Swept Surface

[OberGue]

Overview

swept is a tool within the splinepy.helpme.create environment to provide sweeping a cross section along a trajectory.

Addressed issues

• Referring to this discussion topic.

Showcase

In order to create a spline patch of a spaghetti pasta, we can pass a circular cross-section and an arbitrary trajectory. The result can be both a 3-dimensional volume spline or a 2-dimensional shell spline, depending on the dimension of your cross-section.

import splinepy
spaghetti = splinepy.helpme.create.swept(cross_section, trajectory)

Checklists

• [ ] Documentations are up-to-date.
• [x] Added example(s)
• [x] Added test(s)

Summary by CodeRabbit

• New Features

  • Introduced a demonstration script for creating and visualizing swept surfaces and solids using spline representations.
  • Enhanced the sweeping process with advanced mathematical techniques for better control over rotation and placement of splines.

• Tests

  • Added multiple test functions to evaluate swept spline functionality, including basic operations, comparison with extruded surfaces, and validation of control point placement and cross-section alignment.

[jzwar]

Nice, can you post some screenshots?

[OberGue]

Nice, can you post some screenshots?

Sure! Be aware that work is still in progress.

[coderabbitai[bot]]

Walkthrough

The recent updates introduce a new example script for creating and visualizing swept surfaces and solids using spline representations in the splinepy library. Enhancements to the swept function allow for improved control over the sweeping process. The changes also involve the addition of various cross-section shapes and their visualization, along with new test cases to ensure functionality.

Changes

Files	Change Summaries
examples/show_swept.py	Added functionality to demonstrate the creation and visualization of swept surfaces and solids, including various cross-section shapes.
splinepy/helpme/create.py	Expanded the swept function to enhance control over rotation and placement options for sweeping cross-sections along trajectories.
tests/helpme/test_create.py	Introduced test functions to validate swept spline functionality and compare with extruded surfaces.
splinepy/bspline.py	Minor code cleanup in the remove_knots method by removing unnecessary whitespace.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant ExampleScript as show_swept.py
    participant SplinePy as splinepy.create.py
    participant Visualizer as gustaf

    User->>ExampleScript: Run script
    ExampleScript->>SplinePy: Call swept(cross_section, trajectory)
    SplinePy-->>ExampleScript: Return swept_surface
    ExampleScript->>Visualizer: Visualize trajectory, cross-section, and swept_surface
    ExampleScript->>User: Display result

Poem

In the world of splines, a tale unfolds,
With trajectories swept, new wonders are told.
From cross-sections fine, surfaces arise,
Visualized with care, they dazzle the eyes.
Through math so advanced, they weave and entwine,
Splines of beauty, intricate by design.
🎨✨

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[OberGue]

@coderabbitai generate pytest-file for the sweeping routine

[coderabbitai[bot]]

[!TIP] For best results, initiate chat on the files or code changes.

@OberGue, here is the pytest file for the swept function in splinepy/helpme/create.py:

import pytest
import numpy as np
from splinepy import BSpline, NURBS
from splinepy.helpme.create import swept

def test_swept_basic_functionality():
    cross_section = BSpline(
        degrees=[2],
        control_points=[[0, 0], [0.5, 1], [1, 0]],
        knot_vectors=[[0, 0, 0, 1, 1, 1]]
    )
    trajectory = BSpline(
        degrees=[3],
        control_points=[[0, 0], [1, 2], [2, 3], [3, 3]],
        knot_vectors=[[0, 0, 0, 0, 1, 1, 1, 1]]
    )
    result = swept(cross_section, trajectory)
    assert result is not None
    assert result.control_points.shape[0] == cross_section.control_points.shape[0] * trajectory.control_points.shape[0]

def test_swept_with_custom_normal():
    cross_section = BSpline(
        degrees=[2],
        control_points=[[0, 0], [0.5, 1], [1, 0]],
        knot_vectors=[[0, 0, 0, 1, 1, 1]]
    )
    trajectory = BSpline(
        degrees=[3],
        control_points=[[0, 0], [1, 2], [2, 3], [3, 3]],
        knot_vectors=[[0, 0, 0, 0, 1, 1, 1, 1]]
    )
    custom_normal = np.array([0, 1, 0])
    result = swept(cross_section, trajectory, cross_section_normal=custom_normal)
    assert result is not None

def test_swept_invalid_inputs():
    cross_section = BSpline(
        degrees=[2],
        control_points=[[0, 0], [0.5, 1], [1, 0]],
        knot_vectors=[[0, 0, 0, 1, 1, 1]]
    )
    invalid_trajectory = "invalid_trajectory"
    with pytest.raises(NotImplementedError):
        swept(cross_section, invalid_trajectory)

    invalid_cross_section = "invalid_cross_section"
    trajectory = BSpline(
        degrees=[3],
        control_points=[[0, 0], [1, 2], [2, 3], [3, 3]],
        knot_vectors=[[0, 0, 0, 0, 1, 1, 1, 1]]
    )
    with pytest.raises(NotImplementedError):
        swept(invalid_cross_section, trajectory)

def test_swept_rational_splines():
    cross_section = NURBS(
        degrees=[2],
        control_points=[[0, 0], [0.5, 1], [1, 0]],
        weights=[1, 0.5, 1],
        knot_vectors=[[0, 0, 0, 1, 1, 1]]
    )
    trajectory = NURBS(
        degrees=[3],
        control_points=[[0, 0], [1, 2], [2, 3], [3, 3]],
        weights=[1, 0.5, 0.5, 1],
        knot_vectors=[[0, 0, 0, 0, 1, 1, 1, 1]]
    )
    result = swept(cross_section, trajectory)
    assert result is not None
    assert result.is_rational

This test suite includes:

• Basic functionality tests.
• Tests with custom cross-section normals.
• Tests for invalid cross-section and trajectory inputs.
• Tests for rational splines.

Feel free to run these tests and let me know if any adjustments are needed!

Analysis chain

--- ---

Scripts executed

The following scripts were executed for the analysis: --- Script: ```shell #!/bin/bash # Search for the `swept` function in `splinepy/helpme/create.py` ast-grep --lang python --pattern $'def swept($_, $_, $_):' splinepy/helpme/create.py ``` Length of output: 85 --- --- Script: ```shell #!/bin/bash # Search for all function definitions in `splinepy/helpme/create.py` ast-grep --lang python --pattern $'def $_($_):' splinepy/helpme/create.py ``` Length of output: 74 --- --- Script: ```shell #!/bin/bash # List the contents of the `splinepy/helpme/` directory to verify `create.py` exists ls splinepy/helpme/ # Display the contents of `create.py` if it exists if [ -f splinepy/helpme/create.py ]; then cat splinepy/helpme/create.py fi ``` Length of output: 41109

[OberGue]

@coderabbitai update the sequence diagram

[coderabbitai[bot]]

[!TIP] For best results, initiate chat on the files or code changes.

@OberGue, here is the updated sequence diagram for the swept function:

sequenceDiagram
    participant User
    participant SweptFunction as swept()
    participant Spline as Spline
    participant Numpy as np
    participant Log as log

    User->>SweptFunction: Call swept(cross_section, trajectory, ...)
    SweptFunction->>Spline: Validate cross_section and trajectory
    SweptFunction->>Numpy: Set default cross_section_normal if None
    SweptFunction->>SweptFunction: Initialize transformation matrices
    SweptFunction->>Spline: Calculate tangent vectors and B-vectors
    SweptFunction->>SweptFunction: Calculate rotation matrix for cross_section
    SweptFunction->>SweptFunction: Perform sweeping process
    SweptFunction->>Spline: Handle rational splines if applicable
    SweptFunction->>User: Return swept_spline

This diagram captures the key steps and interactions within the swept function. Let me know if any further adjustments are needed!

Analysis chain

Scripts executed

The following scripts were executed for the analysis: Script: ```shell #!/bin/bash # Extract the implementation of the `swept` function from `splinepy/helpme/create.py` ast-grep --lang python --pattern $'def swept($_, $_, $_, $_, $_):\n $$$' splinepy/helpme/create.py ``` Length of output: 19056

[OberGue]

Tip

For best results, initiate chat on the files or code changes.

@OberGue, here is the updated sequence diagram for the swept function:

sequenceDiagram
    participant User
    participant SweptFunction as swept()
    participant Spline as Spline
    participant Numpy as np
    participant Log as log

    User->>SweptFunction: Call swept(cross_section, trajectory, ...)
    SweptFunction->>Spline: Validate cross_section and trajectory
    SweptFunction->>Numpy: Set default cross_section_normal if None
    SweptFunction->>SweptFunction: Initialize transformation matrices
    SweptFunction->>Spline: Calculate tangent vectors and B-vectors
    SweptFunction->>SweptFunction: Calculate rotation matrix for cross_section
    SweptFunction->>SweptFunction: Perform sweeping process
    SweptFunction->>Spline: Handle rational splines if applicable
    SweptFunction->>User: Return swept_spline

This diagram captures the key steps and interactions within the swept function. Let me know if any further adjustments are needed! Analysis chain Scripts executed

@coderabbitai Please be more superficial. Additionally, I only want the columns "user", "show_swept" and "create-file"

[coderabbitai[bot]]

[!TIP] For best results, initiate chat on the files or code changes.

@OberGue, I've simplified the sequence diagram as requested, focusing only on the interactions between the "user", "show_swept", and "create-file" columns:

sequenceDiagram
    participant User
    participant ShowSwept as show_swept.py
    participant CreateFile as create.py

    User->>ShowSwept: Call show_swept.py
    ShowSwept->>CreateFile: Call swept() from create.py
    CreateFile->>ShowSwept: Return swept_spline
    ShowSwept->>User: Display results

This diagram now captures the key interactions between the user, the show_swept.py file, and the create.py file where the swept function is defined. Let me know if any further adjustments are needed!

[j042]

Good progress! If you are done with comments, can you please resolve the conversations? Feel free to leave a note if needed