8000 Add composition to columns in the dataframe by raphaeltimbo · Pull Request #43 · petrobras/ccp · GitHub
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Add composition to columns in the dataframe #43

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Add composition to columns in the dataframe #43

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49 changes: 44 additions & 5 deletions ccp/evaluation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,11 @@ def __init__(
- Suction temperature: should be 'Ts' (degK) in the DataFrame;
- Discharge temperature: should be 'Td' (degK) in the DataFrame;
- Speed: should be 'speed' (rad/s) in the DataFrame.
operation_fluid : dict, list
Dictionary with constituent and composition.
(e.g.: fluid={'Oxygen': 0.2096, 'Nitrogen': 0.7812, 'Argon': 0.0092})
or list with the constituents, in this case the constituents will be
columns in the data DataFrame.
window : int, optional
Window size for rolling calculation, meaning how many rolls will be used
to calculate the fluctuation.
Expand Down Expand Up @@ -92,6 +97,27 @@ def __init__(
self.impellers_new = kwargs.get("impellers_new")
self.df = kwargs.get("df")

def get_composition(self, row):
"""Get composition from row.

Parameters
----------
row : pandas.Series
Row from DataFrame.

Returns
-------
dict
Dictionary with composition.
"""
if isinstance(self.operation_fluid, list):
composition = {}
for key in self.operation_fluid:
composition[key] = row[key]
else:
composition = self.operation_fluid
return composition

def _run(self):
df = self.data.copy()
df = filter_data(
Expand All @@ -107,11 +133,12 @@ def _run(self):
df["v_s"] = 0
df["speed_sound"] = 0
for i, row in df.iterrows():
fluid = self.get_composition(row)
# create state
state = State(
p=Q_(row.ps, self.data_units["ps"]),
T=Q_(row.Ts, self.data_units["Ts"]),
fluid=self.operation_fluid,
fluid=fluid,
)
df.loc[i, "v_s"] = state.v().m
df.loc[i, "speed_sound"] = state.speed_sound().m
Expand Down Expand Up @@ -161,10 +188,11 @@ def _run(self):
print("Converting curves")
for i in tqdm(range(kmeans.n_clusters)):
cluster_series = df[df["cluster"] == 0].iloc[0]
fluid = self.get_composition(cluster_series)
suc_new = State(
p=Q_(cluster_series.ps_center, self.data_units["ps"]),
T=Q_(cluster_series.Ts_center, self.data_units["Ts"]),
fluid=self.operation_fluid,
fluid=fluid,
)
imp_new = Impeller.convert_from(self.impellers, suc=suc_new, speed="same")
self.impellers_new.append(imp_new)
Expand All @@ -176,19 +204,20 @@ def _run(self):

args_list = []
for i, row in df.iterrows():
fluid = self.get_composition(row)
# calculate point
arg_dict = {
"flow_m": row.flow_m,
"speed": Q_(row.speed, self.data_units["speed"]),
"suc": State(
p=Q_(row.ps, self.data_units["ps"]),
T=Q_(row.Ts, self.data_units["Ts"]),
fluid=self.operation_fluid,
fluid=fluid,
),
"disch": State(
p=Q_(row.pd, self.data_units["pd"]),
T=Q_(row.Td, self.data_units["Td"]),
fluid=self.operation_fluid,
fluid=fluid,
),
"imp_new": self.impellers_new[int(row.cluster)],
}
Expand Down Expand Up @@ -323,4 +352,14 @@ def get_interpolated_point(x):
expected_point = imp_new.point(flow_m=x["flow_m"], speed=x["speed"])
except:
print("Error for expected point with args:", x)
return expected_point
# return a dummy point in case of error
expected_point = Point(
suc=State(p=Q_(1, "bar"), T=Q_(50, "degC"), fluid={"co2": 1}),
disch=State(p=Q_(2, "bar"), T=Q_(100, "degC"), fluid={"co2": 1}),
flow_v=1,
speed=1,
)
expected_point.eff = np.nan
expected_point.head = np.nan
expected_point.power = np.nan
return expected_point
0