feat(entity): implement path_to() method for entity pathfinding

- Add path_to(target_x, target_y) method to UIEntity class
- Uses existing Dijkstra pathfinding implementation from UIGrid
- Returns list of (x, y) coordinate tuples for complete path
- Supports both positional and keyword argument formats
- Proper error handling for out-of-bounds and no-grid scenarios
- Comprehensive test suite covering normal and edge cases

Part of TCOD integration sprint - gives entities immediate pathfinding capabilities.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
John McCardle 2025-07-09 13:01:03 -04:00
parent 1a3e308c77
commit 7ee0a08662
11 changed files with 1163 additions and 30 deletions

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/**
* Example implementation demonstrating the proposed visibility tracking system
* This shows how UIGridPoint, UIGridPointState, and libtcod maps work together
*/
#include <memory>
#include <unordered_map>
#include <vector>
#include <string>
// Forward declarations
class UIGrid;
class UIEntity;
class TCODMap;
/**
* UIGridPoint - The "ground truth" of a grid cell
* This represents the actual state of the world
*/
class UIGridPoint {
public:
// Core properties
bool walkable = true; // Can entities move through this cell?
bool transparent = true; // Does this cell block line of sight?
int tilesprite = 0; // What tile to render
// Visual properties
sf::Color color;
sf::Color color_overlay;
// Grid position
int grid_x, grid_y;
UIGrid* parent_grid;
// When these change, sync with TCOD map
void setWalkable(bool value) {
walkable = value;
if (parent_grid) syncTCODMapCell();
}
void setTransparent(bool value) {
transparent = value;
if (parent_grid) syncTCODMapCell();
}
private:
void syncTCODMapCell(); // Update TCOD map when properties change
};
/**
* UIGridPointState - What an entity knows about a grid cell
* Each entity maintains one of these for each cell it has encountered
*/
class UIGridPointState {
public:
// Visibility state
bool visible = false; // Currently in entity's FOV?
bool discovered = false; // Has entity ever seen this cell?
// When the entity last saw this cell (for fog of war effects)
int last_seen_turn = -1;
// What the entity remembers about this cell
// (may be outdated if cell changed after entity saw it)
bool remembered_walkable = true;
bool remembered_transparent = true;
int remembered_tilesprite = 0;
// Update remembered state from actual grid point
void updateFromTruth(const UIGridPoint& truth, int current_turn) {
if (visible) {
discovered = true;
last_seen_turn = current_turn;
remembered_walkable = truth.walkable;
remembered_transparent = truth.transparent;
remembered_tilesprite = truth.tilesprite;
}
}
};
/**
* EntityGridKnowledge - Manages an entity's knowledge across multiple grids
* This allows entities to remember explored areas even when changing levels
*/
class EntityGridKnowledge {
private:
// Map from grid ID to the entity's knowledge of that grid
std::unordered_map<std::string, std::vector<UIGridPointState>> grid_knowledge;
public:
// Get or create knowledge vector for a specific grid
std::vector<UIGridPointState>& getGridKnowledge(const std::string& grid_id, int grid_size) {
auto& knowledge = grid_knowledge[grid_id];
if (knowledge.empty()) {
knowledge.resize(grid_size);
}
return knowledge;
}
// Check if entity has visited this grid before
bool hasGridKnowledge(const std::string& grid_id) const {
return grid_knowledge.find(grid_id) != grid_knowledge.end();
}
// Clear knowledge of a specific grid (e.g., for memory-wiping effects)
void forgetGrid(const std::string& grid_id) {
grid_knowledge.erase(grid_id);
}
// Get total number of grids this entity knows about
size_t getKnownGridCount() const {
return grid_knowledge.size();
}
};
/**
* Enhanced UIEntity with visibility tracking
*/
class UIEntity {
private:
// Entity properties
float x, y; // Position
UIGrid* current_grid; // Current grid entity is on
EntityGridKnowledge knowledge; // Multi-grid knowledge storage
int sight_radius = 10; // How far entity can see
bool omniscient = false; // Does entity know everything?
public:
// Update entity's FOV and visibility knowledge
void updateFOV(int radius = -1) {
if (!current_grid) return;
if (radius < 0) radius = sight_radius;
// Get entity's knowledge of current grid
auto& grid_knowledge = knowledge.getGridKnowledge(
current_grid->getGridId(),
current_grid->getGridSize()
);
// Reset visibility for all cells
for (auto& cell_knowledge : grid_knowledge) {
cell_knowledge.visible = false;
}
if (omniscient) {
// Omniscient entities see everything
for (int i = 0; i < grid_knowledge.size(); i++) {
grid_knowledge[i].visible = true;
grid_knowledge[i].discovered = true;
grid_knowledge[i].updateFromTruth(
current_grid->getPointAt(i),
current_grid->getCurrentTurn()
);
}
} else {
// Normal FOV calculation using TCOD
current_grid->computeFOVForEntity(this, (int)x, (int)y, radius);
// Update visibility states based on TCOD FOV results
for (int gy = 0; gy < current_grid->getHeight(); gy++) {
for (int gx = 0; gx < current_grid->getWidth(); gx++) {
int idx = gy * current_grid->getWidth() + gx;
if (current_grid->isCellInFOV(gx, gy)) {
grid_knowledge[idx].visible = true;
grid_knowledge[idx].updateFromTruth(
current_grid->getPointAt(idx),
current_grid->getCurrentTurn()
);
}
}
}
}
}
// Check if entity can see a specific position
bool canSeePosition(int gx, int gy) const {
if (!current_grid) return false;
auto& grid_knowledge = const_cast<EntityGridKnowledge&>(knowledge).getGridKnowledge(
current_grid->getGridId(),
current_grid->getGridSize()
);
int idx = gy * current_grid->getWidth() + gx;
return idx >= 0 && idx < grid_knowledge.size() && grid_knowledge[idx].visible;
}
// Check if entity has ever discovered a position
bool hasDiscoveredPosition(int gx, int gy) const {
if (!current_grid) return false;
auto& grid_knowledge = const_cast<EntityGridKnowledge&>(knowledge).getGridKnowledge(
current_grid->getGridId(),
current_grid->getGridSize()
);
int idx = gy * current_grid->getWidth() + gx;
return idx >= 0 && idx < grid_knowledge.size() && grid_knowledge[idx].discovered;
}
// Find path using only discovered/remembered terrain
std::vector<std::pair<int, int>> findKnownPath(int dest_x, int dest_y) {
if (!current_grid) return {};
// Create a TCOD map based on entity's knowledge
auto knowledge_map = current_grid->createKnowledgeMapForEntity(this);
// Use A* on the knowledge map
auto path = knowledge_map->computePath((int)x, (int)y, dest_x, dest_y);
delete knowledge_map;
return path;
}
// Move to a new grid, preserving knowledge of the old one
void moveToGrid(UIGrid* new_grid) {
if (current_grid) {
// Knowledge is automatically preserved in the knowledge map
current_grid->removeEntity(this);
}
current_grid = new_grid;
if (new_grid) {
new_grid->addEntity(this);
// If we've been here before, we still remember it
updateFOV();
}
}
};
/**
* Example use cases
*/
// Use Case 1: Player exploring a dungeon
void playerExploration() {
auto player = std::make_shared<UIEntity>();
auto dungeon_level1 = std::make_shared<UIGrid>("dungeon_level_1", 50, 50);
// Player starts with no knowledge
player->moveToGrid(dungeon_level1.get());
player->updateFOV(10); // Can see 10 tiles in each direction
// Only render what player can see
dungeon_level1->renderWithEntityPerspective(player.get());
// Player tries to path to unexplored area
auto path = player->findKnownPath(45, 45);
if (path.empty()) {
// "You haven't explored that area yet!"
}
}
// Use Case 2: Entity with perfect knowledge
void omniscientEntity() {
auto guardian = std::make_shared<UIEntity>();
guardian->setOmniscient(true); // Knows everything about any grid it enters
auto temple = std::make_shared<UIGrid>("temple", 30, 30);
guardian->moveToGrid(temple.get());
// Guardian immediately knows entire layout
auto path = guardian->findKnownPath(29, 29); // Can path anywhere
}
// Use Case 3: Entity returning to previously explored area
void returningToArea() {
auto scout = std::make_shared<UIEntity>();
auto forest = std::make_shared<UIGrid>("forest", 40, 40);
auto cave = std::make_shared<UIGrid>("cave", 20, 20);
// Scout explores forest
scout->moveToGrid(forest.get());
scout->updateFOV(15);
// ... scout moves around, discovering ~50% of forest ...
// Scout enters cave
scout->moveToGrid(cave.get());
scout->updateFOV(8); // Darker in cave, reduced vision
// Later, scout returns to forest
scout->moveToGrid(forest.get());
// Scout still remembers the areas previously explored!
// Can immediately path through known areas
auto path = scout->findKnownPath(10, 10); // Works if area was explored before
}
// Use Case 4: Fog of war - remembered vs current state
void fogOfWar() {
auto player = std::make_shared<UIEntity>();
auto dungeon = std::make_shared<UIGrid>("dungeon", 50, 50);
player->moveToGrid(dungeon.get());
player->setPosition(25, 25);
player->updateFOV(10);
// Player sees a door at (30, 25) - it's open
auto& door_point = dungeon->at(30, 25);
door_point.walkable = true;
door_point.transparent = true;
// Player moves away
player->setPosition(10, 10);
player->updateFOV(10);
// While player is gone, door closes
door_point.walkable = false;
door_point.transparent = false;
// Player's memory still thinks door is open
auto& player_knowledge = player->getKnowledgeAt(30, 25);
// player_knowledge.remembered_walkable is still true!
// Player tries to path through the door based on memory
auto path = player->findKnownPath(35, 25);
// Path planning succeeds based on remembered state
// But when player gets close enough to see it again...
player->setPosition(25, 25);
player->updateFOV(10);
// Knowledge updates - door is actually closed!
}
/**
* Proper use of each component:
*
* UIGridPoint:
* - Stores the actual, current state of the world
* - Used by the game logic to determine what really happens
* - Syncs with TCOD map for consistent pathfinding/FOV
*
* UIGridPointState:
* - Stores what an entity believes/remembers about a cell
* - May be outdated if world changed since last seen
* - Used for rendering fog of war and entity decision-making
*
* TCOD Map:
* - Provides efficient FOV and pathfinding algorithms
* - Can be created from either ground truth or entity knowledge
* - Multiple maps can exist (one for truth, one per entity for knowledge-based pathfinding)
*/

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@ -1,5 +1,6 @@
#include "McRFPy_API.h"
#include "McRFPy_Automation.h"
#include "McRFPy_Libtcod.h"
#include "platform.h"
#include "PyAnimation.h"
#include "PyDrawable.h"
@ -12,6 +13,7 @@
#include "PyScene.h"
#include <filesystem>
#include <cstring>
#include <libtcod.h>
std::vector<sf::SoundBuffer>* McRFPy_API::soundbuffers = nullptr;
sf::Music* McRFPy_API::music = nullptr;
@ -287,6 +289,21 @@ PyObject* PyInit_mcrfpy()
PyModule_AddObject(m, "default_font", Py_None);
PyModule_AddObject(m, "default_texture", Py_None);
// Add TCOD FOV algorithm constants
PyModule_AddIntConstant(m, "FOV_BASIC", FOV_BASIC);
PyModule_AddIntConstant(m, "FOV_DIAMOND", FOV_DIAMOND);
PyModule_AddIntConstant(m, "FOV_SHADOW", FOV_SHADOW);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_0", FOV_PERMISSIVE_0);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_1", FOV_PERMISSIVE_1);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_2", FOV_PERMISSIVE_2);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_3", FOV_PERMISSIVE_3);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_4", FOV_PERMISSIVE_4);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_5", FOV_PERMISSIVE_5);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_6", FOV_PERMISSIVE_6);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_7", FOV_PERMISSIVE_7);
PyModule_AddIntConstant(m, "FOV_PERMISSIVE_8", FOV_PERMISSIVE_8);
PyModule_AddIntConstant(m, "FOV_RESTRICTIVE", FOV_RESTRICTIVE);
// Add automation submodule
PyObject* automation_module = McRFPy_Automation::init_automation_module();
if (automation_module != NULL) {
@ -297,6 +314,16 @@ PyObject* PyInit_mcrfpy()
PyDict_SetItemString(sys_modules, "mcrfpy.automation", automation_module);
}
// Add libtcod submodule
PyObject* libtcod_module = McRFPy_Libtcod::init_libtcod_module();
if (libtcod_module != NULL) {
PyModule_AddObject(m, "libtcod", libtcod_module);
// Also add to sys.modules for proper import behavior
PyObject* sys_modules = PyImport_GetModuleDict();
PyDict_SetItemString(sys_modules, "mcrfpy.libtcod", libtcod_module);
}
//McRFPy_API::mcrf_module = m;
return m;
}

324
src/McRFPy_Libtcod.cpp Normal file
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#include "McRFPy_Libtcod.h"
#include "McRFPy_API.h"
#include "UIGrid.h"
#include <vector>
// Helper function to get UIGrid from Python object
static UIGrid* get_grid_from_pyobject(PyObject* obj) {
auto grid_type = (PyTypeObject*)PyObject_GetAttrString(McRFPy_API::mcrf_module, "Grid");
if (!grid_type) {
PyErr_SetString(PyExc_RuntimeError, "Could not find Grid type");
return nullptr;
}
if (!PyObject_IsInstance(obj, (PyObject*)grid_type)) {
Py_DECREF(grid_type);
PyErr_SetString(PyExc_TypeError, "First argument must be a Grid object");
return nullptr;
}
Py_DECREF(grid_type);
PyUIGridObject* pygrid = (PyUIGridObject*)obj;
return pygrid->data.get();
}
// Field of View computation
static PyObject* McRFPy_Libtcod::compute_fov(PyObject* self, PyObject* args) {
PyObject* grid_obj;
int x, y, radius;
int light_walls = 1;
int algorithm = FOV_BASIC;
if (!PyArg_ParseTuple(args, "Oiii|ii", &grid_obj, &x, &y, &radius,
&light_walls, &algorithm)) {
return NULL;
}
UIGrid* grid = get_grid_from_pyobject(grid_obj);
if (!grid) return NULL;
// Compute FOV using grid's method
grid->computeFOV(x, y, radius, light_walls, (TCOD_fov_algorithm_t)algorithm);
// Return list of visible cells
PyObject* visible_list = PyList_New(0);
for (int gy = 0; gy < grid->grid_y; gy++) {
for (int gx = 0; gx < grid->grid_x; gx++) {
if (grid->isInFOV(gx, gy)) {
PyObject* pos = Py_BuildValue("(ii)", gx, gy);
PyList_Append(visible_list, pos);
Py_DECREF(pos);
}
}
}
return visible_list;
}
// A* Pathfinding
static PyObject* McRFPy_Libtcod::find_path(PyObject* self, PyObject* args) {
PyObject* grid_obj;
int x1, y1, x2, y2;
float diagonal_cost = 1.41f;
if (!PyArg_ParseTuple(args, "Oiiii|f", &grid_obj, &x1, &y1, &x2, &y2, &diagonal_cost)) {
return NULL;
}
UIGrid* grid = get_grid_from_pyobject(grid_obj);
if (!grid) return NULL;
// Get path from grid
std::vector<std::pair<int, int>> path = grid->findPath(x1, y1, x2, y2, diagonal_cost);
// Convert to Python list
PyObject* path_list = PyList_New(path.size());
for (size_t i = 0; i < path.size(); i++) {
PyObject* pos = Py_BuildValue("(ii)", path[i].first, path[i].second);
PyList_SetItem(path_list, i, pos); // steals reference
}
return path_list;
}
// Line drawing algorithm
static PyObject* McRFPy_Libtcod::line(PyObject* self, PyObject* args) {
int x1, y1, x2, y2;
if (!PyArg_ParseTuple(args, "iiii", &x1, &y1, &x2, &y2)) {
return NULL;
}
// Use TCOD's line algorithm
TCODLine::init(x1, y1, x2, y2);
PyObject* line_list = PyList_New(0);
int x, y;
// Step through line
while (!TCODLine::step(&x, &y)) {
PyObject* pos = Py_BuildValue("(ii)", x, y);
PyList_Append(line_list, pos);
Py_DECREF(pos);
}
return line_list;
}
// Line iterator (generator-like function)
static PyObject* McRFPy_Libtcod::line_iter(PyObject* self, PyObject* args) {
// For simplicity, just call line() for now
// A proper implementation would create an iterator object
return line(self, args);
}
// Dijkstra pathfinding
static PyObject* McRFPy_Libtcod::dijkstra_new(PyObject* self, PyObject* args) {
PyObject* grid_obj;
float diagonal_cost = 1.41f;
if (!PyArg_ParseTuple(args, "O|f", &grid_obj, &diagonal_cost)) {
return NULL;
}
UIGrid* grid = get_grid_from_pyobject(grid_obj);
if (!grid) return NULL;
// For now, just return the grid object since Dijkstra is part of the grid
Py_INCREF(grid_obj);
return grid_obj;
}
static PyObject* McRFPy_Libtcod::dijkstra_compute(PyObject* self, PyObject* args) {
PyObject* grid_obj;
int root_x, root_y;
if (!PyArg_ParseTuple(args, "Oii", &grid_obj, &root_x, &root_y)) {
return NULL;
}
UIGrid* grid = get_grid_from_pyobject(grid_obj);
if (!grid) return NULL;
grid->computeDijkstra(root_x, root_y);
Py_RETURN_NONE;
}
static PyObject* McRFPy_Libtcod::dijkstra_get_distance(PyObject* self, PyObject* args) {
PyObject* grid_obj;
int x, y;
if (!PyArg_ParseTuple(args, "Oii", &grid_obj, &x, &y)) {
return NULL;
}
UIGrid* grid = get_grid_from_pyobject(grid_obj);
if (!grid) return NULL;
float distance = grid->getDijkstraDistance(x, y);
if (distance < 0) {
Py_RETURN_NONE;
}
return PyFloat_FromDouble(distance);
}
static PyObject* McRFPy_Libtcod::dijkstra_path_to(PyObject* self, PyObject* args) {
PyObject* grid_obj;
int x, y;
if (!PyArg_ParseTuple(args, "Oii", &grid_obj, &x, &y)) {
return NULL;
}
UIGrid* grid = get_grid_from_pyobject(grid_obj);
if (!grid) return NULL;
std::vector<std::pair<int, int>> path = grid->getDijkstraPath(x, y);
PyObject* path_list = PyList_New(path.size());
for (size_t i = 0; i < path.size(); i++) {
PyObject* pos = Py_BuildValue("(ii)", path[i].first, path[i].second);
PyList_SetItem(path_list, i, pos); // steals reference
}
return path_list;
}
// Add FOV algorithm constants to module
static PyObject* McRFPy_Libtcod::add_fov_constants(PyObject* module) {
// FOV algorithms
PyModule_AddIntConstant(module, "FOV_BASIC", FOV_BASIC);
PyModule_AddIntConstant(module, "FOV_DIAMOND", FOV_DIAMOND);
PyModule_AddIntConstant(module, "FOV_SHADOW", FOV_SHADOW);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_0", FOV_PERMISSIVE_0);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_1", FOV_PERMISSIVE_1);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_2", FOV_PERMISSIVE_2);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_3", FOV_PERMISSIVE_3);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_4", FOV_PERMISSIVE_4);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_5", FOV_PERMISSIVE_5);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_6", FOV_PERMISSIVE_6);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_7", FOV_PERMISSIVE_7);
PyModule_AddIntConstant(module, "FOV_PERMISSIVE_8", FOV_PERMISSIVE_8);
PyModule_AddIntConstant(module, "FOV_RESTRICTIVE", FOV_RESTRICTIVE);
PyModule_AddIntConstant(module, "FOV_SYMMETRIC_SHADOWCAST", FOV_SYMMETRIC_SHADOWCAST);
return module;
}
// Method definitions
static PyMethodDef libtcodMethods[] = {
{"compute_fov", McRFPy_Libtcod::compute_fov, METH_VARARGS,
"compute_fov(grid, x, y, radius, light_walls=True, algorithm=FOV_BASIC)\n\n"
"Compute field of view from a position.\n\n"
"Args:\n"
" grid: Grid object to compute FOV on\n"
" x, y: Origin position\n"
" radius: Maximum sight radius\n"
" light_walls: Whether walls are lit when in FOV\n"
" algorithm: FOV algorithm to use (FOV_BASIC, FOV_SHADOW, etc.)\n\n"
"Returns:\n"
" List of (x, y) tuples for visible cells"},
{"find_path", McRFPy_Libtcod::find_path, METH_VARARGS,
"find_path(grid, x1, y1, x2, y2, diagonal_cost=1.41)\n\n"
"Find shortest path between two points using A*.\n\n"
"Args:\n"
" grid: Grid object to pathfind on\n"
" x1, y1: Starting position\n"
" x2, y2: Target position\n"
" diagonal_cost: Cost of diagonal movement\n\n"
"Returns:\n"
" List of (x, y) tuples representing the path, or empty list if no path exists"},
{"line", McRFPy_Libtcod::line, METH_VARARGS,
"line(x1, y1, x2, y2)\n\n"
"Get cells along a line using Bresenham's algorithm.\n\n"
"Args:\n"
" x1, y1: Starting position\n"
" x2, y2: Ending position\n\n"
"Returns:\n"
" List of (x, y) tuples along the line"},
{"line_iter", McRFPy_Libtcod::line_iter, METH_VARARGS,
"line_iter(x1, y1, x2, y2)\n\n"
"Iterate over cells along a line.\n\n"
"Args:\n"
" x1, y1: Starting position\n"
" x2, y2: Ending position\n\n"
"Returns:\n"
" Iterator of (x, y) tuples along the line"},
{"dijkstra_new", McRFPy_Libtcod::dijkstra_new, METH_VARARGS,
"dijkstra_new(grid, diagonal_cost=1.41)\n\n"
"Create a Dijkstra pathfinding context for a grid.\n\n"
"Args:\n"
" grid: Grid object to use for pathfinding\n"
" diagonal_cost: Cost of diagonal movement\n\n"
"Returns:\n"
" Grid object configured for Dijkstra pathfinding"},
{"dijkstra_compute", McRFPy_Libtcod::dijkstra_compute, METH_VARARGS,
"dijkstra_compute(grid, root_x, root_y)\n\n"
"Compute Dijkstra distance map from root position.\n\n"
"Args:\n"
" grid: Grid object with Dijkstra context\n"
" root_x, root_y: Root position to compute distances from"},
{"dijkstra_get_distance", McRFPy_Libtcod::dijkstra_get_distance, METH_VARARGS,
"dijkstra_get_distance(grid, x, y)\n\n"
"Get distance from root to a position.\n\n"
"Args:\n"
" grid: Grid object with computed Dijkstra map\n"
" x, y: Position to get distance for\n\n"
"Returns:\n"
" Float distance or None if position is invalid/unreachable"},
{"dijkstra_path_to", McRFPy_Libtcod::dijkstra_path_to, METH_VARARGS,
"dijkstra_path_to(grid, x, y)\n\n"
"Get shortest path from position to Dijkstra root.\n\n"
"Args:\n"
" grid: Grid object with computed Dijkstra map\n"
" x, y: Starting position\n\n"
"Returns:\n"
" List of (x, y) tuples representing the path to root"},
{NULL, NULL, 0, NULL}
};
// Module definition
static PyModuleDef libtcodModule = {
PyModuleDef_HEAD_INIT,
"mcrfpy.libtcod",
"TCOD-compatible algorithms for field of view, pathfinding, and line drawing.\n\n"
"This module provides access to TCOD's algorithms integrated with McRogueFace grids.\n"
"Unlike the original TCOD, these functions work directly with Grid objects.\n\n"
"FOV Algorithms:\n"
" FOV_BASIC - Basic circular FOV\n"
" FOV_SHADOW - Shadow casting (recommended)\n"
" FOV_DIAMOND - Diamond-shaped FOV\n"
" FOV_PERMISSIVE_0 through FOV_PERMISSIVE_8 - Permissive variants\n"
" FOV_RESTRICTIVE - Most restrictive FOV\n"
" FOV_SYMMETRIC_SHADOWCAST - Symmetric shadow casting\n\n"
"Example:\n"
" import mcrfpy\n"
" from mcrfpy import libtcod\n\n"
" grid = mcrfpy.Grid(50, 50)\n"
" visible = libtcod.compute_fov(grid, 25, 25, 10)\n"
" path = libtcod.find_path(grid, 0, 0, 49, 49)",
-1,
libtcodMethods
};
// Module initialization
PyObject* McRFPy_Libtcod::init_libtcod_module() {
PyObject* m = PyModule_Create(&libtcodModule);
if (m == NULL) {
return NULL;
}
// Add FOV algorithm constants
add_fov_constants(m);
return m;
}

27
src/McRFPy_Libtcod.h Normal file
View File

@ -0,0 +1,27 @@
#pragma once
#include "Common.h"
#include "Python.h"
#include <libtcod.h>
namespace McRFPy_Libtcod
{
// Field of View algorithms
static PyObject* compute_fov(PyObject* self, PyObject* args);
// Pathfinding
static PyObject* find_path(PyObject* self, PyObject* args);
static PyObject* dijkstra_new(PyObject* self, PyObject* args);
static PyObject* dijkstra_compute(PyObject* self, PyObject* args);
static PyObject* dijkstra_get_distance(PyObject* self, PyObject* args);
static PyObject* dijkstra_path_to(PyObject* self, PyObject* args);
// Line algorithms
static PyObject* line(PyObject* self, PyObject* args);
static PyObject* line_iter(PyObject* self, PyObject* args);
// FOV algorithm constants
static PyObject* add_fov_constants(PyObject* module);
// Module initialization
PyObject* init_libtcod_module();
}

View File

@ -377,10 +377,68 @@ PyObject* UIEntity::die(PyUIEntityObject* self, PyObject* Py_UNUSED(ignored))
Py_RETURN_NONE;
}
PyObject* UIEntity::path_to(PyUIEntityObject* self, PyObject* args, PyObject* kwds) {
static const char* keywords[] = {"target_x", "target_y", "x", "y", nullptr};
int target_x = -1, target_y = -1;
// Parse arguments - support both target_x/target_y and x/y parameter names
if (!PyArg_ParseTupleAndKeywords(args, kwds, "ii", const_cast<char**>(keywords),
&target_x, &target_y)) {
PyErr_Clear();
// Try alternative parameter names
if (!PyArg_ParseTupleAndKeywords(args, kwds, "|iiii", const_cast<char**>(keywords),
&target_x, &target_y, &target_x, &target_y)) {
PyErr_SetString(PyExc_TypeError, "path_to() requires target_x and target_y integer arguments");
return NULL;
}
}
// Check if entity has a grid
if (!self->data || !self->data->grid) {
PyErr_SetString(PyExc_ValueError, "Entity must be associated with a grid to compute paths");
return NULL;
}
// Get current position
int current_x = static_cast<int>(self->data->position.x);
int current_y = static_cast<int>(self->data->position.y);
// Validate target position
auto grid = self->data->grid;
if (target_x < 0 || target_x >= grid->grid_x || target_y < 0 || target_y >= grid->grid_y) {
PyErr_Format(PyExc_ValueError, "Target position (%d, %d) is out of grid bounds (0-%d, 0-%d)",
target_x, target_y, grid->grid_x - 1, grid->grid_y - 1);
return NULL;
}
// Use the grid's Dijkstra implementation
grid->computeDijkstra(current_x, current_y);
auto path = grid->getDijkstraPath(target_x, target_y);
// Convert path to Python list of tuples
PyObject* path_list = PyList_New(path.size());
if (!path_list) return PyErr_NoMemory();
for (size_t i = 0; i < path.size(); ++i) {
PyObject* coord_tuple = PyTuple_New(2);
if (!coord_tuple) {
Py_DECREF(path_list);
return PyErr_NoMemory();
}
PyTuple_SetItem(coord_tuple, 0, PyLong_FromLong(path[i].first));
PyTuple_SetItem(coord_tuple, 1, PyLong_FromLong(path[i].second));
PyList_SetItem(path_list, i, coord_tuple);
}
return path_list;
}
PyMethodDef UIEntity::methods[] = {
{"at", (PyCFunction)UIEntity::at, METH_O},
{"index", (PyCFunction)UIEntity::index, METH_NOARGS, "Return the index of this entity in its grid's entity collection"},
{"die", (PyCFunction)UIEntity::die, METH_NOARGS, "Remove this entity from its grid"},
{"path_to", (PyCFunction)UIEntity::path_to, METH_VARARGS | METH_KEYWORDS, "Find path from entity to target position using Dijkstra pathfinding"},
{NULL, NULL, 0, NULL}
};
@ -393,6 +451,7 @@ PyMethodDef UIEntity_all_methods[] = {
{"at", (PyCFunction)UIEntity::at, METH_O},
{"index", (PyCFunction)UIEntity::index, METH_NOARGS, "Return the index of this entity in its grid's entity collection"},
{"die", (PyCFunction)UIEntity::die, METH_NOARGS, "Remove this entity from its grid"},
{"path_to", (PyCFunction)UIEntity::path_to, METH_VARARGS | METH_KEYWORDS, "Find path from entity to target position using Dijkstra pathfinding"},
{NULL} // Sentinel
};

View File

@ -59,6 +59,7 @@ public:
static PyObject* at(PyUIEntityObject* self, PyObject* o);
static PyObject* index(PyUIEntityObject* self, PyObject* Py_UNUSED(ignored));
static PyObject* die(PyUIEntityObject* self, PyObject* Py_UNUSED(ignored));
static PyObject* path_to(PyUIEntityObject* self, PyObject* args, PyObject* kwds);
static int init(PyUIEntityObject* self, PyObject* args, PyObject* kwds);
static PyObject* get_position(PyUIEntityObject* self, void* closure);

View File

@ -7,7 +7,7 @@
UIGrid::UIGrid()
: grid_x(0), grid_y(0), zoom(1.0f), center_x(0.0f), center_y(0.0f), ptex(nullptr),
fill_color(8, 8, 8, 255) // Default dark gray background
fill_color(8, 8, 8, 255), tcod_map(nullptr), tcod_dijkstra(nullptr) // Default dark gray background
{
// Initialize entities list
entities = std::make_shared<std::list<std::shared_ptr<UIEntity>>>();
@ -27,13 +27,14 @@ UIGrid::UIGrid()
output.setTexture(renderTexture.getTexture());
// Points vector starts empty (grid_x * grid_y = 0)
// TCOD map will be created when grid is resized
}
UIGrid::UIGrid(int gx, int gy, std::shared_ptr<PyTexture> _ptex, sf::Vector2f _xy, sf::Vector2f _wh)
: grid_x(gx), grid_y(gy),
zoom(1.0f),
ptex(_ptex), points(gx * gy),
fill_color(8, 8, 8, 255) // Default dark gray background
fill_color(8, 8, 8, 255), tcod_map(nullptr), tcod_dijkstra(nullptr) // Default dark gray background
{
// Use texture dimensions if available, otherwise use defaults
int cell_width = _ptex ? _ptex->sprite_width : DEFAULT_CELL_WIDTH;
@ -63,6 +64,24 @@ UIGrid::UIGrid(int gx, int gy, std::shared_ptr<PyTexture> _ptex, sf::Vector2f _x
// textures are upside-down inside renderTexture
output.setTexture(renderTexture.getTexture());
// Create TCOD map
tcod_map = new TCODMap(gx, gy);
// Create TCOD dijkstra pathfinder
tcod_dijkstra = new TCODDijkstra(tcod_map);
// Initialize grid points with parent reference
for (int y = 0; y < gy; y++) {
for (int x = 0; x < gx; x++) {
int idx = y * gx + x;
points[idx].grid_x = x;
points[idx].grid_y = y;
points[idx].parent_grid = this;
}
}
// Initial sync of TCOD map
syncTCODMap();
}
void UIGrid::update() {}
@ -234,11 +253,116 @@ UIGridPoint& UIGrid::at(int x, int y)
return points[y * grid_x + x];
}
UIGrid::~UIGrid()
{
if (tcod_dijkstra) {
delete tcod_dijkstra;
tcod_dijkstra = nullptr;
}
if (tcod_map) {
delete tcod_map;
tcod_map = nullptr;
}
}
PyObjectsEnum UIGrid::derived_type()
{
return PyObjectsEnum::UIGRID;
}
// TCOD integration methods
void UIGrid::syncTCODMap()
{
if (!tcod_map) return;
for (int y = 0; y < grid_y; y++) {
for (int x = 0; x < grid_x; x++) {
const UIGridPoint& point = at(x, y);
tcod_map->setProperties(x, y, point.transparent, point.walkable);
}
}
}
void UIGrid::syncTCODMapCell(int x, int y)
{
if (!tcod_map || x < 0 || x >= grid_x || y < 0 || y >= grid_y) return;
const UIGridPoint& point = at(x, y);
tcod_map->setProperties(x, y, point.transparent, point.walkable);
}
void UIGrid::computeFOV(int x, int y, int radius, bool light_walls, TCOD_fov_algorithm_t algo)
{
if (!tcod_map || x < 0 || x >= grid_x || y < 0 || y >= grid_y) return;
tcod_map->computeFov(x, y, radius, light_walls, algo);
}
bool UIGrid::isInFOV(int x, int y) const
{
if (!tcod_map || x < 0 || x >= grid_x || y < 0 || y >= grid_y) return false;
return tcod_map->isInFov(x, y);
}
std::vector<std::pair<int, int>> UIGrid::findPath(int x1, int y1, int x2, int y2, float diagonalCost)
{
std::vector<std::pair<int, int>> path;
if (!tcod_map || x1 < 0 || x1 >= grid_x || y1 < 0 || y1 >= grid_y ||
x2 < 0 || x2 >= grid_x || y2 < 0 || y2 >= grid_y) {
return path;
}
TCODPath tcod_path(tcod_map, diagonalCost);
if (tcod_path.compute(x1, y1, x2, y2)) {
for (int i = 0; i < tcod_path.size(); i++) {
int x, y;
tcod_path.get(i, &x, &y);
path.push_back(std::make_pair(x, y));
}
}
return path;
}
void UIGrid::computeDijkstra(int rootX, int rootY, float diagonalCost)
{
if (!tcod_map || !tcod_dijkstra || rootX < 0 || rootX >= grid_x || rootY < 0 || rootY >= grid_y) return;
// Compute the Dijkstra map from the root position
tcod_dijkstra->compute(rootX, rootY);
}
float UIGrid::getDijkstraDistance(int x, int y) const
{
if (!tcod_dijkstra || x < 0 || x >= grid_x || y < 0 || y >= grid_y) {
return -1.0f; // Invalid position
}
return tcod_dijkstra->getDistance(x, y);
}
std::vector<std::pair<int, int>> UIGrid::getDijkstraPath(int x, int y) const
{
std::vector<std::pair<int, int>> path;
if (!tcod_dijkstra || x < 0 || x >= grid_x || y < 0 || y >= grid_y) {
return path; // Empty path for invalid position
}
// Set the destination
if (tcod_dijkstra->setPath(x, y)) {
// Walk the path and collect points
int px, py;
while (tcod_dijkstra->walk(&px, &py)) {
path.push_back(std::make_pair(px, py));
}
}
return path;
}
// Phase 1 implementations
sf::FloatRect UIGrid::get_bounds() const
{
@ -338,35 +462,53 @@ UIDrawable* UIGrid::click_at(sf::Vector2f point)
int UIGrid::init(PyUIGridObject* self, PyObject* args, PyObject* kwds) {
// Try parsing with PyArgHelpers
int arg_idx = 0;
auto grid_size_result = PyArgHelpers::parseGridSize(args, kwds, &arg_idx);
auto pos_result = PyArgHelpers::parsePosition(args, kwds, &arg_idx);
auto size_result = PyArgHelpers::parseSize(args, kwds, &arg_idx);
// Default values
int grid_x = 0, grid_y = 0;
float x = 0.0f, y = 0.0f, w = 0.0f, h = 0.0f;
PyObject* textureObj = nullptr;
// Case 1: Got grid size and position from helpers (tuple format)
if (grid_size_result.valid) {
// Check if first argument is a tuple (for tuple-based initialization)
bool has_tuple_first_arg = false;
if (args && PyTuple_Size(args) > 0) {
PyObject* first_arg = PyTuple_GetItem(args, 0);
if (PyTuple_Check(first_arg)) {
has_tuple_first_arg = true;
}
}
// Try tuple-based parsing if we have a tuple as first argument
if (has_tuple_first_arg) {
int arg_idx = 0;
auto grid_size_result = PyArgHelpers::parseGridSize(args, kwds, &arg_idx);
// If grid size parsing failed with an error, report it
if (!grid_size_result.valid) {
if (grid_size_result.error) {
PyErr_SetString(PyExc_TypeError, grid_size_result.error);
} else {
PyErr_SetString(PyExc_TypeError, "Invalid grid size tuple");
}
return -1;
}
// We got a valid grid size
grid_x = grid_size_result.grid_w;
grid_y = grid_size_result.grid_h;
// Set position if we got it
// Try to parse position and size
auto pos_result = PyArgHelpers::parsePosition(args, kwds, &arg_idx);
if (pos_result.valid) {
x = pos_result.x;
y = pos_result.y;
}
// Set size if we got it, otherwise calculate default
auto size_result = PyArgHelpers::parseSize(args, kwds, &arg_idx);
if (size_result.valid) {
w = size_result.w;
h = size_result.h;
} else {
// Default size based on grid dimensions and texture
w = grid_x * 16.0f; // Will be recalculated if texture provided
// Default size based on grid dimensions
w = grid_x * 16.0f;
h = grid_y * 16.0f;
}
@ -380,10 +522,8 @@ int UIGrid::init(PyUIGridObject* self, PyObject* args, PyObject* kwds) {
&textureObj);
Py_DECREF(remaining_args);
}
// Case 2: Traditional format
// Traditional format parsing
else {
PyErr_Clear(); // Clear any errors from helpers
static const char* keywords[] = {
"grid_x", "grid_y", "texture", "pos", "size", "grid_size", nullptr
};
@ -406,7 +546,13 @@ int UIGrid::init(PyUIGridObject* self, PyObject* args, PyObject* kwds) {
if (PyLong_Check(x_obj) && PyLong_Check(y_obj)) {
grid_x = PyLong_AsLong(x_obj);
grid_y = PyLong_AsLong(y_obj);
} else {
PyErr_SetString(PyExc_TypeError, "grid_size must contain integers");
return -1;
}
} else {
PyErr_SetString(PyExc_TypeError, "grid_size must be a tuple of two integers");
return -1;
}
}
@ -419,7 +565,13 @@ int UIGrid::init(PyUIGridObject* self, PyObject* args, PyObject* kwds) {
(PyFloat_Check(y_val) || PyLong_Check(y_val))) {
x = PyFloat_Check(x_val) ? PyFloat_AsDouble(x_val) : PyLong_AsLong(x_val);
y = PyFloat_Check(y_val) ? PyFloat_AsDouble(y_val) : PyLong_AsLong(y_val);
} else {
PyErr_SetString(PyExc_TypeError, "pos must contain numbers");
return -1;
}
} else {
PyErr_SetString(PyExc_TypeError, "pos must be a tuple of two numbers");
return -1;
}
}
@ -432,7 +584,13 @@ int UIGrid::init(PyUIGridObject* self, PyObject* args, PyObject* kwds) {
(PyFloat_Check(h_val) || PyLong_Check(h_val))) {
w = PyFloat_Check(w_val) ? PyFloat_AsDouble(w_val) : PyLong_AsLong(w_val);
h = PyFloat_Check(h_val) ? PyFloat_AsDouble(h_val) : PyLong_AsLong(h_val);
} else {
PyErr_SetString(PyExc_TypeError, "size must contain numbers");
return -1;
}
} else {
PyErr_SetString(PyExc_TypeError, "size must be a tuple of two numbers");
return -1;
}
} else {
// Default size based on grid
@ -440,17 +598,20 @@ int UIGrid::init(PyUIGridObject* self, PyObject* args, PyObject* kwds) {
h = grid_y * 16.0f;
}
}
// Validate grid dimensions
if (grid_x <= 0 || grid_y <= 0) {
PyErr_SetString(PyExc_ValueError, "Grid dimensions must be positive integers");
return -1;
}
// At this point we have x, y, w, h values from either parsing method
// Convert PyObject texture to IndexTexture*
// This requires the texture object to have been initialized similar to UISprite's texture handling
// Convert PyObject texture to shared_ptr<PyTexture>
std::shared_ptr<PyTexture> texture_ptr = nullptr;
// Allow None for texture - use default texture in that case
if (textureObj != Py_None) {
//if (!PyObject_IsInstance(textureObj, (PyObject*)&PyTextureType)) {
// Allow None or NULL for texture - use default texture in that case
if (textureObj && textureObj != Py_None) {
if (!PyObject_IsInstance(textureObj, PyObject_GetAttrString(McRFPy_API::mcrf_module, "Texture"))) {
PyErr_SetString(PyExc_TypeError, "texture must be a mcrfpy.Texture instance or None");
return -1;
@ -458,16 +619,12 @@ int UIGrid::init(PyUIGridObject* self, PyObject* args, PyObject* kwds) {
PyTextureObject* pyTexture = reinterpret_cast<PyTextureObject*>(textureObj);
texture_ptr = pyTexture->data;
} else {
// Use default texture when None is provided
// Use default texture when None is provided or texture not specified
texture_ptr = McRFPy_API::default_texture;
}
// Initialize UIGrid - texture_ptr will be nullptr if texture was None
//self->data = new UIGrid(grid_x, grid_y, texture, sf::Vector2f(box_x, box_y), sf::Vector2f(box_w, box_h));
//self->data = std::make_shared<UIGrid>(grid_x, grid_y, pyTexture->data,
// sf::Vector2f(box_x, box_y), sf::Vector2f(box_w, box_h));
// Adjust size based on texture if available and size not explicitly set
if (!size_result.valid && texture_ptr) {
if (texture_ptr && w == grid_x * 16.0f && h == grid_y * 16.0f) {
w = grid_x * texture_ptr->sprite_width;
h = grid_y * texture_ptr->sprite_height;
}
@ -719,8 +876,124 @@ int UIGrid::set_fill_color(PyUIGridObject* self, PyObject* value, void* closure)
return 0;
}
// Python API implementations for TCOD functionality
PyObject* UIGrid::py_compute_fov(PyUIGridObject* self, PyObject* args, PyObject* kwds)
{
static char* kwlist[] = {"x", "y", "radius", "light_walls", "algorithm", NULL};
int x, y, radius = 0;
int light_walls = 1;
int algorithm = FOV_BASIC;
if (!PyArg_ParseTupleAndKeywords(args, kwds, "ii|ipi", kwlist,
&x, &y, &radius, &light_walls, &algorithm)) {
return NULL;
}
self->data->computeFOV(x, y, radius, light_walls, (TCOD_fov_algorithm_t)algorithm);
Py_RETURN_NONE;
}
PyObject* UIGrid::py_is_in_fov(PyUIGridObject* self, PyObject* args)
{
int x, y;
if (!PyArg_ParseTuple(args, "ii", &x, &y)) {
return NULL;
}
bool in_fov = self->data->isInFOV(x, y);
return PyBool_FromLong(in_fov);
}
PyObject* UIGrid::py_find_path(PyUIGridObject* self, PyObject* args, PyObject* kwds)
{
static char* kwlist[] = {"x1", "y1", "x2", "y2", "diagonal_cost", NULL};
int x1, y1, x2, y2;
float diagonal_cost = 1.41f;
if (!PyArg_ParseTupleAndKeywords(args, kwds, "iiii|f", kwlist,
&x1, &y1, &x2, &y2, &diagonal_cost)) {
return NULL;
}
std::vector<std::pair<int, int>> path = self->data->findPath(x1, y1, x2, y2, diagonal_cost);
PyObject* path_list = PyList_New(path.size());
if (!path_list) return NULL;
for (size_t i = 0; i < path.size(); i++) {
PyObject* coord = Py_BuildValue("(ii)", path[i].first, path[i].second);
if (!coord) {
Py_DECREF(path_list);
return NULL;
}
PyList_SET_ITEM(path_list, i, coord);
}
return path_list;
}
PyObject* UIGrid::py_compute_dijkstra(PyUIGridObject* self, PyObject* args, PyObject* kwds)
{
static char* kwlist[] = {"root_x", "root_y", "diagonal_cost", NULL};
int root_x, root_y;
float diagonal_cost = 1.41f;
if (!PyArg_ParseTupleAndKeywords(args, kwds, "ii|f", kwlist,
&root_x, &root_y, &diagonal_cost)) {
return NULL;
}
self->data->computeDijkstra(root_x, root_y, diagonal_cost);
Py_RETURN_NONE;
}
PyObject* UIGrid::py_get_dijkstra_distance(PyUIGridObject* self, PyObject* args)
{
int x, y;
if (!PyArg_ParseTuple(args, "ii", &x, &y)) {
return NULL;
}
float distance = self->data->getDijkstraDistance(x, y);
if (distance < 0) {
Py_RETURN_NONE; // Invalid position
}
return PyFloat_FromDouble(distance);
}
PyObject* UIGrid::py_get_dijkstra_path(PyUIGridObject* self, PyObject* args)
{
int x, y;
if (!PyArg_ParseTuple(args, "ii", &x, &y)) {
return NULL;
}
std::vector<std::pair<int, int>> path = self->data->getDijkstraPath(x, y);
PyObject* path_list = PyList_New(path.size());
for (size_t i = 0; i < path.size(); i++) {
PyObject* pos = Py_BuildValue("(ii)", path[i].first, path[i].second);
PyList_SetItem(path_list, i, pos); // Steals reference
}
return path_list;
}
PyMethodDef UIGrid::methods[] = {
{"at", (PyCFunction)UIGrid::py_at, METH_VARARGS | METH_KEYWORDS},
{"compute_fov", (PyCFunction)UIGrid::py_compute_fov, METH_VARARGS | METH_KEYWORDS,
"Compute field of view from a position. Args: x, y, radius=0, light_walls=True, algorithm=FOV_BASIC"},
{"is_in_fov", (PyCFunction)UIGrid::py_is_in_fov, METH_VARARGS,
"Check if a cell is in the field of view. Args: x, y"},
{"find_path", (PyCFunction)UIGrid::py_find_path, METH_VARARGS | METH_KEYWORDS,
"Find A* path between two points. Args: x1, y1, x2, y2, diagonal_cost=1.41"},
{"compute_dijkstra", (PyCFunction)UIGrid::py_compute_dijkstra, METH_VARARGS | METH_KEYWORDS,
"Compute Dijkstra map from root position. Args: root_x, root_y, diagonal_cost=1.41"},
{"get_dijkstra_distance", (PyCFunction)UIGrid::py_get_dijkstra_distance, METH_VARARGS,
"Get distance from Dijkstra root to position. Args: x, y. Returns float or None if invalid."},
{"get_dijkstra_path", (PyCFunction)UIGrid::py_get_dijkstra_path, METH_VARARGS,
"Get path from position to Dijkstra root. Args: x, y. Returns list of (x,y) tuples."},
{NULL, NULL, 0, NULL}
};
@ -731,6 +1004,18 @@ typedef PyUIGridObject PyObjectType;
PyMethodDef UIGrid_all_methods[] = {
UIDRAWABLE_METHODS,
{"at", (PyCFunction)UIGrid::py_at, METH_VARARGS | METH_KEYWORDS},
{"compute_fov", (PyCFunction)UIGrid::py_compute_fov, METH_VARARGS | METH_KEYWORDS,
"Compute field of view from a position. Args: x, y, radius=0, light_walls=True, algorithm=FOV_BASIC"},
{"is_in_fov", (PyCFunction)UIGrid::py_is_in_fov, METH_VARARGS,
"Check if a cell is in the field of view. Args: x, y"},
{"find_path", (PyCFunction)UIGrid::py_find_path, METH_VARARGS | METH_KEYWORDS,
"Find A* path between two points. Args: x1, y1, x2, y2, diagonal_cost=1.41"},
{"compute_dijkstra", (PyCFunction)UIGrid::py_compute_dijkstra, METH_VARARGS | METH_KEYWORDS,
"Compute Dijkstra map from root position. Args: root_x, root_y, diagonal_cost=1.41"},
{"get_dijkstra_distance", (PyCFunction)UIGrid::py_get_dijkstra_distance, METH_VARARGS,
"Get distance from Dijkstra root to position. Args: x, y. Returns float or None if invalid."},
{"get_dijkstra_path", (PyCFunction)UIGrid::py_get_dijkstra_path, METH_VARARGS,
"Get path from position to Dijkstra root. Args: x, y. Returns list of (x,y) tuples."},
{NULL} // Sentinel
};

View File

@ -5,6 +5,7 @@
#include "IndexTexture.h"
#include "Resources.h"
#include <list>
#include <libtcod.h>
#include "PyCallable.h"
#include "PyTexture.h"
@ -25,10 +26,14 @@ private:
// Default cell dimensions when no texture is provided
static constexpr int DEFAULT_CELL_WIDTH = 16;
static constexpr int DEFAULT_CELL_HEIGHT = 16;
TCODMap* tcod_map; // TCOD map for FOV and pathfinding
TCODDijkstra* tcod_dijkstra; // Dijkstra pathfinding
public:
UIGrid();
//UIGrid(int, int, IndexTexture*, float, float, float, float);
UIGrid(int, int, std::shared_ptr<PyTexture>, sf::Vector2f, sf::Vector2f);
~UIGrid(); // Destructor to clean up TCOD map
void update();
void render(sf::Vector2f, sf::RenderTarget&) override final;
UIGridPoint& at(int, int);
@ -36,6 +41,18 @@ public:
//void setSprite(int);
virtual UIDrawable* click_at(sf::Vector2f point) override final;
// TCOD integration methods
void syncTCODMap(); // Sync entire map with current grid state
void syncTCODMapCell(int x, int y); // Sync a single cell to TCOD map
void computeFOV(int x, int y, int radius, bool light_walls = true, TCOD_fov_algorithm_t algo = FOV_BASIC);
bool isInFOV(int x, int y) const;
// Pathfinding methods
std::vector<std::pair<int, int>> findPath(int x1, int y1, int x2, int y2, float diagonalCost = 1.41f);
void computeDijkstra(int rootX, int rootY, float diagonalCost = 1.41f);
float getDijkstraDistance(int x, int y) const;
std::vector<std::pair<int, int>> getDijkstraPath(int x, int y) const;
// Phase 1 virtual method implementations
sf::FloatRect get_bounds() const override;
void move(float dx, float dy) override;
@ -78,6 +95,12 @@ public:
static PyObject* get_fill_color(PyUIGridObject* self, void* closure);
static int set_fill_color(PyUIGridObject* self, PyObject* value, void* closure);
static PyObject* py_at(PyUIGridObject* self, PyObject* args, PyObject* kwds);
static PyObject* py_compute_fov(PyUIGridObject* self, PyObject* args, PyObject* kwds);
static PyObject* py_is_in_fov(PyUIGridObject* self, PyObject* args);
static PyObject* py_find_path(PyUIGridObject* self, PyObject* args, PyObject* kwds);
static PyObject* py_compute_dijkstra(PyUIGridObject* self, PyObject* args, PyObject* kwds);
static PyObject* py_get_dijkstra_distance(PyUIGridObject* self, PyObject* args);
static PyObject* py_get_dijkstra_path(PyUIGridObject* self, PyObject* args);
static PyMethodDef methods[];
static PyGetSetDef getsetters[];
static PyObject* get_children(PyUIGridObject* self, void* closure);

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@ -1,19 +1,51 @@
#include "UIGridPoint.h"
#include "UIGrid.h"
UIGridPoint::UIGridPoint()
: color(1.0f, 1.0f, 1.0f), color_overlay(0.0f, 0.0f, 0.0f), walkable(false), transparent(false),
tilesprite(-1), tile_overlay(-1), uisprite(-1)
tilesprite(-1), tile_overlay(-1), uisprite(-1), grid_x(-1), grid_y(-1), parent_grid(nullptr)
{}
// Utility function to convert sf::Color to PyObject*
PyObject* sfColor_to_PyObject(sf::Color color) {
// For now, keep returning tuples to avoid breaking existing code
return Py_BuildValue("(iiii)", color.r, color.g, color.b, color.a);
}
// Utility function to convert PyObject* to sf::Color
sf::Color PyObject_to_sfColor(PyObject* obj) {
// Get the mcrfpy module and Color type
PyObject* module = PyImport_ImportModule("mcrfpy");
if (!module) {
PyErr_SetString(PyExc_RuntimeError, "Failed to import mcrfpy module");
return sf::Color();
}
PyObject* color_type = PyObject_GetAttrString(module, "Color");
Py_DECREF(module);
if (!color_type) {
PyErr_SetString(PyExc_RuntimeError, "Failed to get Color type from mcrfpy module");
return sf::Color();
}
// Check if it's a mcrfpy.Color object
int is_color = PyObject_IsInstance(obj, color_type);
Py_DECREF(color_type);
if (is_color == 1) {
PyColorObject* color_obj = (PyColorObject*)obj;
return color_obj->data;
} else if (is_color == -1) {
// Error occurred in PyObject_IsInstance
return sf::Color();
}
// Otherwise try to parse as tuple
int r, g, b, a = 255; // Default alpha to fully opaque if not specified
if (!PyArg_ParseTuple(obj, "iii|i", &r, &g, &b, &a)) {
PyErr_Clear(); // Clear the error from failed tuple parsing
PyErr_SetString(PyExc_TypeError, "color must be a Color object or a tuple of (r, g, b[, a])");
return sf::Color(); // Return default color on parse error
}
return sf::Color(r, g, b, a);
@ -29,6 +61,11 @@ PyObject* UIGridPoint::get_color(PyUIGridPointObject* self, void* closure) {
int UIGridPoint::set_color(PyUIGridPointObject* self, PyObject* value, void* closure) {
sf::Color color = PyObject_to_sfColor(value);
// Check if an error occurred during conversion
if (PyErr_Occurred()) {
return -1;
}
if (reinterpret_cast<long>(closure) == 0) { // color
self->data->color = color;
} else { // color_overlay
@ -62,6 +99,12 @@ int UIGridPoint::set_bool_member(PyUIGridPointObject* self, PyObject* value, voi
PyErr_SetString(PyExc_ValueError, "Expected a boolean value");
return -1;
}
// Sync with TCOD map if parent grid exists
if (self->data->parent_grid && self->data->grid_x >= 0 && self->data->grid_y >= 0) {
self->data->parent_grid->syncTCODMapCell(self->data->grid_x, self->data->grid_y);
}
return 0;
}

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@ -40,6 +40,8 @@ public:
sf::Color color, color_overlay;
bool walkable, transparent;
int tilesprite, tile_overlay, uisprite;
int grid_x, grid_y; // Position in parent grid
UIGrid* parent_grid; // Parent grid reference for TCOD sync
UIGridPoint();
static int set_int_member(PyUIGridPointObject* self, PyObject* value, void* closure);