KececiLayout

| Documentation | Paper | |:-----------------:|:---------:| | | |

---

🌐 English

Kececi Layout (Keçeci Yerleşimi)

KececiLayout is a deterministic graph layout algorithm designed for visualizing linear or sequential structures with a characteristic "zig-zag" or "serpentine" pattern.

Python implementation of the Keçeci layout algorithm for graph visualization.

---

Description

This algorithm arranges nodes sequentially along a primary axis and offsets them alternately along a secondary axis. It's particularly useful for path graphs, chains, or showing progression.

Key Features: * Linear Focus: Ideal for visualizing paths, chains, or ordered processes. * Deterministic: Produces identical results for the same input. * Overlap Reduction: Prevents node collisions by spreading them across axes. * Parametric: Fully customizable with parameters like primary_spacing, secondary_spacing, primary_direction, and secondary_start.

=> v0.2.7: Curved, transparent, 3D, and expanding=True styles supported.

---

Installation

bash conda install bilgi::kececilayout -y pip install kececilayout

🔗 PyPI | Conda | GitHub

---

Usage

Example with NetworkX

```python import networkx as nx import matplotlib.pyplot as plt import kececilayout as kl

G = nx.pathgraph(10) pos = kl.kececilayoutv4( G, primaryspacing=1.0, secondaryspacing=0.5, primarydirection='top-down', secondary_start='right' )

plt.figure(figsize=(6, 8)) nx.draw(G, pos=pos, withlabels=True, nodecolor='skyblue', node_size=500) plt.title("Kececi Layout with NetworkX") plt.axis('equal') plt.show() ```

Example with iGraph

```python import igraph as ig import matplotlib.pyplot as plt from kececilayout import kececilayoutv4_igraph

G = ig.Graph.Ring(10, circular=False) poslist = kececilayoutv4igraph(G, primarydirection='left-to-right', secondarystart='up') layout = ig.Layout(pos_list)

fig, ax = plt.subplots(figsize=(8, 6)) ig.plot(G, target=ax, layout=layout, vertexlabel=[f"N{i}" for i in range(10)]) ax.setaspect('equal') plt.show() ```

Example with RustworkX

```python import rustworkx as rx import kececilayout as kl import matplotlib.pyplot as plt

G = rx.generators.pathgraph(10) pos = kl.kececilayoutv4(G, primarydirection='bottom-up')

Use matplotlib for drawing (see full example in repo)

```

Example with Networkit

```python import networkit as nk import kececilayout as kl import matplotlib.pyplot as plt

G = nk.graph.Graph(10) for i in range(9): G.addEdge(i, i+1) pos = kl.kececilayoutv4(G)

Draw with matplotlib

```

Example with Graphillion

```python import graphillion as gg import kececilayout as kl import matplotlib.pyplot as plt

universe = [(i, i+1) for i in range(1, 10)] gg.GraphSet.setuniverse(universe) gs = gg.GraphSet() pos = kl.kececilayout_v4(gs)

Draw with matplotlib

```

---

Supported Backends

• NetworkX
• igraph
• Rustworkx
• Networkit
• Graphillion

Note: All backends are supported via unified kececi_layout_v4 function.

---

Advanced Drawing Styles

Use draw_kececi for enhanced visualizations:

python kl.draw_kececi(G, style='curved') # Smooth curved edges kl.draw_kececi(G, style='transparent') # Opacity based on edge length kl.draw_kececi(G, style='3d') # 3D helix layout

---

License

MIT License. See LICENSE for details.

---

Citation

If this library was useful in your research, please cite:

bibtex @misc{kececi_2025_15313946, author = {Keçeci, Mehmet}, title = {kececilayout}, month = may, year = 2025, publisher = {Zenodo}, version = {0.2.7}, doi = {10.5281/zenodo.15313946}, url = {https://doi.org/10.5281/zenodo.15313946} }

---

🇹🇷 Türkçe

Keçeci Yerleşimi (Kececi Layout)

KececiLayout, doğrusal veya ardışık yapıları görselleştirmek için tasarlanmış, karakteristik bir "zıgzag" veya "yılanvari" desen oluşturan deterministik bir graf yerleşim algoritmasıdır.

Graf görselleştirme için Keçeci yerleşim algoritmasının Python uygulaması.

---

Açıklama

Bu algoritma, düğümleri birincil eksen boyunca sıralı olarak yerleştirir ve ikincil eksen boyunca dönüşümlü olarak kaydırır. Yol grafları, zincirler veya ilerlemeyi göstermek için özellikle kullanışlıdır.

Temel Özellikler: * Doğrusal Odak: Yollar, zincirler veya sıralı süreçler için idealdir. * Deterministik: Aynı giriş için her zaman aynı çıktıyı üretir. * Çakışmayı Azaltma: Düğümleri eksenler boyunca yayarak çakışmaları önler. * Parametrik: primary_spacing, secondary_spacing, primary_direction, secondary_start gibi parametrelerle özelleştirilebilir.

=> v0.2.7: Eğri, şeffaf, 3B ve expanding=True stilleri desteklenir.

---

Kurulum

bash conda install bilgi::kececilayout -y pip install kececilayout

🔗 PyPI | Conda | GitHub

---

Kullanım

NetworkX ile Örnek

```python import networkx as nx import matplotlib.pyplot as plt import kececilayout as kl

G = nx.pathgraph(10) pos = kl.kececilayoutv4( G, primaryspacing=1.0, secondaryspacing=0.5, primarydirection='top-down', secondary_start='right' )

plt.figure(figsize=(6, 8)) nx.draw(G, pos=pos, withlabels=True, nodecolor='skyblue', node_size=500) plt.title("Kececi Layout with NetworkX") plt.axis('equal') plt.show() ```

iGraph ile Örnek

```python import igraph as ig import matplotlib.pyplot as plt from kececilayout import kececilayoutv4_igraph

G = ig.Graph.Ring(10, circular=False) poslist = kececilayoutv4igraph(G, primarydirection='left-to-right', secondarystart='up') layout = ig.Layout(pos_list)

fig, ax = plt.subplots(figsize=(8, 6)) ig.plot(G, target=ax, layout=layout, vertexlabel=[f"N{i}" for i in range(10)]) ax.setaspect('equal') plt.show() ```

RustworkX ile Örnek

```python import rustworkx as rx import kececilayout as kl import matplotlib.pyplot as plt

G = rx.generators.pathgraph(10) pos = kl.kececilayoutv4(G, primarydirection='bottom-up')

Matplotlib ile çizim yapılabilir

```

Networkit ile Örnek

```python import networkit as nk import kececilayout as kl import matplotlib.pyplot as plt

G = nk.graph.Graph(10) for i in range(9): G.addEdge(i, i+1) pos = kl.kececilayoutv4(G)

Matplotlib ile çizim

```

Graphillion ile Örnek

```python import graphillion as gg import kececilayout as kl import matplotlib.pyplot as plt

universe = [(i, i+1) for i in range(1, 10)] gg.GraphSet.setuniverse(universe) gs = gg.GraphSet() pos = kl.kececilayout_v4(gs)

Matplotlib ile çizim

```

---

Desteklenen Kütüphaneler

• NetworkX
• igraph
• Rustworkx
• Networkit
• Graphillion

Not: Tüm kütüphaneler kececi_layout_v4 fonksiyonu ile desteklenir.

---

Gelişmiş Çizim Stilleri

draw_kececi ile gelişmiş görselleştirmeler:

python kl.draw_kececi(G, style='curved') # Eğri kenarlar kl.draw_kececi(G, style='transparent') # Kenar uzunluğuna göre şeffaflık kl.draw_kececi(G, style='3d') # 3B heliks yerleşimi

---

Lisans

MIT Lisansı. Detaylar için LICENSE dosyasına bakın.

---

Atıf

Araştırmanızda bu kütüphaneyi kullandıysanız, lütfen aşağıdaki gibi atıf yapın:

bibtex @misc{kececi_2025_15313946, author = {Keçeci, Mehmet}, title = {kececilayout}, month = may, year = 2025, publisher = {Zenodo}, version = {0.2.7}, doi = {10.5281/zenodo.15313946}, url = {https://doi.org/10.5281/zenodo.15313946} }

---

📚 Documentation

For full documentation, visit:
https://kececilayout.readthedocs.io

---

KececiLayout

| Documentation| Paper| |:----------------:|:--------:| |||

---

PyPI
Conda
DOI
License: MIT

---

Kececi Layout (Keçeci Yerleşimi): A deterministic graph layout algorithm designed for visualizing linear or sequential structures with a characteristic "zig-zag" or "serpentine" pattern.

Python implementation of the Keçeci layout algorithm for graph visualization.

---

Description / Açıklama

This algorithm arranges nodes sequentially along a primary axis and offsets them alternately along a secondary axis. It's particularly useful for path graphs, chains, or showing progression.

Bu algoritma, düğümleri birincil eksen boyunca sıralı olarak yerleştirir ve ikincil eksen boyunca dönüşümlü olarak kaydırır. Yol grafları, zincirler veya ilerlemeyi göstermek için özellikle kullanışlıdır.

=> 0.2.6: Curved, transparent, 3d, expanding=True

---

English Description

Keçeci Layout:

A deterministic node placement algorithm used in graph visualization. In this layout, nodes are arranged sequentially along a defined primary axis. Each subsequent node is then alternately offset along a secondary, perpendicular axis, typically moving to one side of the primary axis and then the other. Often, the magnitude of this secondary offset increases as nodes progress along the primary axis, creating a characteristic "zig-zag" or "serpentine" pattern.

Key Characteristics: * Linear Focus: Particularly useful for visualizing linear or sequential structures, such as paths, chains, or ordered processes. * Deterministic: Produces the exact same layout for the same graph and parameters every time. * Overlap Reduction: Helps prevent node collisions by spreading nodes out away from the primary axis. * Parametric: Can be customized using parameters such as the primary direction (e.g., top-down), the starting side for the secondary offset (e.g., start_right), and the spacing along both axes (primary_spacing, secondary_spacing).

---

Türkçe Tanımlama

Keçeci Yerleşimi (Keçeci Layout):

Graf görselleştirmede kullanılan deterministik bir düğüm yerleştirme algoritmasıdır. Bu yöntemde düğümler, belirlenen birincil (ana) eksen boyunca sıralı olarak yerleştirilir. Her bir sonraki düğüm, ana eksenin bir sağına bir soluna (veya bir üstüne bir altına) olmak üzere, ikincil eksen doğrultusunda dönüşümlü olarak kaydırılır. Genellikle, ana eksende ilerledikçe ikincil eksendeki kaydırma miktarı artar ve bu da karakteristik bir "zıgzag" veya "yılanvari" desen oluşturur.

Temel Özellikleri: * Doğrusal Odak: Özellikle yollar (paths), zincirler veya sıralı süreçler gibi doğrusal veya ardışık yapıları görselleştirmek için kullanışlıdır. * Deterministik: Aynı graf ve parametrelerle her zaman aynı sonucu üretir. * Çakışmayı Azaltma: Düğümleri ana eksenden uzağa yayarak çakışmaları önlemeye yardımcı olur. * Parametrik: Ana eksenin yönü (örn. top-down), ikincil kaydırmanın başlangıç yönü (örn. start_right) ve eksenler arası boşluklar (primary_spacing, secondary_spacing) gibi parametrelerle özelleştirilebilir.

---

Installation / Kurulum

```bash conda install bilgi::kececilayout -y

pip install kececilayout ``` https://anaconda.org/bilgi/kececilayout

https://pypi.org/project/KececiLayout/

https://github.com/WhiteSymmetry/kececilayout

https://zenodo.org/records/15313947

https://zenodo.org/records/15314329

---

Usage / Kullanım

The layout function generally accepts a graph object and returns positions.

Example with NetworkX

```python import networkx as nx import matplotlib.pyplot as plt import kececilayout as kl # Assuming the main function is imported like this import random

Create a graph

G = nx.path_graph(10)

Calculate layout positions using the generic function

(Assuming kl.kececilayoutv4 is the main/generic function)

pos = kl.kececilayoutv4(G, primaryspacing=1.0, secondaryspacing=0.5, primarydirection='top-down', secondarystart='right')

Draw the graph

plt.figure(figsize=(6, 8)) nx.draw(G, pos=pos, withlabels=True, nodecolor='skyblue', nodesize=500, fontsize=10) plt.title("Keçeci Layout with NetworkX") plt.axis('equal') # Ensure aspect ratio is equal plt.show() ```

```python import matplotlib.pyplot as plt import math import networkx as nx import kececilayout as kl import random

try: import kececilayout as kl except ImportError: print("Error: 'kececilayout.py' not found or could not be imported.") print("Please ensure the file containing kececilayout_v4 is accessible.") exit()

--- General Layout Parameters ---

LAYOUTPARAMS = { 'primaryspacing': 1.0, 'secondaryspacing': 0.6, # Make the zigzag noticeable 'primarydirection': 'top-down', 'secondarystart': 'right' } NNODES = 10 # Number of nodes in the example graph

=== NetworkX Example ===

try: import networkx as nx print("\n--- NetworkX Example ---")

# Generate graph (Path graph)
G_nx = nx.path_graph(N_NODES)
print(f"NetworkX graph generated: {G_nx.number_of_nodes()} nodes, {G_nx.number_of_edges()} edges")

# Calculate layout
print("Calculating Keçeci Layout...")
# Call the layout function from the imported module
pos_nx = kl.kececi_layout_v4(G_nx, **LAYOUT_PARAMS)
# print("NetworkX positions:", pos_nx) # Debug print if needed

# Plot
plt.figure(figsize=(6, 8)) # Suitable figure size for vertical layout
nx.draw(G_nx,               # NetworkX graph object
        pos=pos_nx,         # Positions calculated by Kececi Layout
        with_labels=True,   # Show node labels (indices)
        node_color='skyblue',# Node color
        node_size=700,      # Node size
        font_size=10,       # Label font size
        edge_color='gray')  # Edge color

plt.title(f"NetworkX ({N_NODES} Nodes) with Keçeci Layout") # Plot title
plt.xlabel("X Coordinate") # X-axis label
plt.ylabel("Y Coordinate") # Y-axis label
plt.axis('equal')       # Ensure equal aspect ratio for correct spacing perception
# plt.grid(False)         # Ensure grid is off
plt.show()              # Display the plot

except ImportError: print("NetworkX is not installed. Skipping this example.") except Exception as e: print(f"An error occurred in the NetworkX example: {e}") import traceback traceback.print_exc()

print("\n--- NetworkX Example Finished ---") ```

---

Example with iGraph

```python import igraph as ig import matplotlib.pyplot as plt

Assuming a specific function for igraph exists or the generic one handles it

from kececilayout import kececilayoutv4_igraph # Adjust import if needed import random

Create a graph

G = ig.Graph.Ring(10, circular=False) # Path graph equivalent for i in range(G.vcount()): G.vs[i]["name"] = f"N{i}"

Calculate layout positions (returns a list of coords)

poslist = kececilayoutv4igraph(G, primaryspacing=1.5, secondaryspacing=1.0, primarydirection='left-to-right', secondarystart='up') layout = ig.Layout(coords=pos_list)

Draw the graph

fig, ax = plt.subplots(figsize=(8, 6)) ig.plot( G, target=ax, layout=layout, vertexlabel=G.vs["name"], vertexcolor="lightblue", vertexsize=30 ) ax.settitle("Keçeci Layout with iGraph") ax.set_aspect('equal', adjustable='box') plt.show() ```

```python import matplotlib.pyplot as plt import math import igraph as ig import kececilayout as kl

try: import kececilayout as kl except ImportError: print("Error: 'kececilayout.py' not found or could not be imported.") print("Please ensure the file containing kececilayout_v4 is accessible.") exit()

--- General Layout Parameters ---

LAYOUTPARAMS = { 'primaryspacing': 1.0, 'secondaryspacing': 0.6, # Make the zigzag noticeable 'primarydirection': 'top-down', 'secondarystart': 'right' } NNODES = 10 # Number of nodes in the example graph

=== igraph Example ===

try: import igraph as ig print("\n--- igraph Example ---")

# Generate graph (Path graph using Ring(circular=False))
G_ig = ig.Graph.Ring(N_NODES, directed=False, circular=False)
print(f"igraph graph generated: {G_ig.vcount()} vertices, {G_ig.ecount()} edges")

# Calculate layout
print("Calculating Keçeci Layout...")
# Call the layout function from the imported module
pos_ig = kl.kececi_layout_v4(G_ig, **LAYOUT_PARAMS)
# print("igraph positions (dict):", pos_ig) # Debug print if needed

# Convert positions dict to list ordered by vertex index for ig.plot
layout_list_ig = []
plot_possible = True
if pos_ig: # Check if dictionary is not empty
    try:
        # Generate list: [pos_ig[0], pos_ig[1], ..., pos_ig[N-1]]
        layout_list_ig = [pos_ig[i] for i in range(G_ig.vcount())]
        # print("igraph layout (list):", layout_list_ig) # Debug print if needed
    except KeyError as e:
         print(f"ERROR: Key {e} not found while creating position list for igraph.")
         print("The layout function might not have returned positions for all vertices.")
         plot_possible = False # Cannot plot if list is incomplete
else:
    print("ERROR: Keçeci Layout returned empty positions for igraph.")
    plot_possible = False

# Plot using igraph's plotting capabilities
print("Plotting graph using igraph.plot...")
fig, ax = plt.subplots(figsize=(6, 8)) # Generate matplotlib figure and axes

if plot_possible:
    ig.plot(G_ig,
            target=ax,           # Draw on the matplotlib axes
            layout=layout_list_ig, # Use the ORDERED LIST of coordinates
            vertex_label=[str(i) for i in range(G_ig.vcount())], # Labels 0, 1,...
            vertex_color='lightgreen',
            vertex_size=30,      # Note: igraph vertex_size scale differs
            edge_color='gray')
else:
     ax.text(0.5, 0.5, "Plotting failed:\nMissing or incomplete layout positions.",
             ha='center', va='center', color='red', fontsize=12) # Error message on plot

ax.set_title(f"igraph ({N_NODES} Nodes) with Keçeci Layout") # Plot title
ax.set_aspect('equal', adjustable='box') # Ensure equal aspect ratio
# ax.grid(False) # Ensure grid is off
plt.show()              # Display the plot

except ImportError: print("python-igraph is not installed. Skipping this example.") except Exception as e: print(f"An error occurred in the igraph example: {e}") import traceback traceback.print_exc()

print("\n--- igraph Example Finished ---") ```

---

Example with RustworkX

```python import matplotlib.pyplot as plt from matplotlib.collections import LineCollection # Efficient edge drawing import math import rustworkx as rx import kececilayout as kl import random

try: import kececilayout as kl except ImportError: print("Error: 'kececilayout.py' not found or could not be imported.") print("Please ensure the file containing kececilayout_v4 is accessible.") exit()

--- General Layout Parameters ---

LAYOUTPARAMS = { 'primaryspacing': 1.0, 'secondaryspacing': 0.6, # Make the zigzag noticeable 'primarydirection': 'top-down', 'secondarystart': 'right' } NNODES = 10 # Number of nodes in the example graph

=== Rustworkx Example ===

try: import rustworkx as rx print("\n--- Rustworkx Example ---")

# Generate graph (Path graph)
G_rx = rx.generators.path_graph(N_NODES)
print(f"Rustworkx graph generated: {G_rx.num_nodes()} nodes, {G_rx.num_edges()} edges")

# Calculate layout
print("Calculating Keçeci Layout...")
# Call the layout function from the imported module
pos_rx = kl.kececi_layout_v4(G_rx, **LAYOUT_PARAMS)
# print("Rustworkx positions:", pos_rx) # Debug print if needed

# Plot using Matplotlib directly (Rustworkx doesn't have a built-in draw)
print("Plotting graph using Matplotlib...")
plt.figure(figsize=(6, 8))
ax = plt.gca() # Get current axes

node_indices_rx = G_rx.node_indices() # Get node indices [0, 1, ...]

# Check if all nodes have positions
if not all(idx in pos_rx for idx in node_indices_rx):
     print("ERROR: Rustworkx positions dictionary does not cover all nodes!")
     # Decide how to handle: exit, plot partial, etc.
else:
    # Draw nodes
    x_coords_rx = [pos_rx[i][0] for i in node_indices_rx]
    y_coords_rx = [pos_rx[i][1] for i in node_indices_rx]
    ax.scatter(x_coords_rx, y_coords_rx, s=700, c='#88CCEE', zorder=2, label='Nodes') # Skyblue color

    # Draw labels
    for i in node_indices_rx:
        ax.text(pos_rx[i][0], pos_rx[i][1], str(i), ha='center', va='center', fontsize=10, zorder=3)

    # Draw edges using LineCollection for efficiency
    edge_lines = []
    for u, v in G_rx.edge_list(): # Get list of edges (node index pairs)
        if u in pos_rx and v in pos_rx:
            # Segment format: [(x1, y1), (x2, y2)]
            edge_lines.append([pos_rx[u], pos_rx[v]])
        else:
            print(f"Warning: Position not found for edge ({u},{v}) in Rustworkx graph.")

    if edge_lines:
        lc = LineCollection(edge_lines, colors='gray', linewidths=1.0, zorder=1, label='Edges')
        ax.add_collection(lc) # Add edges to the plot axes

plt.title(f"Rustworkx ({N_NODES} Nodes) with Keçeci Layout (Matplotlib)") # Plot title
plt.xlabel("X Coordinate") # X-axis label
plt.ylabel("Y Coordinate") # Y-axis label
plt.axis('equal')       # Ensure equal aspect ratio
# plt.grid(False)         # Ensure grid is off
plt.show()              # Display the plot

except ImportError: print("Rustworkx is not installed. Skipping this example.") except Exception as e: print(f"An error occurred in the Rustworkx example: {e}") import traceback traceback.print_exc()

print("\n--- Rustworkx Example Finished ---") ```

---

Example with Networkit

```python import matplotlib.pyplot as plt from matplotlib.collections import LineCollection # Efficient edge drawing import math import networkit as nk import kececilayout as kl import random

try: import kececilayout as kl except ImportError: print("Error: 'kececilayout.py' not found or could not be imported.") print("Please ensure the file containing kececilayout_v4 is accessible.") exit()

--- General Layout Parameters ---

LAYOUTPARAMS = { 'primaryspacing': 1.0, 'secondaryspacing': 0.6, # Make the zigzag noticeable 'primarydirection': 'top-down', 'secondarystart': 'right' } NNODES = 10 # Number of nodes in the example graph

=== Networkit Example ===

try: import networkit as nk print("\n--- Networkit Example ---")

# Generate graph (Path graph, manually)
G_nk = nk.graph.Graph(N_NODES, weighted=False, directed=False) # Generate empty graph container
print("Empty Networkit graph generated.")
# Add nodes first (Networkit often requires this)
for i in range(N_NODES):
    if not G_nk.hasNode(i): # Check if node already exists (good practice)
         G_nk.addNode()
print(f"{G_nk.numberOfNodes()} nodes added.")
# Add edges
for i in range(N_NODES - 1):
    G_nk.addEdge(i, i+1) # Add edges 0-1, 1-2, ...
print(f"Networkit graph constructed: {G_nk.numberOfNodes()} nodes, {G_nk.numberOfEdges()} edges")

# Calculate layout
print("Calculating Keçeci Layout...")
# Call the layout function from the imported module
pos_nk = kl.kececi_layout_v4(G_nk, **LAYOUT_PARAMS)
# print("Networkit positions:", pos_nk) # Debug print if needed

# Plot using Matplotlib directly (Networkit doesn't have a simple built-in draw)
print("Plotting graph using Matplotlib...")
plt.figure(figsize=(6, 8))
ax = plt.gca() # Get current axes

node_indices_nk = sorted(list(G_nk.iterNodes())) # Get node indices [0, 1, ...]

# Check if all nodes have positions
if not all(idx in pos_nk for idx in node_indices_nk):
     print("ERROR: Networkit positions dictionary does not cover all nodes!")
else:
    # Draw nodes
    x_coords_nk = [pos_nk[i][0] for i in node_indices_nk]
    y_coords_nk = [pos_nk[i][1] for i in node_indices_nk]
    ax.scatter(x_coords_nk, y_coords_nk, s=700, c='coral', zorder=2, label='Nodes')

    # Draw labels
    for i in node_indices_nk:
        ax.text(pos_nk[i][0], pos_nk[i][1], str(i), ha='center', va='center', fontsize=10, zorder=3)

    # Draw edges using LineCollection
    edge_lines_nk = []
    for u, v in G_nk.iterEdges(): # Iterate through edges
        if u in pos_nk and v in pos_nk:
             edge_lines_nk.append([pos_nk[u], pos_nk[v]])
        else:
             print(f"Warning: Position not found for edge ({u},{v}) in Networkit graph.")

    if edge_lines_nk:
         lc_nk = LineCollection(edge_lines_nk, colors='gray', linewidths=1.0, zorder=1, label='Edges')
         ax.add_collection(lc_nk)

plt.title(f"Networkit ({N_NODES} Nodes) with Keçeci Layout (Matplotlib)") # Plot title
plt.xlabel("X Coordinate") # X-axis label
plt.ylabel("Y Coordinate") # Y-axis label
plt.axis('equal')       # Ensure equal aspect ratio
# plt.grid(False)         # Ensure grid is off
plt.show()              # Display the plot

except ImportError: print("Networkit is not installed. Skipping this example.") except Exception as e: print(f"An error occurred in the Networkit example: {e}") import traceback traceback.print_exc()

print("\n--- Networkit Example Finished ---") ```

---

Example with Graphillion

```python import matplotlib.pyplot as plt from matplotlib.collections import LineCollection # Efficient edge drawing import math import itertools # Graphillion might implicitly need itertools if findmaxnode_id uses it internally import graphillion as gg import kececilayout as kl import random

try: import kececilayout as kl except ImportError: print("Error: 'kececilayout.py' not found or could not be imported.") print("Please ensure the file containing kececilayout_v4 is accessible.") exit()

--- General Layout Parameters ---

LAYOUTPARAMS = { 'primaryspacing': 1.0, 'secondaryspacing': 0.6, # Make the zigzag noticeable 'primarydirection': 'top-down', 'secondarystart': 'right' } NNODES = 10 # Number of nodes in the example graph (will be 1 to N_NODES)

=== Graphillion Example ===

try: import graphillion as gg print("\n--- Graphillion Example ---")

# Define the universe of possible edges (Path graph, 1-based indexing common)
universe = []
# Edges (1,2), (2,3), ..., (N_NODES-1, N_NODES)
for i in range(1, N_NODES):
    universe.append((i, i + 1))
gg.GraphSet.set_universe(universe)
max_node_gg = N_NODES # We know the max node ID for this simple case
print(f"Graphillion universe defined: {len(universe)} edges, max node ID {max_node_gg}")

# Generate a GraphSet object (can be empty, layout function uses the universe)
# The layout function provided seems to derive nodes from the universe edges.
gs = gg.GraphSet()

# Calculate layout
print("Calculating Keçeci Layout...")
# Call the layout function; it should handle the Graphillion GraphSet object
# and likely use 1-based indexing based on the universe.
pos_gg = kl.kececi_layout_v4(gs, **LAYOUT_PARAMS)
# print("Graphillion positions:", pos_gg) # Debug print if needed

# Plot using Matplotlib directly (Graphillion has no plotting)
print("Plotting graph using Matplotlib...")
plt.figure(figsize=(6, 8))
ax = plt.gca() # Get current axes

# Node indices are expected to be 1, 2, ... N_NODES from the universe
node_indices_gg = sorted(pos_gg.keys())

# Check if all expected nodes (1 to N_NODES) have positions
expected_nodes = set(range(1, N_NODES + 1))
if not expected_nodes.issubset(set(node_indices_gg)):
     print(f"ERROR: Graphillion positions missing expected nodes. Found: {node_indices_gg}, Expected: {list(expected_nodes)}")
else:
    # Draw nodes
    x_coords_gg = [pos_gg[i][0] for i in node_indices_gg]
    y_coords_gg = [pos_gg[i][1] for i in node_indices_gg]
    ax.scatter(x_coords_gg, y_coords_gg, s=700, c='gold', zorder=2, label='Nodes')

    # Draw labels (using the 1-based indices)
    for i in node_indices_gg:
        ax.text(pos_gg[i][0], pos_gg[i][1], str(i), ha='center', va='center', fontsize=10, zorder=3)

    # Draw edges using LineCollection (from the defined universe)
    edge_lines_gg = []
    for u, v in universe: # Use the universe edges
        if u in pos_gg and v in pos_gg:
             edge_lines_gg.append([pos_gg[u], pos_gg[v]])
        else:
             print(f"Warning: Position not found for universe edge ({u},{v}) in Graphillion.")

    if edge_lines_gg:
        lc_gg = LineCollection(edge_lines_gg, colors='gray', linewidths=1.0, zorder=1, label='Edges')
        ax.add_collection(lc_gg)

plt.title(f"Graphillion ({N_NODES} Nodes) with Keçeci Layout (Matplotlib)") # Plot title
plt.xlabel("X Coordinate") # X-axis label
plt.ylabel("Y Coordinate") # Y-axis label
plt.axis('equal')       # Ensure equal aspect ratio
# plt.grid(False)         # Ensure grid is off
plt.show()              # Display the plot

except ImportError: print("Graphillion is not installed. Skipping this example.") except Exception as e: print(f"An error occurred in the Graphillion example: {e}") import traceback traceback.print_exc()

print("\n--- Graphillion Example Finished ---") ```

---

Supported Backends / Desteklenen Kütüphaneler

The layout functions are designed to work with graph objects from the following libraries:

• NetworkX: (networkx.Graph, networkx.DiGraph, etc.)
• igraph: (igraph.Graph)
• Rustworkx: (Requires appropriate conversion or adapter function)
• Networkit: (Requires appropriate conversion or adapter function)
• Graphillion: (Requires appropriate conversion or adapter function)

Note: Direct support might vary. Check specific function documentation for compatibility details.

---

License / Lisans

This project is licensed under the MIT License. See the LICENSE file for details.

```

Ek Notlar:

• Rozetler (Badges): Başlangıçta PyPI ve Lisans rozetleri ekledim (yorum satırı içinde). Eğer projeniz PyPI'da yayınlandıysa veya bir CI/CD süreci varsa, ilgili rozetleri eklemek iyi bir pratiktir.
• LICENSE Dosyası: LICENSE bölümünde bir LICENSE dosyasına referans verdim. Projenizin kök dizininde MIT lisans metnini içeren bir LICENSE dosyası oluşturduğunuzdan emin olun.
• İçe Aktarma Yolları: Örneklerde import kececilayout as kl veya from kececilayout import kececi_layout_v4_igraph gibi varsayımsal içe aktarma yolları kullandım. Kendi paket yapınıza göre bunları ayarlamanız gerekebilir.
• Fonksiyon Adları: Örneklerde kececi_layout_v4 ve kececi_layout_v4_igraph gibi fonksiyon adlarını kullandım. Gerçek fonksiyon adlarınız farklıysa bunları güncelleyin.
• Görselleştirme: Örneklere matplotlib.pyplot kullanarak temel görselleştirme adımlarını ekledim, bu da kullanıcıların sonucu nasıl görebileceğini gösterir. Eksen oranlarını eşitlemek (axis('equal') veya set_aspect('equal')) layout'un doğru görünmesi için önemlidir. ```

Citation

If this library was useful to you in your research, please cite us. Following the GitHub citation standards, here is the recommended citation.

BibTeX

```bibtex @misc{kececi202515313946, author = {Keçeci, Mehmet}, title = {kececilayout}, month = may, year = 2025, publisher = {PyPI, Anaconda, Github, Zenodo}, version = {0.2.0}, doi = {10.5281/zenodo.15313946}, url = {https://doi.org/10.5281/zenodo.15313946}, }

@misc{kececi202515314329, author = {Keçeci, Mehmet}, title = {Keçeci Layout}, month = may, year = 2025, publisher = {Zenodo}, version = {1.0.0}, doi = {10.5281/zenodo.15314329}, url = {https://doi.org/10.5281/zenodo.15314329}, } ```

APA

```

Keçeci, M. (2025). Deterministic Visualization of Distribution Power Grids: Integration of Power Grid Model and Keçeci Layout. Open Science Articles (OSAs), Zenodo. https://doi.org/10.5281/zenodo.16934620

Keçeci, M. (2025). Graf Teorisi Eğitiminde Yeni Bir Araç: Z3 ve Keçeci Dizilimi ile Hamilton Probleminin İnteraktif Keşfi. Open Science Articles (OSAs), Zenodo. https://doi.org/10.5281/zenodo.16883657

Keçeci, M. (2025). The Keçeci Layout: A Deterministic Visualisation Framework for the Structural Analysis of Ordered Systems in Chemistry and Environmental Science. Open Science Articles (OSAs), Zenodo. https://doi.org/10.5281/zenodo.16696713

Keçeci, M. (2025). The Keçeci Layout: A Deterministic, Order-Preserving Visualization Algorithm for Structured Systems. Open Science Articles (OSAs), Zenodo. https://doi.org/10.5281/zenodo.16526798

Keçeci, M. (2025). Keçeci Deterministic Zigzag Layout. WorkflowHub. https://doi.org/10.48546/workflowhub.document.31.1

Keçeci, M. (2025). Keçeci Zigzag Layout Algorithm. Authorea. https://doi.org/10.22541/au.175087581.16524538/v1

Keçeci, M. (2025). The Keçeci Layout: A Structural Approach for Interdisciplinary Scientific Analysis. Open Science Articles (OSAs), Zenodo. https://doi.org/10.5281/zenodo.15792684

Keçeci, M. (2025). When Nodes Have an Order: The Keçeci Layout for Structured System Visualization. HAL open science. https://hal.science/hal-05143155; https://doi.org/10.13140/RG.2.2.19098.76484

Keçeci, M. (2025). The Keçeci Layout: A Cross-Disciplinary Graphical Framework for Structural Analysis of Ordered Systems. Authorea. https://doi.org/10.22541/au.175156702.26421899/v1

Keçeci, M. (2025). Beyond Traditional Diagrams: The Keçeci Layout for Structural Thinking. Knowledge Commons. https://doi.org/10.17613/v4w94-ak572

Keçeci, M. (2025). The Keçeci Layout: A Structural Approach for Interdisciplinary Scientific Analysis. figshare. Journal contribution. https://doi.org/10.6084/m9.figshare.29468135

Keçeci, M. (2025, July 3). The Keçeci Layout: A Structural Approach for Interdisciplinary Scientific Analysis. OSF. https://doi.org/10.17605/OSF.IO/9HTG3

Keçeci, M. (2025). Beyond Topology: Deterministic and Order-Preserving Graph Visualization with the Keçeci Layout. WorkflowHub. https://doi.org/10.48546/workflowhub.document.34.4

Keçeci, M. (2025). A Graph-Theoretic Perspective on the Keçeci Layout: Structuring Cross-Disciplinary Inquiry. Preprints. https://doi.org/10.20944/preprints202507.0589.v1

Keçeci, M. (2025). Keçeci Layout. Open Science Articles (OSAs), Zenodo. https://doi.org/10.5281/zenodo.15314328

Keçeci, M. (2025). kececilayout [Data set]. WorkflowHub. https://doi.org/10.48546/workflowhub.datafile.17.1

Keçeci, M. (2025, May 1). Kececilayout. Open Science Articles (OSAs), Zenodo. https://doi.org/10.5281/zenodo.15313946

```

Chicago

```

Keçeci, Mehmet. The Keçeci Layout: A Deterministic Visualisation Framework for the Structural Analysis of Ordered Systems in Chemistry and Environmental Science. Open Science Articles (OSAs), Zenodo, 2025. https://doi.org/10.5281/zenodo.16696713

Keçeci, Mehmet. The Keçeci Layout: A Deterministic, Order-Preserving Visualization Algorithm for Structured Systems. Open Science Articles (OSAs), Zenodo, 2025. https://doi.org/10.5281/zenodo.16526798

Keçeci, Mehmet. kececilayout [Data set]. WorkflowHub, 2025. https://doi.org/10.48546/workflowhub.datafile.17.1

Keçeci, Mehmet. "Kececilayout". Open Science Articles (OSAs), Zenodo, 2025. https://doi.org/10.5281/zenodo.15313946.

Keçeci, Mehmet. "Keçeci Layout". Open Science Articles (OSAs), Zenodo, 2025. https://doi.org/10.5281/zenodo.15314328. ```