Machine Limit¶
Particula Index / Particula / Util / Machine Limit
Auto-generated documentation for particula.util.machine_limit module.
get_safe_exp¶
Show source in machine_limit.py:12
Compute the exponential of each element in the input array, with overflow protection.
The exponential is calculated using: - y = exp(x), where x is clipped to avoid exceeding machine limits.
Arguments¶
- value : Array-like of values to exponentiate.
Returns¶
- np.ndarray of exponentiated values, with machine-level clipping.
Examples¶
import numpy as np
import particula as par
arr = np.array([0, 10, 1000])
print(par.get_safe_exp(arr))
# Output: [1.00000000e+000 2.20264658e+004 1.79769313e+308]
References¶
- "Floating Point Arithmetic," NumPy Documentation, NumPy.org.
Signature¶
def get_safe_exp(value: ArrayLike) -> np.ndarray: ...
get_safe_log¶
Show source in machine_limit.py:44
Compute the natural logarithm of each element in the input array, with underflow protection.
The natural log is calculated using: - y = ln(x), where x is clipped away from zero to maintain positivity.
Arguments¶
- value : Array-like of values for logarithm calculation.
Returns¶
- np.ndarray of natural logarithms, with machine-level clipping.
Examples¶
import numpy as np
import particula as par
arr = np.array([1e-320, 1.0, 10.0])
print(get_safe_log(arr))
# Output: [-7.40545337e+02 0.00000000e+00 2.30258509e+00]
References¶
- "Logarithms and Machine Precision," NumPy Documentation, NumPy.org.
Signature¶
def get_safe_log(value: ArrayLike) -> np.ndarray: ...
get_safe_log10¶
Show source in machine_limit.py:76
Compute the base-10 logarithm of each element in the input array, with underflow protection.
The base-10 log is calculated using: - y = log10(x), where x is clipped away from zero to maintain positivity.
Arguments¶
- value : Array-like of values for base-10 logarithm calculation.
Returns¶
- np.ndarray of base-10 logarithms, with machine-level clipping.
Examples¶
import numpy as np
import particula as par
arr = np.array([1e-320, 1.0, 1000.0])
print(par.get_safe_log10(arr))
# Output: [-320. 0. 3. ]
References¶
- "Logarithms and Machine Precision," NumPy Documentation, NumPy.org.
Signature¶
def get_safe_log10(value: ArrayLike) -> np.ndarray: ...