functions

ampdb(amp)

Convert amplitude to decibels.

Source code in mmm_utils/functions.py

def ampdb(amp: float) -> float:
    """Convert amplitude to decibels."""
    if amp <= 0:
        return -float('inf')  # Return negative infinity for zero or negative amplitude
    return 20.0 * np.log10(amp)

clip(val, min_val, max_val)

Clip a value to be within a specified range.

Source code in mmm_utils/functions.py

def clip(val: float, min_val: float, max_val: float) -> float:
    """Clip a value to be within a specified range."""
    return max(min_val, min(max_val, val))

cpsmidi(frequency)

Convert frequency in Hz to MIDI note number

Source code in mmm_utils/functions.py

def cpsmidi(frequency: float) -> float:
    """Convert frequency in Hz to MIDI note number"""
    return 69.0 + 12 * math.log2(frequency / 440.0)

lincurve(value, in_min, in_max, out_min, out_max, curve=0)

Linear-to-curve transform

Parameters:

Name	Type	Description	Default
value	float	Input value to transform	required
in_min	float	Minimum of input range (linear)	required
in_max	float	Maximum of input range (linear)	required
out_min	float	Minimum of output range	required
out_max	float	Maximum of output range	required
curve	float	Curve parameter curve = 0: linear curve > 0: exponential-like (steep at end) curve < 0: logarithmic-like (steep at start)	0

Returns:

Type	Description
float	Curved output value

Source code in mmm_utils/functions.py

def lincurve(value: float, in_min: float, in_max: float, out_min: float, out_max: float, curve: float = 0) -> float:
    """
    Linear-to-curve transform

    Args:
        value: Input value to transform
        in_min: Minimum of input range (linear)
        in_max: Maximum of input range (linear)
        out_min: Minimum of output range
        out_max: Maximum of output range
        curve: Curve parameter
               curve = 0: linear
               curve > 0: exponential-like (steep at end)
               curve < 0: logarithmic-like (steep at start)

    Returns:
        Curved output value
    """
    # Normalize input to 0-1 range
    normalized = (value - in_min) / (in_max - in_min)

    if curve == 0:
        # Linear case
        curved = normalized
    else:
        # Apply curve transformation
        if curve > 0:
            # Exponential-like curve
            curved = (np.exp(curve * normalized) - 1) / (np.exp(curve) - 1)
        else:
            # Logarithmic-like curve (curve < 0)
            curved = np.log(1 + abs(curve) * normalized) / np.log(1 + abs(curve))

    # Map to output range
    result = out_min + curved * (out_max - out_min)
    return result

linexp(value, in_min, in_max, out_min, out_max)

Linear-to-exponential transform

Parameters:

Name	Type	Description	Default
value	float	Input value to transform	required
in_min	float	Minimum of input range (linear)	required
in_max	float	Maximum of input range (linear)	required
out_min	float	Minimum of output range (exponential)	required
out_max	float	Maximum of output range (exponential)	required

Returns:

Type	Description
float	Exponentially scaled output value

Source code in mmm_utils/functions.py

def linexp(value: float, in_min: float, in_max: float, out_min: float, out_max: float) -> float:
    """
    Linear-to-exponential transform

    Args:
        value: Input value to transform
        in_min: Minimum of input range (linear)
        in_max: Maximum of input range (linear)
        out_min: Minimum of output range (exponential)
        out_max: Maximum of output range (exponential)

    Returns:
        Exponentially scaled output value
    """
    if out_min <= 0 or out_max <= 0:
        raise ValueError("Output range must be positive for exponential scaling")

    # Normalize input to 0-1 range
    normalized = (value - in_min) / (in_max - in_min)

    # Apply exponential scaling
    ratio = out_max / out_min
    result = out_min * (ratio ** normalized)

    return result

linlin(value, in_min, in_max, out_min, out_max)

Linear-linear transform: map value from input range to output range

Parameters:

Name	Type	Description	Default
value	float	Input value to transform	required
in_min	float	Minimum of input range	required
in_max	float	Maximum of input range	required
out_min	float	Minimum of output range	required
out_max	float	Maximum of output range	required

Returns:

Type	Description
float	Transformed value in output range

Source code in mmm_utils/functions.py

def linlin(value: float, in_min: float, in_max: float, out_min: float, out_max: float) -> float:
    """
    Linear-linear transform: map value from input range to output range

    Args:
        value: Input value to transform
        in_min: Minimum of input range
        in_max: Maximum of input range
        out_min: Minimum of output range
        out_max: Maximum of output range

    Returns:
        Transformed value in output range
    """
    return out_min + (value - in_min) * (out_max - out_min) / (in_max - in_min)

midicps(midi_note)

Convert MIDI note number to frequency in Hz

Source code in mmm_utils/functions.py

def midicps(midi_note: float) -> float:
    """Convert MIDI note number to frequency in Hz"""
    return 440.0 * (2.0 ** ((midi_note - 69.0) / 12.0))

scale(val=0, in_min=0, in_max=1, out_min=0, out_max=1)

Scale a value from one range to another.

Source code in mmm_utils/functions.py

def scale(val: float = 0, in_min: float = 0, in_max: float = 1, out_min: float = 0, out_max: float = 1) -> float:
    """Scale a value from one range to another."""
    in_range = in_max - in_min
    norm_val = (val - in_min) / in_range if in_range != 0 else 0
    out_range = out_max - out_min
    scaled_val = (norm_val * out_range) + out_min
    return scaled_val