Version 0.1.5

examples/flame_matplotlib.py

@@ -0,0 +1,62 @@
+"""
+Example: Flame Chart with Matplotlib Backend
+
+This example demonstrates how to create a flame chart visualization
+using the matplotlib backend. Flame charts are useful for visualizing
+hierarchical profiling data, showing function call stacks and their
+execution times.
+"""
+
+from maxplotlib import Canvas
+
+# Example profiling data: function call hierarchy
+# Each function has: label, parent index (None for root), and duration
+labels = [
+    "main()",  # 0 - root
+    "process_data()",  # 1 - child of main
+    "load_file()",  # 2 - child of process_data
+    "parse_json()",  # 3 - child of process_data
+    "validate()",  # 4 - child of process_data
+    "compute()",  # 5 - child of main
+    "algorithm_a()",  # 6 - child of compute
+    "algorithm_b()",  # 7 - child of compute
+    "save_results()",  # 8 - child of main
+]
+
+parents = [
+    None,  # main() is root
+    0,  # process_data() called by main()
+    1,  # load_file() called by process_data()
+    1,  # parse_json() called by process_data()
+    1,  # validate() called by process_data()
+    0,  # compute() called by main()
+    5,  # algorithm_a() called by compute()
+    5,  # algorithm_b() called by compute()
+    0,  # save_results() called by main()
+]
+
+# Duration of each function call (in milliseconds)
+values = [100, 40, 10, 15, 15, 50, 25, 25, 10]
+
+# Start times for each function (when they begin execution)
+start_times = [0, 0, 0, 10, 25, 40, 40, 65, 90]
+
+# Create canvas and add flame chart
+canvas = Canvas(nrows=1, ncols=1, figsize=(12, 6))
+canvas.flame_chart(
+    labels=labels,
+    parents=parents,
+    values=values,
+    start_times=start_times,
+    colormap="viridis",
+    edgecolor="black",
+)
+
+# Configure the plot
+canvas.set_xlabel("Time (ms)")
+canvas.set_ylabel("Stack Depth")
+canvas.set_title("Flame Chart: Function Call Hierarchy")
+
+# Save the figure
+canvas.savefig("flame_matplotlib.png", backend="matplotlib")
+print("Flame chart saved as flame_matplotlib.png")

examples/flame_plotext.py

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+"""
+Example: Flame Chart with Plotext Backend
+
+This example demonstrates how to create a flame chart visualization
+using the plotext backend for terminal/console output.
+"""
+
+from maxplotlib import Canvas
+
+# Example profiling data: function call hierarchy
+labels = [
+    "main()",  # 0 - root
+    "process_data()",  # 1 - child of main
+    "load_file()",  # 2 - child of process_data
+    "parse_json()",  # 3 - child of process_data
+    "validate()",  # 4 - child of process_data
+    "compute()",  # 5 - child of main
+    "algorithm_a()",  # 6 - child of compute
+    "algorithm_b()",  # 7 - child of compute
+    "save_results()",  # 8 - child of main
+]
+
+parents = [
+    None,  # main() is root
+    0,  # process_data() called by main()
+    1,  # load_file() called by process_data()
+    1,  # parse_json() called by process_data()
+    1,  # validate() called by process_data()
+    0,  # compute() called by main()
+    5,  # algorithm_a() called by compute()
+    5,  # algorithm_b() called by compute()
+    0,  # save_results() called by main()
+]
+
+# Duration of each function call (in milliseconds)
+values = [100, 40, 10, 15, 15, 50, 25, 25, 10]
+
+# Start times for each function (when they begin execution)
+start_times = [0, 0, 0, 10, 25, 40, 40, 65, 90]
+
+# Create canvas and add flame chart
+canvas = Canvas(nrows=1, ncols=1)
+canvas.flame_chart(
+    labels=labels,
+    parents=parents,
+    values=values,
+    start_times=start_times,
+    colormap="viridis",
+)
+
+# Configure the plot
+canvas.set_xlabel("Time (ms)")
+canvas.set_ylabel("Stack Depth")
+canvas.set_title("Flame Chart: Function Call Hierarchy")
+
+# Save the figure
+canvas.savefig("flame_plotext.txt", backend="plotext")
+print("Flame chart saved as flame_plotext.txt")

examples/flame_plotly.py

@@ -0,0 +1,60 @@
+"""
+Example: Flame Chart with Plotly Backend
+
+This example demonstrates how to create an interactive flame chart
+using the plotly backend. The interactive nature allows zooming and
+hovering over function calls to see details.
+"""
+
+from maxplotlib import Canvas
+
+# Example profiling data: function call hierarchy
+labels = [
+    "main()",  # 0 - root
+    "process_data()",  # 1 - child of main
+    "load_file()",  # 2 - child of process_data
+    "parse_json()",  # 3 - child of process_data
+    "validate()",  # 4 - child of process_data
+    "compute()",  # 5 - child of main
+    "algorithm_a()",  # 6 - child of compute
+    "algorithm_b()",  # 7 - child of compute
+    "save_results()",  # 8 - child of main
+]
+
+parents = [
+    None,  # main() is root
+    0,  # process_data() called by main()
+    1,  # load_file() called by process_data()
+    1,  # parse_json() called by process_data()
+    1,  # validate() called by process_data()
+    0,  # compute() called by main()
+    5,  # algorithm_a() called by compute()
+    5,  # algorithm_b() called by compute()
+    0,  # save_results() called by main()
+]
+
+# Duration of each function call (in milliseconds)
+values = [100, 40, 10, 15, 15, 50, 25, 25, 10]
+
+# Start times for each function (when they begin execution)
+start_times = [0, 0, 0, 10, 25, 40, 40, 65, 90]
+
+# Create canvas and add flame chart
+canvas = Canvas(nrows=1, ncols=1, figsize=(12, 6))
+canvas.flame_chart(
+    labels=labels,
+    parents=parents,
+    values=values,
+    start_times=start_times,
+    colormap="Plasma",
+    edgecolor="black",
+)
+
+# Configure the plot
+canvas.set_xlabel("Time (ms)")
+canvas.set_ylabel("Stack Depth")
+canvas.set_title("Interactive Flame Chart: Function Call Hierarchy")
+
+# Save the figure
+canvas.savefig("flame_plotly.html", backend="plotly")
+print("Interactive flame chart saved as flame_plotly.html")

examples/flame_tikz.py

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+"""
+Example: Flame Chart with TikzFigure Backend
+
+This example demonstrates how to create a flame chart visualization
+using the tikzfigure backend for LaTeX/PDF output.
+"""
+
+from maxplotlib import Canvas
+
+# Example profiling data: function call hierarchy
+labels = [
+    "main()",  # 0 - root
+    "process_data()",  # 1 - child of main
+    "load_file()",  # 2 - child of process_data
+    "parse_json()",  # 3 - child of process_data
+    "validate()",  # 4 - child of process_data
+    "compute()",  # 5 - child of main
+    "algorithm_a()",  # 6 - child of compute
+    "algorithm_b()",  # 7 - child of compute
+    "save_results()",  # 8 - child of main
+]
+
+parents = [
+    None,  # main() is root
+    0,  # process_data() called by main()
+    1,  # load_file() called by process_data()
+    1,  # parse_json() called by process_data()
+    1,  # validate() called by process_data()
+    0,  # compute() called by main()
+    5,  # algorithm_a() called by compute()
+    5,  # algorithm_b() called by compute()
+    0,  # save_results() called by main()
+]
+
+# Duration of each function call (in milliseconds)
+values = [100, 40, 10, 15, 15, 50, 25, 25, 10]
+
+# Start times for each function (when they begin execution)
+start_times = [0, 0, 0, 10, 25, 40, 40, 65, 90]
+
+# Create canvas and add flame chart
+canvas = Canvas(nrows=1, ncols=1)
+canvas.flame_chart(
+    labels=labels,
+    parents=parents,
+    values=values,
+    start_times=start_times,
+)
+
+# Configure the plot
+canvas.set_xlabel("Time (ms)")
+canvas.set_ylabel("Stack Depth")
+canvas.set_title("Flame Chart: Function Call Hierarchy")
+
+# Save the figure
+canvas.savefig("flame_tikz.pdf", backend="tikzfigure")
+print("Flame chart saved as flame_tikz.pdf")

examples/gantt_matplotlib.py

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+import numpy as np
+
+from maxplotlib import Canvas
+
+
+def main() -> None:
+    # Define project tasks
+    tasks = [
+        "Planning",
+        "Design",
+        "Development",
+        "Testing",
+        "Deployment",
+        "Documentation",
+    ]
+
+    # Start times (in days from project start)
+    start_times = np.array([0, 5, 10, 25, 35, 30])
+
+    # Duration of each task (in days)
+    durations = np.array([5, 5, 15, 10, 5, 10])
+
+    # Create canvas
+    canvas = Canvas(width="14cm", ratio=0.6, dpi=150)
+
+    # Add gantt chart
+    canvas.gantt(
+        tasks=tasks,
+        start_times=start_times,
+        durations=durations,
+        color="steelblue",
+        alpha=0.7,
+        edgecolor="black",
+        label="Project Tasks",
+    )
+
+    # Configure plot
+    canvas.set_title("Project Timeline - Gantt Chart")
+    canvas.set_xlabel("Days from Project Start")
+    canvas.set_ylabel("Tasks")
+    canvas.set_grid(True)
+    canvas.set_xlim(0, 45)
+
+    # Save figure
+    canvas.savefig("gantt_matplotlib.png", backend="matplotlib")
+    print("Gantt chart saved as gantt_matplotlib.png")
+
+
+if __name__ == "__main__":
+    main()

examples/gantt_plotext.py

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+import numpy as np
+
+from maxplotlib import Canvas
+
+
+def main() -> None:
+    # Define project tasks
+    tasks = [
+        "Planning",
+        "Design",
+        "Development",
+        "Testing",
+        "Deployment",
+        "Documentation",
+    ]
+
+    # Start times (in days from project start)
+    start_times = np.array([0, 5, 10, 25, 35, 30])
+
+    # Duration of each task (in days)
+    durations = np.array([5, 5, 15, 10, 5, 10])
+
+    # Create canvas
+    canvas = Canvas(width="14cm", ratio=0.6)
+
+    # Add gantt chart
+    canvas.gantt(
+        tasks=tasks,
+        start_times=start_times,
+        durations=durations,
+        color="cyan",
+        label="Project Tasks",
+    )
+
+    # Configure plot
+    canvas.set_title("Project Timeline - Gantt Chart (Plotext)")
+    canvas.set_xlabel("Days from Project Start")
+    canvas.set_ylabel("Tasks")
+    canvas.set_grid(True)
+    canvas.set_xlim(0, 45)
+
+    # Save figure (plotext renders to terminal)
+    canvas.savefig("gantt_plotext.txt", backend="plotext")
+    print("Gantt chart saved as gantt_plotext.txt")
+
+
+if __name__ == "__main__":
+    main()

examples/gantt_plotly.py

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+import numpy as np
+
+from maxplotlib import Canvas
+
+
+def main() -> None:
+    # Define project tasks
+    tasks = [
+        "Planning",
+        "Design",
+        "Development",
+        "Testing",
+        "Deployment",
+        "Documentation",
+    ]
+
+    # Start times (in days from project start)
+    start_times = np.array([0, 5, 10, 25, 35, 30])
+
+    # Duration of each task (in days)
+    durations = np.array([5, 5, 15, 10, 5, 10])
+
+    # Create canvas
+    canvas = Canvas(width="14cm", ratio=0.6)
+
+    # Add gantt chart
+    canvas.gantt(
+        tasks=tasks,
+        start_times=start_times,
+        durations=durations,
+        color="steelblue",
+        alpha=0.7,
+        label="Project Tasks",
+    )
+
+    # Configure plot
+    canvas.set_title("Project Timeline - Gantt Chart (Plotly)")
+    canvas.set_xlabel("Days from Project Start")
+    canvas.set_ylabel("Tasks")
+    canvas.set_grid(True)
+    canvas.set_xlim(0, 45)
+
+    # Save figure
+    canvas.savefig("gantt_plotly.html", backend="plotly")
+    print("Gantt chart saved as gantt_plotly.html")
+
+
+if __name__ == "__main__":
+    main()