ntrfc.math package¶
Submodules¶
ntrfc.math.methods module¶
- ntrfc.math.methods.C_barycentric(R)¶
- ntrfc.math.methods.autocorr(signal)¶
- Param:
signal - numpy-array.
- ntrfc.math.methods.autocorrelate(series)¶
Compute the autocorrelation function of a given time series.
- Parameters:
series (array-like) – The 1D time series to be autocorrelated.
- Returns:
The autocorrelation function of the input series.
- Return type:
array-like
- ntrfc.math.methods.calcAnisoEigs(anisotropy_matrix)¶
- ntrfc.math.methods.calcAnisoMatrix(reynoldsstress_tensor)¶
- ntrfc.math.methods.find_nearest(array, value)¶
- ntrfc.math.methods.is_equidistant(arr, tolerance=1e-08)¶
- ntrfc.math.methods.minmax_normalize(series_array)¶
Normalize a given 1D array to the range [0, 1] using min-max normalization.
- Parameters:
series_array (array-like) – The 1D array to be normalized.
- Returns:
The normalized 1D array with values in the range [0, 1].
- Return type:
array-like
Note
If all values in the input array are the same, the function will return the input array unchanged.
- ntrfc.math.methods.reldiff(a, b)¶
Calculates the relative difference between two values or arrays of values.
Parameters: a (float or numpy array): The first value or array of values to compare. b (float or numpy array): The second value or array of values to compare.
Returns: float or numpy array: The relative difference between a and b. If a and b are both numpy arrays, the output will be a numpy array of the same shape. If one input is a float and the other is a numpy array, the output will be a numpy array of the same shape as the input array.
Notes: The relative difference is defined as the absolute difference between the two values divided by the average of their absolute values. If a and b are equal, the relative difference is 0. If either a or b is zero, the absolute difference between the two values is returned instead of the relative difference.
- ntrfc.math.methods.return_intersection(hist_1, hist_2)¶
Calculate the intersection of two histograms.
- Parameters:
hist_1 (numpy.ndarray) – The first histogram to be compared.
hist_2 (numpy.ndarray) – The second histogram to be compared.
- Returns:
The intersection of the two histograms.
- Return type:
float
- ntrfc.math.methods.zero_crossings(data_series)¶
ntrfc.math.vectorcalc module¶
Created on Sun Oct 4 19:01:50 2020
@author: malte
- ntrfc.math.vectorcalc.RotFromTwoVecs(vec1, vec2)¶
Find the rotation matrix that aligns vec1 to vec2 :param vec1: A 3d “source” vector :param vec2: A 3d “destination” vector :return mat: A transform matrix (3x3) which when applied to vec1, aligns it with vec2.
- ntrfc.math.vectorcalc.Rx(xAngle)¶
using radiant :param xAngle: angle in rad :return: rotation matrix
- ntrfc.math.vectorcalc.Ry(yAngle)¶
using radiant :param yAngle: angle in rad :return: rotation matrix
- ntrfc.math.vectorcalc.Rz(zAngle)¶
using radiant :param zAngle: angle in rad :return: rotation matrix
- ntrfc.math.vectorcalc.calc_largedistant_idx(x_koords, y_koords)¶
tested method to find indices of coordinates of a 2d-pointcloud with the biggest distance :param x_koords: array of xcords :param y_koords: array of ycords :return: index_1,index_2 (int)
- ntrfc.math.vectorcalc.closest_node_index(node, nodes)¶
- ntrfc.math.vectorcalc.distant_node_index(node, nodes)¶
- ntrfc.math.vectorcalc.ellipsoidVol(sig)¶
tested method to compute the ellipsoid volume by the sigma-parameters of a parametric ellipsoid :param sig: :return:
- ntrfc.math.vectorcalc.eulersFromRPG(R)¶
- ntrfc.math.vectorcalc.findNearest(array, point)¶
- ntrfc.math.vectorcalc.gradToRad(angle)¶
tested method to translate from grad to rad :param angle: :return:
- ntrfc.math.vectorcalc.line_intersection(point_a1, point_a2, point_b1, point_b2)¶
- ntrfc.math.vectorcalc.lineseg_dist(p, a, b)¶
- Parameters:
p – point
a – line point a
b – line point b
- Returns:
distance
- ntrfc.math.vectorcalc.posVec(vec)¶
- ntrfc.math.vectorcalc.randomOrthMat()¶
- ntrfc.math.vectorcalc.randomUnitVec()¶
tested method to generate a random unit vector :return:
- ntrfc.math.vectorcalc.symToMatrix(symTensor)¶
tested translates symmetric tensor notation to complete matrix :param symTensor: :return:
- ntrfc.math.vectorcalc.unitvec(vec)¶
- ntrfc.math.vectorcalc.unitvec_list(vecs)¶
- ntrfc.math.vectorcalc.vecAbs(vec)¶
method to calculate the absolute value of a vector :param vec: :return:
- ntrfc.math.vectorcalc.vecAbs_list(vecs)¶
method to calculate the absolute value of a vector :param np.array vec with shape (n,3): :return: array of magnitudes in shape (n)
- ntrfc.math.vectorcalc.vecAngle(vec1, vec2)¶
Returns the angle in radians between vectors ‘v1’ and ‘v2’:
- angle_between((1, 0, 0), (0, 1, 0))
1.5707963267948966
- angle_between((1, 0, 0), (1, 0, 0))
0.0
- angle_between((1, 0, 0), (-1, 0, 0))
3.141592653589793
- ntrfc.math.vectorcalc.vecDir(vec)¶
tested method to compute the direction of a vector :param vec: :return: unit vec
- ntrfc.math.vectorcalc.vecProjection(direction, vector)¶
Calculate the projection of a vector onto a direction vector.
Parameters: direction (list or numpy array): The direction vector onto which the projection will be calculated. vector (list or numpy array): The vector to be projected onto the direction vector.
Returns: projection (numpy array): A vector representing the projection of the input vector onto the direction vector.