for producing an Xy-pic description of an arrow. The principal goal of this class is to abstract away the string representation of an arrow and to also provide the functionality to produce the actual Xy-pic string. unit sets the unit which will be used to specify the amount of curving and other distances. horizontal_direction should be a string of "r" or "l" specifying the horizontal offset of the target cell of the arrow relatively to the current one. vertical_direction should specify the vertical offset using a series of either "d" or "u". label_position should be either "^", "_", or "|" to specify that the label should be positioned above the arrow, below the arrow or just over the arrow, in a break. Note that the notions "above" and "below" are relative to arrow direction. label stores the morphism label. This works as follows (disregard the yet unexplained arguments): >>> from sympy.categories.diagram_drawing import ArrowStringDescription >>> astr = ArrowStringDescription( ... unit="mm", curving=None, curving_amount=None, ... looping_start=None, looping_end=None, horizontal_direction="d", ... vertical_direction="r", label_position="_", label="f") >>> print(str(astr)) \ar[dr]_{f} curving should be one of "^", "_" to specify in which direction the arrow is going to curve. curving_amount is a number describing how many unit's the morphism is going to curve: >>> astr = ArrowStringDescription( ... unit="mm", curving="^", curving_amount=12, ... looping_start=None, looping_end=None, horizontal_direction="d", ... vertical_direction="r", label_position="_", label="f") >>> print(str(astr)) \ar@/^12mm/[dr]_{f} looping_start and looping_end are currently only used for loop morphisms, those which have the same domain and codomain. These two attributes should store a valid Xy-pic direction and specify, correspondingly, the direction the arrow gets out into and the direction the arrow gets back from: >>> astr = ArrowStringDescription( ... unit="mm", curving=None, curving_amount=None, ... looping_start="u", looping_end="l", horizontal_direction="", ... vertical_direction="", label_position="_", label="f") >>> print(str(astr)) \ar@(u,l)[]_{f} label_displacement controls how far the arrow label is from the ends of the arrow. For example, to position the arrow label near the arrow head, use ">": >>> astr = ArrowStringDescription( ... unit="mm", curving="^", curving_amount=12, ... looping_start=None, looping_end=None, horizontal_direction="d", ... vertical_direction="r", label_position="_", label="f") >>> astr.label_displacement = ">" >>> print(str(astr)) \ar@/^12mm/[dr]_>{f} Finally, arrow_style is used to specify the arrow style. To get a dashed arrow, for example, use "{-->}" as arrow style: >>> astr = ArrowStringDescription( ... unit="mm", curving="^", curving_amount=12, ... looping_start=None, looping_end=None, horizontal_direction="d", ... vertical_direction="r", label_position="_", label="f") >>> astr.arrow_style = "{-->}" >>> print(str(astr)) \ar@/^12mm/@{-->}[dr]_{f} Notes ===== Instances of :class:ArrowStringDescription will be constructed by :class:XypicDiagramDrawer and provided for further use in formatters. The user is not expected to construct instances of :class:ArrowStringDescription themselves. To be able to properly utilise this class, the reader is encouraged to checkout the Xy-pic user guide, available at [Xypic]. See Also ======== XypicDiagramDrawer References ========== [Xypic] http://xy-pic.sourceforge.net/ """ def __init__(self, unit, curving, curving_amount, looping_start, looping_end, horizontal_direction, vertical_direction, label_position, label): self.unit = unit self.curving = curving self.curving_amount = curving_amount self.looping_start = looping_start self.looping_end = looping_end self.horizontal_direction = horizontal_direction self.vertical_direction = vertical_direction self.label_position = label_position self.label = label self.label_displacement = "" self.arrow_style = "" # This flag shows that the position of the label of this # morphism was set while typesetting a curved morphism and # should not be modified later. self.forced_label_position = False def __str__(self): if self.curving: curving_str = "@/%s%d%s/" % (self.curving, self.curving_amount, self.unit) else: curving_str = "" if self.looping_start and self.looping_end: looping_str = "@(%s,%s)" % (self.looping_start, self.looping_end) else: looping_str = "" if self.arrow_style: style_str = "@" + self.arrow_style else: style_str = "" return "\\ar%s%s%s[%s%s]%s%s{%s}" % \ (curving_str, looping_str, style_str, self.horizontal_direction, self.vertical_direction, self.label_position, self.label_displacement, self.label)
[docs]class XypicDiagramDrawer(object): r""" Given a :class:Diagram and the corresponding :class:DiagramGrid, produces the Xy-pic representation of the diagram. The most important method in this class is draw. Consider the following triangle diagram: >>> from sympy.categories import Object, NamedMorphism, Diagram >>> from sympy.categories import DiagramGrid, XypicDiagramDrawer >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g], {g * f: "unique"}) To draw this diagram, its objects need to be laid out with a :class:DiagramGrid:: >>> grid = DiagramGrid(diagram) Finally, the drawing: >>> drawer = XypicDiagramDrawer() >>> print(drawer.draw(diagram, grid)) \xymatrix{ A \ar[d]_{g\circ f} \ar[r]^{f} & B \ar[ld]^{g} \\ C & } For further details see the docstring of this method. To control the appearance of the arrows, formatters are used. The dictionary arrow_formatters maps morphisms to formatter functions. A formatter is accepts an :class:ArrowStringDescription and is allowed to modify any of the arrow properties exposed thereby. For example, to have all morphisms with the property unique appear as dashed arrows, and to have their names prepended with \exists !, the following should be done: >>> def formatter(astr): ... astr.label = "\exists !" + astr.label ... astr.arrow_style = "{-->}" >>> drawer.arrow_formatters["unique"] = formatter >>> print(drawer.draw(diagram, grid)) \xymatrix{ A \ar@{-->}[d]_{\exists !g\circ f} \ar[r]^{f} & B \ar[ld]^{g} \\ C & } To modify the appearance of all arrows in the diagram, set default_arrow_formatter. For example, to place all morphism labels a little bit farther from the arrow head so that they look more centred, do as follows: >>> def default_formatter(astr): ... astr.label_displacement = "(0.45)" >>> drawer.default_arrow_formatter = default_formatter >>> print(drawer.draw(diagram, grid)) \xymatrix{ A \ar@{-->}[d]_(0.45){\exists !g\circ f} \ar[r]^(0.45){f} & B \ar[ld]^(0.45){g} \\ C & } In some diagrams some morphisms are drawn as curved arrows. Consider the following diagram: >>> D = Object("D") >>> E = Object("E") >>> h = NamedMorphism(D, A, "h") >>> k = NamedMorphism(D, B, "k") >>> diagram = Diagram([f, g, h, k]) >>> grid = DiagramGrid(diagram) >>> drawer = XypicDiagramDrawer() >>> print(drawer.draw(diagram, grid)) \xymatrix{ A \ar[r]_{f} & B \ar[d]^{g} & D \ar[l]^{k} \ar@/_3mm/[ll]_{h} \\ & C & } To control how far the morphisms are curved by default, one can use the unit and default_curving_amount attributes: >>> drawer.unit = "cm" >>> drawer.default_curving_amount = 1 >>> print(drawer.draw(diagram, grid)) \xymatrix{ A \ar[r]_{f} & B \ar[d]^{g} & D \ar[l]^{k} \ar@/_1cm/[ll]_{h} \\ & C & } In some diagrams, there are multiple curved morphisms between the same two objects. To control by how much the curving changes between two such successive morphisms, use default_curving_step: >>> drawer.default_curving_step = 1 >>> h1 = NamedMorphism(A, D, "h1") >>> diagram = Diagram([f, g, h, k, h1]) >>> grid = DiagramGrid(diagram) >>> print(drawer.draw(diagram, grid)) \xymatrix{ A \ar[r]_{f} \ar@/^1cm/[rr]^{h_{1}} & B \ar[d]^{g} & D \ar[l]^{k} \ar@/_2cm/[ll]_{h} \\ & C & } The default value of default_curving_step is 4 units. See Also ======== draw, ArrowStringDescription """ def __init__(self): self.unit = "mm" self.default_curving_amount = 3 self.default_curving_step = 4 # This dictionary maps properties to the corresponding arrow # formatters. self.arrow_formatters = {} # This is the default arrow formatter which will be applied to # each arrow independently of its properties. self.default_arrow_formatter = None @staticmethod def _process_loop_morphism(i, j, grid, morphisms_str_info, object_coords): """ Produces the information required for constructing the string representation of a loop morphism. This function is invoked from _process_morphism. See Also ======== _process_morphism """ curving = "" label_pos = "^" looping_start = "" looping_end = "" # This is a loop morphism. Count how many morphisms stick # in each of the four quadrants. Note that straight # vertical and horizontal morphisms count in two quadrants # at the same time (i.e., a morphism going up counts both # in the first and the second quadrants). # The usual numbering (counterclockwise) of quadrants # applies. quadrant = [0, 0, 0, 0] obj = grid[i, j] for m, m_str_info in morphisms_str_info.items(): if (m.domain == obj) and (m.codomain == obj): # That's another loop morphism. Check how it # loops and mark the corresponding quadrants as # busy. (l_s, l_e) = (m_str_info.looping_start, m_str_info.looping_end) if (l_s, l_e) == ("r", "u"): quadrant[0] += 1 elif (l_s, l_e) == ("u", "l"): quadrant[1] += 1 elif (l_s, l_e) == ("l", "d"): quadrant[2] += 1 elif (l_s, l_e) == ("d", "r"): quadrant[3] += 1 continue if m.domain == obj: (end_i, end_j) = object_coords[m.codomain] goes_out = True elif m.codomain == obj: (end_i, end_j) = object_coords[m.domain] goes_out = False else: continue d_i = end_i - i d_j = end_j - j m_curving = m_str_info.curving if (d_i != 0) and (d_j != 0): # This is really a diagonal morphism. Detect the # quadrant. if (d_i > 0) and (d_j > 0): quadrant[0] += 1 elif (d_i > 0) and (d_j < 0): quadrant[1] += 1 elif (d_i < 0) and (d_j < 0): quadrant[2] += 1 elif (d_i < 0) and (d_j > 0): quadrant[3] += 1 elif d_i == 0: # Knowing where the other end of the morphism is # and which way it goes, we now have to decide # which quadrant is now the upper one and which is # the lower one. if d_j > 0: if goes_out: upper_quadrant = 0 lower_quadrant = 3 else: upper_quadrant = 3 lower_quadrant = 0 else: if goes_out: upper_quadrant = 2 lower_quadrant = 1 else: upper_quadrant = 1 lower_quadrant = 2 if m_curving: if m_curving == "^": quadrant[upper_quadrant] += 1 elif m_curving == "_": quadrant[lower_quadrant] += 1 else: # This morphism counts in both upper and lower # quadrants. quadrant[upper_quadrant] += 1 quadrant[lower_quadrant] += 1 elif d_j == 0: # Knowing where the other end of the morphism is # and which way it goes, we now have to decide # which quadrant is now the left one and which is # the right one. if d_i < 0: if goes_out: left_quadrant = 1 right_quadrant = 0 else: left_quadrant = 0 right_quadrant = 1 else: if goes_out: left_quadrant = 3 right_quadrant = 2 else: left_quadrant = 2 right_quadrant = 3 if m_curving: if m_curving == "^": quadrant[left_quadrant] += 1 elif m_curving == "_": quadrant[right_quadrant] += 1 else: # This morphism counts in both upper and lower # quadrants. quadrant[left_quadrant] += 1 quadrant[right_quadrant] += 1 # Pick the freest quadrant to curve our morphism into. freest_quadrant = 0 for i in range(4): if quadrant[i] < quadrant[freest_quadrant]: freest_quadrant = i # Now set up proper looping. (looping_start, looping_end) = [("r", "u"), ("u", "l"), ("l", "d"), ("d", "r")][freest_quadrant] return (curving, label_pos, looping_start, looping_end) @staticmethod def _process_horizontal_morphism(i, j, target_j, grid, morphisms_str_info, object_coords): """ Produces the information required for constructing the string representation of a horizontal morphism. This function is invoked from _process_morphism. See Also ======== _process_morphism """ # The arrow is horizontal. Check if it goes from left to # right (backwards == False) or from right to left # (backwards == True). backwards = False start = j end = target_j if end < start: (start, end) = (end, start) backwards = True # Let's see which objects are there between start and # end, and then count how many morphisms stick out # upwards, and how many stick out downwards. # # For example, consider the situation: # # B1 C1 # | | # A--B--C--D # | # B2 # # Between the objects A and D there are two objects: # B and C. Further, there are two morphisms which # stick out upward (the ones between B1 and B and # between C and C1) and one morphism which sticks out # downward (the one between B and B2). # # We need this information to decide how to curve the # arrow between A and D. First of all, since there # are two objects between A and D, we must curve the # arrow. Then, we will have it curve downward, because # there is more space (less morphisms stick out downward # than upward). up = [] down = [] straight_horizontal = [] for k in range(start + 1, end): obj = grid[i, k] if not obj: continue for m in morphisms_str_info: if m.domain == obj: (end_i, end_j) = object_coords[m.codomain] elif m.codomain == obj: (end_i, end_j) = object_coords[m.domain] else: continue if end_i > i: down.append(m) elif end_i < i: up.append(m) elif not morphisms_str_info[m].curving: # This is a straight horizontal morphism, # because it has no curving. straight_horizontal.append(m) if len(up) < len(down): # More morphisms stick out downward than upward, let's # curve the morphism up. if backwards: curving = "_" label_pos = "_" else: curving = "^" label_pos = "^" # Assure that the straight horizontal morphisms have # their labels on the lower side of the arrow. for m in straight_horizontal: (i1, j1) = object_coords[m.domain] (i2, j2) = object_coords[m.codomain] m_str_info = morphisms_str_info[m] if j1 < j2: m_str_info.label_position = "_" else: m_str_info.label_position = "^" # Don't allow any further modifications of the # position of this label. m_str_info.forced_label_position = True else: # More morphisms stick out downward than upward, let's # curve the morphism up. if backwards: curving = "^" label_pos = "^" else: curving = "_" label_pos = "_" # Assure that the straight horizontal morphisms have # their labels on the upper side of the arrow. for m in straight_horizontal: (i1, j1) = object_coords[m.domain] (i2, j2) = object_coords[m.codomain] m_str_info = morphisms_str_info[m] if j1 < j2: m_str_info.label_position = "^" else: m_str_info.label_position = "_" # Don't allow any further modifications of the # position of this label. m_str_info.forced_label_position = True return (curving, label_pos) @staticmethod def _process_vertical_morphism(i, j, target_i, grid, morphisms_str_info, object_coords): """ Produces the information required for constructing the string representation of a vertical morphism. This function is invoked from _process_morphism. See Also ======== _process_morphism """ # This arrow is vertical. Check if it goes from top to # bottom (backwards == False) or from bottom to top # (backwards == True). backwards = False start = i end = target_i if end < start: (start, end) = (end, start) backwards = True # Let's see which objects are there between start and # end, and then count how many morphisms stick out to # the left, and how many stick out to the right. # # See the corresponding comment in the previous branch of # this if-statement for more details. left = [] right = [] straight_vertical = [] for k in range(start + 1, end): obj = grid[k, j] if not obj: continue for m in morphisms_str_info: if m.domain == obj: (end_i, end_j) = object_coords[m.codomain] elif m.codomain == obj: (end_i, end_j) = object_coords[m.domain] else: continue if end_j > j: right.append(m) elif end_j < j: left.append(m) elif not morphisms_str_info[m].curving: # This is a straight vertical morphism, # because it has no curving. straight_vertical.append(m) if len(left) < len(right): # More morphisms stick out to the left than to the # right, let's curve the morphism to the right. if backwards: curving = "^" label_pos = "^" else: curving = "_" label_pos = "_" # Assure that the straight vertical morphisms have # their labels on the left side of the arrow. for m in straight_vertical: (i1, j1) = object_coords[m.domain] (i2, j2) = object_coords[m.codomain] m_str_info = morphisms_str_info[m] if i1 < i2: m_str_info.label_position = "^" else: m_str_info.label_position = "_" # Don't allow any further modifications of the # position of this label. m_str_info.forced_label_position = True else: # More morphisms stick out to the right than to the # left, let's curve the morphism to the left. if backwards: curving = "_" label_pos = "_" else: curving = "^" label_pos = "^" # Assure that the straight vertical morphisms have # their labels on the right side of the arrow. for m in straight_vertical: (i1, j1) = object_coords[m.domain] (i2, j2) = object_coords[m.codomain] m_str_info = morphisms_str_info[m] if i1 < i2: m_str_info.label_position = "_" else: m_str_info.label_position = "^" # Don't allow any further modifications of the # position of this label. m_str_info.forced_label_position = True return (curving, label_pos) def _process_morphism(self, diagram, grid, morphism, object_coords, morphisms, morphisms_str_info): """ Given the required information, produces the string representation of morphism. """ def repeat_string_cond(times, str_gt, str_lt): """ If times > 0, repeats str_gt times times. Otherwise, repeats str_lt -times times. """ if times > 0: return str_gt * times else: return str_lt * (-times) def count_morphisms_undirected(A, B): """ Counts how many processed morphisms there are between the two supplied objects. """ return len([m for m in morphisms_str_info if set([m.domain, m.codomain]) == set([A, B])]) def count_morphisms_filtered(dom, cod, curving): """ Counts the processed morphisms which go out of dom into cod with curving curving. """ return len([m for m, m_str_info in morphisms_str_info.items() if (m.domain, m.codomain) == (dom, cod) and (m_str_info.curving == curving)]) (i, j) = object_coords[morphism.domain] (target_i, target_j) = object_coords[morphism.codomain] # We now need to determine the direction of # the arrow. delta_i = target_i - i delta_j = target_j - j vertical_direction = repeat_string_cond(delta_i, "d", "u") horizontal_direction = repeat_string_cond(delta_j, "r", "l") curving = "" label_pos = "^" looping_start = "" looping_end = "" if (delta_i == 0) and (delta_j == 0): # This is a loop morphism. (curving, label_pos, looping_start, looping_end) = XypicDiagramDrawer._process_loop_morphism( i, j, grid, morphisms_str_info, object_coords) elif (delta_i == 0) and (abs(j - target_j) > 1): # This is a horizontal morphism. (curving, label_pos) = XypicDiagramDrawer._process_horizontal_morphism( i, j, target_j, grid, morphisms_str_info, object_coords) elif (delta_j == 0) and (abs(i - target_i) > 1): # This is a vertical morphism. (curving, label_pos) = XypicDiagramDrawer._process_vertical_morphism( i, j, target_i, grid, morphisms_str_info, object_coords) count = count_morphisms_undirected(morphism.domain, morphism.codomain) curving_amount = "" if curving: # This morphisms should be curved anyway. curving_amount = self.default_curving_amount + count * \ self.default_curving_step elif count: # There are no objects between the domain and codomain of # the current morphism, but this is not there already are # some morphisms with the same domain and codomain, so we # have to curve this one. curving = "^" filtered_morphisms = count_morphisms_filtered( morphism.domain, morphism.codomain, curving) curving_amount = self.default_curving_amount + \ filtered_morphisms * \ self.default_curving_step # Let's now get the name of the morphism. morphism_name = "" if isinstance(morphism, IdentityMorphism): morphism_name = "id_{%s}" + latex(obj) elif isinstance(morphism, CompositeMorphism): component_names = [latex(Symbol(component.name)) for component in morphism.components] component_names.reverse() morphism_name = "\\circ ".join(component_names) elif isinstance(morphism, NamedMorphism): morphism_name = latex(Symbol(morphism.name)) return ArrowStringDescription( self.unit, curving, curving_amount, looping_start, looping_end, horizontal_direction, vertical_direction, label_pos, morphism_name) @staticmethod def _check_free_space_horizontal(dom_i, dom_j, cod_j, grid): """ For a horizontal morphism, checks whether there is free space (i.e., space not occupied by any objects) above the morphism or below it. """ if dom_j < cod_j: (start, end) = (dom_j, cod_j) backwards = False else: (start, end) = (cod_j, dom_j) backwards = True # Check for free space above. if dom_i == 0: free_up = True else: free_up = all([grid[dom_i - 1, j] for j in range(start, end + 1)]) # Check for free space below. if dom_i == grid.height - 1: free_down = True else: free_down = all([not grid[dom_i + 1, j] for j in range(start, end + 1)]) return (free_up, free_down, backwards) @staticmethod def _check_free_space_vertical(dom_i, cod_i, dom_j, grid): """ For a vertical morphism, checks whether there is free space (i.e., space not occupied by any objects) to the left of the morphism or to the right of it. """ if dom_i < cod_i: (start, end) = (dom_i, cod_i) backwards = False else: (start, end) = (cod_i, dom_i) backwards = True # Check if there's space to the left. if dom_j == 0: free_left = True else: free_left = all([not grid[i, dom_j - 1] for i in range(start, end + 1)]) if dom_j == grid.width - 1: free_right = True else: free_right = all([not grid[i, dom_j + 1] for i in range(start, end + 1)]) return (free_left, free_right, backwards) @staticmethod def _check_free_space_diagonal(dom_i, cod_i, dom_j, cod_j, grid): """ For a diagonal morphism, checks whether there is free space (i.e., space not occupied by any objects) above the morphism or below it. """ def abs_xrange(start, end): if start < end: return range(start, end + 1) else: return range(end, start + 1) if dom_i < cod_i and dom_j < cod_j: # This morphism goes from top-left to # bottom-right. (start_i, start_j) = (dom_i, dom_j) (end_i, end_j) = (cod_i, cod_j) backwards = False elif dom_i > cod_i and dom_j > cod_j: # This morphism goes from bottom-right to # top-left. (start_i, start_j) = (cod_i, cod_j) (end_i, end_j) = (dom_i, dom_j) backwards = True if dom_i < cod_i and dom_j > cod_j: # This morphism goes from top-right to # bottom-left. (start_i, start_j) = (dom_i, dom_j) (end_i, end_j) = (cod_i, cod_j) backwards = True elif dom_i > cod_i and dom_j < cod_j: # This morphism goes from bottom-left to # top-right. (start_i, start_j) = (cod_i, cod_j) (end_i, end_j) = (dom_i, dom_j) backwards = False # This is an attempt at a fast and furious strategy to # decide where there is free space on the two sides of # a diagonal morphism. For a diagonal morphism # starting at (start_i, start_j) and ending at # (end_i, end_j) the rectangle defined by these # two points is considered. The slope of the diagonal # alpha is then computed. Then, for every cell # (i, j) within the rectangle, the slope # alpha1 of the line through (start_i, # start_j) and (i, j) is considered. If # alpha1 is between 0 and alpha, the point # (i, j) is above the diagonal, if alpha1 is # between alpha and infinity, the point is below # the diagonal. Also note that, with some beforehand # precautions, this trick works for both the main and # the secondary diagonals of the rectangle. # I have considered the possibility to only follow the # shorter diagonals immediately above and below the # main (or secondary) diagonal. This, however, # wouldn't have resulted in much performance gain or # better detection of outer edges, because of # relatively small sizes of diagram grids, while the # code would have become harder to understand. alpha = float(end_i - start_i)/(end_j - start_j) free_up = True free_down = True for i in abs_xrange(start_i, end_i): if not free_up and not free_down: break for j in abs_xrange(start_j, end_j): if not free_up and not free_down: break if (i, j) == (start_i, start_j): continue if j == start_j: alpha1 = "inf" else: alpha1 = float(i - start_i)/(j - start_j) if grid[i, j]: if (alpha1 == "inf") or (abs(alpha1) > abs(alpha)): free_down = False elif abs(alpha1) < abs(alpha): free_up = False return (free_up, free_down, backwards) def _push_labels_out(self, morphisms_str_info, grid, object_coords): """ For all straight morphisms which form the visual boundary of the laid out diagram, puts their labels on their outer sides. """ def set_label_position(free1, free2, pos1, pos2, backwards, m_str_info): """ Given the information about room available to one side and to the other side of a morphism (free1 and free2), sets the position of the morphism label in such a way that it is on the freer side. This latter operations involves choice between pos1 and pos2, taking backwards in consideration. Thus this function will do nothing if either both free1 == True and free2 == True or both free1 == False and free2 == False. In either case, choosing one side over the other presents no advantage. """ if backwards: (pos1, pos2) = (pos2, pos1) if free1 and not free2: m_str_info.label_position = pos1 elif free2 and not free1: m_str_info.label_position = pos2 for m, m_str_info in morphisms_str_info.items(): if m_str_info.curving or m_str_info.forced_label_position: # This is either a curved morphism, and curved # morphisms have other magic, or the position of this # label has already been fixed. continue if m.domain == m.codomain: # This is a loop morphism, their labels, again have a # different magic. continue (dom_i, dom_j) = object_coords[m.domain] (cod_i, cod_j) = object_coords[m.codomain] if dom_i == cod_i: # Horizontal morphism. (free_up, free_down, backwards) = XypicDiagramDrawer._check_free_space_horizontal( dom_i, dom_j, cod_j, grid) set_label_position(free_up, free_down, "^", "_", backwards, m_str_info) elif dom_j == cod_j: # Vertical morphism. (free_left, free_right, backwards) = XypicDiagramDrawer._check_free_space_vertical( dom_i, cod_i, dom_j, grid) set_label_position(free_left, free_right, "_", "^", backwards, m_str_info) else: # A diagonal morphism. (free_up, free_down, backwards) = XypicDiagramDrawer._check_free_space_diagonal( dom_i, cod_i, dom_j, cod_j, grid) set_label_position(free_up, free_down, "^", "_", backwards, m_str_info) @staticmethod def _morphism_sort_key(morphism, object_coords): """ Provides a morphism sorting key such that horizontal or vertical morphisms between neighbouring objects come first, then horizontal or vertical morphisms between more far away objects, and finally, all other morphisms. """ (i, j) = object_coords[morphism.domain] (target_i, target_j) = object_coords[morphism.codomain] if morphism.domain == morphism.codomain: # Loop morphisms should get after diagonal morphisms # so that the proper direction in which to curve the # loop can be determined. return (3, 0, default_sort_key(morphism)) if target_i == i: return (1, abs(target_j - j), default_sort_key(morphism)) if target_j == j: return (1, abs(target_i - i), default_sort_key(morphism)) # Diagonal morphism. return (2, 0, default_sort_key(morphism)) @staticmethod def _build_xypic_string(diagram, grid, morphisms, morphisms_str_info, diagram_format): """ Given a collection of :class:ArrowStringDescription describing the morphisms of a diagram and the object layout information of a diagram, produces the final Xy-pic picture. """ # Build the mapping between objects and morphisms which have # them as domains. object_morphisms = {} for obj in diagram.objects: object_morphisms[obj] = [] for morphism in morphisms: object_morphisms[morphism.domain].append(morphism) result = "\\xymatrix%s{\n" % diagram_format for i in range(grid.height): for j in range(grid.width): obj = grid[i, j] if obj: result += latex(obj) + " " morphisms_to_draw = object_morphisms[obj] for morphism in morphisms_to_draw: result += str(morphisms_str_info[morphism]) + " " # Don't put the & after the last column. if j < grid.width - 1: result += "& " # Don't put the line break after the last row. if i < grid.height - 1: result += "\\\\" result += "\n" result += "}\n" return result
[docs] def draw(self, diagram, grid, masked=None, diagram_format=""): r""" Returns the Xy-pic representation of diagram laid out in grid. Consider the following simple triangle diagram. >>> from sympy.categories import Object, NamedMorphism, Diagram >>> from sympy.categories import DiagramGrid, XypicDiagramDrawer >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g], {g * f: "unique"}) To draw this diagram, its objects need to be laid out with a :class:DiagramGrid:: >>> grid = DiagramGrid(diagram) Finally, the drawing: >>> drawer = XypicDiagramDrawer() >>> print(drawer.draw(diagram, grid)) \xymatrix{ A \ar[d]_{g\circ f} \ar[r]^{f} & B \ar[ld]^{g} \\ C & } The argument masked can be used to skip morphisms in the presentation of the diagram: >>> print(drawer.draw(diagram, grid, masked=[g * f])) \xymatrix{ A \ar[r]^{f} & B \ar[ld]^{g} \\ C & } Finally, the diagram_format argument can be used to specify the format string of the diagram. For example, to increase the spacing by 1 cm, proceeding as follows: >>> print(drawer.draw(diagram, grid, diagram_format="@+1cm")) \xymatrix@+1cm{ A \ar[d]_{g\circ f} \ar[r]^{f} & B \ar[ld]^{g} \\ C & } """ # This method works in several steps. It starts by removing # the masked morphisms, if necessary, and then maps objects to # their positions in the grid (coordinate tuples). Remember # that objects are unique in Diagram and in the layout # produced by DiagramGrid, so every object is mapped to a # single coordinate pair. # # The next step is the central step and is concerned with # analysing the morphisms of the diagram and deciding how to # draw them. For example, how to curve the arrows is decided # at this step. The bulk of the analysis is implemented in # _process_morphism, to the result of which the # appropriate formatters are applied. # # The result of the previous step is a list of # ArrowStringDescription. After the analysis and # application of formatters, some extra logic tries to assure # better positioning of morphism labels (for example, an # attempt is made to avoid the situations when arrows cross # labels). This functionality constitutes the next step and # is implemented in _push_labels_out. Note that label # positions which have been set via a formatter are not # affected in this step. # # Finally, at the closing step, the array of # ArrowStringDescription and the layout information # incorporated in DiagramGrid are combined to produce the # resulting Xy-pic picture. This part of code lies in # _build_xypic_string. if not masked: morphisms_props = grid.morphisms else: morphisms_props = {} for m, props in grid.morphisms.items(): if m in masked: continue morphisms_props[m] = props # Build the mapping between objects and their position in the # grid. object_coords = {} for i in range(grid.height): for j in range(grid.width): if grid[i, j]: object_coords[grid[i, j]] = (i, j) morphisms = sorted(morphisms_props, key=lambda m: XypicDiagramDrawer._morphism_sort_key( m, object_coords)) # Build the tuples defining the string representations of # morphisms. morphisms_str_info = {} for morphism in morphisms: string_description = self._process_morphism( diagram, grid, morphism, object_coords, morphisms, morphisms_str_info) if self.default_arrow_formatter: self.default_arrow_formatter(string_description) for prop in morphisms_props[morphism]: # prop is a Symbol. TODO: Find out why. if prop.name in self.arrow_formatters: formatter = self.arrow_formatters[prop.name] formatter(string_description) morphisms_str_info[morphism] = string_description # Reposition the labels a bit. self._push_labels_out(morphisms_str_info, grid, object_coords) return XypicDiagramDrawer._build_xypic_string( diagram, grid, morphisms, morphisms_str_info, diagram_format)
[docs]def xypic_draw_diagram(diagram, masked=None, diagram_format="", groups=None, **hints): r""" Provides a shortcut combining :class:DiagramGrid and :class:XypicDiagramDrawer. Returns an Xy-pic presentation of diagram. The argument masked is a list of morphisms which will be not be drawn. The argument diagram_format is the format string inserted after "\xymatrix". groups should be a set of logical groups. The hints will be passed directly to the constructor of :class:DiagramGrid. For more information about the arguments, see the docstrings of :class:DiagramGrid and XypicDiagramDrawer.draw. Examples ======== >>> from sympy.categories import Object, NamedMorphism, Diagram >>> from sympy.categories import xypic_draw_diagram >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> diagram = Diagram([f, g], {g * f: "unique"}) >>> print(xypic_draw_diagram(diagram)) \xymatrix{ A \ar[d]_{g\circ f} \ar[r]^{f} & B \ar[ld]^{g} \\ C & } See Also ======== XypicDiagramDrawer, DiagramGrid """ grid = DiagramGrid(diagram, groups, **hints) drawer = XypicDiagramDrawer() return drawer.draw(diagram, grid, masked, diagram_format)
@doctest_depends_on(exe=('latex', 'dvipng'), modules=('pyglet',))
[docs]def preview_diagram(diagram, masked=None, diagram_format="", groups=None, output='png', viewer=None, euler=True, **hints): """ Combines the functionality of xypic_draw_diagram and sympy.printing.preview. The arguments masked, diagram_format, groups, and hints are passed to xypic_draw_diagram, while output, viewer, and euler are passed to preview. Examples ======== >>> from sympy.categories import Object, NamedMorphism, Diagram >>> from sympy.categories import preview_diagram >>> A = Object("A") >>> B = Object("B") >>> C = Object("C") >>> f = NamedMorphism(A, B, "f") >>> g = NamedMorphism(B, C, "g") >>> d = Diagram([f, g], {g * f: "unique"}) >>> preview_diagram(d) See Also ======== xypic_diagram_drawer """ from sympy.printing import preview latex_output = xypic_draw_diagram(diagram, masked, diagram_format, groups, **hints) preview(latex_output, output, viewer, euler, ("xypic",))