Math operations. More...
Macros | |
#define | VL_E 2.718281828459045 |
Euler constant. | |
#define | VL_LOG_OF_2 0.693147180559945 |
Logarithm of 2 (math constant) | |
#define | VL_PI 3.141592653589793 |
Pi (math constant) | |
#define | VL_EPSILON_F 1.19209290E-07F |
IEEE single precision epsilon (math constant) | |
#define | VL_EPSILON_D 2.220446049250313e-16 |
IEEE double precision epsilon (math constant) | |
#define | VL_NAN_F (vl_nan_f.value) |
IEEE single precision NaN (not signaling) | |
#define | VL_INFINITY_F (vl_infinity_f.value) |
IEEE single precision positive infinity (not signaling) | |
#define | VL_NAN_D (vl_nan_d.value) |
IEEE double precision NaN (not signaling) | |
#define | VL_INFINITY_D (vl_infinity_d.value) |
IEEE double precision positive infinity (not signaling) |
Typedefs | |
typedef float(* | VlFloatVectorComparisonFunction )(vl_size dimension, float const *X, float const *Y) |
Pointer to a function to compare vectors of floats. | |
typedef double(* | VlDoubleVectorComparisonFunction )(vl_size dimension, double const *X, double const *Y) |
Pointer to a function to compare vectors of doubles. | |
typedef float(* | VlFloatVector3ComparisonFunction )(vl_size dimension, float const *X, float const *Y, float const *Z) |
Pointer to a function to compare 3 vectors of doubles. | |
typedef double(* | VlDoubleVector3ComparisonFunction )(vl_size dimension, double const *X, double const *Y, double const *Z) |
Pointer to a function to compare 3 vectors of doubles. | |
typedef enum _VlVectorComparisonType | VlVectorComparisonType |
Vector comparison types. |
Enumerations | |
enum | _VlVectorComparisonType { VlDistanceL1, VlDistanceL2, VlDistanceChi2, VlDistanceHellinger, VlDistanceJS, VlDistanceMahalanobis, VlKernelL1, VlKernelL2, VlKernelChi2, VlKernelHellinger, VlKernelJS } |
Vector comparison types. More... |
Functions | |
float | vl_mod_2pi_f (float x) |
Fast mod(x, 2 * VL_PI) | |
double | vl_mod_2pi_d (double x) |
Fast mod(x, 2 * VL_PI) | |
long int | vl_floor_f (float x) |
Floor and convert to integer. | |
long int | vl_floor_d (double x) |
Floor and convert to integer. | |
long int | vl_ceil_f (float x) |
Ceil and convert to integer. | |
long int | vl_ceil_d (double x) |
Ceil and convert to integer. | |
long int | vl_round_f (float x) |
Round. | |
long int | vl_round_d (double x) |
Round. | |
float | vl_abs_f (float x) |
Fast abs(x) | |
double | vl_abs_d (double x) |
Fast abs(x) | |
double | vl_log2_d (double x) |
Base-2 logaritghm. | |
float | vl_log2_f (float x) |
Base-2 logaritghm. | |
double | vl_sqrt_d (double x) |
Square root. | |
float | vl_sqrt_f (float x) |
Square root. | |
vl_bool | vl_is_nan_f (float x) |
Check whether a floating point value is NaN. | |
vl_bool | vl_is_nan_d (double x) |
Check whether a floating point value is NaN. | |
vl_bool | vl_is_inf_f (float x) |
Check whether a floating point value is infinity. | |
vl_bool | vl_is_inf_d (double x) |
Check whether a floating point value is infinity. | |
float | vl_fast_atan2_f (float y, float x) |
Fast atan2 approximation. | |
double | vl_fast_atan2_d (double y, double x) |
Fast atan2 approximation. | |
float | vl_fast_resqrt_f (float x) |
Fast resqrt approximation. | |
double | vl_fast_resqrt_d (double x) |
Fast resqrt approximation. | |
float | vl_fast_sqrt_f (float x) |
Fast sqrt approximation. | |
double | vl_fast_sqrt_d (float x) |
Fast sqrt approximation. | |
vl_uint32 | vl_fast_sqrt_ui32 (vl_uint32 x) |
Fast sqrt approximation. | |
vl_uint16 | vl_fast_sqrt_ui16 (vl_uint16 x) |
Fast sqrt approximation. | |
vl_uint8 | vl_fast_sqrt_ui8 (vl_uint8 x) |
Fast sqrt approximation. | |
char const * | vl_get_vector_comparison_type_name (int type) |
Get the symbolic name of a vector comparison type. | |
VlFloatVectorComparisonFunction | vl_get_vector_comparison_function_f (VlVectorComparisonType type) |
Get vector comparison function from comparison type. | |
VlDoubleVectorComparisonFunction | vl_get_vector_comparison_function_d (VlVectorComparisonType type) |
Get vector comparison function from comparison type. | |
void | vl_eval_vector_comparison_on_all_pairs_f (float *result, vl_size dimension, float const *X, vl_size numDataX, float const *Y, vl_size numDataY, VlFloatVectorComparisonFunction function) |
Evaluate vector comparison function on all vector pairs. | |
void | vl_eval_vector_comparison_on_all_pairs_d (double *result, vl_size dimension, double const *X, vl_size numDataX, double const *Y, vl_size numDataY, VlDoubleVectorComparisonFunction function) |
Evaluate vector comparison function on all vector pairs. |
Variables | |
union { | |
} | vl_nan_f |
IEEE single precision quiet NaN constant. | |
union { | |
} | vl_infinity_f |
IEEE single precision infinity constant. | |
union { | |
} | vl_nan_d |
IEEE double precision quiet NaN constant. | |
union { | |
} | vl_infinity_d |
IEEE double precision infinity constant. |
Detailed Description
Comparing vectors
mathop.h includes a number of functions to quickly compute distances or similarity of pairs of vector. Applications include clustering and evaluation of SVM-like classifiers.
Use vl_get_vector_comparison_function_f or vl_get_vector_comparison_function_d obtain an approprite function to comprare vectors of floats or doubles, respectively. Such functions are usually optimized (for instance, on X86 platforms they use the SSE vector extension) and are several times faster than a naive implementation. vl_eval_vector_comparison_on_all_pairs_f and vl_eval_vector_comparison_on_all_pairs_d can be used to evaluate the comparison function on all pairs of one or two sequences of vectors.
Let \( \mathbf{x} = (x_1,\dots,x_d) \) and \( \mathbf{y} = (y_1,\dots,y_d) \) be two vectors. The following comparison functions are supported:
\( l^1 \) | VlDistanceL1 | \( \sum_{i=1}^d |x_i - y_i| \) | l1 distance (squared intersection metric) |
\( l^2 \) | VlDistanceL2 | \(\sum_{i=1}^d (x_i - y_i)^2\) | Squared Euclidean disance |
\( \chi^2 \) | VlDistanceChi2 | \(\sum_{i=1}^d \frac{(x_i - y_i)^2}{x_i + y_i}\) | Squared chi-square distance |
- | VlDistanceHellinger | \(\sum_{i=1}^d (\sqrt{x_i} - \sqrt{y_i})^2\) | Squared Hellinger's distance |
- | VlDistanceJS | \( \sum_{i=1}^d \left( x_i \log\frac{2x_i}{x_i+y_i} + y_i \log\frac{2y_i}{x_i+y_i} \right) \) | Squared Jensen-Shannon distance |
\( l^1 \) | VlKernelL1 | \( \sum_{i=1}^d \min\{ x_i, y_i \} \) | intersection kernel |
\( l^2 \) | VlKernelL2 | \(\sum_{i=1}^d x_iy_i \) | linear kernel |
\( \chi^2 \) | VlKernelChi2 | \(\sum_{i=1}^d 2 \frac{x_iy_i}{x_i + y_i}\) | chi-square kernel |
- | VlKernelHellinger | \(\sum_{i=1}^d 2 \sqrt{x_i y_i}\) | Hellinger's kernel (Bhattacharya coefficient) |
- | VlKernelJS | \( \sum_{i=1}^d \left( \frac{x_i}{2} \log_2\frac{x_i+y_i}{x_i} + \frac{y_i}{2} \log_2\frac{x_i+y_i}{y_i} \right) \) | Jensen-Shannon kernel |
- Remarks:
- The definitions have been choosen so that corresponding kernels and distances are related by the equation:
\[ d^2(\mathbf{x},\mathbf{y}) = k(\mathbf{x},\mathbf{x}) +k(\mathbf{y},\mathbf{y}) -k(\mathbf{x},\mathbf{y}) -k(\mathbf{y},\mathbf{x}) \]
This means that each of these distances can be interpreted as a squared distance or metric in the corresponding reproducing kernel Hilbert space. Notice in particular that the \( l^1 \) or Manhattan distance is also a squared distance in this sense.
Macro Definition Documentation
#define VL_EPSILON_D 2.220446049250313e-16 |
1.0 + VL_EPSILON_D
is the smallest representable double precision number greater than 1.0
. Numerically, VL_EPSILON_D is equal to \( 2^{-52} \).
#define VL_EPSILON_F 1.19209290E-07F |
1.0F + VL_EPSILON_F
is the smallest representable single precision number greater than 1.0F
. Numerically, VL_EPSILON_F is equal to \( 2^{-23} \).
Enumeration Type Documentation
- Enumerator:
Function Documentation
|
inline |
- See also:
- vl_abs_f
|
inline |
- Parameters:
-
x argument.
- Returns:
abs(x)
|
inline |
- See also:
- vl_ceil_f
|
inline |
- Parameters:
-
x argument.
- Returns:
lceilf(x)
vl_eval_vector_comparison_on_all_pairs_d | ( | double * | result, |
vl_size | dimension, | ||
double const * | X, | ||
vl_size | numDataX, | ||
double const * | Y, | ||
vl_size | numDataY, | ||
VlDoubleVectorComparisonFunction | function | ||
) |
vl_eval_vector_comparison_on_all_pairs_f | ( | float * | result, |
vl_size | dimension, | ||
float const * | X, | ||
vl_size | numDataX, | ||
float const * | Y, | ||
vl_size | numDataY, | ||
VlFloatVectorComparisonFunction | function | ||
) |
- Parameters:
-
result comparison matrix (output). dimension number of vector components (rows of X and Y). X data matrix X. Y data matrix Y. numDataX number of vectors in X (columns of X) numDataY number of vectros in Y (columns of Y) function vector comparison function.
The function evaluates function on all pairs of columns from matrices X and Y, filling a numDataX by numDataY matrix.
If Y is a null pointer the function compares all columns from X with themselves.
|
inline |
- See also:
- vl_fast_atan2_f
|
inline |
- Parameters:
-
y argument. x argument.
The function computes a relatively rough but fast approximation of atan2(y,x)
.
- Algorithm
The algorithm approximates the function \( f(r)=atan((1-r)/(1+r)) \), \( r \in [-1,1] \) with a third order polynomial \( f(r)=c_0 + c_1 r + c_2 r^2 + c_3 r^3 \). To fit the polynomial we impose the constraints
\begin{eqnarray*} f(+1) &=& c_0 + c_1 + c_2 + c_3 = atan(0) = 0,\\ f(-1) &=& c_0 - c_1 + c_2 - c_3 = atan(\infty) = \pi/2,\\ f(0) &=& c_0 = atan(1) = \pi/4. \end{eqnarray*}
The last degree of freedom is fixed by minimizing the \( l^{\infty} \) error, which yields
\[ c_0=\pi/4, \quad c_1=-0.9675, \quad c_2=0, \quad c_3=0.1821, \]
with maximum error of 0.0061 radians at 0.35 degrees.
- Returns:
- Approximation of
atan2(y,x)
.
|
inline |
- See also:
- vl_fast_resqrt_d
|
inline |
- Parameters:
-
x argument.
- Returns:
- approximation of
resqrt(x)
.
The function quickly computes an approximation of \( x^{-1/2} \).
- Algorithm
The goal is to compute \( y = x^{-1/2} \), which we do by finding the solution of \( 0 = f(y) = y^{-2} - x \) by two Newton steps. Each Newton iteration is given by
\[ y \leftarrow y - \frac{f(y)}{\frac{df(y)}{dy}} = y + \frac{1}{2} (y-xy^3) = \frac{y}{2} \left( 3 - xy^2 \right) \]
which yields a simple polynomial update rule.
The clever bit (attributed to either J. Carmack or G. Tarolli) is the way an initial guess \( y \approx x^{-1/2} \) is chosen.
- See also:
- Inverse Sqare Root.
|
inline |
- See also:
- vl_fast_sqrt_f
|
inline |
- Parameters:
-
x argument.
- Returns:
- approximation of
sqrt(x)
.
The function computes a cheap approximation of sqrt(x)
.
- Floating-point algorithm
For the floating point cases, the function uses vl_fast_resqrt_f (or vl_fast_resqrt_d) to compute x * vl_fast_resqrt_f(x)
.
- Integer algorithm
We seek for the largest integer y such that \( y^2 \leq x \). Write \( y = w + b_k 2^k + z \) where the binary expansion of the various variable is
\[ x = \sum_{i=0}^{n-1} 2^i a_i, \qquad w = \sum_{i=k+1}^{m-1} 2^i b_i, \qquad z = \sum_{i=0}^{k-1} 2^i b_i. \]
Assume w known. Expanding the square and using the fact that \( b_k^2=b_k \), we obtain the following constraint for \( b_k \) and z:
\[ x - w^2 \geq 2^k ( 2 w + 2^k ) b_k + z (z + 2wz + 2^{k+1}z b_k) \]
A necessary condition for \( b_k = 1 \) is that this equation is satisfied for \( z = 0 \) (as the second term is always non-negative). In fact, this condition is also sufficient, since we are looking for the largest solution y.
This yields the following iterative algorithm. First, note that if x is stored in n bits, where n is even, then the integer square root does not require more than \( m = n / 2 \) bit to be stored. Thus initially, \( w = 0 \) and \( k = m - 1 = n/2 - 1 \). Then, at each iteration the equation is tested, determining \( b_{m-1}, b_{m-2}, ... \) in this order.
- See also:
- vl_fast_sqrt_f
- See also:
- vl_fast_sqrt_f
- See also:
- vl_fast_sqrt_f
|
inline |
- See also:
- vl_floor_f
|
inline |
- Parameters:
-
x argument.
- Returns:
- Similar to
(int) floor(x)
vl_get_vector_comparison_function_d | ( | VlVectorComparisonType | type | ) |
- See also:
- vl_get_vector_comparison_function_f
vl_get_vector_comparison_function_f | ( | VlVectorComparisonType | type | ) |
- Parameters:
-
type vector comparison type.
- Returns:
- comparison function.
|
inline |
- Parameters:
-
type vector comparison type.
- Returns:
- data symbolic name.
|
inline |
- Parameters:
-
x argument.
- Returns:
- true if x is infinity.
|
inline |
- Parameters:
-
x argument.
- Returns:
- true if x is infinity.
|
inline |
- Parameters:
-
x argument.
- Returns:
- true if x is NaN.
|
inline |
- Parameters:
-
x argument.
- Returns:
- true if x is NaN.
|
inline |
- Parameters:
-
x argument.
- Returns:
log(x)
.
|
inline |
- Parameters:
-
x argument.
- Returns:
log(x)
.
|
inline |
- See also:
- vl_mod_2pi_f
|
inline |
- Parameters:
-
x input value.
- Returns:
mod(x, 2 * VL_PI)
The function is optimized for small absolute values of x.
The result is guaranteed to be not smaller than 0. However, due to finite numerical precision and rounding errors, the result can be equal to 2 * VL_PI (for instance, if x
is a very small negative number).
|
inline |
- Parameters:
-
x argument.
- Returns:
lround(x)
This function is either the same or similar to C99lround()
.
|
inline |
- Parameters:
-
x argument.
- Returns:
lroundf(x)
This function is either the same or similar to C99lroundf()
.
|
inline |
- Parameters:
-
x argument.
- Returns:
sqrt(x)
.
|
inline |
- Parameters:
-
x argument.
- Returns:
sqrt(x)
.
Variable Documentation
union { ... } vl_infinity_d |
union { ... } vl_infinity_f |
union { ... } vl_nan_d |
union { ... } vl_nan_f |