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mynumpy.py Ramses.py

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esea_info 3 years ago
parent b3307e8c22
commit 1a036210ac
19 changed files with 3270 additions and 72 deletions
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  1. 150
      Ramses.py
  2. 13
      app.py
  3. 297
      calfile/profile/Back_SAM_852F.dat
  4. 297
      calfile/profile/Back_SAM_859F.dat
  5. 297
      calfile/profile/Back_SAM_85B5.dat
  6. 297
      calfile/profile/CalAQ_SAM_852F.dat
  7. 297
      calfile/profile/CalAQ_SAM_859F.dat
  8. 297
      calfile/profile/CalAQ_SAM_85B5.dat
  9. 297
      calfile/profile/Cal_SAM_852F.dat
  10. 297
      calfile/profile/Cal_SAM_859F.dat
  11. 297
      calfile/profile/Cal_SAM_85B5.dat
  12. 81
      calfile/profile/SAMIP_50ED_ALL.ini
  13. 32
      calfile/profile/SAM_852F.ini
  14. 30
      calfile/profile/SAM_859F.ini
  15. 30
      calfile/profile/SAM_85B5.ini
  16. 17
      config.yml
  17. 11
      myconfig.py
  18. 199
      mynumpy.py
  19. 102
      profiler.py

150
Ramses.py
Unescape View File

@ -26,26 +26,25 @@ class Ramses(object):
@param : 23 ..07 .... 06 05 04 03 02 01 00
ip信息不包含
@Returns : realWavelength Intensity
@ 积分时间 04 07 , 选 07
"""
self.buf = b''
self.mode = 0 # 默认0 空气中，1：水中
self.buf_ip = b''
self.it = None
self.light_int = None # 未标定的整数值
self.spectrum = None # 光谱强度
# self.current_buf = ""
# self.current_buf_seq = 0
# self.current_it_int = {"it": 0, "light_int": []} # 积分时间及换算的整数值
# self.res = {"wavelength": [], "light": []}
self.cal_cfg = {}
self.ip = []
self.cal_cfg = {} # 单个传感器标定文件还是多个传感器的？
# self.current_cal = {} # 当前传感器的序列号
pass
def setBuf(self, buf: bytes):
def setBuf( self, buf: bytes ):
self.buf = buf
pass
def setMode(self, mode=1):
self.mode = 1
def setMode( self, mode = 1 ):
self.mode = mode
pass
def setCalCfg(self, d: dict):
@ -56,6 +55,9 @@ class Ramses(object):
self.cal_cfg = d
pass
def get_ip(self):
return self.ip
def getSpectrum(self):
return self.spectrum
@ -83,7 +85,10 @@ class Ramses(object):
pass
def dealBuf(self, ip_included:bool=False):
"""多个传感器的数据处理， 头部是否包含Ip帧的信息"""
"""
头部是否包含Ip帧的信息
?? 不支持多个传感器的标定文件
"""
log.info(f" dealBuf ", __name__)
res = {}
@ -91,27 +96,31 @@ class Ramses(object):
if len_ < 576:
return
if ip_included:
self.buf_ip = self.buf[:26]
self.ip = self.decode_ip_buf(self.buf_ip, self.cal_cfg)
self.buf = self.buf[26:]
len_ = len_ - 26
if len_ % 576 != 0:
return
for i in range(int(len_/576)):
res.update({i+1: {}})
for i in range( int(len_/576) ):
res.update( {i+1: {}} )
temp_buf = self.buf[7:71] + self.buf[79:143] + \
self.buf[151:215] + self.buf[223:287] + \
self.buf[295:359] + self.buf[367:431] + \
self.buf[439:503] + self.buf[511:575]
self.ConvertAndCalibrate( temp_buf )
# print(len(temp_buf))
temp = self.__ConvertBytesToInt(temp_buf)
res.update( { i+1: temp } )
# temp = self.__ConvertBytesToInt(temp_buf)
# res.update( { i+1: temp } )
# print(res)
pass
def ConvertAndCalibrate(self,) -> None:
'''单个成功数据转化 标定'''
log.debug(f" ConvertAndCalibrate ", __name__)
temp = self.__ConvertBytesToInt( )
# print( f"int : {self.it} {temp}" )
self.__CalibrateSpectrumData( )
pass
@ -119,34 +128,40 @@ class Ramses(object):
def __ConvertBytesToInt(self ) -> None:
res = {}
d = [] # List [ Tuple[ it:int, sing_set:tuple[int] ] ]
self.it = 2 << int(self.buf[1]) # integrated time
# self.it = 2 << int(self.buf[0]) # integrated time
self.light_int = struct.unpack(
"<HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH \
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH \
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH \
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH", self.buf[2:])
# print( self.light_int )
def __CalibrateSpectrumData(self ,) :
t0 = 8092
log.debug(f" __CalibrateSpectrumData ..... ", __name__)
raw = np.asarray(self.light_int, dtype=float)
B0 = np.asarray(self.cal_cfg["b0"], dtype=float)
B1 = np.asarray(self.cal_cfg["b1"], dtype=float)
Mn = raw/65535
Bn = B0 + B1 * (self.it/t0)
Bn = B0 + B1 * ( self.it/t0 )
Cn = Mn-Bn
Offset = self.getOffset(
Cn, int(self.cal_cfg['DarkPixelStart']), int(self.cal_cfg['DarkPixelStop']))
Dn = Cn-Offset
En = Dn * (t0/self.it)
Dn = Cn - Offset
En = Dn * ( t0/self.it )
if self.mode == 0:
Fn = En/np.asarray(self.cal_cfg["cal"], dtype=float) # 空气的标定文件
else:
Fn = En/np.asarray(self.cal_cfg["calaq"], dtype=float) # 水中的标定文件
# Fn = En/np.asarray(self.cal_cfg["cal"], dtype=float) # 空气或水中的标定文件
self.spectrum = Fn
# print(self.spectrum)
def getOffset(self, data: np.ndarray, start: int, stop: int):
@ -154,20 +169,95 @@ class Ramses(object):
for i in range(start-1, stop, 1):
ret = ret + data[i]
return ret / (stop - start + 1)
pass
# def read_bin(self,fpath: Path):
# log.debug(f" readbin: ", __name__, "", "" )
# ret = None
# if not fpath.exists() :
# log.info(f"not find file: {fpath} ")
# return ret
# with open(fpath, 'rb') as file:
# ret = file.read()
# return ret
# log.debug(f" readbin: {ret} ", __name__, "", "" )
# return ret
# pass
def removeMask(self, buf:bytes ) -> bytes:
'''去除遮罩 0x64 0x65 0x66 0x67'''
ret = b''
flag = False
blen = len(buf)
for i in range(blen):
if flag == False and buf[i] == 64 :
flag = True
continue
if flag == False and buf[i] != 64 :
ret = ret + buf[i].to_bytes( 1, byteorder = 'big' )
continue
if flag == True and buf[i] == 100:
ret = ret + b'\x40'
flag = False
continue
if flag == True and buf[i] == 101:
ret = ret + b'\x23'
flag = False
continue
if flag == True and buf[i] == 102:
ret = ret + b'\x11'
flag = False
continue
if flag == True and buf[i] == 103:
ret = ret + b'\x13'
flag = False
continue
return ret
pass
def decode_ip_buf(self, buf, ip_cal:dict):
tmpbuf = buf
if len(tmpbuf) ==26 and tmpbuf[0] == 0x13:
tmpbuf = tmpbuf[2:]
Incl_XGain = float(ip_cal['Incl_XOffset'] )
Incl_XOffset = float(ip_cal['Incl_XOffset'] )
Incl_YGain = float(ip_cal['Incl_YGain'] )
Incl_YOffset = float(ip_cal['Incl_YOffset'] )
Incl_KRef = float(ip_cal['Incl_KRef'] )
Press_Sens_mV_bar_1mA = float(ip_cal['Press_Sens_mV_bar_1mA'] )
Incl_KBG = float(ip_cal['Incl_KBG'] )
Press_Sens_mV_bar_4mA = float(ip_cal['Press_Sens_mV_bar_4mA'] )
Press_Gain = float(ip_cal['Press_Gain'] )
Press_Surface_bar = float(ip_cal['Press_Surface_bar'] )
ip_info = struct.unpack("<BBBBBBBBBBBBBBBBBBBBBBBB", buf)
byte11 = ip_info[11]
byte12 = ip_info[12]
byte13 = ip_info[13]
byte14 = ip_info[14]
byte15 = ip_info[15]
byte16 = ip_info[16]
byte17 = ip_info[17]
byte18 = ip_info[18]
byte19 = ip_info[19]
byte20 = ip_info[20]
byte21 = ip_info[21]
byte22 = ip_info[22]
X = (byte11 -Incl_XOffset) / Incl_XGain # 单位 度
Y = (byte12 - Incl_YOffset ) / Incl_YGain # 单位 度
npress = byte14 *256 + byte13
nbg = byte18 * 256 + byte17
nrefh = byte20 * 256 + byte19
nrefl = byte22 * 256 + byte21
noffset = nrefl - ( Incl_KRef * (nrefh-nrefl))
VPress = Incl_KBG * (npress-noffset) / (nbg- noffset) #电压值
press_sens = Press_Sens_mV_bar_4mA
if press_sens <= 0:
press_sens = 4* Press_Sens_mV_bar_1mA
p_bar = 1000 * VPress / (press_sens * Press_Gain )
press_delta = p_bar - 1.021
depth_m = press_delta * 10
return [depth_m,X,Y]
def getWavelength(self,) -> list:
ret = []
for i in range(1,256):
tmp = float(self.cal_cfg['c0s']) + float(self.cal_cfg['c1s'])*i \
+ float(self.cal_cfg['c2s'])*i*i + float(self.cal_cfg['c3s'])*i*i*i
ret.append(tmp)
pass
return ret
pass
if __name__ == "__main__":

13
app.py
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@ -18,7 +18,7 @@ if __name__ == "__main__":
#######################################
device_id = DEVICE_ID # 多个设备
device_type = DeviceType.AWRAMS.name
device_type = DeviceType.PROFILE.name
mycfg = MyConfig()
# 配置反演需要的参数 波长 间隔
@ -26,7 +26,7 @@ if __name__ == "__main__":
log.info(f"Retrieve: {retrieve}", __name__, "", "")
# log.info(f"syscfg: {device}", __name__, "", "")
mycfg.setDeviceType(DeviceType.AWRAMS)
mycfg.setDeviceType(device_type)
init_para = mycfg.read_yaml()
log.info(f"Current Device: {device_type} ", __name__, "", "")
log.info(f"Sensor: {init_para}", __name__, "", "")
@ -47,10 +47,11 @@ if __name__ == "__main__":
log.info(f"v: {cfgr.configuration}", __name__, "", "")
cal_cfg.update({k:cfgr.cal_configuration})
# log.warning(f"cal_cfg: {cal_cfg}", __name__, "", "")
log.warning(f"cal_cfg 2: {cal_cfg[2].keys()}", __name__, "", "")
log.warning(f"cal_cfg 3: {cal_cfg[3].keys()}", __name__, "", "")
log.info(f"传感器配置文件读取成功", __name__, "", "")
# log.warning(f"cal_cfg: {cal_cfg[2]}", __name__, "", "")
log.warning( f"cal_cfg 2: {cal_cfg[2].keys()}", __name__, "", "")
# log.warning( f"cal_cfg 2: {cal_cfg[2]}", __name__, "", "")
# log.warning( f"cal_cfg 3: {cal_cfg[3].keys()}", __name__, "", "")
log.info( f"传感器配置文件读取成功", __name__, "", "" )
# ????????????
# 不同设备类型接收不同，修改receive.py

297
calfile/profile/Back_SAM_852F.dat
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@ -0,0 +1,297 @@
[Spectrum]
Version = 1
IDData = DLAB_2016-11-29_14-47-59_729_812
IDDevice = SAM_852F
IDDataType = SPECTRUM
IDDataTypeSub1 = BACK
IDDataTypeSub2 =
IDDataTypeSub3 =
DateTime = 2016-11-29 14:41:43
PositionLatitude = 0
PositionLongitude = 0
Comment =
CommentSub1 =
CommentSub2 =
CommentSub3 =
IDMethodType = SAM Calibration Station
MethodName = SAM_Calibration_Station
Mission =
MissionSub = 0
RecordType = 0
[Attributes]
CalFactor = 1
IDBasisSpec =
IDDataBack =
IDDataCal =
IntegrationTime = 8192
P31 = -1
P31e = 0
PathLength = +INF
RAWDynamic = 65535
Temperature = +NAN
Unit1 = $05 $00 Pixel
Unit2 = $03 $05 Intensity counts
Unit3 = $03 $05 Intensity counts
Unit4 = $f1 $00 Status
[END] of [Attributes]
[DATA]
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[END] of [Spectrum]

297
calfile/profile/Back_SAM_859F.dat
Unescape View File

@ -0,0 +1,297 @@
[Spectrum]
Version = 1
IDData = DLAB_2018-05-04_11-56-28_529_586
IDDevice = SAM_859F
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[END] of [Spectrum]

297
calfile/profile/Back_SAM_85B5.dat
Unescape View File

@ -0,0 +1,297 @@
[Spectrum]
Version = 1
IDData = DLAB_2018-06-11_15-23-57_730_586
IDDevice = SAM_85B5
IDDataType = SPECTRUM
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IDDataTypeSub3 =
DateTime = 2018-06-11 15:17:40
PositionLatitude = 0
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Comment =
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Mission =
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P31 = -1
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RAWDynamic = 65535
Temperature = +NAN
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[END] of [DATA]
[END] of [Spectrum]

297
calfile/profile/CalAQ_SAM_852F.dat
Unescape View File

@ -0,0 +1,297 @@
[Spectrum]
Version = 1
IDData = AquaDLAB_2016-12-07_12-02-43_591_545
IDDevice = SAM_852F
IDDataType = SPECTRUM
IDDataTypeSub1 = CAL
IDDataTypeSub2 = Aqua
IDDataTypeSub3 =
DateTime = 2016-12-07 12:01:43
PositionLatitude = 0
PositionLongitude = 0
Comment =
CommentSub1 =
CommentSub2 =
CommentSub3 =
IDMethodType =
MethodName =
Mission = No Mission
MissionSub = 1
RecordType = 0
[Attributes]
CalFactor = 1
IDBasisSpec =
IDDataBack = DLAB_2016-11-29_14-47-59_729_812
IDDataCal =
IntegrationTime = 256
P31 = -1
P31e = 0
PathLength = +INF
RAWDynamic = 65535
Temperature = +NAN
Unit1 = $05 $00 Pixel
Unit2 = $04 $09 1/Intensity (m^2 nm)/mW
Unit3 = $04 $09 1/Intensity (m^2 nm)/mW
Unit4 = $f1 $00 Status
[END] of [Attributes]
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297
calfile/profile/CalAQ_SAM_859F.dat
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@ -0,0 +1,297 @@
[Spectrum]
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297
calfile/profile/CalAQ_SAM_85B5.dat
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@ -0,0 +1,297 @@
[Spectrum]
Version = 1
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297
calfile/profile/Cal_SAM_852F.dat
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[Spectrum]
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IDData = AirDLAB_2016-12-07_12-00-24_364_510
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297
calfile/profile/Cal_SAM_859F.dat
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[Spectrum]
Version = 1
IDData = DLAB_2018-05-24_13-29-20_305_176
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[END] of [Spectrum]

297
calfile/profile/Cal_SAM_85B5.dat
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[Spectrum]
Version = 1
IDData = DLAB_2018-06-13_11-56-08_604_111
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112 1.02045255259373 0 0
113 1.00192289281247 0 0
114 0.987093337695555 0 0
115 0.973433543184599 0 0
116 0.961454156421677 0 0
117 0.949336048850277 0 0
118 0.937190359719721 0 0
119 0.925018119816345 0 0
120 0.911316167695048 0 0
121 0.897751565127677 0 0
122 0.885763756400802 0 0
123 0.875253674622747 0 0
124 0.866439225407856 0 0
125 0.859594015285511 0 0
126 0.856442344648432 0 0
127 0.854520610650332 0 0
128 0.853095084706978 0 0
129 0.851996897997662 0 0
130 0.849373999218705 0 0
131 0.845008414644852 0 0
132 0.837447706997702 0 0
133 0.828042280687475 0 0
134 0.816973957953628 0 0
135 0.804392597259629 0 0
136 0.790971383923797 0 0
137 0.777350907812577 0 0
138 0.764886212005326 0 0
139 0.753124860834896 0 0
140 0.74238339492221 0 0
141 0.731621293455726 0 0
142 0.720137856580817 0 0
143 0.707681887074656 0 0
144 0.692857487682284 0 0
145 0.676149155140644 0 0
146 0.657691286728854 0 0
147 0.637091724889135 0 0
148 0.615841105000382 0 0
149 0.593277961352052 0 0
150 0.571635565839856 0 0
151 0.550558744253774 0 0
152 0.529727893337181 0 0
153 0.50958610090654 0 0
154 0.490923786532866 0 0
155 0.472942835508178 0 0
156 0.455966760194577 0 0
157 0.439389399108222 0 0
158 0.42326262400571 0 0
159 0.408064966451864 0 0
160 0.392531100434587 0 0
161 0.376760145430696 0 0
162 0.361340837642809 0 0
163 0.345797349215964 0 0
164 0.330538900755072 0 0
165 0.315423852713651 0 0
166 0.300655326757946 0 0
167 0.286125136929255 0 0
168 0.27220666979537 0 0
169 0.258963801456755 0 0
170 0.246515726736969 0 0
171 0.23471243489257 0 0
172 0.223963260764627 0 0
173 0.213811227531161 0 0
174 0.204848303945938 0 0
175 0.196342813423038 0 0
176 0.188347519381911 0 0
177 0.180847277367304 0 0
178 0.173574321958823 0 0
179 0.166782572540461 0 0
180 0.159983659268987 0 0
181 0.153496471427164 0 0
182 0.146983276179518 0 0
183 0.140664487031456 0 0
184 0.134679615950644 0 0
185 0.128426075217298 0 0
186 0.122768803469292 0 0
187 0.116973531179931 0 0
188 0.111227699506044 0 0
189 0.10561644888568 0 0
190 0.0999165260100575 0 0
191 0.09399466356358 0 0
192 0.0884689961099718 0 0
193 0.0833768260697751 0 0
194 0.0789223013382674 0 0
195 0.0748108094846383 0 0
196 0.0710379549143775 0 0
197 +NAN 0 0
198 +NAN 0 0
199 +NAN 0 0
200 +NAN 0 0
201 +NAN 0 0
202 +NAN 0 0
203 +NAN 0 0
204 +NAN 0 0
205 +NAN 0 0
206 +NAN 0 0
207 +NAN 0 0
208 +NAN 0 0
209 +NAN 0 0
210 +NAN 0 0
211 +NAN 0 0
212 +NAN 0 0
213 +NAN 0 0
214 +NAN 0 0
215 +NAN 0 0
216 +NAN 0 0
217 +NAN 0 0
218 +NAN 0 0
219 +NAN 0 0
220 +NAN 0 0
221 +NAN 0 0
222 +NAN 0 0
223 +NAN 0 0
224 +NAN 0 0
225 +NAN 0 0
226 +NAN 0 0
227 +NAN 0 0
228 +NAN 0 0
229 +NAN 0 0
230 +NAN 0 0
231 +NAN 0 0
232 +NAN 0 0
233 +NAN 0 0
234 +NAN 0 0
235 +NAN 0 0
236 +NAN 0 0
237 +NAN 0 0
238 +NAN 0 0
239 +NAN 0 0
240 +NAN 0 0
241 +NAN 0 0
242 +NAN 0 0
243 +NAN 0 0
244 +NAN 0 0
245 +NAN 0 0
246 +NAN 0 0
247 +NAN 0 0
248 +NAN 0 0
249 +NAN 0 0
250 +NAN 0 0
251 +NAN 0 0
252 +NAN 0 0
253 +NAN 0 0
254 +NAN 0 0
255 +NAN 0 0
[END] of [DATA]
[END] of [Spectrum]

81
calfile/profile/SAMIP_50ED_ALL.ini
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@ -0,0 +1,81 @@
[DEVICE]
Version = 0
IDDevice = SAMIP_50ED
IDDeviceType = SAMIP
IDDeviceTypeSub1 = ACC-2
IDDeviceTypeSub2 = VIS
IDDeviceTypeSub3 =
DateTime = 2018-06-19 12:08:40
Comment =
RecordType = 0
IDDeviceMaster =
[ATTRIBUTES]
IDDeviceSAM = SAM_859F
IDDeviceIP = IP_C121
[END] of [ATTRIBUTES]
[END] of [DEVICE]
[DEVICE]
Version = 0
IDDevice = IP_C121
IDDeviceType = IP
IDDeviceTypeSub1 =
IDDeviceTypeSub2 =
IDDeviceTypeSub3 =
DateTime = 2018-06-19 12:01:08
Comment =
RecordType = 0
IDDeviceMaster = SAMIP_50ED
[ATTRIBUTES]
Incl_Orientation = up
Incl_Xgain = 1.0
Incl_Xoffset = 125
Incl_Ygain = 0.9375
Incl_Yoffset = 126
Incl_KBG = 1.2073
Incl_Kref = 0.1275
Press_Current_mA = 1.08
Press_Surface_bar = 5.57
Press_Gain = 2.7
WithIncl = 1
WithPress = 1
Press_Sens_mV_bar_4mA = 71.36
Press_Sens_mV_bar_1mA = 17.84
Press_Type = PA-10/TAB/10bar
CalibrationDate = 08.06.2018
[END] of [ATTRIBUTES]
[END] of [DEVICE]
[DEVICE]
Version = 0
IDDevice = SAM_859F
IDDeviceType = SAM
IDDeviceTypeSub1 = ACC-2
IDDeviceTypeSub2 = VIS
IDDeviceTypeSub3 =
DateTime = 2018-05-30 12:14:10
Comment =
RecordType = 0
IDDeviceMaster = SAMIP_50ED
[ATTRIBUTES]
c0s = +3.019290000E+02
c1s = +3.345130000E+00
c2s = +2.651460000E-04
c3s = -1.753680000E-06
DarkPixelStart = 237
DarkPixelStop = 254
Reverse = 0
c4s = +0.000000000E+00
IDDataCal = DLAB_2019-08-28_14-44-55_098_198
IDDataBack = DLAB_2019-08-28_12-24-09_763_812
IDDataCalAQ = DLAB_2019-08-28_14-47-19_914_233
Firmware = 2.06
[END] of [ATTRIBUTES]
[END] of [DEVICE]

32
calfile/profile/SAM_852F.ini
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@ -0,0 +1,32 @@
[Device]
Version = 0
IDDevice = SAM_852F
IDDeviceType = SAM
IDDeviceTypeSub1 = ACC-2
IDDeviceTypeSub2 = VIS
IDDeviceTypeSub3 =
RecordType = 0
DateTime = 2016-12-07 12:03:12
IDDeviceMaster =
Comment =
[Attributes]
DarkPixelStart = 237
DarkPixelStop = 254
Firmware = 2.06
IDDataBack = DLAB_2016-11-29_14-47-59_729_812
IDDataCal = DLAB_2016-12-07_12-00-24_364_510
IDDataCalAQ = DLAB_2016-12-07_12-02-43_591_545
IntegrationTime = 0
Reverse = 0
SerialNo_MMS = 103307
WavelengthRange = 310..1100
c0s = 299.895
c1s = 3.31161
c2s = 0.00031652
c3s = -1.73194e-06
c4s = +0.000000000E+00
cs = 102842
[END] of [Attributes]
[END] of [Device]

30
calfile/profile/SAM_859F.ini
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@ -0,0 +1,30 @@
[Device]
Version = 0
IDDevice = SAM_859F
IDDeviceType = SAM
IDDeviceTypeSub1 = ARC
IDDeviceTypeSub2 = VIS
IDDeviceTypeSub3 =
RecordType = 0
DateTime = 2018-05-24 13:30:20
IDDeviceMaster =
Comment = ARC VIS
[Attributes]
DarkPixelStart = 237
DarkPixelStop = 254
Firmware = 2.06
IDDataBack = DLAB_2018-05-04_11-56-28_529_586
IDDataCal = DLAB_2018-05-24_13-29-20_305_176
IDDataCalAQ = DLAB_2018-05-24_13-29-21_895_177
IntegrationTime = 0
Reverse = 0
SerialNo_MMS =
c0s = 299.971
c1s = 3.32431
c2s = 0.000391882
c3s = -1.91435e-06
c4s = +0.000000000E+00
[END] of [Attributes]
[END] of [Device]

30
calfile/profile/SAM_85B5.ini
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@ -0,0 +1,30 @@
[Device]
Version = 0
IDDevice = SAM_85B5
IDDeviceType = SAM
IDDeviceTypeSub1 = ARC
IDDeviceTypeSub2 = VIS
IDDeviceTypeSub3 =
RecordType = 0
DateTime = 2018-06-13 11:58:48
IDDeviceMaster =
Comment = ARC VIS
[Attributes]
DarkPixelStart = 237
DarkPixelStop = 254
Firmware = 2.06
IDDataBack = DLAB_2018-06-11_15-23-57_730_586
IDDataCal = DLAB_2018-06-13_11-56-08_604_111
IDDataCalAQ = DLAB_2018-06-13_11-58-21_312_112
IntegrationTime = 0
Reverse = 0
SerialNo_MMS =
c0s = 300.14
c1s = 3.3268
c2s = 0.000314225
c3s = -1.90331e-06
c4s = +0.000000000E+00
[END] of [Attributes]
[END] of [Device]

17
config.yml
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@ -1,20 +1,11 @@
2:
1:
FUNC: Lsky
SN: '85B5'
2:
FUNC: Esky
FUNC: Ed
SN: '50ED'
3:
FUNC: Lwater
SN: '852F'
3:
1:
FUNC: Lsky
SN: '85B5'
2:
FUNC: Esky
SN: '50ED'
SN: '85B5'
3:
FUNC: Lwater
FUNC: Lu
SN: '852F'

11
myconfig.py
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@ -60,8 +60,9 @@ class RamsesPROFILE(Enum):
Ed = 1
Esky = 2
Lu = 3 #upwelling
Lw = 4
Rs = 5
Res = 4 # 多组数据获得一个 Kd Ed0 Ku Lu0 Lw Rs
# Lw = 4
# Rs = 5
IP_CAL = {
"Incl_Orientation": "up",
@ -162,19 +163,19 @@ class MyConfig(object):
if self.device_type == None:
self.system_cfg = None
temp_cfg = {}
if self.device_type == DeviceType.AWRAMS:
if self.device_type == DeviceType.AWRAMS.name:
temp_cfg = {
1: {"SN": "85B5", "FUNC": RamsesAWRAMS(1).name},
2: {"SN": "50ED", "FUNC": RamsesAWRAMS(2).name},
3: {"SN": "852F", "FUNC": RamsesAWRAMS(3).name}
}
if self.device_type == DeviceType.SURFACE:
if self.device_type == DeviceType.SURFACE.name:
temp_cfg = {
1: {"SN": "85B5", "FUNC": RamsesSURFACE(1).name},
2: {"SN": "50ED", "FUNC": RamsesSURFACE(2).name},
3: {"SN": "852F", "FUNC": RamsesSURFACE(3).name}
}
if self.device_type == DeviceType.PROFILE:
if self.device_type == DeviceType.PROFILE.name:
temp_cfg = {
1: {"SN": "85B5", "FUNC": RamsesPROFILE(1).name},
2: {"SN": "50ED", "FUNC": RamsesPROFILE(2).name},

199
mynumpy.py
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@ -0,0 +1,199 @@
import numpy as np
from pathlib import Path
TOKEN = ";"
SAVE_EXT_NAME = ".csv"
class MyNumpy(object):
def __init__(self,):
# self.first_ndarray = np.array([])
# self.two_d_ndarray = np.ndarray([])
pass
def row_stack_nd_nd(self, nd1:np.ndarray, nd2:np.ndarray):
if nd1.ndim == 1:
np.stack( (nd1, nd2), 0) # 两个一位数组 ，0 上下叠加，1：转置水平叠加
pass
else:
np.vstack( (nd1, nd2)) # 垂直上下叠加
pass
pass
def col_stack_nd_nd(self,nd1:np.ndarray, nd2:np.ndarray):
if nd1.ndim == 1:
np.stack( (nd1, nd2), 1) # 两个一位数组 ，0 上下叠加，1：转置水平叠加
pass
else:
np.hstack( (nd1, nd2.reshape(-1,1)) ) # 垂直上下叠加
pass
def get_time_wl_data_from_csv(self, fpath:Path, sn,fname):
data =[]
file_name = fpath.joinpath( fname + SAVE_EXT_NAME)
try:
readout = np.loadtxt(file_name, dtype = float, delimiter = TOKEN)
except IOError:
# self.makeMsg( 2, file_name + " 文件不存在 " )
readout = np.array([])
raise Exception( "IOError : 文件不存在")
except Exception as e :
# self.makeMsg( 2, "警告： %s" %e )
readout = np.array([])
raise Exception( e)
first_column = readout[1:,0]
header = readout[0,1:]
data = readout[1:,1:]
return first_column,header,data
pass
def get_header_data_from_csv(self, fpath:Path, sn,fname):
data =[]
file_name = fpath.joinpath( fname + SAVE_EXT_NAME)
try:
readout = np.loadtxt(file_name, dtype = float, delimiter = TOKEN)
except IOError:
# self.makeMsg( 2, file_name + " 文件不存在 " )
readout = np.array([])
raise Exception( "IOError : 文件不存在")
except Exception as e :
# self.makeMsg( 2, "警告 %s" % e )
readout = np.array([])
header = readout[0,:]
data = readout[1:,:]
return header,data
pass
def combine_col_row_data (self, col, row, data ):
"""
@description : 结合 时间 波长 数据，存到 csv
考虑 data 是一维的情况，不考虑为空
col header data 皆为 ndarray 格式
col data 二维 ,header 一维二维都可以 尽量用2维
"""
print( "__combine_col_row_data and return" )
# print( col.shape )
# print( row.shape )
# print( data.shape )
new_d = np.array( [ ] )
# 处理数据维度不符
if col.shape[0] != data.shape[0]:
raise Exception("ndarray shape 不对不能合并！")
return new_d
if row.shape[1] != col.shape[1] + data.shape[1]:
raise Exception("ndarray shape 不对不能合并！")
return new_d
# 给新数据 拼接上新的时间 column
try:
new_d = np.column_stack( ( col, data) )
except Exception as e :
raise Exception("合并数据col data 失败！")
# 拼接上波长作为 头部
try:
new_d = np.row_stack( ( row ,new_d ) )
except Exception as e :
raise Exception("合并数据row data 失败！")
# print( " new_d %s " % new_d.shape)
return new_d
pass
def combine_col_row_data_to_csv(self,col,row,data, path_name:Path):
"""
@description : 结合 时间 波长 数据，存到 csv
考虑 data 是一维的情况，不考虑为空
col header data 皆为 ndarray 格式
col data 二维 ,header 一维二维都可以 尽量用2维
"""
print( "__combine_col_row_data_to_csv" )
# print( col.shape )
# print( row.shape )
# print( data.shape )
new_d = np.array( [ ] )
# 处理数据维度不符
if col.shape[0] != data.shape[0]:
return new_d
if row.shape[0] != col.shape[1] + data.shape[1]:
return new_d
# 给新数据 拼接上新的时间 column
try:
new_d = np.column_stack( ( col, data) )
except Exception as e :
# self.makeMsg ( 2, "警告：拼接出错。 " + e )
raise Exception("合并数据col data 失败！")
# 拼接上波长作为 头部
try:
new_d = np.row_stack( ( row ,new_d ) )
except Exception as e :
# self.makeMsg ( 2, "警告：拼接出错。 " + e )
raise Exception("合并数据row data 失败！")
# print( " new_d %s " % new_d.shape)
try:
np.savetxt( path_name, new_d, fmt='%8f', delimiter=TOKEN)
except Exception as e:
# self.makeMsg(2, "警告：%s %s " % (e, path_name) )
raise Exception("保存文件 失败！")
pass
pass
if __name__ == '__main__':
mnp = MyNumpy()
a = np.arange(0, 60, 5)
a = a.reshape(3, 4)
print(a)
aa = np.array([1,2,3])
bb = np.array([4,5,6])
cc = np.array([7,8,9])
s = np.stack( (aa,bb) ,0 ) # 行合并
ss = np.vstack( (s,cc) )
sss = np.stack( (aa,bb) ,1 )
ssss = np.hstack( (sss,cc.reshape(-1,1))) # 列合并,reshape(-1,1)
aa = np.stack( (aa,bb) ,0 ) # 行合并
print(s)
print(ss)
print(sss)
print(cc)
print(cc.reshape(-1,1))
print(ssss)
print(aa)
pass
'''
np.stack( (aa,bb) ,0 ) 增加了维度
np.stack( (aa,bb) ,1 )
np.vstack( (s,cc) ) # 不增加维度
np.column_stack( (sss,cc.T))
'''

102
profiler.py
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@ -14,6 +14,8 @@ import time
import locale
import struct
import numpy as np
from scipy.optimize import leastsq
from pathlib import PurePath,Path
from myconfig import CURRENT_DIR,DATA_DIR,OUTPUT_DIR,NEWLINE,ROWFACTOR,SAVE_EXT_NAME,TOKEN
from myconfig import DeviceType,RamsesSURFACE,RamsesAWRAMS,RamsesPROFILE
@ -319,6 +321,10 @@ class Profiler(object):
入口： dealOneMeasurement_Handheld()
参考： 分组写成函数,一次测量多组数据分离出来。
保存： 按时间文件夹保存
@comment
1号数据： Ed 带倾斜 samip
2号数据： Esky 可能没有 ? 如何判断，信息帧的序列号？ 数据？
3号数据： Lu
"""
self.device_type = DeviceType.PROFILE.name
self.device_enum = None
@ -355,9 +361,9 @@ class Profiler(object):
self.info_dict = {}
self.res = {} # 最终结果{ld: esky: lu: Lw: Rs:}
self.depth_m_offset = 0.0
self.depth_m = 0.0
self.tilt_x = 0.0
self.tilt_y = 0.0
# self.depth_m = 0.0
# self.tilt_x = 0.0
# self.tilt_y = 0.0
self.depth_tilt_x_y = [] # [ {"depth":, "tilt_x": ,"tilt_y": }]
# 方法
@ -552,7 +558,6 @@ class Profiler(object):
pass
# 当前文件名 ？
self.hhp.setMode(1)
self.current_measure_time = self.getCurrentMeasureTimeFromInfoDict()
self.get_ymdhms()
@ -571,15 +576,24 @@ class Profiler(object):
self.decode_sensor_buf()
# 解析Buf, 对buf分组，获得[{lsky: esky : lwater} .... ]
# 可能需要 传感器序列号数据，判断几个传感器。 如何判断几个传感器？？
len_total = len(self.intensity_before_avg)
if len_total%self.measurement_repeat != 0:
self.res = {}
return # 返回退出
# 可能需要 传感器序列号数据，判断几个传感器。 如何判断几个传感器？？?????
# 剖面
# 去掉倾斜不达标的数据 -- 格式ndarray 多维数组？
self.remove_data_with_tilt_beyond( self.depth_tilt_x_y, self.intensity_before_avg )
# 获得数据去拟合 -- 分拆Ed Lu
depth_ndarray = np.array(self.depth_tilt_x_y)
depth_ndarray = depth_ndarray[:,0]
data = np.array( self.intensity_before_avg )
# 剖面 - 校正文件要用水的，计算深度值 ？？
res = self.leastsq_fitting( self.depth_tilt_x_y, self.intensity_before_avg )
# group_num = int(len_total/self.measurement_repeat)
@ -591,6 +605,59 @@ class Profiler(object):
# self.dealMultiGroup(group_num)
def remove_data_with_tilt_beyond( self, arr_x:list, arr_y:list, degree):
if len(arr_x) != len(arr_y.shape):
raise MyException( f"深度和数据的维度有误" )
pass
for i in range( len(arr_x),0,-1 ):
if abs( arr_x[i][1] ) > degree or abs( arr_x[i][2] ) > degree:
arr_x.pop(i)
arr_y.pop(i)
pass
pass
pass
def leastsq_fitting( self, arr_x, arr_y ):
"""
@description : arr_x arr_y 是不同波长数据
对其列上的每个值拟合获得kd ln(lu0)
也可以对 arr_y 先切片
最小二乘只能遍历处理
arr_y 包含 Ed Lu 返回两组数据
"""
log.info(f" ->>>> ", __name__, 'leastsq_fitting')
res = np.array([])
print(arr_x.shape)
print(arr_y.shape)
for i in range( arr_y.shape[1] ) :
# 切出第一列
row_ = arr_x
column_ = arr_y[:,i]
# 拟合
p0 = [1,20]
para = leastsq( self.fitting_error, p0, args = ( row_, column_ ) )
if not res.size :
res = para[0]
else:
res = np.vstack( (res, para[0]) )
# 转置 返回,第一列为 k, 第二列为 ln(Lu0-)
print(" __ndarray_ln_leastsq_fitting ...... %s %s " % res.shape )
print(res)
return res.T
# 需要拟合的函数 fitting_func
def fitting_func( self, p, x ):
k,b=p
return k*x+b
# 拟合的残差函数
def fitting_error(self,p,x,y):
return self.fitting_func(p,x)-y
def dealMultiGroup(self, group_num:int ):
log.info(f"group_num: {group_num}", __name__, "dealMultiGroup")
# 分组进行处理
@ -735,13 +802,18 @@ class Profiler(object):
cfg = self.getCfgByFunc( func)
if i == 1 or i==3: # 两个空气中一个水中注意序号
self.ramses.setMode(1) # 水中？？？ 另外一个是空气中的
if i == 1: # 获得深度倾斜
# self.decode_ip_buf( ip_buf, cfg )
x_y_depth_m = self.ramses.decode_ip_buf( ip_buf, cfg)
self.depth_tilt_x_y.append(x_y_depth_m)
self.ramses.setCalCfg(cfg)
self.ramses.resetItSpectrum()
self.ramses.ConvertAndCalibrate()
res.update({ func : self.ramses.spectrum })
# 处理 深度倾斜 数据
self.decode_ip_buf(ip_buf)
# depth_m_x_y = self.ramses.decode_ip_buf( ip_buf, cfg)
# self.decode_ip_buf(ip_buf)
self.intensity_before_avg.append( res )
pass
@ -774,12 +846,10 @@ class Profiler(object):
self.intensity_before_avg.append( res )
pass
def decode_ip_buf( self,buf) :
def decode_ip_buf( self, buf, ip_cal) :
'''Ed校正文件去处理数据'''
depth_m = 0.0
tilt_x = 0.0
tilt_y = 0.0
self.depth_tilt_x_y.append( {"depth":depth_m, "tilt_x":tilt_x ,"tilt_y":tilt_y } )
res = self.ramses.decode_ip_buf(buf,ip_cal)
self.depth_tilt_x_y.append(res)
pass
def getAvg( self, d:list) :

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