diff --git a/chla-model.py b/chla-model.py
new file mode 100644
index 0000000..0e1a914
--- /dev/null
+++ b/chla-model.py
@@ -0,0 +1,239 @@
+import argparse
+import pandas as pd
+import numpy as np
+
+
+def find_nearest_bandnumber(wavelength, wavelengths):
+    differences = np.abs(wavelengths - wavelength)
+    min_position = np.argmin(differences)
+    return int(min_position)
+
+
+def deglint(wavelengths, reflectance, start_wave=730, end_wave=750):
+    """去除水表耀光"""
+    s = find_nearest_bandnumber(start_wave, wavelengths)
+    e = find_nearest_bandnumber(end_wave, wavelengths)
+
+    glint = np.mean(reflectance[s:e + 1])
+    deglinted_ref = reflectance - glint
+    deglinted_ref[deglinted_ref < 0] = 0
+
+    return deglinted_ref
+
+
+def replace_non_valid_number(x):
+    """检查并替换无效数字"""
+    if np.isnan(x) or np.isinf(x) or x < 0 or x > 65535:
+        return 0.0
+    return x
+
+
+def safe_divide(numerator, denominator, default_value=0.0):
+    """安全除法，避免除零错误"""
+    if denominator == 0 or np.isnan(denominator) or np.isinf(denominator):
+        return default_value
+    return numerator / denominator
+
+
+def chl_a(wavelengths, reflectance):
+    """计算叶绿素a"""
+    r651 = reflectance[find_nearest_bandnumber(651, wavelengths)]
+    r707 = reflectance[find_nearest_bandnumber(707, wavelengths)]
+    r670 = reflectance[find_nearest_bandnumber(670, wavelengths)]
+
+    denominator = safe_divide(r707 - r670, 1, default_value=1)
+    content = 5.534 + 9.809 * (r651 - r707) / denominator
+    return replace_non_valid_number(content)
+
+
+def pc(wavelengths, reflectance):
+    """计算藻蓝素"""
+    r620 = reflectance[find_nearest_bandnumber(620, wavelengths)]
+    r665 = reflectance[find_nearest_bandnumber(665, wavelengths)]
+    r709 = reflectance[find_nearest_bandnumber(709, wavelengths)]
+    r778 = reflectance[find_nearest_bandnumber(778, wavelengths)]  # 修正了波段索引
+
+    # 计算背景值bb
+    bb_denom = safe_divide(0.082 - 0.6 * r778, 1, default_value=1)
+    bb = 2.71 * 0.6 * r778 / bb_denom
+
+    # 计算叶绿素chl
+    chl_denom = safe_divide(r665, 1, default_value=1)
+    chl = (r709 / chl_denom * (0.727 + bb) - bb - 0.401) * (1 / 0.68)
+
+    # 计算藻蓝素
+    pc_denom = safe_divide(r620, 1, default_value=1)
+    content = (r709 / pc_denom * (0.727 + bb) - bb - 0.281) * (1 / 0.84) - 0.24 * chl
+    return replace_non_valid_number(content)
+
+
+def nh3(wavelengths, reflectance):
+    """计算氨氮"""
+    band_500 = reflectance[find_nearest_bandnumber(500, wavelengths)]
+    band_600 = reflectance[find_nearest_bandnumber(600, wavelengths)]
+    band_850 = reflectance[find_nearest_bandnumber(850, wavelengths)]
+
+    ratio1 = safe_divide(band_500, band_850, default_value=1)
+    ratio2 = safe_divide(band_600, band_500, default_value=1)
+
+    x13 = np.log(ratio1) if ratio1 > 0 else 0
+    x23 = np.exp(ratio2)
+
+    content = 0.139 * x23 - 0.508 * x13 - 0.672
+    return replace_non_valid_number(content)
+
+
+def tn(wavelengths, reflectance):
+    """计算总氮"""
+    band_500 = reflectance[find_nearest_bandnumber(500, wavelengths)]
+    band_600 = reflectance[find_nearest_bandnumber(600, wavelengths)]
+    band_850 = reflectance[find_nearest_bandnumber(850, wavelengths)]
+
+    ratio1 = safe_divide(band_500, band_850, default_value=1)
+    ratio2 = safe_divide(band_600, band_500, default_value=1)
+
+    x13 = np.log(ratio1) if ratio1 > 0 else 0
+    x23 = np.exp(ratio2)
+
+    content = 0.059 * x23 - 0.089 * x13 - 0.012
+    return replace_non_valid_number(content)
+
+
+def tp(wavelengths, reflectance):
+    """计算总磷"""
+    band_440 = reflectance[find_nearest_bandnumber(440, wavelengths)]
+    band_500 = reflectance[find_nearest_bandnumber(500, wavelengths)]
+    band_800 = reflectance[find_nearest_bandnumber(800, wavelengths)]
+
+    ratio1 = safe_divide(band_500, band_440, default_value=1)
+    ratio2 = safe_divide(band_500, band_800, default_value=1)
+
+    x12 = np.log(ratio1) if ratio1 > 0 else 0
+    x17 = np.exp(ratio2)
+
+    content = 0.066 * x12 - 0.159 * x17 - 0.012
+    return replace_non_valid_number(content)
+
+
+def mno4(wavelengths, reflectance):
+    """计算高锰酸盐"""
+    band_440 = reflectance[find_nearest_bandnumber(440, wavelengths)]
+    band_500 = reflectance[find_nearest_bandnumber(500, wavelengths)]
+    band_610 = reflectance[find_nearest_bandnumber(610, wavelengths)]
+    band_800 = reflectance[find_nearest_bandnumber(800, wavelengths)]
+
+    x3 = safe_divide(band_500, band_440, default_value=1)
+    x6 = safe_divide(band_610, band_800, default_value=1)
+
+    content = 1.13 * x3 - 1.29 * x6 - 5.95
+    return replace_non_valid_number(content)
+
+
+def tss(wavelengths, reflectance):
+    """计算总悬浮物"""
+    band_490 = reflectance[find_nearest_bandnumber(490, wavelengths)]
+    band_555 = reflectance[find_nearest_bandnumber(555, wavelengths)]
+    band_670 = reflectance[find_nearest_bandnumber(670, wavelengths)]
+
+    x1 = band_555 + band_670
+    x2 = safe_divide(band_490, band_555, default_value=1)
+
+    content_tmp = 0.58213 + 23.84071 * x1 - 0.48532 * x2
+    content = np.exp(content_tmp)
+
+    return replace_non_valid_number(content)
+
+
+def CDOM(wavelengths, reflectance):
+    """计算有色可溶性有机物"""
+    band_560 = reflectance[find_nearest_bandnumber(560, wavelengths)]
+    band_660 = reflectance[find_nearest_bandnumber(660, wavelengths)]
+
+    x1 = band_560 + band_660
+    content = 40.75 * np.exp(-2.463 * x1)
+
+    return replace_non_valid_number(content)
+
+
+def SD(wavelengths, reflectance):
+    """计算透明度"""
+    band_440 = reflectance[find_nearest_bandnumber(440, wavelengths)]
+    band_700 = reflectance[find_nearest_bandnumber(700, wavelengths)]
+
+    x1 = safe_divide(band_700, band_440, default_value=1)
+    content = 1.17 * x1 - 27.43
+
+    return replace_non_valid_number(content)
+
+
+def process_spectral_file(input_csv_path, output_csv_path):
+    # 读取CSV文件，第一行为列名
+    df = pd.read_csv(input_csv_path)
+
+    # 提取波长数据（假设波长在列名中）
+    # 跳过前18列非光谱数据，从第19列开始是光谱数据
+    wavelength_columns = df.columns[1:]
+
+    # 将列名转换为浮点数（波长值）
+    try:
+        wavelengths = np.array([float(col) for col in wavelength_columns])
+    except ValueError:
+        # 如果列名不是数值，尝试从第一行获取波长值
+        wavelengths = df.iloc[0, 1:].astype(float).values
+        # 删除第一行（波长行）
+        df = df.iloc[1:]
+
+    # 创建结果DataFrame
+    results = {
+        'timestamp': df.iloc[:, 0],  # 假设时间戳在第一列
+        'chl-a': [],
+        'pc': [],
+        'nh3': [],
+        'tn': [],
+        'tp': [],
+        'mno4': [],
+        'tss': [],
+        'CDOM': [],
+        'SD': []
+    }
+
+    # 逐行处理数据
+    for i, row in df.iterrows():
+        # 提取反射率数据（第19列到最后一列）
+        reflectance = row.iloc[1:].astype(float).values
+
+        # 去除水表耀光
+
+        deglinted_ref = reflectance
+        # deglinted_ref = deglint(wavelengths, reflectance)
+
+        # 计算各项水质参数
+        results['chl-a'].append(chl_a(wavelengths, deglinted_ref))
+        results['pc'].append(pc(wavelengths, deglinted_ref))
+        results['nh3'].append(nh3(wavelengths, deglinted_ref))
+        results['tn'].append(tn(wavelengths, deglinted_ref))
+        results['tp'].append(tp(wavelengths, deglinted_ref))
+        results['mno4'].append(mno4(wavelengths, deglinted_ref))
+        results['tss'].append(tss(wavelengths, deglinted_ref))
+        results['CDOM'].append(CDOM(wavelengths, deglinted_ref))
+        results['SD'].append(SD(wavelengths, deglinted_ref))
+
+    # 创建结果DataFrame并保存
+    result_df = pd.DataFrame(results)
+    result_df.to_csv(output_csv_path, index=False)
+    print(f"结果已保存到 {output_csv_path}")
+#
+
+input_csv_path = r"D:\WQ\zhanghuilai\hyperspectral-inversion\data\input\一代高光谱\2025-07-11_2025-07-21\筛选.csv"
+output_csv_path = r"D:\WQ\zhanghuilai\hyperspectral-inversion\data\input\一代高光谱\2025-07-11_2025-07-21/不去耀斑index.csv"
+process_spectral_file(input_csv_path, output_csv_path)
+
+
+#
+# if __name__ == "__main__":
+#     parser = argparse.ArgumentParser(description='高光谱水质参数反演')
+#     parser.add_argument('--input', type=str, required=True, help='输入CSV文件路径')
+#     parser.add_argument('--output', type=str, required=True, help='输出CSV文件路径')
+#     args = parser.parse_args()
+#
+#     process_spectral_file(args.input, args.output)
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