More Math

Adds math nodes for numbers and types which do not need it. I got inspired by was_extras node.

WARNING This node is not compatible to ComfyUI-Impact-Pack and ComfyUI-Ovi which forces older antlr version

Quickstart

1. Install ComfyUI.
2. Clone this repository into ComfyUI/custom_nodes.
3. open command prompt/terminal/bash in your comfy folder
4. activate environment ./venv/Scripts/activate
5. install antlr pip install -U antlr4-python3-runtime==4.13.2
6. Restart ComfyUI.

You can also get the node from comfy manager under the name of More math.

Features

• functions and variables in math expressions

• Conversion between INT and FLOAT; AUDIO and IMAGE (red - real - strenght of cosine of frequency; blue - imaginary - strenght of sine of frequency; green - log1p of amplitude - just so it looks good to humans)

• Nodes for FLOAT, CONDITIONING, LATENT, IMAGE, NOISE, AUDIO, VIDEO, MODEL, CLIP and VAE

• Vector Math: Support for List literals [v1, v2, ...] and operations between lists/scalars/tensors

Operators

• Math: +, -, *, /, %, ^, |x| (norm/abs)
• Boolean: <, <=, >, >=, ==, != (false = 0.0, true = 1.0)
• Lists: [v1, v2, ...] (Vector math supported, mostly usefull in conv and permute)
  • You can also use lists to do math with input tensor (image, noise, conditioing, latent, audio) which results in batched output.
  • print_shape(a) = torch.Shape[1,1024,1024,3]; b = a*[0,0.2,-0.3]; print_shape(b) = torch.Shape[3,1024,1024,3]
  • You can <operator> batched tensor with another tensor which is not batched (dim[0] = 1) - the non batched tensor will be duplicated along batch dimension
  • In imageMath node you can use 3 element list to specify a color of image. You cannot use any imput tensor, doing so will result in behaviour in subpoint 1 in list

Functions

Basic Math

• abs(x) or |x|: Absolute value. For float abs(x) and |x| are the same. For tensor abs(x) calculates element-wise absolute value and for |x| it calculates L2 norm (euclidean norm).
• sqrt(x): Square root.
• ln(x): Natural logarithm (base e).
• log(x): Logarithm base 10.
• exp(x): Exponential function (e^x).
• pow(x, y): Power function (x^y).
• floor(x): Rounds down to nearest integer.
• ceil(x): Rounds up to nearest integer.
• round(x): Rounds to nearest integer.
• fract(x): Returns the fractional part of x (x - floor(x)).
• sign(x): Returns -1 for negative, 1 for positive, 0 for zero.
• gamma(x): Gamma function.
• range(start, end, step): Generates a list of values from start (inclusive) to end (exclusive) with given step.

Trigonometric

• sin(x), cos(x), tan(x)
• asin(x), acos(x), atan(x)
• atan2(y, x): Arctangent of y/x, handling quadrants.

Hyperbolic

• sinh(x), cosh(x), tanh(x)
• asinh(x), acosh(x), atanh(x)

Machine Learning / Activation

• relu(x): Rectified Linear Unit (max(0, x)).
• gelu(x): Gaussian Error Linear Unit.
• softplus(x): Softplus function (log(1 + e^x)).
• sigm(x): Sigmoid function (1 / (1 + e^-x)).

Shaders / Interpolation

• clamp(x, min, max): Constrains x to be between min and max.
• lerp(a, b, w): Linear interpolation: a + (b - a) * w.
• step(x, edge): Returns 1.0 if x >= edge, else 0.0.
• smoothstep(x, edge0, edge1): Hermite interpolation between edge0 and edge1.

Aggregates & Tensor Operations

• tmin(x, y): Element-wise minimum of x and y.
• tmax(x, y): Element-wise maximum of x and y.
• smin(x, ...): Scalar minimum. Returns the single smallest value across all input tensors/values.
• smax(x, ...): Scalar maximum. Returns the single largest value across all input tensors/values.
• tnorm(x): Tensor Normalizes x (L2 norm along last dimension).
• snorm(x): Scalar L2 norm of the entire tensor.
• swap(tensor, dim, index1, index2): Swaps two slices of a tensor along a specified dimension. (Tensor only)

Advanced Tensor Operations (Tensor Only)

• map(tensor, c1, ...): Remaps tensor using source coordinates.

  • Up to 3 coordinate mapping functions can be provided which map to the last (up to 3) dimensions of the tensor. Rest uses identity mapping.

• conv(tensor, kw, [kh], [kd], k_expr): Applies a convolution to tensor.

  • k_expr can be a math expression (using kX, kY, kZ) or a list literal.

• permute(tensor, dims): Rearranges the dimensions of the tensor. (e.g., permute(a, [2, 3, 0, 1]))

• reshape(tensor, shape): Reshapes the tensor to a new shape. (e.g., reshape(a, [S0*S1, S2, S3]))

FFT (Tensor Only)

• fft(x): Fast Fourier Transform (Time to Frequency).
• ifft(x): Inverse Fast Fourier Transform (Frequency to Time).
• angle(x): Returns the element-wise angle (phase) of the complex tensor.

Utility

• print(x): Prints the value of x to the console and returns x.
• print_shape(x) or pshp: Prints the shape of x to the console and returns x.

Variables

• Common variables (except FLOAT, MODEL, VAE and CLIP):

  • D{N} - position in n-th dimension of tensor (for example D0, D1, D2, ...)
  • S{N} - size of n-th dimension of tensor (for example S0, S1, S2, ...)

• common inputs (matches node input type):

  • a, b, c, d

• Extra floats:

  • w, x, y, z

• INSIDE IFFT

  • F or frequency_count – frequency count (freq domain, iFFT only)
  • K or frequency – isotropic frequency (Euclidean norm of indices, iFFT only)
  • Kx, Ky, K_dimN - frequency index for specific dimension
  • Fx, Fy, F_dimN - frequency count for specific dimension

• IMAGE and LATENT:

  • C or channel - channel of image
  • X - position X in image. 0 is in top left
  • Y - position Y in image. 0 is in top left
  • W or width - width of image. y/width = 1
  • H or height- height of image. x/height = 1
  • B or 'batch' - position in batch
  • T or batch_count - number of batches
  • N or channel_count - count of channels

• IMAGE KERNEL:

  • kX, kY - position in kernel. Centered at 0.0.
  • kW, kernel_width - width of kernel.
  • kH, kernel_height - height of kernel.
  • kD, kernel_depth - depth of kernel.

• AUDIO:

  • B or 'batch' - position in batch
  • N or channel_count - count of channels
  • C or channel - channel of audio
  • S or sample – current audio sample
  • 'T' or 'sample_count` - audio lenght in samples
  • R or sample_rate – sample rate

• VIDEO

  • refer to IMAGE and LATENT for visual part (but batch is frame and batch_count is frame_count)
  • refer to AUDIO for sound part

• NOISE

  • refer to IMAGE and LATENT for most variables
  • I or input_latent – latent used as input to generate noise before noise is generated into it

• CONDITIONING and FLOAT

  • no additional variables
  • F or frequency_count – frequency count (freq domain, iFFT only)
  • K or frequency – isotropic frequency (Euclidean norm of indices, iFFT only)
  • Kx, Ky, Kz, Kw,Kv, Ku, K_dimN - frequency index for specific dimension
  • Fx, Fy, Fz, Fw,Fv,Fu, F_dimN - frequency count for specific dimension

• Constants: e, pi