Package: numspark
NumSpark (Version 1.2)NumSpark is a Python library that provides mathematical operations and functions for numerical calculations. It includes operations on lists, vectors, matrices, sets, and various mathematical functions.Installation and Dependenciespipinstallnumsparknumpy
sympyConstantsNumSpark provides the following constants:PI: The mathematical constant π (pi).E: The mathematical constant e (base of the natural logarithm).INFINITY,INF,inf: Represents positive infinity.NAN,NaN,nan: Represents not a number.TRUE,true: Represents the boolean value True.FALSE,false: Represents the boolean value False.NONE,NULL,none,null: Represents None or null.List OperationsTheListclass provides various element-wise operations on lists:element_wise_operation: Perform an element-wise operation on multiple lists.product: Compute the element-wise product of multiple lists.scalarProduct: Multiply each element of a list by a scalar value.add: Compute the element-wise addition of multiple lists.scalarAdd: Add a scalar value to each element of a list.sub: Compute the element-wise subtraction of multiple lists.scalarSub: Subtract a scalar value from each element of a list.div: Compute the element-wise division of multiple lists.scalarDiv: Divide each element of a list by a scalar value.floorDiv: Compute the element-wise floor division of multiple lists.scalarFloorDiv: Perform floor division of each element of a list by a scalar value.modulo: Compute the element-wise modulo operation of multiple lists.scalarModulo: Perform modulo operation on each element of a list with a scalar value.pow: Compute the element-wise power of a list with a scalar value.flatten: Flatten a nested list to a single list.Vector OperationsTheVectorclass provides operations on 3-dimensional vectors:add: Add multiple 3-dimensional vectors.sub: Subtract multiple 3-dimensional vectors.crossProduct: Compute the cross product of multiple 3-dimensional vectors.dotProduct: Compute the dot product of multiple 3-dimensional vectors.magnitude: Compute the magnitude of a 3-dimensional vector.projection: Compute the projection of one 3-dimensional vector onto another.angleOfProjection: Compute the angle of projection between two 3-dimensional vectors.Matrix OperationsTheMatrixclass provides operations on matrices:isMatrix: Check if a given nested list is a matrix.isSquare: Check if a given matrix is square.add: Add multiple matrices element-wise.scalarAdd: Add a scalar value to each element of a matrix.sub: Subtract multiple matrices element-wise.scalarSub: Subtract a scalar value from each element of a matrix.product: Multiply multiple matrices.scalarProduct: Multiply each element of a matrix by a scalar value.T: Transpose a matrix.subMatrix: Extract a submatrix by removing a specific row and column from the original matrix.det: Calculate the determinant of a square matrix.cofactor: Calculate the cofactors of a square matrix.adjoint: Calculate the adjoint (adjugate) of a square matrix.inv: Calculate the inverse of a square matrix.traces: Calculate the sum of the diagonal elements of a square matrix.diagonalSum: Calculate the sum of the diagonal and anti-diagonal elements of a square matrix.removeCol: Remove a specific column from a matrix.removeRow: Remove a specific row from a matrix.reciprocal: Calculate the reciprocal of each element in a matrix.Set OperationsTheSetclass provides operations on sets:toSet: Convert a list to a set, removing duplicates.intersect: Compute the intersection of multiple sets.union: Compute the union of multiple sets.belongsTo: Check if an element belongs to a set.subSet: Check if one set is a subset of another.Mathematical FunctionsNumSpark includes variousmathematicalfunctions:max: Find the maximum value in an array.min: Find the minimum value in an array.sin: Compute the sine of an angle (in radians or degrees).cos: Compute the cosine of an angle (in radians or degrees).tan: Compute the tangent of an angle (in radians or degrees).cot: Compute the cotangent of an angle (in radians or degrees).cosec: Compute the cosecant of an angle (in radians or degrees).sec: Compute the secant of an angle (in radians or degrees).asin: Compute the arcsine of an angle (in radians).acos: Compute the arccosine of an angle (in radians).atan: Compute the arctangent of an angle (in radians).acot: Compute the arccotangent of an angle (in radians).acosec: Compute the arccosecant of an angle (in radians).asec: Compute the arcsecant of an angle (in radians).sqrt: Compute the square root of a number.cbrt: Compute the cube root of a number.power: Compute the power of a number with a given exponent.exp: Compute the exponential function of a number.factorial: Compute the factorial of a number.fibSequence: Generate a Fibonacci sequence up to a given number.floor: Round a number down to the nearest integer.ceil: Round a number up to the nearest integer.quadratic_roots: Calculate the roots of a quadratic equation.log: Compute the logarithm of a number (base 10).ln: Compute the natural logarithm of a number (base e).logn: Compute the logarithm of a number with a specified base.permutation: Calculate the number of permutations ofnobjects takenrat a time.combination: Calculate the number of combinations ofnobjects takenrat a time.product: Compute the product of elements in an array.summation: Compute the sum of elements in an array.mean: Calculate the arithmetic mean (average) of an array.median: Calculate the median of an array.mode: Calculate the mode of an array.variance: Calculate the variance of an array (sample or population).standard_deviation: Calculate the standard deviation of an array (sample or population).skewness: Calculate the skewness of an array.kurtosis: Calculate the kurtosis of an array.geometric_mean: Calculate the geometric mean of an arrayharmonic_mean(array: list): Calculates the harmonic mean of a list of numbers.correlation_coefficient(x: list, y: list): Computes the correlation coefficient between two lists of numbers.slope_intercept(array1: list, array2: list): Calculates the slope and intercept of the linear regression line for two arrays of data points.moving_average(array: list, steps: int): Computes the moving average of a list of numbers using a given window size.exponential_moving_average(array: list, alpha: int|float): Calculates the exponential moving average of a list of numbers using a smoothing factoralpha.mean_sqrd_error(actual: list, predicted: list): Computes the mean squared error between two lists of actual and predicted values.root_mean_sqrd_error(actual: list, predicted: list): Calculates the root mean squared error between two lists of actual and predicted values.errors(actual: list, predicted: list): Calculates the errors (differences) between two lists of actual and predicted values.mean_error(actual: list, predicted: list): Computes the mean error (average of errors) between two lists of actual and predicted values.power(base: int|float, exponent: int|float): Raises the base to the power of the exponent.power_sum(array: list, exponent: int|float): Computes the sum of the elements in the array raised to the power of the given exponent.power_array(array: list, exponent: int|float): Generates a new list with elements from the input list raised to the power of the given exponent.primes(limit: int): Generates a list of prime numbers up to a given limit.isprime(number: int): Checks if a given number is prime.cost_function(actual: list, predicted: list): Computes the cost function (mean squared error) between two lists of actual and predicted values for a regression problem.scaling(array: list, feature_range: tuple = (0, 1)): Scales the values in the array to a specified feature range (default 0 to 1).gaussian(array: list): Generates a list of values representing the Gaussian distribution based on the input data.sigmoid(x: int): Computes the sigmoid function for a given input.zscore(array: list, number: int) -> int|float: Calculates the z-score of a given number in relation to a list of data.euclidean_distance(array1: list, array2: list): Calculates the Euclidean distance between two lists of coordinates (2D).manhattan_distance(array1: list, array2: list): Computes the Manhattan distance between two lists of coordinates (2D).camberra_distance(array1: list, array2: list): Calculates the Canberra distance between two lists of coordinates (2D).integrate(expression: str, wrt: str = "x"): Performs symbolic integration of a given expression with respect to the specified variable.derivate(expression: str, wrt: str = "x"): Performs symbolic differentiation of a given expression with respect to the specified variable.