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awrams/awrams.py

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dataclass first
2 years ago
from dataclasses import dataclass,field
from pathlib import Path
from typing import Any,List
from enum import Enum
import numpy as np
import struct
import time
from myRamses import RamsesFactoryHandle
from tools.mylogger import log
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from myconfig import TOKEN,NEWLINE
dataclass first
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@dataclass
class InfoFrame(object):
infoBytes:bytes = None
time_str:str= None
time_stamp:int= None
year:str= None
month:str= None
day:str= None
hour:str= None
minute:str= None
second:str= None
Roll: int= None
Pitch:int= None
Yaw:int= None
Hx:int= None
Hy:int= None
lon:int= None
lat:int= None
satelite_num:int= None
PDOP:int= None
HDOP:int= None
VDOP:int= None
Temperature:int= None
Humidity:int = None
Battery:int= None
ErrorCode:int= None
Azimuth:int= None
RunAngle:int= None
MeasureGroupNum:int= None
Tiltx:int= None
Tilty:int= None
Depth:int= None
SN1:str= None
SN2:str= None
SN3:str= None
MeasureInterval :int= None
MeasureRepeat: int= None
def output_info_frame(self, ):
pass
def get_year(self, ):
return self.year
def set_info_frame(self, info:bytes):
try:
temp = struct.unpack("<BBBBBBHHHHHHIIHHHHHBBBHHIfff \
HHHBHBHHHHH",
info)
except Exception as e:
return
temp = list(temp) # tuple to list
# print(f" ==========={temp} {temp[0]}")
time_ = "20" + f"{str(temp[0])}" + "-" + f"{str(temp[1])}" + "-" + f"{str(temp[2])}" + " " \
+ f"{str(temp[3])}" + ":" + f"{str(temp[4])}" + ":" + f"{str(temp[5])}"
# print(f" ==========={time_}")
self.time_str = time_
self.time_stamp = 0
self.year:str = str(temp[0])
self.month:str = str(temp[1])
self.day:str = str(temp[2])
self.hour:str = str(temp[3])
self.minute:str = str(temp[4])
self.second:str = str(temp[5])
self.Roll: int = temp[6]
self.Pitch:int = temp[7]
self.Yaw:int = temp[8]
self.Hx:int = temp[9]
self.Hy:int = temp[10]
self.Hz:int = temp[11]
self.lon:int = temp[12]
self.lat:int = temp[13]
self.satelite_num:int = temp[14]
self.PDOP:int = temp[15]
self.HDOP:int = temp[16]
self.VDOP:int = temp[17]
self.Temperature:int = temp[18]
self.Humidity:int = temp[19]
self.Battery:int = temp[20]
self.ErrorCode:int = temp[21]
self.Azimuth:int = temp[22]
self.RunAngle:int = temp[23]
self.MeasureGroupNum:int = temp[24]
self.Tiltx:int = temp[25]
self.Tilty:int = temp[26]
self.Depth:int = temp[27]
self.SN1:str = hex(temp[28])[2:].upper()
self.SN2:str = hex(temp[29])[2:].upper()
self.SN3:str = hex(temp[30])[2:].upper()
self.MeasureInterval :int = temp[31]
self.MeasureRepeat: int = temp[32]
# print( self)
pass
@dataclass
class DataFrame(object):
''' AWRAMS 数据无需 remove_mask
多组 : 每组类似 15 + 26 + 576*3
数据接收方式： AWRAMS格式, 从文件读取
'''
deviceID:int = None
measureId: int = None
dataBytes:List[bytes] = None
groupNUm: int = 1
data_group:List[bytes] = None # 多组 每组三个传感器 [ Group1, group2, group3 group4 group5 ]
data_group_senor_bytes:List[List[bytes]] = None# [ [IP_byte, Sennsor1_byte,sensor2_byte,sensor3_byte], ] 先分测量组再传感器
data_sensor_group_bytes:List[List[bytes]] = None# [ [sensor1_grp1,sensor1_grp2,sensor1_grp3,sensor1_grp4,sensor1_grp5], ] 先传感器，再测量组
data_ip: List[List[bytes]] =None # IP数据
wavelength: List = None
spectrum: List = None
def set_data_bytes_list(self, data_frame:List[bytes]):
self.dataBytes = []
self.dataBytes = data_frame
pass
def set_data_bytes(self, byt:bytes):
''' 不含 15个 AA...头 , 26(*) +576(*) '''
self.dataBytes = []
# 判断是否包含IP部分数据
self.dataBytes = [byt]
pass
def set_data_group(self,groups:list):
self.data_group = groups
self.groupNum = len(self.data_group)
pass
def split_by_sensor(self,):
''' 兼容需求，需将 26个Ip信息帧传出去 '''
self.groupNum = len(self.dataBytes)
self.data_sensor_group_bytes =[]
self.data_ip = []
for i in range(3):
sensor = [] # 每组开始，赋予空值
for j in range(self.groupNum):
self.data_ip.append( self.dataBytes[j][:26] )
buf = self.dataBytes[j][26:]
sensor.append ( buf[i*576 : 576+i*576] )
pass
self.data_sensor_group_bytes.append(sensor)
pass
def split_by_measure(self,):
for i in range(self.groupNUm):
buf = self.data_group[i][41:]
measureGroup = [ ]
measureGroup.append( buf[0:576] )
measureGroup.append( buf[576:576+576] )
measureGroup.append( buf[576+576:576+576+576] )
self.data_group_senor_bytes.append(measureGroup)
pass
@dataclass
class AWRAMSData(object):
deviceid:int =None
configSensor:List[str] = None # 序列号 Lsky Esky Lwater
configFunc:List[str] = None
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currentPath:Path =None
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info_frame:InfoFrame = None
data_frame:DataFrame = None # 数据只到分组成byte结束
ramsesFactoryHandle:List[RamsesFactoryHandle] = None # 多个工厂，每个工厂有自己的 标定文件及参数，工厂标记序列哈，只处理相同序列号的产品数据
data_after_avg:List[int] =None
wavelength:List[int] =None
spectrum:List[int] =None
pass
def __post_init__(self):
assert self.deviceid != None , ">>>> AWRAMSData deviceid is empty"
pass
def build_datafactory_by_configSensor(self,calcfg:dict):
"""
@description : 调用工厂得到整数值
@param : 576字节数据, 数据id(第几个传感器,还是序列号？)
@Returns : List[int]
"""
assert self.configSensor != None, ">>>> AWRAMSData configSensor is None"
self.ramsesFactoryHandle = [None,None,None]
for i in range(0, len( self.configSensor)):
cfg = calcfg[self.configFunc[i]]
tmp_ramses_factory_handle = RamsesFactoryHandle( sn= self.configSensor[i], cfg=cfg )
self.ramsesFactoryHandle[i] = tmp_ramses_factory_handle
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def set_data_frame( self, data_frame:List[bytes], pth:Path, func ):
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"""
@description : data_frame
"""
log.info(f" 处理 data_frame:List[bytes] ",__name__,"set_data_frame")
self.data_frame = DataFrame()
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self.currentPath= pth
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self.data_frame.set_data_bytes_list(data_frame )
# 对数据进行分组 split_by_sensor(self,)
self.data_frame.split_by_sensor()
self.spectrum =[]
self.wavelength =[]
# 分组后的数据 传给RamsesFactory 的 deal_raw_data_list, 返回平均值
for i in range( len(self.data_frame.data_sensor_group_bytes) ):
log.info( f" {i} ......... {len(self.data_frame.data_sensor_group_bytes[i])}",__name__, "set_data_frame ")
# log.info( f" {i} ......... ",__name__, "set_data_frame ")
self.ramsesFactoryHandle[i].deal_raw_data_list( self.data_frame.data_sensor_group_bytes[i] )
self.ramsesFactoryHandle[i].rf.get_wavelenth()
self.spectrum.append (self.ramsesFactoryHandle[i].rf.data_after_cal)
self.wavelength.append (self.ramsesFactoryHandle[i].rf.Wavelength)
# 补充IP解析数据
# 回调函数
func( self.wavelength, self.spectrum )
def set_info_frame(self, info_frame:bytes):
self.info_frame = InfoFrame()
self.info_frame.set_info_frame(info_frame) #已经解析
pass
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dataclass first
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class mycfg(object):
sensor_cfg = { 2: {1: {'FUNC': 'Lsky', 'SN': '85B5'}, 2: {'FUNC': 'Esky', 'SN': '50ED'}, 3: {'FUNC': 'Lwater', 'SN': '852F'}} }
cal_cfg={2:
{'Lsky': {'SN': '85B5', 'FUNC': 'Lsky', 'TYPE': 'SAM', 'samsn': '85B5', 'inifile': 'SAM_85B5.ini', 'calfile': 'Cal_SAM_85B5.dat', 'calaqfile': 'CalAQ_SAM_85B5.dat', 'backfile': 'Back_SAM_85B5.dat', 'cal': ['+NAN', '+NAN', '+NAN', '0.380824258865919', '0.480956813156357', '0.57671205380196', '0.643896236957154', '0.711054782209677', '0.758265752350778', '0.808854255795615', '0.869466331079482', '0.925321324749243', '1.00927399148091', '1.08699883630787', '1.18347377446848', '1.29079925777138', '1.39953731633192', '1.49536024576308', '1.57053962346542', '1.61051680455964', '1.60891142181803', '1.58014917632373', '1.54292073894688', '1.49782795775685', '1.46270054563491', '1.43754722159869', '1.42339247548624', '1.42249669690879', '1.43289834559721', '1.45081833970432', '1.48383024473758', '1.53350351710437', '1.59283171118034', '1.66682243068085', '1.75523084376357', '1.8490542829721', '1.94827772413977', '2.05297044933559', '2.15300125225733', '2.24489521732098', '2.32484518002751', '2.37710624055378', '2.41032149129472', '2.41401311078449', '2.39196623346607', '2.35386541795861', '2.30358502851024', '2.24350994611066', '2.18566570348128', '2.13007635400607', '2.08048312730197', '2.03943635277338', '1.9990019487276', '1.9542919602901', '1.90697476815729', '1.86132580586718', '1.81936966943287', '1.78948757961567', '1.77036444175303', '1.76067051308416', '1.76079151769139', '1.76865840458355', '1.78533977613825', '1.81054315659671', '1.84219534093402', '1.88262260694772', '1.92633682221336', '1.96919363361994', '2.00638558730966', '2.03543177536163', '2.05645335730185', '2.06889953924594', '2.07668786673546', '2.07746404954558', '2.07708946852551', '2.07239270419962', '2.06329693588947', '2.05235510505223', '2.03788342455449', '2.01750123705209', '1.99316265318269', '1.96344779927853', '1.92810068074762', '1.89032139564187', '1.84840056738145', '1.80188008685176', '1.7531429855323', '1.70184883503381', '1.64693756964496', '1.59639297188055', '1.55743828612696', '1.53081670223502', '1.509066853406', '1.48974595694359', '1.47286758281018', '1.45660325947575', '1.43667408186819', '1.40947906533906', '1.37746325817173', '1.3399910234164', '1.29987620320872', '1.26173586555032', '1.22580130202006', '1.19650560480134', '1.17258287879559', '1.15326969493003', '1.13448708666807', '1.11395465030131', '1.08753684763482', '1.06275254011917', '1.0408908566722', '1.02045255259373', '1.00192289281247', '0.987093337695555', '0.973433543184599', '0.961454156421677', '0.949336048850277', '0.937190359719721', '0.925018119816345', '0.911316167695048', '0.897751565127677', '0.885763756400802', '0.875253674622747', '0.866439225407856', '0.859594015285511', '0.856442344648432', '0.854520610650332', '0.853095084706978', '0.851996897997662', '0.849373999218705', '0.845008414644852', '0.837447706997702', '0.828042280687475', '0.816973957953628', '0.804392597259629', '0.790971383923797', '0.777350907812577', '0.764886212005326', '0.753124860834896', '0.74238339492221', '0.731621293455726', '0.720137856580817', '0.707681887074656', '0.692857487682284', '0.676149155140644', '0.657691286728854', '0.637091724889135', '0.615841105000382', '0.593277961352052', '0.571635565839856', '0.550558744253774', '0.529727893337181', '0.50958610090654', '0.490923786532866', '0.472942835508178', '0.455966760194577', '0.439389399108222', '0.42326262400571', '0.408064966451864', '0.392531100434587', '0.376760145430696', '0.361340837642809', '0.345797349215964', '0.330538900755072', '0.315423852713651', '0.300655326757946', '0.286125136929255', '0.27220666979537', '0.258963801456755', '0.246515726736969', '0.23471243489257', '0.223963260764627', '0.213811227531161', '0.204848303945938', '0.196342813423038', '0.188347519381911', '0.180847277367304', '0.173574321958823', '0.166782572540461', '0.159983659268987', '0.153496471427164', '0.146983276179518', '0.140664487031456', '0.134679615950644', '0.128426075217298', '0.122768803469292', '0.116973531179931', '0.111227699506044', '0.10561644888568', '0.0999165260100575', '0.09399466356358', '0.0884689961099718', '0.
'Esky': {'SN': '50ED', 'FUNC': 'Esky', 'TYPE': 'SAMIP', 'samsn': '859F', 'inifile': 'SAMIP_50ED_ALL.ini', 'calfile': 'Cal_SAM_859F.dat', 'calaqfile': 'CalAQ_SAM_859F.dat', 'backfile': 'Back_SAM_859F.dat', 'cal': ['+NAN', '+NAN', '+NAN', '+NAN', '0.549282530081406', '0.621825635483575', '0.705214779700439', '0.782494923890489', '0.848306874043027', '0.952625287085828', '1.06364941208026', '1.17099618224932', '1.27964867192574', '1.37878597375063', '1.42771820575638', '1.4380590385421', '1.41583530083466', '1.35751030831315', '1.28801896577964', '1.23773169248486', '1.19003370359023', '1.16911032524399', '1.16789019991587', '1.17908641221467', '1.20561721452238', '1.24993325867368', '1.3042108426727', '1.37841324495146', '1.46663415660191', '1.55813913029349', '1.66686169700722', '1.78274771118438', '1.89315285694338', '2.00609300108623', '2.10386062632617', '2.18077321675475', '2.23620955735442', '2.266135432154', '2.26878990322214', '2.25797663538301', '2.22685859649013', '2.17776313289299', '2.1222752364519', '2.06098344374156', '1.99948809108821', '1.94462577242816', '1.8989381397134', '1.8637403074385', '1.84137175128878', '1.82996842025894', '1.82735603324287', '1.82819560800875', '1.82831225824908', '1.82476779554239', '1.82142520789599', '1.82469614734563', '1.83514598035505', '1.85423698694933', '1.88102853388183', '1.91679111910883', '1.95713305118927', '2.0033013266641', '2.05191276620812', '2.10100127704333', '2.15116215495783', '2.19982933350689', '2.24341508467426', '2.28026480621138', '2.30634686430023', '2.31796219508283', '2.31589695847203', '2.29809543158409', '2.2668387918562', '2.22596956700897', '2.17822422289454', '2.1262484698939', '2.07154274835781', '2.01784816285075', '1.9635850159156', '1.90957838150673', '1.85662335754133', '1.80118393109592', '1.74752896056537', '1.69458207285898', '1.64238998731142', '1.59255947952261', '1.55042463825823', '1.52145095482736', '1.50182839545807', '1.48602912306116', '1.47501182897849', '1.46801797625318', '1.46252443118698', '1.4571840542778', '1.44881752975571', '1.433373570625', '1.4106211402034', '1.38310053980989', '1.35343439202405', '1.32469024445085', '1.29921323938482', '1.2757042981125', '1.25356245928469', '1.23230080447944', '1.20776661327865', '1.18172190161938', '1.16211138784545', '1.14836490545677', '1.13698033747357', '1.12673020620722', '1.115430409999', '1.10428562795353', '1.0934141739792', '1.0851095103506', '1.08102444265095', '1.08007408967758', '1.08238869164072', '1.08781099449618', '1.09202496629142', '1.09279743926351', '1.08928198225434', '1.08099296127192', '1.06779395728469', '1.05125732218958', '1.03307124483462', '1.01642561672595', '1.0017478853335', '0.98877464388953', '0.978591382441999', '0.970432000434175', '0.962460675619692', '0.953651636148435', '0.943103023421902', '0.930554197290447', '0.915976069829803', '0.89827602173614', '0.878650755188226', '0.859108524352699', '0.840122962860222', '0.820853477964574', '0.803547895709764', '0.786651104537257', '0.769194844035412', '0.751217544779413', '0.731862968408631', '0.710478767970412', '0.687207420135085', '0.662469528888512', '0.636358233772055', '0.609121332586544', '0.580838486227566', '0.552767035926316', '0.525876935395925', '0.499896413074609', '0.475284681533185', '0.452387885405863', '0.431848904268036', '0.413013739466993', '0.395710805209202', '0.380181587532903', '0.365591896979342', '0.352105459639395', '0.339276260510366', '0.32616389487977', '0.313880254968568', '0.301213081346406', '0.28867892621412', '0.276332017077307', '0.263867205519659', '0.251559483539307', '0.239917175566115', '0.228872841726392', '0.218348838385983', '0.208663588155861', '0.199488791575245', '0.191252859631973', '0.183364916996847', '0.175877803627425', '0.169219899131997', '0.162866423884395', '0.156727192611269', '0.151124000714184', '0.145138407523578', '0.13971586046093', '0.134506608902369', '0.129059486722317', '0.124203168251957', '0.119075347065844', '0.113513221481262', '0.107843336832916', '0.101790305051534', '0.0961960826886135', '0.0914035900672732', '0.0868727278
'Lwater': {'SN': '852F', 'FUNC': 'Lwater', 'TYPE': 'SAM', 'samsn': '852F', 'inifile': 'SAM_852F.ini', 'calfile': 'Cal_SAM_852F.dat', 'calaqfile': 'CalAQ_SAM_852F.dat', 'backfile': 'Back_SAM_852F.dat', 'cal': ['+NAN', '+NAN', '+NAN', '+NAN', '0.099081925071204', '0.107353085872454', '0.113070264290883', '0.114376499819276', '0.116544285861757', '0.1185169696214', '0.121561138979849', '0.126964155564462', '0.134364254054539', '0.144053858633949', '0.154882735476408', '0.16719673162462', '0.181437615712041', '0.194237970806716', '0.20386154720656', '0.211556336359081', '0.211417859085921', '0.208790218500257', '0.20437467341685', '0.198246352046376', '0.192966396099738', '0.18897229193584', '0.186243043953596', '0.18578727224224', '0.187114583931684', '0.189090911319999', '0.193600418301244', '0.200054490546523', '0.208072057884887', '0.218285958582262', '0.230634876630779', '0.243459214546046', '0.257752719558026', '0.272580246630834', '0.286712281491418', '0.300342726342385', '0.312249154496702', '0.321331680226083', '0.327112591435919', '0.329469692698771', '0.327542874308678', '0.322985767437387', '0.316224456423823', '0.308782990589082', '0.301183418606427', '0.293575702556702', '0.286696408065096', '0.280798842600295', '0.275808444038661', '0.271299340181449', '0.266225534078626', '0.260785177597799', '0.255342424416527', '0.250947812402455', '0.24777514930692', '0.246247860756574', '0.246092032695547', '0.247219177075727', '0.249675195006791', '0.253195744885965', '0.257788026175471', '0.26369589320837', '0.270555680751329', '0.277823002163503', '0.284937579021833', '0.291097253127256', '0.296043211270752', '0.299540235735164', '0.301795150475552', '0.303069111244916', '0.30355995799167', '0.303606664702465', '0.303007474849756', '0.302001653949665', '0.300361927400822', '0.297986890885497', '0.295325565249305', '0.291656567474701', '0.287335862742648', '0.282306131698578', '0.276702242286357', '0.270280607979823', '0.263050805729498', '0.255009286552014', '0.247098798503932', '0.2398191835424', '0.23466817932016', '0.230585310303585', '0.227279061892254', '0.224693206022759', '0.222993136629962', '0.221791418806722', '0.220695274517678', '0.219442816624831', '0.217000405185694', '0.213283732282521', '0.208384750595562', '0.202985389753009', '0.197924660371165', '0.193409646692029', '0.189628652821804', '0.186318519164064', '0.183315563032657', '0.180098687261504', '0.176492614557115', '0.172650422408531', '0.168979191040057', '0.166106531649937', '0.163622827054655', '0.161570328667133', '0.159693607722301', '0.157690305409947', '0.15544650006387', '0.153185383511044', '0.150954772341381', '0.148960802743881', '0.147350785081686', '0.146182367433256', '0.145312879880878', '0.144781245193999', '0.14473607505965', '0.144976432177203', '0.145464936657928', '0.145889790468872', '0.146174517595681', '0.14615421098877', '0.145743119998859', '0.144922809795091', '0.143805231938307', '0.142492952453543', '0.141053445832183', '0.139720571628269', '0.138186469198598', '0.136919534961634', '0.135732624874463', '0.134597268963386', '0.133432724955799', '0.13211501546202', '0.130478475600008', '0.128290801143951', '0.125726707508103', '0.122634784100445', '0.119472073398083', '0.116199128230447', '0.112813911251756', '0.109547291781198', '0.106268392530964', '0.10313443150471', '0.100113578226984', '0.097073834113113', '0.0941199411272616', '0.0911853891891621', '0.0882319764053268', '0.085267274530049', '0.0822333903307463', '0.0792187073154596', '0.0760907077820793', '0.0728848234132589', '0.0697048920692252', '0.0665600438164166', '0.0635411651500916', '0.0606319242880778', '0.0578670530064308', '0.0553155735461356', '0.0529193006810867', '0.050722718025932', '0.0486788470977319', '0.0467747209472673', '0.0450423813898501', '0.0434307741189043', '0.041915712424757', '0.0405250313895705', '0.0390895391040532', '0.0377897158697839', '0.0365016922380464', '0.0351788001916396', '0.0338645937424847', '0.0325302009051183', '0.0312848146149282', '0.0300375958148976', '0.0288302935207691', '0.027652203865544', '0.0264621566
## 封装该类的 处理buf hex2int函数
@dataclass
class AWRAMS(object):
deviceid:int = None
configSensor:List[str] =None # 序列号
configFunc:List[str] =None # 功能 Lsky Esky Lwater
calibrationCfg:dict =None
data : AWRAMSData =None
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wavelength:List[np.ndarray] =None
spectrum:List[np.ndarray] =None
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beginWavelength: float =None
endWavelength: float =None
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rowFactor:float =None
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wvInterval: float =None
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newWavelength:np.ndarray=None
Lsky:np.ndarray =None # 无需记录原始波长，记录插值后的波长
Esky:np.ndarray =None
Lwater:np.ndarray =None
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Lw:np.ndarray =None
Rs:np.ndarray =None
def __post_init__(self):
assert self.deviceid != None
self.data = AWRAMSData(deviceid=self.deviceid )
pass
def set_cfg_calibration(self,calcfg:dict):
assert self.deviceid != None
# assert self.deviceid in calcfg.keys(), f">>>> No calibrations data for the current id {self.deviceid}"
self.calibrationCfg = calcfg
pass
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def set_retrieve(self,rtv:dict):
self.beginWavelength= float(rtv["beginWL"])
self.endWavelength= float(rtv["endWL"])
self.wvInterval= float(rtv["interval"])
self.rowFactor= float(rtv["0.026"])
self.newWavelength=np.linspace(self.beginWavelength,self.endWavelength,self.wvInterval)
pass
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def config_awrams(self, cfg:dict):
assert self.deviceid in cfg.keys(), f'>>>> Cannot get the configuration of device id {self.deviceid}'
self.configSensor = [None,None,None]
self.configFunc = [None,None,None]
# Lsky Esky Lwater
# {1: {'FUNC': 'Lsky', 'SN': '85B5'}, 2: {'FUNC': 'Esky', 'SN': '50ED'}, 3: {'FUNC': 'Lwater', 'SN': '852F'}}
for k,v in cfg.items() :
if v["FUNC"] == "Lsky":
self.configSensor[0] = v["SN"]
self.configFunc[0] = v["FUNC"]
if v["FUNC"] == "Esky":
self.configSensor[1] = v["SN"]
self.configFunc[1] = v["FUNC"]
if v["FUNC"] == "Lwater":
self.configSensor[2] = v["SN"]
self.configFunc[2] = v["FUNC"]
# 将传感器配置传给 AWRAMSDATA
self.data = AWRAMSData( deviceid=self.deviceid, configSensor=self.configSensor, configFunc=self.configFunc )
# 将标定配置传给 AWRAMSData 建立工厂
self.data.build_datafactory_by_configSensor( self.calibrationCfg)
pass
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def callback( self, wavelength:list, spectrum:list ):
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''' 处理返回的数据， 生成Lsky Esky Lwater Lw Rs '''
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log.info( " call back for Lw Rs , 插值， 计算， 保存.................. " )
self.Lsky = np.interp( self.newWavelength, self.wavelength[0], self.spectrum[0])
self.Esky = np.interp( self.newWavelength, self.wavelength[1], self.spectrum[1])
self.Lwater = np.interp( self.newWavelength, self.wavelength[2], self.spectrum[2])
self.Lw = self.Lwater - self.rowFactor * self.Lsky
self.Rs = self.Lw/self.Esky
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self.save()
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# 保存 进一步处理
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def save(self, mode=0):
''' 保存在原文件所在目录 '''
pth = self.data.currentPath
save_fpath = pth.joinpath("res.csv")
ret = ""
ret = ret + str(self.deviceid)+"_"+pth.parts[-1] + TOKEN + self.list2str(list(self.newWavelength))
ret = ret + NEWLINE + "Lsky" + TOKEN + self.list2str( list(self.Lsky) )
ret = ret + NEWLINE + "Esky" + TOKEN + self.list2str( list(self.Esky) )
ret = ret + NEWLINE + "Lwater" + TOKEN + self.list2str( list(self.Lwater) )
ret = ret + NEWLINE + "Lw" + TOKEN + self.list2str( list(self.Lw) )
ret = ret + NEWLINE + "Rs" + TOKEN + self.list2str( list(self.Rs) )
save_fpath.write_text( ret )
pass
def list2str( self, lst:list, token=";" ):
''' 保存在原文件所在目录 '''
ret= ""
for i in range(len(lst)):
if i == 0:
ret = ret + str(lst[i])
else:
ret = ret + TOKEN + str(lst[i])
pass
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class AwramsHandle(object):
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def __init__(self, deviceid=2, cfg=None, calcfg=None, rtv=None):
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self.sensor_cfg = cfg
self.calcfg = calcfg
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self.retrieve = rtv
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self.device_id = deviceid
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self.aw = AWRAMS( deviceid=self.device_id )
self.aw.set_cfg_calibration( self.calcfg )
self.aw.set_retrieve( self.retrieve)
self.aw.config_awrams( self.sensor_cfg )
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pass
def read_one_folder_awrams_online(self, pth:Path):
''' self.data 传数据 info_frame, data_frame'''
log.info(f" 读一个文件夹进行处理 {pth}" ,__name__,"read_one_folder_awrams_online")
bytes_list = []
bin_files = pth.glob('*.bin')
for bf in bin_files:
if bf.name != "info.bin":
bytes_list.append( self.read_bin(bf) )
# print(f"++++++++++ {bytes_list}" )
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self.aw.data.set_data_frame( bytes_list, pth, self.aw.callback ) # 目录也要传过去
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pass
def read_bin(self,fpath: Path):
assert fpath.exists(), f">>>> not find {fpath} "
ret = b''
with open(fpath, 'rb') as file:
ret = file.read()
return ret
pass
pass
class Acfg:
cfg= {1: {'FUNC': 'Lsky', 'SN': '85C2'}, 2: {'FUNC': 'Esky', 'SN': '50ED'}, 3: {'FUNC': 'Lwater', 'SN': '852F'}}
calcfg= {'Lsky': {'SN': '85C2', 'FUNC': 'Lsky', 'TYPE': 'SAM', 'samsn': '85C2', 'inifile': 'SAM_85C2.ini', 'calfile': 'Cal_SAM_85C2.dat', 'calaqfile': 'CalAQ_SAM_85C2.dat', 'backfile': 'Back_SAM_85C2.dat', 'cal': ['+NAN', '+NAN', '+NAN', '+NAN', '0.63607834406219', '0.718127096538326', '0.812216798598817', '0.914442457893824', '1.03343454996493', '1.15933885373154', '1.29479643420084', '1.43677001665361', '1.56848190839848', '1.67447970580786', '1.73889146263122', '1.73244260903254', '1.69192414835577', '1.61622082709111', '1.5270353751059', '1.46047364317447', '1.41296265347303', '1.39311700938614', '1.39852760194912', '1.42554260762195', '1.4700968507055', '1.53635620441153', '1.62082921439482', '1.7237742274692', '1.84755749123585', '1.98432162640748', '2.12689147788928', '2.27366206436985', '2.41515311346652', '2.54267625633242', '2.65248757975216', '2.73468816910085', '2.77942967914337', '2.79565522877852', '2.77806955157777', '2.73891358506136', '2.69063680629234', '2.6282750012231', '2.56338981635672', '2.49687123158122', '2.4309933291301', '2.36993023507549', '2.32161558853422', '2.28314087424895', '2.25846162084215', '2.24994522727437', '2.25549954861938', '2.27668712518828', '2.30493256690767', '2.33255656715114', '2.35720768052834', '2.37757260164886', '2.40002374613635', '2.42905705371268', '2.4673307146952', '2.51294806887351', '2.56575613007937', '2.62193109349514', '2.67842958533042', '2.73753357518048', '2.7913329207665', '2.8423865946084', '2.89027340109411', '2.93157202353872', '2.96274906831744', '2.98346548286676', '2.98798866816702', '2.97297872291037', '2.93559195933884', '2.87662286787444', '2.80380712732453', '2.72275302648293', '2.6373282860483', '2.55448424591999', '2.47778601018081', '2.40377038673745', '2.33484934711808', '2.2698793292122', '2.20651375086021', '2.14704740380438', '2.08988763493926', '2.0346458333411', '1.98224825426305', '1.93452491480363', '1.89146397238956', '1.8653548650058', '1.84879059497611', '1.8371693859594', '1.83197484046632', '1.83105981302589', '1.83169544364263', '1.83369029033973', '1.82985806236537', '1.81684973319988', '1.7961872241934', '1.76710061502081', '1.73459539138238', '1.70421983997876', '1.67561137148482', '1.65483955955664', '1.64005456402998', '1.63103006074007', '1.62646109446179', '1.62483351776729', '1.61794627041935', '1.60638099649103', '1.59160518167625', '1.57856502215575', '1.56723770329055', '1.55884357172436', '1.55081356970191', '1.5440909800073', '1.53473504989623', '1.52335047710565', '1.51140772671503', '1.49628095199023', '1.48082183121466', '1.4668009209167', '1.45300293604089', '1.43913779397284', '1.42471804569399', '1.41116472805909', '1.39601546893463', '1.3795217760198', '1.36066889187826', '1.3395095955925', '1.31771535033317', '1.29387042583309', '1.26955248066416', '1.24679628762607', '1.22528340309588', '1.20486570624273', '1.18549206002717', '1.16756178865017', '1.15111957559202', '1.13469169498467', '1.11621030173639', '1.09569135455521', '1.07275908862679', '1.04573742076401', '1.01572627731635', '0.98381634710957', '0.950352559222019', '0.915760692099546', '0.881456713194727', '0.848044938315892', '0.816038892625263', '0.785024915273114', '0.754850603543375', '0.725690734641156', '0.697449171016547', '0.669846688269734', '0.643097402076866', '0.615807664216611', '0.589686777991522', '0.563134754809732', '0.537416951715189', '0.512092492411016', '0.487999533569422', '0.464888888064952', '0.442938789447448', '0.422687485052752', '0.403811887358409', '0.386602162003576', '0.370223420179536', '0.355850417036878', '0.342554004485098', '0.330263308885894', '0.318892349787717', '0.308390808825048', '0.29923285616278', '0.290049870831026', '0.280987628676386', '0.272166680353347', '0.263184326446838', '0.254328565772045', '0.245533707259442', '0.236284846332185', '0.227364007848682', '0.218575558150069', '0.209919539318749', '0.201723665364338', '0.193439417628863', '0.185095630044576', '0.176908759167827', '0.168492281717065', '0.15971620196905', '0.151519711134016', '0.143896290701505', '0.137256829327417', '0.13133376173
def my_init():
''' 写个handle 类处理'''
cfg = mycfg.cfg
calcfg = mycfg.cal_cfg
device_id = 2
aw = AWRAMS( deviceid=device_id)
aw.set_cfg_calibration(calcfg)
aw.config_awrams(cfg)
if __name__ == '__main__':
# my_init()
ah =AwramsHandle( 2, Acfg.cfg, Acfg.calcfg)
fpath = Path.cwd()
# t= ("data", "2","2002","8", "17","51", "info.bin")
# t= ("data" )
fpath = fpath.joinpath('data\2\2022\8\17\51\0.bin')
# fpath = fpath.joinpath( *t )
# ah.read_one_folder_awrams_online(fpath)
if fpath.exists():
print(" 00000000000000000000000")
else:
print("1111111111111111")
# ah.read_one_folder_awrams_online(fpath)
# data\2\2022\8\17\51\0.bin