The program needs to be configured in the first place. The variables are used as described:
file_root_path # the path the destinated sensor data is in (optional if the location of the sensor configuration is a full path)
current_position # the position in meters where the data should be accassed (mostly the end of the last line)
mysql_config # the configuration of the mysql database (only read accass required)
fetch_limit # the maximum amount of rows to be fetched (only important to get the speeds of the lines from the database -> shouldn't be too small)
fetch_limit_increase_rate # in case the speed data gathered from the sql server isn't enough with the set fetch limit this variable is used to increase the fetch rate
max_fetch_limit # the maximum feth limit. It won't be increased anymore if it has been reached
#######################
# Sensorconfiguration #
#######################
image_sensor = {
"name": "sensor", # sensorname
"position": 0.0, # position of the sensor on the lines in meters (absolute position, not relative to current line)
"data": "file", # the type of the data storage (file|database)
"specification": "image", # the specification of the type (image|csv|[database_table name])
"location": file_root_path + "kinect/", # the path to the data (path|column_numbers|table_field name)
"file_prefixes": [ # the prefixes of the files to seperate them (list)
"color",
"depth"
]
}
csv_sensor = {
"name": "x102",
"position": 0.6,
"data": "file",
"specification": "csv",
"location": file_root_path + "udp_x102/2018_05_24/",
"file_templates": [ # the template in what the files should be renamed to (date parameters are required to directly access the correct file)
"kipro-analyser-data_%(year)s-%(month)s-%(day)s_%(hour)s-%(minute)s-%(second)s.%(millisecond)s.csv"
]
}
database_sensor_1 = {
"name": "x101",
"position": 0.6,
"data": 'database',
'specification': 'data_analyser_x101_daten', # the table in the database
'location': {
'field_no': { # take all data from the following rows
'start': 4, # start row (inclusive)
'end': 19 # last row (exclusive)
}
},
'condition': { # the condition to select the correct data
'datediff': { # datediff means the data with the lowest datediff is taken
'field_name': 'time' # the name of the field to compare the date with
}
}
}
database_sensor_2 = {
"name": "Bandwaage",
"position": 7.6,
"data": "database",
"specification": "opc_data",
"location": {
"field_name": "ITEM_VALUE", # the field name the data is saved in
},
"condition": {
'datediff': {
'field_name': "READ_TIME", # datediff condition
},
'field': { # specific field condition
'field_name': 'ITEM_NAME', # the field
'value': 'ET 200SP-Station_1.ET200SP.OPC_DATA.Messwerte.BANDWAAGE' # the value the field must have
}
}
}
sensors = [image_sensor, csv_sensor, ...] # list with all sensors
######################
# line configuration #
######################
knickband = {
"name": "Knickband",
"database_name": "Knickband", # the name suffix of the database table value the line has (see 'lines' variable)
"id": 0, # the id (should be ascending)
"length": 4.2, # the length of the line im meters
"speed_factor": 1 / 3800 # the speedfactor of the frequency converter number from the database
}
zufuehrband = {
"name": "Zuführband",
"database_name": "Aufgabebunker",
"id": 1,
"length": 6.8,
"speed_factor": 1 / 3800
}
lines = {
"selector_template": "ET 200SP-Station_1.ET200SP.OPC_DATA.Foerderbaender.%(line_name)s.%(value_name)s", # the database template for data for the lines (parameters are required)
"lines": [knickband, zufuehrband] # the list of all lines
}
init_logger()
now = time.time()
logging.debug("Application started")
# create mysql connection
try:
db = mysql.connector.connect(**mysql_config)
except mysql.connector.Error as err:
if err.errno == errorcode.ER_ACCESS_DENIED_ERROR:
logging.critical("Something is wrong with your user name or password")
elif err.errno == errorcode.ER_BAD_DB_ERROR:
logging.critical("Database does not exist")
else:
logging.critical(err)
else:
logging.info("Connected to mysql at %s@%s:%s/%s" % (
mysql_config["user"], mysql_config["host"], mysql_config["port"], mysql_config['database']
))
# Get the speeds from the database
all_v = get_speeds(db)
# TODO probably adapt lengths in get_time_offset_multiple_lines so we don't need the line underneath?
lengths = [f["length"] for f in lines["lines"]]
# optimize file names of analyser
reformat_analyser(analyser)
# !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
# !! important stuff happens here !!
# !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
sensor_data = {}
for sensor in sensors:
# get time offset
time_offset = None
while time_offset is None:
try:
time_offset = get_time_offset_multiple_lines(sensor['position'], current_position, lengths,
all_v)
except IndexError as e:
if (fetch_limit == max_fetch_limit):
logging.critical("Max fetch limit reached. Not enough speed data")
raise ValueError("Max fetch limit reached. Not enough speed data")
logging.debug("Not enough data in %d entries, increasing fetch_limit" % fetch_limit)
fetch_limit += fetch_limit_increase_rate
if (fetch_limit > max_fetch_limit):
fetch_limit = max_fetch_limit
all_v = get_speeds(db)
time_of_sensor_capture = all_v[0][0]["datetime"] - time_offset
sensor_data[sensor['name']] = get_sensor_data(time_of_sensor_capture, sensor, db)
db.close()
logging.info("Program finished in %s seconds" % str(time.time() - now))The tool is adjusted to the current sensors. Minor optimizations might be needed in case a new sensor should be added. In case of an error there is a logfile located in the log directory with additional debug information.