Add integration of physical function #447
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Actionable comments posted: 2
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Files selected for processing (2)
- splinepy/helpme/integrate.py (1 hunks)
- tests/helpme/test_integrate.py (1 hunks)
Additional comments not posted (9)
tests/helpme/test_integrate.py (3)
195-197: Verify the correctness of the analytical integral.Ensure that the analytical integral value ( \frac{125}{6} ) is correct for the given parabolic function over the specified domain.
215-217: Ensure randomness in knot insertion.The insertion of random knots should be verifiable to ensure that it does not introduce unintended behavior.
219-223: LGTM! Ensure the integration function is well-tested.The integration function call and assertion are correctly implemented.
splinepy/helpme/integrate.py (6)
221-223: Update the function signature.The function signature has been updated to include the
splineparameter, which improves clarity and usability.
225-237: Enhance the docstring for clarity.The docstring provides detailed descriptions of the parameters and return type, which enhances documentation and usability.
240-242: Ensure type safety with NotImplementedError.The function raises a
NotImplementedErrorif the inputsplineis not of the expected type, ensuring type safety.
244-246: Retrieve auxiliary information for integration.The function retrieves necessary auxiliary information for integration, ensuring that the process is well-informed.
248-267: Optimize the integration process.The use of
np.einsumfor efficient computation of the integral showcases an optimization in the numerical integration process.
269-277: Handle splines without knot vectors.The function correctly handles cases where the spline does not have knot vectors, ensuring robustness.
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Files selected for processing (1)
- tests/helpme/test_integrate.py (1 hunks)
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tests/helpme/test_integrate.py (4)
199-204: Ensure robustness of the parabolic function implementation.The function currently assumes that
pointsis either a list or a numpy array. Consider adding error handling for unexpected input types.- return (y * (5 - y)).reshape(-1, 1) + else: + raise TypeError("Unsupported type for points") + return (y * (5 - y)).reshape(-1, 1)
207-210: Improve the creation of the rectangle domain.The current method of creating the rectangle domain is correct but can be optimized for readability and maintainability.
- xlin, ylin = np.linspace(0, 1, 3), np.linspace(0, 5, 3) - control_points = np.vstack( - [array.ravel() for array in np.meshgrid(xlin, ylin)] - ).T + xlin, ylin = np.linspace(0, 1, 3), np.linspace(0, 5, 3) + meshgrid = np.meshgrid(xlin, ylin) + control_points = np.vstack([array.ravel() for array in meshgrid]).T
221-223: LGTM! Ensure robustness of the physical function integration.The integration of the physical function is correct. Ensure that
splinepy.helpme.integrate.physical_functionis well-tested.
225-225: LGTM! Ensure the accuracy of the assertion.The assertion to verify the result is correct.
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Actionable comments posted: 2
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Files selected for processing (2)
- splinepy/helpme/integrate.py (2 hunks)
- tests/helpme/test_integrate.py (1 hunks)
Additional context used
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splinepy/helpme/integrate.py
313-313: No newline at end of file
Add trailing newline
(W292)
Additional comments not posted (5)
tests/helpme/test_integrate.py (4)
199-204: Ensure robustness of the parabolic function implementation.The function currently assumes that
pointsis either a list or a numpy array. Consider adding error handling for unexpected input types.- y = points[0][1] if isinstance(points, list) else points[:, 1] + if isinstance(points, list): + y = points[0][1] + elif isinstance(points, np.ndarray): + y = points[:, 1] + else: + raise TypeError("Unsupported type for points")
207-210: Improve the creation of the rectangle domain.The current method of creating the rectangle domain is correct but can be optimized for readability and maintainability.
- xlin = np.linspace(0, 1, 3) - ylin = np.linspace(0, 5, 3) - control_points = np.vstack( - [array.ravel() for array in np.meshgrid(xlin, ylin)] - ).T + xlin, ylin = np.linspace(0, 1, 3), np.linspace(0, 5, 3) + meshgrid = np.meshgrid(xlin, ylin) + control_points = np.vstack([array.ravel() for array in meshgrid]).T
197-197: Ensure robustness of the analytical integral calculation.The calculation of the analytical integral is correct. However, consider adding a comment explaining the formula for clarity.
- integral_analytical = 125 / 6 + integral_analytical = 125 / 6 # Analytical integral of y*(5-y) over [0,1]x[0,5]
218-219: Ensure the randomness of inserted knots.The insertion of random knots is correct. However, consider adding a comment explaining the purpose of inserting random knots for clarity.
- rectangle.insert_knots(0, np_rng.random(2)) - rectangle.insert_knots(1, np_rng.random(2)) + rectangle.insert_knots(0, np_rng.random(2)) # Insert random knots along the first dimension + rectangle.insert_knots(1, np_rng.random(2)) # Insert random knots along the second dimensionsplinepy/helpme/integrate.py (1)
241-242: Fix typographical error in the comment.There is a typographical error in the comment.
i_nputshould beinput.- # Check i_nput type + # Check input typeLikely invalid or redundant comment.
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Files selected for processing (1)
- splinepy/helpme/integrate.py (2 hunks)
Additional comments not posted (5)
splinepy/helpme/integrate.py (5)
225-237: Ensure proper documentation of the function parameters.The docstring should provide comprehensive descriptions of the parameters and the return type.
240-242: LGTM! Type check forsplineparameter.The type check for the
splineparameter ensures that the function only works with spline objects.
245-246: LGTM! Auxiliary information retrieval.The retrieval of auxiliary information for the integration process is correctly implemented.
270-276: LGTM! Integration computation logic for splines without knot vectors.The integration computation logic for splines without knot vectors is correctly implemented.
249-267: Verify the integration computation logic.The integration computation logic for splines with knot vectors appears correct, but ensure that the
einsumoperations are optimized for performance.Verification successful
Integration computation logic is verified.
The integration computation logic for splines with knot vectors has been implemented correctly and the
einsumoperations are optimized for performance using theoptimize=Trueflag.
- The
einsumoperations used in theparametric_functionandphysical_functionmethods withinsplinepy/helpme/integrate.pyare optimized.- The integration logic is correctly applied across various parts of the codebase.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the integration computation logic for splines with knot vectors. # Test: Search for the function usage. Expect: Only occurrences of the new signature. rg --type python -A 10 $'physical_function'Length of output: 73
Script:
#!/bin/bash # Description: Verify the integration computation logic for splines with knot vectors. # Test: Search for the function usage. Expect: Only occurrences of the new signature. rg --type py -A 10 $'function'Length of output: 176668
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Actionable comments posted: 0
Review details
Configuration used: CodeRabbit UI
Review profile: ASSERTIVE
Files selected for processing (2)
- splinepy/helpme/integrate.py (2 hunks)
- tests/helpme/test_integrate.py (1 hunks)
Additional comments not posted (9)
tests/helpme/test_integrate.py (5)
195-197: Ensure robustness of the analytical integral calculation.The calculation of the analytical integral is correct. However, consider adding a comment explaining the formula for clarity.
- integral_analytical = 125 / 6 + integral_analytical = 125 / 6 # Analytical integral of y*(5-y) over [0,1]x[0,5]
199-206: Ensure robustness of the parabolic function implementation.The function currently assumes that
pointsis either a list or a numpy array. Consider adding error handling for unexpected input types.- y = points[0][1] if isinstance(points, list) else points[:, 1] + if isinstance(points, list): + y = points[0][1] + elif isinstance(points, np.ndarray): + y = points[:, 1] + else: + raise TypeError("Unsupported type for points")
208-212: Improve the creation of the rectangle domain.The current method of creating the rectangle domain is correct but can be optimized for readability and maintainability.
- xlin = np.linspace(0, 1, 3) - ylin = np.linspace(0, 5, 3) - control_points = np.vstack( - [array.ravel() for array in np.meshgrid(xlin, ylin)] - ).T + xlin, ylin = np.linspace(0, 1, 3), np.linspace(0, 5, 3) + meshgrid = np.meshgrid(xlin, ylin) + control_points = np.vstack([array.ravel() for array in meshgrid]).T
219-221: Ensure the randomness of inserted knots.The insertion of random knots is correct. However, consider adding a comment explaining the purpose of inserting random knots for clarity.
- rectangle.insert_knots(0, np_rng.random(2)) - rectangle.insert_knots(1, np_rng.random(2)) + rectangle.insert_knots(0, np_rng.random(2)) # Insert random knots along the first dimension + rectangle.insert_knots(1, np_rng.random(2)) # Insert random knots along the second dimension
223-227: Ensure correctness of the integral calculation.The integral calculation is correctly implemented. The assertion checks the computed integral against the analytical value.
The code changes are approved.
splinepy/helpme/integrate.py (4)
221-223: Ensure proper documentation of the function parameters.The docstring should provide comprehensive descriptions of the parameters and the return type.
""" Integrate a function defined within the physical domain Parameters ---------- spline : Spline (self if called via integrator) function : Callable A function to integrate over the physical domain. orders : array-like, optional Integration orders for each parametric dimension. Returns ------- integral : np.ndarray The computed integral over the physical domain. """
243-245: Ensure proper type checking for spline parameter.The function checks if the spline parameter is an instance of the Spline class. This is necessary to ensure that integration is only performed on valid spline objects.
The code changes are approved.
251-271: Optimize the integration logic for splines with knot vectors.The function retrieves necessary information for integration and includes logic to handle cases where the spline has knot vectors. The use of
np.einsumoptimizes the computation.The code changes are approved.
273-280: Optimize the integration logic for splines without knot vectors.The function retrieves necessary information for integration and includes logic to handle cases where the spline does not have knot vectors. The use of
np.einsumoptimizes the computation.The code changes are approved.
Overview
Integration of physical function
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New Features
Tests