tessl/pypi-spiceypy

A Python wrapper for the NAIF CSPICE Toolkit providing essential tools for spacecraft navigation and planetary science calculations

Overview

Eval results

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Vector and Matrix Mathematics

Name: tessl/pypi-spiceypy
Author: tessl

Linear algebra functions for vector operations, matrix manipulations, and mathematical computations commonly used in space geometry. These functions provide the mathematical foundation for coordinate transformations and geometric calculations.

Capabilities

Vector Operations

Basic vector arithmetic and analysis functions.

def vadd(v1: ndarray, v2: ndarray) -> ndarray:
    """
    Add two vectors.
    
    Parameters:
    - v1: ndarray, first vector
    - v2: ndarray, second vector
    
    Returns:
    ndarray: sum vector v1 + v2
    """

def vsub(v1: ndarray, v2: ndarray) -> ndarray:
    """
    Subtract two vectors.
    
    Parameters:
    - v1: ndarray, first vector
    - v2: ndarray, second vector
    
    Returns:
    ndarray: difference vector v1 - v2
    """

def vdot(v1: ndarray, v2: ndarray) -> float:
    """
    Compute dot product of two vectors.
    
    Parameters:
    - v1: ndarray, first vector
    - v2: ndarray, second vector
    
    Returns:
    float: dot product v1 • v2
    """

def vcrss(v1: ndarray, v2: ndarray) -> ndarray:
    """
    Compute cross product of two vectors.
    
    Parameters:
    - v1: ndarray, first vector
    - v2: ndarray, second vector
    
    Returns:
    ndarray: cross product vector v1 × v2
    """

def vnorm(v: ndarray) -> float:
    """
    Compute vector magnitude (norm).
    
    Parameters:
    - v: ndarray, input vector
    
    Returns:
    float: vector magnitude ||v||
    """

def vhat(v: ndarray) -> ndarray:
    """
    Compute unit vector.
    
    Parameters:
    - v: ndarray, input vector
    
    Returns:
    ndarray: unit vector v/||v||
    """

def vscl(s: float, v: ndarray) -> ndarray:
    """
    Scale vector by scalar.
    
    Parameters:
    - s: float, scaling factor
    - v: ndarray, input vector
    
    Returns:
    ndarray: scaled vector s*v
    """

Matrix Operations

Matrix arithmetic and transformation functions.

def mxm(m1: ndarray, m2: ndarray) -> ndarray:
    """
    Multiply two matrices.
    
    Parameters:
    - m1: ndarray, first matrix
    - m2: ndarray, second matrix
    
    Returns:
    ndarray: product matrix m1 * m2
    """

def mxv(m: ndarray, v: ndarray) -> ndarray:
    """
    Multiply matrix by vector.
    
    Parameters:
    - m: ndarray, matrix
    - v: ndarray, vector
    
    Returns:
    ndarray: product vector m * v
    """

def mtxv(m: ndarray, v: ndarray) -> ndarray:
    """
    Multiply transpose of matrix by vector.
    
    Parameters:
    - m: ndarray, matrix
    - v: ndarray, vector
    
    Returns:
    ndarray: product vector m^T * v
    """

def xpose(m: ndarray) -> ndarray:
    """
    Transpose a 3x3 matrix.
    
    Parameters:
    - m: ndarray, 3x3 matrix
    
    Returns:
    ndarray: transposed matrix
    """

def invert(m: ndarray) -> ndarray:
    """
    Invert a matrix.
    
    Parameters:
    - m: ndarray, input matrix
    
    Returns:
    ndarray: inverted matrix
    """

Common Usage Patterns

Vector Analysis

import spiceypy as spice
import numpy as np

# Define two vectors
v1 = np.array([1.0, 2.0, 3.0])
v2 = np.array([4.0, 5.0, 6.0])

# Basic operations
sum_vec = spice.vadd(v1, v2)
dot_product = spice.vdot(v1, v2)
cross_product = spice.vcrss(v1, v2)
magnitude = spice.vnorm(v1)
unit_vector = spice.vhat(v1)

print(f"Sum: {sum_vec}")
print(f"Dot product: {dot_product}")
print(f"Cross product: {cross_product}")
print(f"Magnitude: {magnitude:.3f}")
print(f"Unit vector: {unit_vector}")

Matrix Transformations

# Create rotation matrix and apply to vector
angle = spice.rpd() * 45  # 45 degrees in radians
rotation_matrix = spice.rotate(angle, 3)  # Rotate about Z-axis

vector = np.array([1.0, 0.0, 0.0])
rotated_vector = spice.mxv(rotation_matrix, vector)
print(f"Rotated vector: {rotated_vector}")

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