1. 融合300tc和hpi定标程序；

2. add：300tc中，从spatial bin1和spectral bin1的定标文件生成其他bin2的定标文件；

1.1radiance_calibration_300tc.py

@@ -8,6 +8,7 @@ import sys, os, traceback, re
 import shutil
 from radiance_calibration_ui import Ui_MainWindow
 from library.multithread import Worker
+from library.image_reader_writer import ImageReaderWriter
 import sys, traceback
 from osgeo import gdal
 from scipy.interpolate import interp1d
@@ -32,6 +33,7 @@ class EnterWindow(QMainWindow, Ui_MainWindow):
         self.out_file_bt.clicked.connect(self.select_out_file)
 
         self.operate_bt.clicked.connect(self.operate)
+        self.dark_checkBox.stateChanged.connect(self.disabledDark)
 
         self.tmp_rad_file_path = None  # 用于保存当前路径，下次打开就默认在此路径下
         self.tmp_dn_file_path = None  # 用于保存当前路径，下次打开就默认在此路径下
@@ -91,7 +93,14 @@ class EnterWindow(QMainWindow, Ui_MainWindow):
         self.out_file_le.setText(out_file_path)
 
     def operate(self):
-        self.radiance_calibration_object.operate()
+        if(self.dark_checkBox.isChecked()):
+            self.radiance_calibration_object.operate()
+        else:
+            self.radiance_calibration_object.operate_without_dark()
+
+    def disabledDark(self, isEnable):
+        self.dark_le.setEnabled(isEnable)
+        self.dark_bt.setEnabled(isEnable)
 
 
 class RadianceCalibration():
@@ -251,15 +260,24 @@ class RadianceCalibration():
 
             # 读取影像
             img_proj, img_geotrans, self.img_data = self.read_img(self.dn_file_path)
+            dn_hdr = spectral.envi.read_envi_header(self.get_hdr_filename(self.dn_file_path))
+
+            # 重采样
+            f = interp1d(self.asd_radiance[:, 0], self.asd_radiance[:, 1])
+            # wave_destination = dn_hdr["wavelength"].removeprefix("{").removesuffix("}").split(",")
+            asd_radiance_interpolated = [f(float(i)) for i in dn_hdr["wavelength"]]
+            asd_radiance_interpolated2 = np.array(asd_radiance_interpolated)
 
             # 将影像所有行平均，得到一行（帧）影像
             img_data_ave = np.mean(self.img_data, axis=1)
 
             gain = np.empty((img_data_ave.shape[0], 1, img_data_ave.shape[1]))
             for i in range(gain.shape[2]):
-                gain[:, 0, i] = self.asd_radiance[:, 1] / img_data_ave[:, i]
+                gain[:, 0, i] = asd_radiance_interpolated2 / img_data_ave[:, i]
 
-            self.write_img(self.out_file_path, gain)
+            gain_name = os.path.join(self.out_file_path, "gain.bip")
+            ImageReaderWriter.write_img(gain_name, gain)
+            # self.write_img(gain_name, gain)
         except:
             traceback.print_exc()