These functions provide methods for discrete derivative and integral calculations.
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These functions provide methods for discrete derivative and integral calculations.
◆ chebyshev_data()
def SUAVE.Methods.Utilities.Chebyshev.chebyshev_data.chebyshev_data |
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N = 16 , |
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integration = True , |
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** |
options |
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) |
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Calculates the differentiation and integration matricies
using chebyshev's pseudospectral algorithm, based on cosine
spaced samples in x.
D and I are not symmetric
get derivatives with df_dy = np.dot(D,f)
get integral with int_f = np.dot(I,f)
where f is either a 1-d vector or 2-d column array
A full example is available in the function code.
Assumptions:
None
Source:
N/A
Inputs:
N [-] Number of points
integration (optional) <boolean> Determines if the integration operator is calculated
Outputs:
x [-] N-number of cosine spaced control points, in range [0,1]
D [-] Differentiation operation matrix
I [-] Integration operation matrix, or None if integration = False
Properties Used:
N/A
◆ linear_data()
def SUAVE.Methods.Utilities.Chebyshev.linear_data.linear_data |
( |
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N = 16 , |
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integration = True , |
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** |
options |
|
) |
| |
Calculates the differentiation and integration matricies
using chebyshev's pseudospectral algorithm, based on linearly
spaced samples in x.
D and I are not symmetric
get derivatives with df_dy = np.dot(D,f)
get integral with int_f = np.dot(I,f)
where f is either a 1-d vector or 2-d column array
A full example of how these operators are used is available in
the chebyshev_data.py (same folder)
Assumptions:
None
Source:
N/A
Inputs:
N [-] Number of points
integration (optional) <boolean> Determines if the integration operator is calculated
Outputs:
x [-] N-number of cosine spaced control points, in range [0,1]
D [-] Differentiation operation matrix
I [-] Integration operation matrix, or None if integration = False
Properties Used:
N/A