GDBlas

This native Godot extension provides real and complex matrix algebra. It uses data structures and matrix iterators of Eigen library, also includes ODE solver based on ODEINT.

In version 1.4.0, BoostC++ Geometry algorithms are added.

Demos

1. There is a demo project in demo directory which includes numerous tests and displacement simulation of a flexible structure. Its mathematical model can be found in my PhD thesis (Chapter 6).
2. 3D demo project based on a Godot example. It displays filtered versions of the texture in Viewport as shown below.

https://gist.github.com/user-attachments/assets/aa9c1056-6da8-4c55-9c86-5937d3cd315c

An example:

var gbl = GDBlas.new()
var A = gbl.new_mat(3, 2)
var b = gbl.new_mat(2, 1)
A.from_array([ [1, 2], [3, 4], [5, 6] ])
b.from_array([ [1], [-1] ])
var c = A.prod(b)
print(c.to_array())
c.abs()
print(c.to_array())
c.log()
print(c.to_array())
c.add(3)
print(c.to_array())

will print out

>>> [ [-1], [-1], [-1] ]
>>> [ [1], [1], [1] ]
>>> [ [0], [0], [0] ]
>>> [ [3], [3], [3] ]

Classes

GDBlas

Reference counted base class which is used to create new matrices

Methods

• new_mat(p_rows, p_cols = -1): Creates new real matrix, Usage:

var gbl = GDBlas.new()
var A = gbl.new_mat(3, 12) # Creates a 3 by 12 real matrix
var B = gbl.new_mat(3) # Creates a 3 by 3 real matrix
var C = gbl.new_mat(Vector2i(4, 2)) # Creates a 4 by 2 real matrix

• new_complex_mat(p_rows, p_cols = -1): Creates new complex matrix
• linspace(p_start, p_end, p_count): Creates a column vector of linearly spaced values

var gbl = GDBlas.new()
var A = gbl.linspace(0, 1, 3) # Creates a 3 by 1 matrix with entries [ [0], [0.5], [1] ]

• mat_to_image_data(p_mat_array: Array, p_channel_width: int = 1): Places the entries of GDBlasMat objects in p_mat_array into a PackedByteArray which matches the data structure returned from Image::get_data().

var gbl = GDBlas.new()
var dim = Vector2i(480, 640)
var R = gbl.new_mat(dim)
var G = gbl.new_mat(dim)
var B = gbl.new_mat(dim)

# fill and process R, G, B matrices

var pack: PackedByteArray = gbl.mat_to_image_data([ R, G, B ])
# An RGB8 formatted Image object can be created by using the data in 'pack'

• area(p_polygon: PackedVector2Array): Calculates the area of polygon. Points must be ordered in clockwise (CW) direction.

Boost Geometry

Data structures

List of Boost Geometry data structures and their representations in GDScript to be used by GDBlas's bindings of Boost Geometry algorithms.

• model::point ≡ Vector2
• model::linestring ≡ PackedVector2Array
• model::ring ≡ PackedVector2Array if the first and last values of the array are equal.
• model::polygon ≡ Array of PackedVector2Array where the first entry represents the outer ring and the other entries represent inner rings.
  • ring_type model::polygon::outer ≡ PackedVector2Array where the first and last values of the array are equal.
  • ring_type model::polygon::inners[i] ≡ PackedVector2Array where the first and last values of the array are equal.
• model::box ≡ Rect2

Algorithms

• area
• buffer
• centroid
• clear
• closest_points
• convert
• convex_hull
• correct
• covered_by
• crosses
• densify
• difference
• discrete_frechet_distance
• discrete_hausdorff_distance
• disjoint
• distance
• envelope
• equals
• intersection
• intersects
• is_empty
• is_simple
• is_valid
• length
• overlaps
• perimeter
• relation
• reverse
• simplify
• sym_difference
• touches
• transform
• union_
• unique
• within

Return types and errors

The algorithms above may not be used all combinations of models. In such cases and error message is emitted and function returns an invalid value. The map of return types and invalid values are given below.

• bool return types: Returns int. 1 = true, 0 = false, negative value on error.
• int return types: Returns int, negative value on error.
• double return types: Returns float, NaN on error.
• model::polygon return types: Returns Array of PackedVector2Array, empty Array on error.
• model::ring return types: Returns PackedVector2Array, empty PackedVector2Array on error.
• model::line return types: Returns PackedVector2Array, empty PackedVector2Array on error.
• model::point return types: Returns Vector2, Vector2(NaN, NaN) on error.
• model::box return types: Returns Rect2, Rect2(NaN, NaN, NaN, NaN) on error.

Examples

You can check the tests in demo/GDBlasTest.gd for learning how to use.

GDBlasMat

Reference counted real or complex matrix object. A real matrix returns enries as a float and complex matrix as Vector2.

Methods

• resize(m: Variant, n: int = -1): Resizes matrix to m by n if both are integer. n is not required if m is Vector2i.
• copy(): Creates a copy of matrix.

var gbl = GDBlas.new()
var A = gbl.new_mat(3)
var B = A.copy()

• dimension(): Returns the size of matrix as a Vector2i object
• get(i, j, m = -1, n = -1): Get a matrix entry or a submatrix of size m by n starting ith row and jth column. Returns 0 on success or error value.

var gbl = GDBlas.new()
var A = gbl.new_mat(3)
var a00: float = A.get(0, 0)
var Asub: GDBlasMat = A.get(1, 0, 2, 2) # Returns 2 by 2 sub matrix
var Ac = gbl.new_complex_mat(3)
var ac00: Vector2 = A.get(0, 0)

• set(val, i = -1, j = -1): Set a matrix entry or a submatrix of size m by n starting ith row and jth column. Returns 0 on success or error value.

var gbl = GDBlas.new()
var A = gbl.new_mat(3)
var a00: float = A.set(1, 0, 0)
var Asub = gbl.new_mat(2)
A.set(Asub, 1, 0)

• add(val): Adds a number or a matrix of same dimension. Returns 0 on success or error value.

var gbl = GDBlas.new()
var A = gbl.new_mat(3)
A.add(1)
var B = A.copy()
B.add(A)

• mul(val): Multiplies by a number or a matrix of same dimension. Returns 0 on success or error value.
• div(val): Divides by a number or a matrix of same dimension. Returns 0 on success or error value. NOTE: Can not add complex matrices to a real matrix
• sub(val): Subtracts a number or a matrix of same dimension. Returns 0 on success or error value.
• transpose(): Transposes the matrix. Returns 0 on success or error value.
• hermitian(): Hermitian transpose of matrix. Returns 0 on success or error value.
• is_eq(other, p_eps, p_norm_type): Checks if matrices are equal, meaning that norm of their differences are less than p_eps . Returns true or false

var gbl = GDBlas.new()
var A = gbl.new_mat(3)
var B = A.copy()
if A.is_eq(B):
    print("They are equal")

• fill(val): Sets all matrix entries to val. val can be a number or Vector2 if it is a complex matrix. Returns 0 on success.
• eye(val): Sets all diagonal matrix entries to val. val can be a number or Vector2 if it is a complex matrix. Returns 0 on success.
• reset(): Sets all entries to 0.
• conj(): Conjugates all matrix entries. Returns 0 on success.
• real(matrix): Returns or sets the real part of complex matrix. It is equivalent to set(matrix, 0, 0) on real case.
• imag(matrix): Returns or sets the imaginary part of complex matrix. It returns a matrix of zeros for real matrix case.
• prod(matrix): Returns product of matrices.

var gbl = GDBlas.new()
var A = gbl.new_mat(3)
var B = gbl.new_mat(3, 5)
var C = A.prod(B)

It is equivalent to C=AB, column count of A and row count of B must be equal.

• inv(): Computes the inverse of matrix. It can only be applied to square matrices. It will return the inverse matrix or null if matrix is singular.
• from_array(arr): Sets matrix entries according to the values on 2 dimensional array arr. Return 0 on success.

var gbl = GDBlas.new()
var A = gbl.new_mat(3, 2)
A.from_array([ [1, 2], [3, 4], [5, 6] ])

• to_array(): Returns a 2 dimensional array filled with matrix entries.

var gbl = GDBlas.new()
var A = gbl.new_complex_mat(2, 2)
A.eye(Vector2(1, -1))
print(A.to_array())

will print

>>> [ [(1,-1), (0,0)], [(0,0), (1,-1)] ]

• integrate(axis = -1): Calculates sum of matrix entries on given axis. axis=0: sums over rows, axis=1: sums of cols, axis=-1: (default) sum of all entries. Returns a GDBlasMat object containing the sum of values.
• mean(axis = -1): Calculates mean of matrix entries on given axis. axis=0: mean over rows, axis=1: mean of cols, axis=-1: (default) mean of all entries. Returns a GDBlasMat object containing the means.
• min(axis = -1): Finds the minimum of matrix entries on given axis. axis=0: min over rows, axis=1: min of cols, axis=-1: (default) min of all entries. Returns a GDBlasMat object containing the minimums.
• max(axis = -1): Finds the maximum of matrix entries on given axis. axis=0: max over rows, axis=1: max of cols, axis=-1: (default) max of all entries. Returns a GDBlasMat object containing the maximums.
• argmin(axis = -1): Finds the index of minimum of matrix entries on given axis. axis=0: min over rows, axis=1: min of cols, axis=-1: (default) min of all entries. Returns an Array of Vector2i containing the indices of minimums.
• argmax(axis = -1): Finds the index of maximum of matrix entries on given axis. axis=0: max over rows, axis=1: max of cols, axis=-1: (default) max of all entries. Returns an Array of Vector2i containing the indices of minimums.
• norm(norm_type): Computes $L1$, $L_{\infty}$ or Frobenius norm of matrix. Accepted arguments are GDBlas.NORM_1, GDBlas.NORM_INF or GDBlas.NORM_FRO. Returns float.
• eval_ode(p_f: Callable, p_dt: float, p_max_step: float = 1e-2): Evaluates the ordinary differential equation (ODE) defined in p_f for an amount of time given by p_dt starting from the current value of matrix. It can be called on only real n by 1 matrices (equivalent to a column vector). Returns the step count (how many times the ODE function is evaluated) or a negative value on error.

var A: GDBlasMat = null
func ode_fx(x: GDBlasMat, t: float):
    return A.prod(x)

func some_func():
    var gbl = GDBlas.new()
    A = gbl.new_mat(2)
    A.eye(-1)
    var x = gbl.new_mat(2, 1)
    x.fill(1)

    x.eval_ode(ode_fx, 0.5, 1e-3) # Writes final value at t = 0.5 into x itself

• conv(p_other: GDBlasMat, p_same: bool = false): Computes convolution of matrices. If p_same is true, returns the central part of the result.

var gbl = GDBlas.new()
A = gbl.new_mat(m1, n1)
A.from_array( ... ) # Fill with values.
B = gbl.new_mat(m2, n2)
B.from_array( ... ) # Fill with values.
var C = A.conv(B)
assert(C.dimension() == Vector2i(m1 + m2 - 1, n1 + n2 -1))
var D = B.conv(A, 'same')
assert(D.dimension() == Vector2i(m2, n2))

• pack(p_component: int = GDBlas.BOTH_COMPONENTS): Packs matrix entries into a PackedFloat64Array in row major format. Argument p_component can take values GDBlas.REAL_COMPONENT, GDBlas.IMAG_COMPONENT or GDBlas.BOTH_COMPONENTS. If both components of a complex matrix is packed imaginary part of each entry is placed right after the real component in the PackedFloat64Array. Returns PackedFloat64Array.
• unpack(p_packed_data: PackedFloat64Array, p_component: int = GDBlas.BOTH_COMPONENTS, p_step: int = 1, p_offset: int = 0): Unpacks the data in p_packed_data into the matrix. If p_step = n, each nth entry in the p_packed_data placed into the matrix starting from the entry indexed by p_offset. Number of elements in the array divided by p_step must match the matrix dimension.
• downsample(p_factor_m: int, p_factor_n: int, p_filter: GDBlasMat = null): Returns a new matrix constructed by picking rows and columns whose index satisfy row_index % p_factor_m == 0 and col_index % p_factor_n == 0. If p_filter provided, the matrix is filtered (by convolving) by the the coefficients of p_filter before down sampling.

Elementwise functions

A list of implemented math functions are given below. They operate elementwise on the matrix and modifies matrix itself instead of creating a copy. You can visit C++ stdlib documentation for mathematical meaning of these functions.

• f(p_func: Callable, p_args: Array = null, p_indexed: bool = false): Applies p_func on each matrix entry and writes the result in place. If p_indexed is true, p_func can have additional argumens which gives the row and column number of the matrix entry.

func add_1(a):
    return a + 1

func add_const(a, args: Array):
    return a + args[0]

func add_const_2(a, args: Array, i: int, j: int):
    if i < 1 and j < 1:
        return a + args[0]
    else:
        return a

func some_func():
    var gbl = GDBlas.new()
    var A = gbl.new_mat(2, 2)
    A.f(add_1)
    A.f(add_const, [ 3 ])
    A.f(add_const_2, [ 3 ], true)

NOTE: If the matrix is complex, first argument of callable is a Vector2 and its return type must also be Vector2.

• sin()

var gbl = GDBlas.new()
var vec = gbl.linspace(-0.5, 0.5, 256)
vec.mul(2 * PI)
vec.sin() # Calculate sine of vec and write in place.

• cos()
• abs()
• exp()
• log()
• log10()
• log2()
• sqrt()
• cbrt()
• tan()
• asin()
• acos()
• atan()
• sinh()
• cosh()
• tanh()
• atanh()
• erf()
• erfc()
• tgamma()
• lgamma()
• ceil()
• floor()
• trunc()
• round()

Build from source

git clone https://github.com/dmrokan/gdblas.git
cd gdblas
git submodule update --init --recursive

Build boost

cd boost
./bootstrap.sh
./b2 headers

You can visit Boost wiki for more information.

Build extension

scons platform=<platform> target_path=<target_path> target_name=libgdblas

You can visit Godot's build system documentation for more information.