def construct_comps(c, *args):
"""
creates TESPy component from class name provided in the .csv-file and
specifies its parameter
:param c: component information
:type c: pandas.core.series.Series
:returns: instance (*tespy.components.component*) - TESPy component object
**additional arguments in args**
- args[0]: char (*pandas.core.frame.DataFrame*) - DataFrame containing the
x and y data of characteristic functions
"""
target_class = getattr(cmp, c.cp)
instance = target_class(c.label)
kwargs = {}
# basic properties
for key in ['mode', 'design', 'offdesign']:
kwargs[key] = c[key]
for key, value in instance.attr().items():
if key in c:
# component parameters
if isinstance(value, hlp.dc_cp):
dc = hlp.dc_cp(val=c[key],
is_set=c[key + '_set'],
is_var=c[key + '_var'])
kwargs[key] = dc
# component characteristics
elif isinstance(value, hlp.dc_cc):
# finding x and y values of the characteristic function
values = args[0]['id'] == c[key]
x = args[0][values]['x'].values[0]
y = args[0][values]['y'].values[0]
dc = hlp.dc_cc(is_set=c[key + '_set'],
method=c[key + '_method'],
param=c[key + '_param'],
x=x,
y=y)
kwargs[key] = dc
else:
continue
instance.set_attr(**kwargs)
return instance
def test_set_attr_errors(self):
#
labels = [5, 'Label,', 'Labe;l', 'Label.']
for l in labels:
self.cmp_instanciation_ValueError(l)
# ValueErrors
self.set_attr_ValueError(self.comp, offdesign=['Q'])
self.set_attr_ValueError(self.conn, offdesign=['f'])
self.set_attr_ValueError(self.conn, state='f')
self.set_attr_ValueError(self.nw, m_unit='kg')
self.set_attr_ValueError(self.nw, h_unit='kg')
self.set_attr_ValueError(self.nw, p_unit='kg')
self.set_attr_ValueError(self.nw, T_unit='kg')
self.set_attr_ValueError(self.nw, v_unit='kg')
self.create_connection_ValueError('source')
self.create_connection_ValueError('target')
# TypeErrors
self.set_attr_TypeError(self.comp, P=[5])
self.set_attr_TypeError(self.comp, tiP_char=None)
self.set_attr_TypeError(self.comp, design='f')
self.set_attr_TypeError(self.comp, fuel=hlp.dc_cp(val='CH4'))
self.set_attr_TypeError(self.comp, design_path=7)
self.set_attr_TypeError(self.conn, design='h')
self.set_attr_TypeError(self.conn, fluid_balance=1)
self.set_attr_TypeError(self.conn, h0=[4])
self.set_attr_TypeError(self.conn, fluid=5)
self.set_attr_TypeError(self.conn, state=5)
self.set_attr_TypeError(self.conn, design_path=5)
self.set_attr_TypeError(self.nw, m_range=5)
self.set_attr_TypeError(self.nw, p_range=5)
self.set_attr_TypeError(self.nw, h_range=5)
self.set_attr_TypeError(self.nw, T_range=5)
self.bus_add_comps_TypeError({'c': self.conn})
self.bus_add_comps_TypeError({'f': self.comp})
self.bus_add_comps_TypeError({'c': self.comp, 'char': 'Hi'})
self.bus_add_comps_TypeError({'c': self.comp, 'p': 5})
self.bus_add_comps_TypeError({'c': self.comp, 'P_ref': 'what'})
self.create_ref_TypeError([self.conn, 7, 'hi'])
self.create_ref_TypeError([self.conn, 'hi', 0])
self.create_ref_TypeError([self.comp, 1, 0])
# KeyErrors
self.set_attr_KeyError(self.comp, wow=5)
self.set_attr_KeyError(self.conn, jey=5)
self.set_attr_KeyError(self.sub, a=7)
self.get_attr_KeyError(self.comp, 'wow')
self.get_attr_KeyError(self.conn, 'key')
self.get_attr_KeyError(self.bus, 'components')
self.get_attr_KeyError(con.ref(self.conn, 1, 0), 'comp')
self.get_attr_KeyError(self.nw, 'test')
self.get_attr_KeyError(self.sub, 'test')
self.get_attr_KeyError(cmp_char.characteristics(), 'test')
self.get_attr_KeyError(hlp.data_container(), 'somekey')
def construct_comps(c, *args):
r"""
Creates TESPy component from class name provided in the .csv-file and specifies its parameters.
Parameters
----------
c : pandas.core.series.Series
Component information from .csv-file.
args[0] : pandas.core.frame.DataFrame
DataFrame containing the x and y data of characteristic functions.
args[1] : pandas.core.frame.DataFrame
DataFrame containing the x, y, z1 and z2 data of characteristic maps.
Returns
-------
instance : tespy.components.components.component
TESPy component object.
"""
if c.interface:
instance = cmp.subsys_interface(c.label, num_inter=1)
else:
target_class = getattr(cmp, c.cp)
instance = target_class(c.label)
kwargs = {}
# basic properties
for key in ['mode', 'design', 'offdesign']:
kwargs[key] = c[key]
for key, value in instance.attr().items():
if key in c:
# component parameters
if isinstance(value, hlp.dc_cp):
dc = hlp.dc_cp(val=c[key],
is_set=c[key + '_set'], is_var=c[key + '_var'])
kwargs[key] = dc
# component parameters
if isinstance(value, hlp.dc_simple):
dc = hlp.dc_simple(val=c[key], val_set=c[key + '_set'])
kwargs[key] = dc
# component characteristics
elif isinstance(value, hlp.dc_cc):
# finding x and y values of the characteristic function
values = args[0]['id'] == c[key]
try:
x = args[0][values].x.values[0]
y = args[0][values].y.values[0]
except IndexError:
# if characteristics are missing (for compressor map atm)
x = cmp_char.characteristics().x
y = cmp_char.characteristics().y
msg = 'Could not find x and y values for characteristic line, using defaults instead for function ' + key + ' at component ' + c.label + '.'
logging.warning(msg)
char = cmp_char.characteristics(x=x, y=y, method=c[key + '_method'], comp=instance.component())
dc = hlp.dc_cc(is_set=c[key + '_set'],
method=c[key + '_method'],
param=c[key + '_param'],
func=char,
x=x, y=y)
kwargs[key] = dc
# component characteristics
elif isinstance(value, hlp.dc_cm):
# finding x and y values of the characteristic function
values = args[1]['id'] == c[key]
try:
x = list(args[1][values].x.values[0])
y = list(args[1][values].y.values[0])
z1 = list(args[1][values].z1.values[0])
z2 = list(args[1][values].z2.values[0])
except IndexError:
# if characteristics are missing (for compressor map atm)
x = cmp_char.char_map().x
y = cmp_char.char_map().y
z1 = cmp_char.char_map().z1
z2 = cmp_char.char_map().z2
msg = 'Could not find x, y, z1 and z2 values for characteristic map, using defaults instead.'
logging.warning(msg)
char_map = cmp_char.char_map(x=x, y=y, z1=z1, z2=z2, method=c[key + '_method'], comp=instance.component())
dc = hlp.dc_cm(is_set=c[key + '_set'],
method=c[key + '_method'],
param=c[key + '_param'],
func=char_map,
x=x, y=y, z1=z1, z2=z2)
kwargs[key] = dc
# grouped component parameters
elif isinstance(value, hlp.dc_gcp):
dc = hlp.dc_gcp(method=c[key])
kwargs[key] = dc
instance.set_attr(**kwargs)
return instance