calfile/profile/Back_SAM_85B5.dat

@@ -11,7 +11,7 @@ PositionLatitude   = 0
 PositionLongitude  = 0
 Comment            = 
 CommentSub1        = 
-CommentSub2        = immersion_factors_Lu.dat
+CommentSub2        = 
 CommentSub3        = 
 IDMethodType       = SAM Calibration Station
 MethodName         = SAM_Calibration_Station

calfile/profile/immersion_factors_Lu.dat

@@ -1,63 +0,0 @@
-;immersion factors for TriOS radiance
-;wavelength(nm) factors
-350 1.7743
-360 1.7710
-370 1.7681
-380 1.7653
-390 1.7628
-400 1.7604
-410 1.7583
-420 1.7563
-430 1.7544
-440 1.7526
-450 1.7510
-460 1.7494
-470 1.7480
-480 1.7466
-490 1.7454
-500 1.7441
-510 1.7430
-520 1.7419
-530 1.7409
-540 1.7399
-550 1.7390
-560 1.7381
-570 1.7372
-580 1.7364
-590 1.7356
-600 1.7349
-610 1.7342
-620 1.7335
-630 1.7328
-640 1.7322
-650 1.7316
-660 1.7310
-670 1.7305
-680 1.7299
-690 1.7294
-700 1.7289
-710 1.7284
-720 1.7280
-730 1.7275
-740 1.7271
-750 1.7267
-760 1.7263
-770 1.7259
-780 1.7255
-790 1.7251
-800 1.7248
-810 1.7244
-820 1.7241
-830 1.7238
-840 1.7235
-850 1.7232
-860 1.7229
-870 1.7226
-880 1.7223
-890 1.7220
-900 1.7217
-910 1.7215
-920 1.7212
-930 1.7210
-940 1.7207
-950 1.7205

profiler.py

@@ -9,7 +9,7 @@ from scipy.optimize import leastsq
 from datetime import datetime, timedelta
 from myRamses import RamsesFactoryHandle,AirWater
 from tools.mylogger import log
-from myconfig import TOKEN,NEWLINE,DATA_DIR,SAVE_EXT_NAME,CAL_DIR
+from myconfig import TOKEN,NEWLINE,DATA_DIR,SAVE_EXT_NAME 
 from myconfig import  RamsesPROFILE
 
 TIME_STR = "2022-06-10 16:16:16"
@@ -288,7 +288,6 @@ class Profiler(object):
     depth : List[float]     =None
     wavelength:List[np.ndarray]         =None
     spectrum:List[np.ndarray]           =None
-    immersion_factors:np.ndarray = None
     beginWavelength: float  = None
     endWavelength: float    = None
     rowFactor:float         = None
@@ -330,12 +329,6 @@ class Profiler(object):
         self.newWavelength      = np.arange(self.beginWavelength,self.endWavelength,self.wvInterval)
         pass
 
-    def set_immersion_factors(self, ifs:np.ndarray):
-        wv = ifs[:, 0]
-        val = ifs[:, 1]
-        self.immersion_factors = np.interp(self.newWavelength,wv,val)
-        pass
-
     def set_ramses_sensor_numbers(self, num:int = 3):
         self.data.data_frame = DataFrame()
         self.data.data_frame.set_ramses_num( num )
@@ -494,11 +487,7 @@ class Profiler(object):
         '''' Get  Lu0    Ku   '''
         log.info( " get_lu0_Ku.........  ", __class__, "get_Lu0_Ku" )
         x = np.array(self.depth)
-        
-        ## 浸没因子处理 ##
-        tmp  = self.deal_Lu_by_immersion_factors()
-        y = np.log(tmp)   # ln_Lu
-        
+        y = np.log(self.Lu)   # ln_Lu
         self.Ku,ln_Lu0 = self.leastsq_linear_fitting( x, y)
         self.Lu0 = np.exp(ln_Lu0)
 
@@ -517,12 +506,6 @@ class Profiler(object):
         # log.warning(t)
         # log.warning(self.Ed0)
 
-    def deal_Lu_by_immersion_factors ( self, ):
-        '''' ?????? 浸没因子处理 Lu  ??? '''
-        ifs = self.immersion_factors
-        lu  = self.Lu
-        return lu
-    
     def leastsq_linear_fitting( self, arr_depth:np.ndarray, arr_data:np.ndarray ):
         '''最小二乘拟合
         # arr_depth np一维数组
@@ -650,15 +633,7 @@ class ProfilerHandle(object):
 
         self.profiler.data.set_data_frame( bytes_list, pth, self.aw.callback )   # 目录也要传过去
         pass
- 
-    def read_immersion_factors(self,)->np.ndarray: 
-        assert fpath.exists(), f">>>> not find {fpath} "
-        fname   = "immersion_factors_Lu.dat"
-        fpath   = CAL_DIR.joinpath( "profiler" ,fname)
-        ret = np.loadtxt(fpath,skiprows=2)
-        return ret
-        pass
-        
+    
     def read_bin(self,fpath: Path): 
         assert fpath.exists(), f">>>> not find {fpath} "
         ret = b''

receive.py

@@ -219,8 +219,6 @@ class DealData:
         self.profiler_hdl.read_info_path(infopath)
         self.profiler_hdl.profiler.reset_profiler()
         self.profiler_hdl.profiler.data.set_wavelength(  )   # 设置波长
-        # self.profiler_hdl.read_immersion_factors( )  # 读取浸没因子
-        self.profiler_hdl.profiler.set_immersion_factors( self.profiler_hdl.read_immersion_factors( ) ) #设置浸没因子
         self.profiler_hdl.profiler.get_depth_offset()
         self.profiler_hdl.read_sensor_path(sensorpath)