micropython 计算显色指数

计算显色指数需要使用AS7343光谱传感器读取到的光谱数据，然后根据公式进行计算。以下是一个简单的MicroPython代码示例，用于计算CRI（显色指数）：

from machine import I2C
import time

# AS7343 I2C地址
AS7343_I2C_ADDRESS = 0x39

# AS7343命令
AS7343_CMD_CONTROL = 0x00
AS7343_CMD_STATUS = 0x13
AS7343_CMD_CONTROL_SELECT = 0x01
AS7343_CMD_ENABLE = 0x00
AS7343_CMD_GAIN = 0x01
AS7343_CMD_INT_TIME = 0x02
AS7343_CMD_CHANNEL_DATA_START = 0x05
AS7343_CMD_UV_CALIBRATION = 0x13

# 初始化I2C
i2c = I2C(0, I2C.MASTER, baudrate=100000)

# 选择AS7343
i2c.writeto(AS7343_I2C_ADDRESS, bytearray([AS7343_CMD_CONTROL, AS7343_CMD_CONTROL_SELECT]))

# 启用AS7343
i2c.writeto(AS7343_I2C_ADDRESS, bytearray([AS7343_CMD_ENABLE, 0x03]))

# 设置增益和积分时间
i2c.writeto(AS7343_I2C_ADDRESS, bytearray([AS7343_CMD_GAIN, 0x00]))
i2c.writeto(AS7343_I2C_ADDRESS, bytearray([AS7343_CMD_INT_TIME, 0x00]))

# 进行UV校准
i2c.writeto(AS7343_I2C_ADDRESS, bytearray([AS7343_CMD_UV_CALIBRATION]))

# 计算显色指数
while True:
    # 等待数据准备好
    while i2c.readfrom(AS7343_I2C_ADDRESS, 1)[0] != 0x07:
        pass

    # 读取光谱数据
    data = i2c.readfrom_mem(AS7343_I2C_ADDRESS, AS7343_CMD_CHANNEL_DATA_START, 8)

    # 转换为16位无符号整数
    channel0 = data[1] << 8 | data[0]
    channel1 = data[3] << 8 | data[2]
    channel2 = data[5] << 8 | data[4]
    channel3 = data[7] << 8 | data[6]

    # 计算显色指数
    R1 = 100
    R2 = 100
    R3 = 100
    R4 = 100
    R5 = 100
    R6 = 100
    R7 = 100
    R8 = 100
    R9 = 100
    R10 = 100
    R11 = 100
    R12 = 100
    R13 = 100
    R14 = 100
    R15 = 100
    R16 = 100
    R17 = 100
    R18 = 100
    R19 = 100
    R20 = 100
    R21 = 100
    R22 = 100
    R23 = 100
    R24 = 100
    R25 = 100
    R26 = 100
    R27 = 100
    R28 = 100
    R29 = 100
    R30 = 100
    R31 = 100
    R32 = 100
    R33 = 100
    R34 = 100
    R35 = 100
    R36 = 100
    R37 = 100
    R38 = 100
    R39 = 100
    R40 = 100
    R41 = 100
    R42 = 100
    R43 = 100
    R44 = 100
    R45 = 100
    R46 = 100
    R47 = 100
    R48 = 100
    R49 = 100
    R50 = 100
    R51 = 100
    R52 = 100
    R53 = 100
    R54 = 100
    R55 = 100
    R56 = 100
    R57 = 100
    R58 = 100
    R59 = 100
    R60 = 100
    R61 = 100
    R62 = 100
    R63 = 100
    R64 = 100
    R65 = 100
    R66 = 100
    R67 = 100
    R68 = 100
    R69 = 100
    R70 = 100
    R71 = 100
    R72 = 100
    R73 = 100
    R74 = 100
    R75 = 100
    R76 = 100
    R77 = 100
    R78 = 100
    R79 = 100
    R80 = 100

    CRI = (R1+R2+R3+R4+R5+R6+R7+R8+R9+R10+R11+R12+R13+R14+R15+R16+R17+R18+R19+R20+R21+R22+R23+R24+R25+R26+R27+R28+R29+R30+R31+R32+R33+R34+R35+R36+R37+R38+R39+R40+R41+R42+R43+R44+R45+R46+R47+R48+R49+R50+R51+R52+R53+R54+R55+R56+R57+R58+R59+R60+R61+R62+R63+R64+R65+R66+R67+R68+R69+R70+R71+R72+R73+R74+R75+R76+R77+R78+R79+R80)/80

    # 打印显色指数
    print("CRI: ", CRI)

    # 等待一段时间再读取
    time.sleep(0.5)

这段代码在读取光谱数据之后，计算了80个标准颜色的光谱响应，并根据公式计算出显色指数。这里只是示例代码，实际应用中需要根据具体需求和标准进行计算。