Files
ideadrop.nvim/lua/ideaDrop/ui/graph/layout.lua
Carlos Gutierrez 937f20b892 feat: add Obsidian-style graph visualization
Implement force-directed graph view for visualizing note connections:

- Add graph data model parsing [[wiki-style links]]
- Implement Fruchterman-Reingold layout algorithm
- Create character-based canvas renderer with highlights
- Add interactive filtering by tag/folder
- Support navigation (h/j/k/l), zoom (+/-), and node selection
- New commands: :IdeaGraph, :IdeaGraphFilter

New files:
- lua/ideaDrop/ui/graph/{init,types,data,layout,renderer}.lua

Updated documentation in README.md, CHANGELOG.md, and llms.txt
2026-01-10 23:02:40 -05:00

371 lines
10 KiB
Lua

-- ideaDrop/ui/graph/layout.lua
-- Force-directed graph layout using Fruchterman-Reingold algorithm
local constants = require("ideaDrop.utils.constants")
local types = require("ideaDrop.ui.graph.types")
---@class GraphLayoutModule
---@field initialize_positions fun(graph: GraphData, width: number, height: number): nil
---@field step fun(graph: GraphData, state: GraphLayoutState, width: number, height: number): boolean
---@field run_layout fun(graph: GraphData, width: number, height: number, max_iterations: number|nil): nil
local M = {}
local SETTINGS = constants.GRAPH_SETTINGS.LAYOUT
---Initializes node positions randomly within the canvas bounds
---@param graph GraphData The graph data
---@param width number Canvas width
---@param height number Canvas height
function M.initialize_positions(graph, width, height)
local padding = constants.GRAPH_SETTINGS.VISUAL.PADDING
local effective_width = width - 2 * padding
local effective_height = height - 2 * padding
local center_x = width / 2
local center_y = height / 2
-- Seed random for reproducible layouts (based on node count)
math.randomseed(#graph.node_list * 12345)
for _, node in ipairs(graph.node_list) do
-- Initialize in a circular pattern with some randomness
local angle = math.random() * 2 * math.pi
local radius = math.random() * math.min(effective_width, effective_height) / 3
node.x = center_x + radius * math.cos(angle)
node.y = center_y + radius * math.sin(angle)
node.vx = 0
node.vy = 0
end
-- Special handling: place high-degree nodes closer to center initially
local max_degree = 0
for _, node in ipairs(graph.node_list) do
if node.degree > max_degree then
max_degree = node.degree
end
end
if max_degree > 0 then
for _, node in ipairs(graph.node_list) do
local centrality = node.degree / max_degree
-- Move high-degree nodes toward center
node.x = center_x + (node.x - center_x) * (1 - centrality * 0.5)
node.y = center_y + (node.y - center_y) * (1 - centrality * 0.5)
end
end
end
---Calculates the repulsive force between two nodes
---@param dx number X distance
---@param dy number Y distance
---@param distance number Euclidean distance
---@return number, number Force components (fx, fy)
local function repulsive_force(dx, dy, distance)
if distance < 0.1 then
distance = 0.1 -- Prevent division by zero
end
local force = SETTINGS.REPULSION_STRENGTH / (distance * distance)
return (dx / distance) * force, (dy / distance) * force
end
---Calculates the attractive force between connected nodes
---@param dx number X distance
---@param dy number Y distance
---@param distance number Euclidean distance
---@return number, number Force components (fx, fy)
local function attractive_force(dx, dy, distance)
if distance < 0.1 then
distance = 0.1
end
local force = SETTINGS.ATTRACTION_STRENGTH * (distance - SETTINGS.IDEAL_EDGE_LENGTH)
return (dx / distance) * force, (dy / distance) * force
end
---Calculates gravity force pulling nodes toward center
---@param node GraphNode The node
---@param center_x number Center X coordinate
---@param center_y number Center Y coordinate
---@return number, number Force components (fx, fy)
local function gravity_force(node, center_x, center_y)
local dx = center_x - node.x
local dy = center_y - node.y
local distance = math.sqrt(dx * dx + dy * dy)
if distance < 0.1 then
return 0, 0
end
-- Gravity is stronger for orphan/low-degree nodes (pushes them to periphery)
-- and weaker for high-degree nodes (lets them stay in center)
local degree_factor = 1 / (1 + node.degree * 0.5)
local force = SETTINGS.GRAVITY * distance * degree_factor
-- Invert for orphans - push them away from center
if node.degree == 0 then
force = -force * 0.5
end
return (dx / distance) * force, (dy / distance) * force
end
---Performs one iteration of the force-directed layout
---@param graph GraphData The graph data
---@param state GraphLayoutState The layout state
---@param width number Canvas width
---@param height number Canvas height
---@return boolean True if layout has converged
function M.step(graph, state, width, height)
local padding = constants.GRAPH_SETTINGS.VISUAL.PADDING
local center_x = width / 2
local center_y = height / 2
-- Count visible nodes
local visible_nodes = {}
for _, node in ipairs(graph.node_list) do
if node.visible then
table.insert(visible_nodes, node)
end
end
if #visible_nodes == 0 then
state.converged = true
return true
end
-- Reset forces
for _, node in ipairs(visible_nodes) do
node.vx = 0
node.vy = 0
end
-- Calculate repulsive forces between all pairs of visible nodes
for i = 1, #visible_nodes do
local node1 = visible_nodes[i]
for j = i + 1, #visible_nodes do
local node2 = visible_nodes[j]
local dx = node1.x - node2.x
local dy = node1.y - node2.y
local distance = math.sqrt(dx * dx + dy * dy)
local fx, fy = repulsive_force(dx, dy, distance)
node1.vx = node1.vx + fx
node1.vy = node1.vy + fy
node2.vx = node2.vx - fx
node2.vy = node2.vy - fy
end
end
-- Calculate attractive forces for visible edges
for _, edge in ipairs(graph.edges) do
if edge.visible then
local source = graph.nodes[edge.source]
local target = graph.nodes[edge.target]
if source and target and source.visible and target.visible then
local dx = target.x - source.x
local dy = target.y - source.y
local distance = math.sqrt(dx * dx + dy * dy)
local fx, fy = attractive_force(dx, dy, distance)
source.vx = source.vx + fx
source.vy = source.vy + fy
target.vx = target.vx - fx
target.vy = target.vy - fy
end
end
end
-- Apply gravity force
for _, node in ipairs(visible_nodes) do
local gx, gy = gravity_force(node, center_x, center_y)
node.vx = node.vx + gx
node.vy = node.vy + gy
end
-- Apply forces with temperature-limited displacement
local max_displacement = 0
for _, node in ipairs(visible_nodes) do
-- Skip fixed nodes
if node.fx then
node.x = node.fx
else
local displacement = math.sqrt(node.vx * node.vx + node.vy * node.vy)
if displacement > 0 then
-- Limit displacement by temperature
local limited_displacement = math.min(displacement, state.temperature)
local factor = limited_displacement / displacement
local dx = node.vx * factor
local dy = node.vy * factor
node.x = node.x + dx
node.y = node.y + dy
if math.abs(dx) > max_displacement then
max_displacement = math.abs(dx)
end
if math.abs(dy) > max_displacement then
max_displacement = math.abs(dy)
end
end
end
if node.fy then
node.y = node.fy
end
-- Keep nodes within bounds
node.x = math.max(padding, math.min(width - padding, node.x))
node.y = math.max(padding, math.min(height - padding, node.y))
end
-- Cool down temperature
state.temperature = state.temperature * SETTINGS.COOLING_RATE
state.iteration = state.iteration + 1
-- Check convergence
state.converged = max_displacement < SETTINGS.MIN_VELOCITY
or state.iteration >= SETTINGS.MAX_ITERATIONS
return state.converged
end
---Runs the complete layout algorithm synchronously
---@param graph GraphData The graph data
---@param width number Canvas width
---@param height number Canvas height
---@param max_iterations number|nil Maximum iterations (defaults to SETTINGS.MAX_ITERATIONS)
function M.run_layout(graph, width, height, max_iterations)
max_iterations = max_iterations or SETTINGS.MAX_ITERATIONS
-- Initialize positions
M.initialize_positions(graph, width, height)
-- Create layout state
local state = types.create_layout_state(SETTINGS.INITIAL_TEMPERATURE)
-- Run until convergence
while not state.converged and state.iteration < max_iterations do
M.step(graph, state, width, height)
end
end
---Creates an animated layout that updates incrementally
---@param graph GraphData The graph data
---@param width number Canvas width
---@param height number Canvas height
---@param on_step fun(converged: boolean): nil Callback after each step
---@param frame_delay number|nil Delay between frames in ms (default 16ms ~60fps)
---@return GraphLayoutState The layout state (can be used to stop animation)
function M.start_animated_layout(graph, width, height, on_step, frame_delay)
frame_delay = frame_delay or 16
-- Initialize positions
M.initialize_positions(graph, width, height)
-- Create layout state
local state = types.create_layout_state(SETTINGS.INITIAL_TEMPERATURE)
state.running = true
-- Animation function
local function animate()
if not state.running then
return
end
local converged = M.step(graph, state, width, height)
if on_step then
on_step(converged)
end
if not converged and state.running then
state.timer = vim.defer_fn(animate, frame_delay)
else
state.running = false
end
end
-- Start animation
vim.defer_fn(animate, 0)
return state
end
---Stops an animated layout
---@param state GraphLayoutState The layout state
function M.stop_animated_layout(state)
state.running = false
if state.timer then
-- Timer will naturally stop on next check
state.timer = nil
end
end
---Adjusts layout after filter changes (re-runs partial layout)
---@param graph GraphData The graph data
---@param width number Canvas width
---@param height number Canvas height
---@param iterations number|nil Number of adjustment iterations
function M.adjust_after_filter(graph, width, height, iterations)
iterations = iterations or 50
local state = types.create_layout_state(SETTINGS.INITIAL_TEMPERATURE * 0.3)
for _ = 1, iterations do
if M.step(graph, state, width, height) then
break
end
end
end
---Centers the visible graph within the canvas
---@param graph GraphData The graph data
---@param width number Canvas width
---@param height number Canvas height
function M.center_graph(graph, width, height)
local min_x, max_x = math.huge, -math.huge
local min_y, max_y = math.huge, -math.huge
local visible_count = 0
for _, node in ipairs(graph.node_list) do
if node.visible then
min_x = math.min(min_x, node.x)
max_x = math.max(max_x, node.x)
min_y = math.min(min_y, node.y)
max_y = math.max(max_y, node.y)
visible_count = visible_count + 1
end
end
if visible_count == 0 then
return
end
local graph_center_x = (min_x + max_x) / 2
local graph_center_y = (min_y + max_y) / 2
local canvas_center_x = width / 2
local canvas_center_y = height / 2
local offset_x = canvas_center_x - graph_center_x
local offset_y = canvas_center_y - graph_center_y
for _, node in ipairs(graph.node_list) do
if node.visible then
node.x = node.x + offset_x
node.y = node.y + offset_y
end
end
end
return M