Found 1204 Articles for Numpy

To remove small trailing coefficients from Hermite_e polynomial, use the hermite_e.hermetrim() method in Python Numpy. The method returns a 1-d array with trailing zeros removed. If the resulting series would be empty, a series containing a single zero is returned.The “Small” means “small in absolute value” and is controlled by the parameter tol; “trailing” means highest order coefficient(s), e.g., in [0, 1, 1, 0, 0] (which represents 0 + x + x**2 + 0*x**3 + 0*x**4) both the 3-rd and 4-th order coefficients would be “trimmed. The parameter c is a 1-d array of coefficients, ordered from lowest order to ... Read More

To generate a Vandermonde matrix of the Hermite_e polynomial, use the hermite_e.hermevander() in Python Numpy. The method returns the pseudo-Vandermonde matrix. The shape of the returned matrix is x.shape + (deg + 1, ), where The last index is the degree of the corresponding Hermite_e polynomial. The dtype will be the same as the converted x.The parameter, x returns an Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array. The parameter, deg is the degree of the resulting ... Read More

To compute the roots of a Hermite_e series, use the hermite_e.hermeroots() method in Python Numpy. The method returns an array of the roots of the series. If all the roots are real, then out is also real, otherwise it is complex..The parameter, c is a 1-D array of coefficients. The root estimates are obtained as the eigenvalues of the companion matrix, roots far from the origin of the complex plane may have large errors due to the numerical instability of the series for such values. Roots with multiplicity greater than 1 will also show larger errors as the value of ... Read More

To compute the roots of a Hermite_e series, use the hermite.hermroots() method in Python Numpy. The method returns an Array of the roots of the series. If all the roots are real, then out is also real, otherwise it is complex. The parameter, c is a 1-D array of coefficients.The root estimates are obtained as the eigenvalues of the companion matrix, Roots far from the origin of the complex plane may have large errors due to the numerical instability of the series for such values. Roots with multiplicity greater than 1 will also show larger errors as the value of ... Read More

To generate a Hermite_e series with given complex roots, use the hermite_e.hermefromroots() method in Python Numpy. The method returns a 1-D array of coefficients. If all roots are real then out is a real array, if some of the roots are complex, then out is complex even if all the coefficients in the result are real. The parameter roots are the sequence containing the roots.StepsAt first, import the required library −from numpy.polynomial mport hermite_e as HGenerate a Hermite_e series with given complex roots −j = complex(0, 1) print("Result...", H.hermefromroots((-j, j)))Get the datatype −print("Type...", H.hermefromroots((-j, j)).dtype)Get the shape −print("Shape...", H.hermefromroots((-j, j)).shape)Create ... Read More

To integrate a Hermite_e series, use the hermite_e.hermeint() method in Python. The 1st parameter, c is an array of Hermite_e series coefficients. If c is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index.The 2nd parameter, m is an order of integration, must be positive. The 3rd parameter, k is an integration constant(s). The value of the first integral at lbnd is the first value in the list, the value of the second integral at lbnd is the second value, etc. If k == [] (the default), all constants are ... Read More

To integrate a Hermite_e series, use the hermite_e.hermeint() method in Python. The 1st parameter, c is an array of Hermite_e series coefficients. If c is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index.The 2nd parameter, m is an order of integration, must be positive. (Default: 1). The 3rd parameter, k is an integration constant(s). The value of the first integral at lbnd is the first value in the list, the value of the second integral at lbnd is the second value, etc. If k == [] (the default), all ... Read More

To get the Least squares fit of Hermite_e series to data, use the hermite_e.hermfit() method in Python numpy. The method returns the Hermite_e coefficients ordered from low to high. If y was 2- D, the coefficients for the data in column k of y are in column k. The parameter, x are the xcoordinates of the M sample (data) points (x[i], y[i]).The parameter, y are the y-coordinates of the sample points. Several sets of sample points sharing the same x-coordinates can be (independently) fit with one call to polyfit by passing in for y a 2-D array that contains one ... Read More

To return the scaled companion matrix of a 1-D array of polynomial coefficients, return the hermite_e.hermecompanion() method in Python Numpy. The basis polynomials are scaled so that the companion matrix is symmetric when c is an Hermite_e basis polynomial. This provides better eigenvalue estimates than the unscaled case and for basis polynomials the eigenvalues are guaranteed to be real if numpy.linalg.eigvalsh is used to obtain them.The method returns the Scaled companion matrix of dimensions (deg, deg). The parameter, c is a 1- D array of Hermite series coefficients ordered from low to high degree.StepsAt first, import the required library −import ... Read More

Risk AcceptanceRisk acceptance is also known as risk retention. It is simply accepting the recognized risk without taking any measures to avoid loss or the probability of the risk happening. It includes a decision by management to accept a given risk without more mitigation or transfer, for a period of time.This appears in two classes of circumstances. For risks that are too low to bother protecting against or for which insurance and due diligence are enough, risk is accepted. For risks that are to be mitigated but where mitigation cannot be completed instantaneously or for which rapid mitigation is too ... Read More