def __init__(self, file_path, n_headerlines=1, **kwargs):
"""
Initialize a general csv object
:param file_path: Path to a csv file
:param n_headerlines: number of rows above the first row of data.
:param kwargs: enter an identifying label followed by the index of each column to be read into the object
:return:
"""
with open(file_path) as file_var:
# Iterate over each data type specified in kwargs
# dialect = csv.Sniffer().sniff(file_var.read(2024), delimiters="\t,")
for data_label in kwargs:
dl = data_label.lower()
file_var.seek(0)
input_data = csv.reader(file_var, delimiter=',')
for i in range(0, n_headerlines):
next(input_data)
temp = []
for row in input_data:
if row[kwargs[data_label]] == '':
temp.append(np.nan)
continue
if dl == 'date_time' or dl == 'date' or dl == 'time':
temp.append(
data_tools.str_to_datetime(
row[kwargs[data_label]]))
else:
try:
temp.append(float(row[kwargs[data_label]]))
except ValueError:
temp.append(row[kwargs[data_label]])
setattr(self, data_label, np.array(temp))
def __init__(self, file_path, disp=None, n_headerlines=1, **kwargs):
"""
Initialize a VDR object
:param file_path: Path to a vdr database exported to a csv
:param disp: Displacment per revolution (cm^3)
:param n_headerlines: number of rows above the first row of data.
:param kwargs: enter an identifying label followed by the index of each column to be read into the object
:return:
"""
# The following set of data labels enforces consistent labeling for all VDR objects
data_labs = [
'rpm', 'speed', 'fuel', 'port_fuel', 'star_fuel', 'port_rpm',
'star_rpm', 'port_rpm'
]
data_labs.extend([
'aux_rpm', 'aux_fuel', 'hyd', 'hyd_1', 'hyd_2', 'date_time',
'date', 'time'
])
data_labs.extend([
'supply_temp', 'return_temp', 'port_supply_temp',
'star_supply_temp', 'aux_supply_temp'
])
data_labs.extend(
['port_return_temp', 'star_return_temp', 'aux_return_temp'])
for data_label in kwargs:
if data_label not in data_labs:
raise ValueError(
'Data label ' + data_label +
' is not a permissible label. Permissible labels are: ' +
', '.join(data_labs))
with open(file_path) as file_var:
self.hyd_disp = disp
# Iterate over each data type specified in kwargs
# dialect = csv.Sniffer().sniff(file_var.read(2024), delimiters="\t,")
for data_label in kwargs:
file_var.seek(0)
input_data = csv.reader(file_var, delimiter=',')
for i in range(0, n_headerlines):
next(input_data)
temp = []
for row in input_data:
if row[kwargs[data_label]] == '':
temp.append(np.nan)
continue
if data_label == 'date_time':
temp.append(
data_tools.str_to_datetime(
row[kwargs[data_label]]))
else:
temp.append(float(row[kwargs[data_label]]))
setattr(self, data_label.lower(), np.array(temp))
if disp is not None:
self.hyd_power = self.hyd * self.rpm * disp / 60 * 6894.76 * 1e-6 / 746
def __init__(self, file_path, n_eng=1, port=1, plot_eng=1, delimiter='\t'):
"""
Input params:
file_in a raw data file to read
n_eng number of engines recorded in this file (must be either 1 or 2)
port position of the port engine data in the raw file (1 or 2)
"""
if n_eng == 1:
n_headerlines = 11
self.prop_curve_dict = {'RPM': [], 'power': []}
elif n_eng == 2:
n_headerlines = 14
self.prop_curve_dict = {
'engines': {
'port': {
'RPM': [],
'power': []
},
'starboard': {
'RPM': [],
'power': []
}
}
}
else:
raise ValueError('n_eng must be 1 or 2')
if port > n_eng:
raise ValueError('port must be less than or equal to n_eng')
self.plot_eng = plot_eng
self.n_eng = n_eng
file_var = open(file_path)
input_data = csv.reader(file_var, delimiter=delimiter)
n_timesteps = sum(1 for row in input_data) - n_headerlines
file_var.seek(0)
input_data = csv.reader(file_var, delimiter=delimiter)
self.units = "Time: seconds, Torque: ft-lbs, Power: hp, RPM: RPM"
self.time = np.zeros(n_timesteps)
self.torque = np.zeros(n_timesteps)
self.power = np.zeros(n_timesteps)
self.rpm = np.zeros(n_timesteps)
self.date_time = []
if n_eng == 2:
self.torque2 = np.zeros(n_timesteps)
self.power2 = np.zeros(n_timesteps)
self.rpm2 = np.zeros(n_timesteps)
for row in input_data:
try:
if row[0][0:6] == 'Units:':
self.units = row[0][7:]
elif row[0][0:24] == 'TorqueTrak 1 full scale:':
self.full_scale_torque = float(row[0][25:-6])
elif analysis_functions.is_number(row[-1]):
data_num = input_data.line_num - n_headerlines - 1
self.date_time.append(data_tools.str_to_datetime(row[0]))
self.time[data_num] = float(row[1])
if port == 1:
self.torque[data_num] = float(row[2])
self.power[data_num] = float(row[3])
self.rpm[data_num] = float(row[4])
if n_eng == 2:
self.torque2[data_num] = float(row[5])
self.power2[data_num] = float(row[6])
self.rpm2[data_num] = float(row[7])
else:
self.torque[data_num] = float(row[5])
self.power[data_num] = float(row[6])
self.rpm[data_num] = float(row[7])
self.torque2[data_num] = float(row[2])
self.power2[data_num] = float(row[3])
self.rpm2[data_num] = float(row[4])
except IndexError:
continue
file_var.close()