def test_char_map_number_of_dimensions():
cmp_char.char_map(x=[0, 1, 2], y=[[1, 2, 3, 4], [1, 2, 3, 4]])
def test_char_map_missing_key():
cmp_char.char_map(a=6)
def test_char_map_number_of_points():
cmp_char.char_map(x=[0, 1, 2], y=[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3]])
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
