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feat: add different brightness ramping mechanisms (#699)
* feat: add different brightness ramping mechanisms * Rephrase * Fix curves * update images * link to other graphs * update images
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| """Helper functions for the Adaptive Lighting custom components.""" | ||
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| from __future__ import annotations | ||
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| import base64 | ||
| import colorsys | ||
| import logging | ||
| import math | ||
| from typing import cast | ||
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| _LOGGER = logging.getLogger(__name__) | ||
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| def clamp(value: float, minimum: float, maximum: float) -> float: | ||
| """Clamp value between minimum and maximum.""" | ||
| return max(minimum, min(value, maximum)) | ||
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| def find_a_b(x1: float, x2: float, y1: float, y2: float) -> tuple[float, float]: | ||
| """Compute the values of 'a' and 'b' for a scaled and shifted tanh function. | ||
| Given two points (x1, y1) and (x2, y2), this function calculates the coefficients 'a' and 'b' | ||
| for a tanh function of the form y = 0.5 * (tanh(a * (x - b)) + 1) that passes through these points. | ||
| The derivation is as follows: | ||
| 1. Start with the equation of the tanh function: | ||
| y = 0.5 * (tanh(a * (x - b)) + 1) | ||
| 2. Rearrange the equation to isolate tanh: | ||
| tanh(a * (x - b)) = 2*y - 1 | ||
| 3. Take the inverse tanh (or artanh) on both sides to solve for 'a' and 'b': | ||
| a * (x - b) = artanh(2*y - 1) | ||
| 4. Plug in the points (x1, y1) and (x2, y2) to get two equations. | ||
| Using these, we can solve for 'a' and 'b' as: | ||
| a = (artanh(2*y2 - 1) - artanh(2*y1 - 1)) / (x2 - x1) | ||
| b = x1 - (artanh(2*y1 - 1) / a) | ||
| Parameters | ||
| ---------- | ||
| x1 | ||
| x-coordinate of the first point. | ||
| x2 | ||
| x-coordinate of the second point. | ||
| y1 | ||
| y-coordinate of the first point (should be between 0 and 1). | ||
| y2 | ||
| y-coordinate of the second point (should be between 0 and 1). | ||
| Returns | ||
| ------- | ||
| a | ||
| Coefficient 'a' for the tanh function. | ||
| b | ||
| Coefficient 'b' for the tanh function. | ||
| Notes | ||
| ----- | ||
| The values of y1 and y2 should lie between 0 and 1, inclusive. | ||
| """ | ||
| a = (math.atanh(2 * y2 - 1) - math.atanh(2 * y1 - 1)) / (x2 - x1) | ||
| b = x1 - (math.atanh(2 * y1 - 1) / a) | ||
| return a, b | ||
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| def scaled_tanh( | ||
| x: float, | ||
| a: float, | ||
| b: float, | ||
| y_min: float = 0.0, | ||
| y_max: float = 100.0, | ||
| ) -> float: | ||
| """Apply a scaled and shifted tanh function to a given input. | ||
| This function represents a transformation of the tanh function that scales and shifts | ||
| the output to lie between y_min and y_max. For values of 'x' close to 'x1' and 'x2' | ||
| (used to calculate 'a' and 'b'), the output of this function will be close to 'y_min' | ||
| and 'y_max', respectively. | ||
| The equation of the function is as follows: | ||
| y = y_min + (y_max - y_min) * 0.5 * (tanh(a * (x - b)) + 1) | ||
| Parameters | ||
| ---------- | ||
| x | ||
| The input to the function. | ||
| a | ||
| The scale factor for the tanh function, found using 'find_a_b' function. | ||
| b | ||
| The shift factor for the tanh function, found using 'find_a_b' function. | ||
| y_min | ||
| The minimum value of the output range. Defaults to 0. | ||
| y_max | ||
| The maximum value of the output range. Defaults to 100. | ||
| Returns | ||
| ------- | ||
| float: The output of the function, which lies in the range [y_min, y_max]. | ||
| """ | ||
| return y_min + (y_max - y_min) * 0.5 * (math.tanh(a * (x - b)) + 1) | ||
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| def lerp_color_hsv( | ||
| rgb1: tuple[float, float, float], | ||
| rgb2: tuple[float, float, float], | ||
| t: float, | ||
| ) -> tuple[int, int, int]: | ||
| """Linearly interpolate between two RGB colors in HSV color space.""" | ||
| t = abs(t) | ||
| assert 0 <= t <= 1 | ||
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| # Convert RGB to HSV | ||
| hsv1 = colorsys.rgb_to_hsv(*[x / 255.0 for x in rgb1]) | ||
| hsv2 = colorsys.rgb_to_hsv(*[x / 255.0 for x in rgb2]) | ||
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| # Linear interpolation in HSV space | ||
| hsv = ( | ||
| hsv1[0] + t * (hsv2[0] - hsv1[0]), | ||
| hsv1[1] + t * (hsv2[1] - hsv1[1]), | ||
| hsv1[2] + t * (hsv2[2] - hsv1[2]), | ||
| ) | ||
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| # Convert back to RGB | ||
| rgb = tuple(int(round(x * 255)) for x in colorsys.hsv_to_rgb(*hsv)) | ||
| assert all(0 <= x <= 255 for x in rgb), f"Invalid RGB color: {rgb}" | ||
| return cast(tuple[int, int, int], rgb) | ||
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| def lerp(x, x1, x2, y1, y2): | ||
| """Linearly interpolate between two values.""" | ||
| return y1 + (x - x1) * (y2 - y1) / (x2 - x1) | ||
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| def int_to_base36(num: int) -> str: | ||
| """Convert an integer to its base-36 representation using numbers and uppercase letters. | ||
| Base-36 encoding uses digits 0-9 and uppercase letters A-Z, providing a case-insensitive | ||
| alphanumeric representation. The function takes an integer `num` as input and returns | ||
| its base-36 representation as a string. | ||
| Parameters | ||
| ---------- | ||
| num | ||
| The integer to convert to base-36. | ||
| Returns | ||
| ------- | ||
| str | ||
| The base-36 representation of the input integer. | ||
| Examples | ||
| -------- | ||
| >>> num = 123456 | ||
| >>> base36_num = int_to_base36(num) | ||
| >>> print(base36_num) | ||
| '2N9' | ||
| """ | ||
| alphanumeric_chars = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ" | ||
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| if num == 0: | ||
| return alphanumeric_chars[0] | ||
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| base36_str = "" | ||
| base = len(alphanumeric_chars) | ||
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| while num: | ||
| num, remainder = divmod(num, base) | ||
| base36_str = alphanumeric_chars[remainder] + base36_str | ||
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| return base36_str | ||
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| def short_hash(string: str, length: int = 4) -> str: | ||
| """Create a hash of 'string' with length 'length'.""" | ||
| return base64.b32encode(string.encode()).decode("utf-8").zfill(length)[:length] | ||
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| def remove_vowels(input_str: str, length: int = 4) -> str: | ||
| """Remove vowels from a string and return a string of length 'length'.""" | ||
| vowels = "aeiouAEIOU" | ||
| output_str = "".join([char for char in input_str if char not in vowels]) | ||
| return output_str.zfill(length)[:length] | ||
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| def color_difference_redmean( | ||
| rgb1: tuple[float, float, float], | ||
| rgb2: tuple[float, float, float], | ||
| ) -> float: | ||
| """Distance between colors in RGB space (redmean metric). | ||
| The maximal distance between (255, 255, 255) and (0, 0, 0) ≈ 765. | ||
| Sources: | ||
| - https://en.wikipedia.org/wiki/Color_difference#Euclidean | ||
| - https://www.compuphase.com/cmetric.htm | ||
| """ | ||
| r_hat = (rgb1[0] + rgb2[0]) / 2 | ||
| delta_r, delta_g, delta_b = ( | ||
| (col1 - col2) for col1, col2 in zip(rgb1, rgb2, strict=True) | ||
| ) | ||
| red_term = (2 + r_hat / 256) * delta_r**2 | ||
| green_term = 4 * delta_g**2 | ||
| blue_term = (2 + (255 - r_hat) / 256) * delta_b**2 | ||
| return math.sqrt(red_term + green_term + blue_term) |
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