def document_connection_params(nw, df, c):
"""Document parameter specification of connections.
Parameters
----------
nw : tespy.networks.network.Network
Network object for unit information.
df : pandas.core.frame.DataFrame
DataFrame containing the connection parameter data.
c : tespy.connections.connection.Connection
Connection object, required for LaTeX equation generation.
Returns
-------
latex : str
LaTeX code for all connections.
"""
label = 'Specified connection parameters'
latex = r'\subsection{' + label + '}' + '\n\n'
equations = ''
for col in df.columns:
if col == 'label':
continue
equations += generate_latex_eq(c, fpd[col]['latex_eq'],
fpd[col]['text']) + '\n\n'
col_header = (col.replace('_', r'\_') + ' in ' +
hlp.latex_unit(nw.get_attr(col + '_unit')) + ' ('
r'\ref{eq:Connection_' + fpd[col]['text'] + '})')
df.rename(columns={col: col_header}, inplace=True)
latex += create_latex_table(df, label)
latex += r'\subsection{Equations applied}' + '\n\n'
latex += equations
return latex
def document_connection_params(nw, df, specs, eqs, c, rpt):
"""Document parameter specification of connections.
Parameters
----------
nw : tespy.networks.network.Network
Network object for unit information.
df : pandas.core.frame.DataFrame
DataFrame containing the connection parameter data.
specs : pandas.core.frame.DataFrame
DataFrame containing information on model input specifications.
eqs : list
List of parameters to generate equations for.
c : tespy.connections.connection.Connection
Connection object, required for LaTeX equation generation.
rpt : dict
Formatting data for the report.
Returns
-------
latex : str
LaTeX code for all connections.
"""
if rpt['include_results']:
label = 'Connection specifications and results'
else:
label = 'Specified connection parameters'
latex = r'\subsection{' + label + '}' + '\n\n'
equations = ''
for col in df.columns:
unit = col + '_unit'
if col == 'Td_bp':
unit = 'T_unit'
col_header = (
col.replace('_', r'\_') + ' in ' +
hlp.latex_unit(nw.get_attr(unit)))
if col in eqs:
col_header += (
r' (\ref{eq:Connection_' + fpd[col]['text'] + '})')
equations += generate_latex_eq(
c, fpd[col]['latex_eq'], fpd[col]['text']) + '\n\n'
for row in df.index:
fmt = rpt['Connection'][col]['float_fmt']
if specs.loc[row, col] and rpt['include_results']:
df.loc[row, col] = r'\bftab ' + fmt.format(df.loc[row, col])
else:
df.loc[row, col] = fmt.format(df.loc[row, col])
df.rename(columns={col: col_header}, inplace=True)
num_col = len(df.columns)
latex += create_latex_table(df, label, col_fmt='l' + num_col * 'r')
latex += r'\subsection{Equations applied}' + '\n\n'
latex += equations
return latex
def document_connections(nw, rpt):
"""Document connection specifications.
Parameters
----------
nw : tespy.networks.network.Network
TESPy model.
rpt : dict
Formatting data for the report.
Returns
-------
latex : str
LaTeX code for all connections.
"""
ref_data = {'m': [], 'p': [], 'h': [], 'T': []}
cols = nw.results['Connection'].columns
conn_data = nw.results['Connection'].copy().loc[:, ~cols.isin(nw.fluids)]
fluid_data = nw.results['Connection'].copy().loc[:, nw.fluids]
specs = nw.specifications['Connection'].copy()
if not rpt['include_results']:
conn_data = conn_data[specs]
fluid_data = fluid_data[specs]
# it is possible to exclude fluid results
elif not rpt['Connection']['fluid']['include_results']:
fluid_data = fluid_data[specs]
ref_spec = nw.specifications['Ref'].dropna(
how='all').dropna(how='all', axis=1)
# get some Connection object for equation generator
c = nw.get_conn(specs.index[0])
for c in nw.get_conn(ref_spec.index):
for param in ref_data.keys():
if c.get_attr(param).ref_set:
ref_dict = {'label': c.label.replace('_', r'\_')}
ref_dict.update(
{'reference':
c.get_attr(param).ref.obj.label.replace('_', r'\_'),
'factor in -': c.get_attr(param).ref.factor,
'delta in ' + hlp.latex_unit(
nw.get_attr(param + '_unit')):
c.get_attr(param).ref.delta})
ref_data[param] += [ref_dict]
latex = r'\section{Connections in ' + nw.mode + ' mode}' + '\n\n'
# if list is empty, all parameters will be included
if len(rpt['Connection']['params']) > 0:
for col in conn_data.columns:
if col not in rpt['Connection']['params'] and not any(specs[col]):
conn_data[col] = np.nan
df = data_to_df(conn_data)
if len(df) > 0:
eqs = df[specs].dropna(how='all').dropna(how='all', axis=1).columns
latex += document_connection_params(nw, df, specs, eqs, c, rpt)
df = data_to_df(fluid_data)
if len(df) > 0:
eqs = df[specs].dropna(how='all').dropna(how='all', axis=1).columns
latex += document_connection_fluids(df, specs, eqs, c, rpt)
for property, data in ref_data.items():
df = data_to_df(data)
if len(df) > 0:
latex += document_connection_ref(df, property, c)
return latex
def document_connections(nw):
"""Document connection specifications.
Parameters
----------
nw : tespy.networks.network.Network
TESPy model.
Returns
-------
latex : str
LaTeX code for all connections.
"""
conn_data = []
ref_data = {'m': [], 'p': [], 'h': [], 'T': []}
ref_params = ['m', 'p', 'h', 'T']
fluid_data = []
for c in nw.conns.index:
data_dict = {'label': c.label.replace('_', r'\_')}
fluid_dict = data_dict.copy()
data_dict.update({
param: c.get_attr(param).val
for param in fpd.keys() if c.get_attr(param).val_set
})
conn_data += [data_dict]
for param in ref_params:
if c.get_attr(param).ref_set:
ref_dict = {'label': c.label.replace('_', r'\_')}
ref_dict.update({
'reference':
c.get_attr(param).ref.obj.label.replace('_', r'\_'),
'factor in -':
c.get_attr(param).ref.factor,
'delta in ' + hlp.latex_unit(nw.get_attr(param + '_unit')):
c.get_attr(param).ref.delta
})
ref_data[param] += [ref_dict]
fluid_dict.update({
fluid: c.fluid.val[fluid]
for fluid in nw.fluids if c.fluid.val_set[fluid]
})
if c.fluid.balance:
fluid_dict.update({'balance': c.fluid.balance})
fluid_data += [fluid_dict]
latex = r'\section{Connections in ' + nw.mode + ' mode}' + '\n\n'
df = data_to_df(conn_data)
if len(df) > 0:
latex += document_connection_params(nw, df, c)
df = data_to_df(fluid_data)
if len(df) > 0:
latex += document_connection_fluids(df, c)
for property, data in ref_data.items():
df = data_to_df(data)
if len(df) > 0:
latex += document_connection_ref(df, property, c)
return latex