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openego/ding0 | ding0/grid/lv_grid/build_grid.py | select_grid_model_ria | def select_grid_model_ria(lvgd, sector):
"""Select a typified grid for retail/industrial and agricultural
Parameters
----------
lvgd : ding0.core.structure.regions.LVGridDistrictDing0
Low-voltage grid district object
sector : str
Either 'retail/industrial' or 'agricultural'. Dependi... | python | def select_grid_model_ria(lvgd, sector):
"""Select a typified grid for retail/industrial and agricultural
Parameters
----------
lvgd : ding0.core.structure.regions.LVGridDistrictDing0
Low-voltage grid district object
sector : str
Either 'retail/industrial' or 'agricultural'. Dependi... | [
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openego/ding0 | ding0/grid/lv_grid/build_grid.py | grid_model_params_ria | def grid_model_params_ria(lvgd):
"""Determine grid model parameters for LV grids of sectors
retail/industrial and agricultural
Parameters
----------
lvgd : LVGridDistrictDing0
Low-voltage grid district object
Returns
-------
:obj:`dict`
Structural description of (pa... | python | def grid_model_params_ria(lvgd):
"""Determine grid model parameters for LV grids of sectors
retail/industrial and agricultural
Parameters
----------
lvgd : LVGridDistrictDing0
Low-voltage grid district object
Returns
-------
:obj:`dict`
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openego/ding0 | ding0/grid/lv_grid/build_grid.py | build_lv_graph_ria | def build_lv_graph_ria(lvgd, grid_model_params):
"""Build graph for LV grid of sectors retail/industrial and agricultural
Based on structural description of LV grid topology for sectors
retail/industrial and agricultural (RIA) branches for these sectors are
created and attached to the LV grid's MV-LV s... | python | def build_lv_graph_ria(lvgd, grid_model_params):
"""Build graph for LV grid of sectors retail/industrial and agricultural
Based on structural description of LV grid topology for sectors
retail/industrial and agricultural (RIA) branches for these sectors are
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openego/ding0 | ding0/grid/lv_grid/build_grid.py | select_grid_model_residential | def select_grid_model_residential(lvgd):
"""Selects typified model grid based on population
Parameters
----------
lvgd : LVGridDistrictDing0
Low-voltage grid district object
Returns
-------
:pandas:`pandas.DataFrame<dataframe>`
Selected string of typified model grid
:pa... | python | def select_grid_model_residential(lvgd):
"""Selects typified model grid based on population
Parameters
----------
lvgd : LVGridDistrictDing0
Low-voltage grid district object
Returns
-------
:pandas:`pandas.DataFrame<dataframe>`
Selected string of typified model grid
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openego/ding0 | ding0/grid/lv_grid/build_grid.py | build_lv_graph_residential | def build_lv_graph_residential(lvgd, selected_string_df):
"""Builds nxGraph based on the LV grid model
Parameters
----------
lvgd : LVGridDistrictDing0
Low-voltage grid district object
selected_string_df: :pandas:`pandas.DataFrame<dataframe>`
Table of strings of the selected grid mo... | python | def build_lv_graph_residential(lvgd, selected_string_df):
"""Builds nxGraph based on the LV grid model
Parameters
----------
lvgd : LVGridDistrictDing0
Low-voltage grid district object
selected_string_df: :pandas:`pandas.DataFrame<dataframe>`
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lvgd : LVGridDistrictDing0
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openego/ding0 | ding0/grid/lv_grid/build_grid.py | build_residential_branches | def build_residential_branches(lvgd):
"""Based on population and identified peak load data, the according grid
topology for residential sector is determined and attached to the grid graph
Parameters
----------
lvgd : LVGridDistrictDing0
Low-voltage grid district object
"""
# Choice... | python | def build_residential_branches(lvgd):
"""Based on population and identified peak load data, the according grid
topology for residential sector is determined and attached to the grid graph
Parameters
----------
lvgd : LVGridDistrictDing0
Low-voltage grid district object
"""
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Low-voltage grid district object | [
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openego/ding0 | ding0/tools/results.py | lv_grid_generators_bus_bar | def lv_grid_generators_bus_bar(nd):
"""
Calculate statistics about generators at bus bar in LV grids
Parameters
----------
nd : ding0.NetworkDing0
Network container object
Returns
-------
lv_stats : dict
Dict with keys of LV grid repr() on first level. Each of the grids... | python | def lv_grid_generators_bus_bar(nd):
"""
Calculate statistics about generators at bus bar in LV grids
Parameters
----------
nd : ding0.NetworkDing0
Network container object
Returns
-------
lv_stats : dict
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openego/ding0 | ding0/tools/results.py | save_nd_to_pickle | def save_nd_to_pickle(nd, path='', filename=None):
"""Use pickle to save the whole nd-object to disc
The network instance is entirely pickled to a file.
Parameters
----------
nd : NetworkDing0
Ding0 grid container object
path : str
Absolute or relative path where pickle should ... | python | def save_nd_to_pickle(nd, path='', filename=None):
"""Use pickle to save the whole nd-object to disc
The network instance is entirely pickled to a file.
Parameters
----------
nd : NetworkDing0
Ding0 grid container object
path : str
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openego/ding0 | ding0/tools/results.py | load_nd_from_pickle | def load_nd_from_pickle(filename=None, path=''):
"""
Use pickle to save the whole nd-object to disc
Parameters
----------
filename : str
Filename of nd pickle
path : str
Absolute or relative path where pickle should be saved. Default is ''
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"""
Use pickle to save the whole nd-object to disc
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filename : str
Filename of nd pickle
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Absolute or relative path where pickle should be saved. Default is ''
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openego/ding0 | ding0/tools/results.py | plot_cable_length | def plot_cable_length(stats, plotpath):
"""
Cable length per MV grid district
"""
# cable and line kilometer distribution
f, axarr = plt.subplots(2, 2, sharex=True)
stats.hist(column=['Length of MV overhead lines'], bins=5, alpha=0.5, ax=axarr[0, 0])
stats.hist(column=['Length of MV undergr... | python | def plot_cable_length(stats, plotpath):
"""
Cable length per MV grid district
"""
# cable and line kilometer distribution
f, axarr = plt.subplots(2, 2, sharex=True)
stats.hist(column=['Length of MV overhead lines'], bins=5, alpha=0.5, ax=axarr[0, 0])
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openego/ding0 | ding0/tools/results.py | plot_generation_over_load | def plot_generation_over_load(stats, plotpath):
"""
Plot of generation over load
"""
# Generation capacity vs. peak load
sns.set_context("paper", font_scale=1.1)
sns.set_style("ticks")
# reformat to MW
gen_cap_indexes = ["Gen. Cap. of MV at v_level 4",
"Gen. Cap... | python | def plot_generation_over_load(stats, plotpath):
"""
Plot of generation over load
"""
# Generation capacity vs. peak load
sns.set_context("paper", font_scale=1.1)
sns.set_style("ticks")
# reformat to MW
gen_cap_indexes = ["Gen. Cap. of MV at v_level 4",
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openego/ding0 | ding0/tools/results.py | concat_nd_pickles | def concat_nd_pickles(self, mv_grid_districts):
"""
Read multiple pickles, join nd objects and save to file
Parameters
----------
mv_grid_districts : list
Ints describing MV grid districts
"""
pickle_name = cfg_ding0.get('output', 'nd_pickle')
# self.nd = self.read_pickles_from... | python | def concat_nd_pickles(self, mv_grid_districts):
"""
Read multiple pickles, join nd objects and save to file
Parameters
----------
mv_grid_districts : list
Ints describing MV grid districts
"""
pickle_name = cfg_ding0.get('output', 'nd_pickle')
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openego/ding0 | ding0/tools/results.py | calculate_lvgd_stats | def calculate_lvgd_stats(nw):
"""
LV Statistics for an arbitrary network
Parameters
----------
nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
Returns
-------
lvgd_stats : pandas.DataFrame
Dataframe containing several statistical numbers about the LVGD
... | python | def calculate_lvgd_stats(nw):
"""
LV Statistics for an arbitrary network
Parameters
----------
nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
Returns
-------
lvgd_stats : pandas.DataFrame
Dataframe containing several statistical numbers about the LVGD
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openego/ding0 | ding0/tools/results.py | calculate_mvgd_stats | def calculate_mvgd_stats(nw):
"""
MV Statistics for an arbitrary network
Parameters
----------
nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
Returns
-------
mvgd_stats : pandas.DataFrame
Dataframe containing several statistical numbers about the MVGD
... | python | def calculate_mvgd_stats(nw):
"""
MV Statistics for an arbitrary network
Parameters
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nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
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-------
mvgd_stats : pandas.DataFrame
Dataframe containing several statistical numbers about the MVGD
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openego/ding0 | ding0/tools/results.py | calculate_mvgd_voltage_current_stats | def calculate_mvgd_voltage_current_stats(nw):
"""
MV Voltage and Current Statistics for an arbitrary network
Parameters
----------
nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
Returns
-------
pandas.DataFrame
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"""
MV Voltage and Current Statistics for an arbitrary network
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----------
nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
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openego/ding0 | ding0/tools/results.py | calculate_lvgd_voltage_current_stats | def calculate_lvgd_voltage_current_stats(nw):
"""
LV Voltage and Current Statistics for an arbitrary network
Note
----
Aggregated Load Areas are excluded.
Parameters
----------
nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
Returns
-------
pandas.Data... | python | def calculate_lvgd_voltage_current_stats(nw):
"""
LV Voltage and Current Statistics for an arbitrary network
Note
----
Aggregated Load Areas are excluded.
Parameters
----------
nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
Returns
-------
pandas.Data... | [
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openego/ding0 | ding0/tools/results.py | init_mv_grid | def init_mv_grid(mv_grid_districts=[3545], filename='ding0_tests_grids_1.pkl'):
'''Runs ding0 over the districtis selected in mv_grid_districts
It also writes the result in filename. If filename = False,
then the network is not saved.
Parameters
----------
mv_grid_districts: :any:`list` of :ob... | python | def init_mv_grid(mv_grid_districts=[3545], filename='ding0_tests_grids_1.pkl'):
'''Runs ding0 over the districtis selected in mv_grid_districts
It also writes the result in filename. If filename = False,
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openego/ding0 | ding0/tools/results.py | process_stats | def process_stats(mv_districts,
n_of_districts,
source,
mode,
critical,
filename,
output):
'''Generates stats dataframes for districts in mv_districts.
If source=='ding0', then runned districts are saved... | python | def process_stats(mv_districts,
n_of_districts,
source,
mode,
critical,
filename,
output):
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openego/ding0 | ding0/tools/results.py | parallel_running_stats | def parallel_running_stats(districts_list,
n_of_processes,
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critical=False,
save_csv=False,
... | python | def parallel_running_stats(districts_list,
n_of_processes,
n_of_districts=1,
source='pkl',
mode='',
critical=False,
save_csv=False,
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openego/ding0 | ding0/tools/results.py | export_network | def export_network(nw, mode=''):
"""
Export all nodes and lines of the network nw as DataFrames
Parameters
----------
nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
mode: str
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"""
Export all nodes and lines of the network nw as DataFrames
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nw: :any:`list` of NetworkDing0
The MV grid(s) to be studied
mode: str
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openego/ding0 | ding0/examples/example_analyze_multiple_grid_districts.py | ding0_exemplary_plots | def ding0_exemplary_plots(stats, base_path=BASEPATH):
"""
Analyze multiple grid district data generated with Ding0.
Parameters
----------
stats : pandas.DataFrame
Statistics of each MV grid districts
base_path : str
Root directory of Ding0 data structure, i.e. '~/.ding0' (which ... | python | def ding0_exemplary_plots(stats, base_path=BASEPATH):
"""
Analyze multiple grid district data generated with Ding0.
Parameters
----------
stats : pandas.DataFrame
Statistics of each MV grid districts
base_path : str
Root directory of Ding0 data structure, i.e. '~/.ding0' (which ... | [
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openego/ding0 | ding0/examples/example_analyze_multiple_grid_districts.py | nd_load_and_stats | def nd_load_and_stats(filenames, base_path=BASEPATH):
"""
Load multiple files from disk and generate stats
Passes the list of files assuming the ding0 data structure as default in
:code:`~/.ding0`.
Data will be concatenated and key indicators for each grid district are
returned in table and gra... | python | def nd_load_and_stats(filenames, base_path=BASEPATH):
"""
Load multiple files from disk and generate stats
Passes the list of files assuming the ding0 data structure as default in
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openego/ding0 | ding0/flexopt/reinforce_measures.py | reinforce_branches_current | def reinforce_branches_current(grid, crit_branches):
#TODO: finish docstring
""" Reinforce MV or LV grid by installing a new branch/line type
Parameters
----------
grid : GridDing0
Grid identifier.
crit_branches : dict
Dict of critical branches with max. relative overloading... | python | def reinforce_branches_current(grid, crit_branches):
#TODO: finish docstring
""" Reinforce MV or LV grid by installing a new branch/line type
Parameters
----------
grid : GridDing0
Grid identifier.
crit_branches : dict
Dict of critical branches with max. relative overloading... | [
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openego/ding0 | ding0/flexopt/reinforce_measures.py | reinforce_branches_voltage | def reinforce_branches_voltage(grid, crit_branches, grid_level='MV'):
#TODO: finish docstring
""" Reinforce MV or LV grid by installing a new branch/line type
Parameters
----------
grid : GridDing0
Grid identifier.
crit_branches : :any:`list` of :obj:`int`
List of critical branc... | python | def reinforce_branches_voltage(grid, crit_branches, grid_level='MV'):
#TODO: finish docstring
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Parameters
----------
grid : GridDing0
Grid identifier.
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openego/ding0 | ding0/flexopt/reinforce_measures.py | extend_substation | def extend_substation(grid, critical_stations, grid_level):
"""
Reinforce MV or LV substation by exchanging the existing trafo and
installing a parallel one if necessary.
First, all available transformers in a `critical_stations` are extended to
maximum power. If this does not solve all present iss... | python | def extend_substation(grid, critical_stations, grid_level):
"""
Reinforce MV or LV substation by exchanging the existing trafo and
installing a parallel one if necessary.
First, all available transformers in a `critical_stations` are extended to
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openego/ding0 | ding0/flexopt/reinforce_measures.py | extend_substation_voltage | def extend_substation_voltage(crit_stations, grid_level='LV'):
"""
Extend substation if voltage issues at the substation occur
Follows a two-step procedure:
i) Existing transformers are extended by replacement with large nominal
apparent power
ii) New additional transformers adde... | python | def extend_substation_voltage(crit_stations, grid_level='LV'):
"""
Extend substation if voltage issues at the substation occur
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i) Existing transformers are extended by replacement with large nominal
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openego/ding0 | ding0/flexopt/reinforce_measures.py | reinforce_lv_branches_overloading | def reinforce_lv_branches_overloading(grid, crit_branches):
"""
Choose appropriate cable type for branches with line overloading
Parameters
----------
grid : LVGridDing0
Ding0 LV grid object
crit_branches : :any:`list`
List of critical branches incl. its line loading
Notes
... | python | def reinforce_lv_branches_overloading(grid, crit_branches):
"""
Choose appropriate cable type for branches with line overloading
Parameters
----------
grid : LVGridDing0
Ding0 LV grid object
crit_branches : :any:`list`
List of critical branches incl. its line loading
Notes
... | [
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openego/ding0 | ding0/flexopt/reinforce_measures.py | extend_trafo_power | def extend_trafo_power(extendable_trafos, trafo_params):
"""
Extend power of first trafo in list of extendable trafos
Parameters
----------
extendable_trafos : :any:`list`
Trafos with rated power below maximum size available trafo
trafo_params : :pandas:`pandas.DataFrame<dataframe>`
... | python | def extend_trafo_power(extendable_trafos, trafo_params):
"""
Extend power of first trafo in list of extendable trafos
Parameters
----------
extendable_trafos : :any:`list`
Trafos with rated power below maximum size available trafo
trafo_params : :pandas:`pandas.DataFrame<dataframe>`
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.add_generator | def add_generator(self, generator):
"""Adds a generator to _generators and grid graph if not already existing
Parameters
----------
generator : GridDing0
Description #TODO
"""
if generator not in self._generators and isinstance(generator,
... | python | def add_generator(self, generator):
"""Adds a generator to _generators and grid graph if not already existing
Parameters
----------
generator : GridDing0
Description #TODO
"""
if generator not in self._generators and isinstance(generator,
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.graph_add_node | def graph_add_node(self, node_object):
"""Adds a station or cable distributor object to grid graph if not already existing
Parameters
----------
node_object : GridDing0
Description #TODO
"""
if ((node_object not in self._graph.nodes()) and
... | python | def graph_add_node(self, node_object):
"""Adds a station or cable distributor object to grid graph if not already existing
Parameters
----------
node_object : GridDing0
Description #TODO
"""
if ((node_object not in self._graph.nodes()) and
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.graph_draw | def graph_draw(self, mode):
""" Draws grid graph using networkx
This method is for debugging purposes only.
Use ding0.tools.plots.plot_mv_topology() for advanced plotting.
Parameters
----------
mode : str
Mode selection 'MV' or 'LV'.
Not... | python | def graph_draw(self, mode):
""" Draws grid graph using networkx
This method is for debugging purposes only.
Use ding0.tools.plots.plot_mv_topology() for advanced plotting.
Parameters
----------
mode : str
Mode selection 'MV' or 'LV'.
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.graph_nodes_sorted | def graph_nodes_sorted(self):
""" Returns an (ascending) sorted list of graph's nodes (name is used as key).
Returns
-------
:any:`list`
Description #TODO check
"""
return sorted(self._graph.nodes(), key=lambda _: repr(_)) | python | def graph_nodes_sorted(self):
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Returns
-------
:any:`list`
Description #TODO check
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.graph_nodes_from_branch | def graph_nodes_from_branch(self, branch):
""" Returns nodes that are connected by `branch`
Args
----
branch: BranchDing0
Description #TODO
Returns
-------
(:obj:`GridDing0`, :obj:`GridDing0`)
2-tuple of nodes (Ding0 objec... | python | def graph_nodes_from_branch(self, branch):
""" Returns nodes that are connected by `branch`
Args
----
branch: BranchDing0
Description #TODO
Returns
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(:obj:`GridDing0`, :obj:`GridDing0`)
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.graph_branches_from_node | def graph_branches_from_node(self, node):
""" Returns branches that are connected to `node`
Args
----
node: GridDing0
Ding0 object (member of graph)
Returns
-------
:any:`list`
List of tuples (node in :obj:`GridDing0`, branch in :... | python | def graph_branches_from_node(self, node):
""" Returns branches that are connected to `node`
Args
----
node: GridDing0
Ding0 object (member of graph)
Returns
-------
:any:`list`
List of tuples (node in :obj:`GridDing0`, branch in :... | [
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.graph_edges | def graph_edges(self):
""" Returns a generator for iterating over graph edges
The edge of a graph is described by the two adjacent node and the branch
object itself. Whereas the branch object is used to hold all relevant
power system parameters.
Yields
------
in... | python | def graph_edges(self):
""" Returns a generator for iterating over graph edges
The edge of a graph is described by the two adjacent node and the branch
object itself. Whereas the branch object is used to hold all relevant
power system parameters.
Yields
------
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.find_path | def find_path(self, node_source, node_target, type='nodes'):
"""Determines shortest path
Determines the shortest path from `node_source` to
`node_target` in _graph using networkx' shortest path
algorithm.
Args
----
node_source: GridDing0
source node,... | python | def find_path(self, node_source, node_target, type='nodes'):
"""Determines shortest path
Determines the shortest path from `node_source` to
`node_target` in _graph using networkx' shortest path
algorithm.
Args
----
node_source: GridDing0
source node,... | [
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.find_and_union_paths | def find_and_union_paths(self, node_source, nodes_target):
""" Determines shortest paths from `node_source` to all nodes in `node_target` in _graph using find_path().
The branches of all paths are stored in a set - the result is a list of unique branches.
Args
----
node_source:... | python | def find_and_union_paths(self, node_source, nodes_target):
""" Determines shortest paths from `node_source` to all nodes in `node_target` in _graph using find_path().
The branches of all paths are stored in a set - the result is a list of unique branches.
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----
node_source:... | [
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.graph_path_length | def graph_path_length(self, node_source, node_target):
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Args
----
node_source: GridDing0
source node, member of _graph
node_target:... | python | def graph_path_length(self, node_source, node_target):
""" Calculates the absolute distance between `node_source` and `node_target` in meters using find_path() and branches' length attribute.
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----
node_source: GridDing0
source node, member of _graph
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openego/ding0 | ding0/core/network/__init__.py | GridDing0.graph_isolated_nodes | def graph_isolated_nodes(self):
""" Finds isolated nodes = nodes with no neighbors (degree zero)
Returns
-------
:any:`list` of :obj:`GridDing0`
List of nodes (Ding0 objects)
"""
return sorted(nx.isolates(self._graph), key=lambda x: repr(x)) | python | def graph_isolated_nodes(self):
""" Finds isolated nodes = nodes with no neighbors (degree zero)
Returns
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:any:`list` of :obj:`GridDing0`
List of nodes (Ding0 objects)
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openego/ding0 | ding0/core/network/__init__.py | StationDing0.add_transformer | def add_transformer(self, transformer):
"""Adds a transformer to _transformers if not already existing
Args
----
transformer : StationDing0
Description #TODO
"""
if transformer not in self.transformers() and isinstance(transformer, TransformerDing0):
... | python | def add_transformer(self, transformer):
"""Adds a transformer to _transformers if not already existing
Args
----
transformer : StationDing0
Description #TODO
"""
if transformer not in self.transformers() and isinstance(transformer, TransformerDing0):
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openego/ding0 | ding0/core/network/__init__.py | RingDing0.branches | def branches(self):
""" #TODO: description
"""
for branch in self._grid.graph_edges():
if branch['branch'].ring == self:
yield branch | python | def branches(self):
""" #TODO: description
"""
for branch in self._grid.graph_edges():
if branch['branch'].ring == self:
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openego/ding0 | ding0/core/network/__init__.py | RingDing0.lv_load_areas | def lv_load_areas(self):
""" #TODO: description
"""
for lv_load_area in self._grid._graph.nodes():
if isinstance(lv_load_area, LVLoadAreaDing0):
if lv_load_area.ring == self:
yield lv_load_area | python | def lv_load_areas(self):
""" #TODO: description
"""
for lv_load_area in self._grid._graph.nodes():
if isinstance(lv_load_area, LVLoadAreaDing0):
if lv_load_area.ring == self:
yield lv_load_area | [
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openego/ding0 | ding0/core/network/__init__.py | CircuitBreakerDing0.open | def open(self):
""" Open a Circuit Breaker #TODO Check
"""
self.branch_nodes = self.grid.graph_nodes_from_branch(self.branch)
self.grid._graph.remove_edge(self.branch_nodes[0], self.branch_nodes[1])
self.status = 'open' | python | def open(self):
""" Open a Circuit Breaker #TODO Check
"""
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openego/ding0 | ding0/core/network/__init__.py | CircuitBreakerDing0.close | def close(self):
""" Close a Circuit Breaker #TODO Check
"""
self.grid._graph.add_edge(self.branch_nodes[0], self.branch_nodes[1], branch=self.branch)
self.status = 'closed' | python | def close(self):
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openego/ding0 | ding0/core/structure/regions.py | MVGridDistrictDing0.lv_load_areas | def lv_load_areas(self):
"""Returns a generator for iterating over load_areas
Yields
------
int
generator for iterating over load_areas
"""
for load_area in sorted(self._lv_load_areas, key=lambda _: repr(_)):
yield load_area | python | def lv_load_areas(self):
"""Returns a generator for iterating over load_areas
Yields
------
int
generator for iterating over load_areas
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openego/ding0 | ding0/core/structure/regions.py | MVGridDistrictDing0.add_lv_load_area | def add_lv_load_area(self, lv_load_area):
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Args
----
lv_load_area: LVLoadAreaDing0
instance of class LVL... | python | def add_lv_load_area(self, lv_load_area):
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----
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openego/ding0 | ding0/core/structure/regions.py | MVGridDistrictDing0.add_lv_load_area_group | def add_lv_load_area_group(self, lv_load_area_group):
"""Adds a LV load_area to _lv_load_areas if not already existing.
"""
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self._lv_load_area_groups.append(lv_load_area_group) | python | def add_lv_load_area_group(self, lv_load_area_group):
"""Adds a LV load_area to _lv_load_areas if not already existing.
"""
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openego/ding0 | ding0/core/structure/regions.py | MVGridDistrictDing0.add_peak_demand | def add_peak_demand(self):
"""Summarizes peak loads of underlying load_areas in kVA.
(peak load sum and peak load of satellites)
"""
peak_load = peak_load_satellites = 0
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peak_load += lv_load_area.peak_load
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"""Summarizes peak loads of underlying load_areas in kVA.
(peak load sum and peak load of satellites)
"""
peak_load = peak_load_satellites = 0
for lv_load_area in self.lv_load_areas():
peak_load += lv_load_area.peak_load
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openego/ding0 | ding0/core/structure/regions.py | MVGridDistrictDing0.add_aggregated_peak_demand | def add_aggregated_peak_demand(self):
"""Summarizes peak loads of underlying aggregated load_areas"""
peak_load_aggregated = 0
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if lv_load_area.is_aggregated:
peak_load_aggregated += lv_load_area.peak_load
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"""Summarizes peak loads of underlying aggregated load_areas"""
peak_load_aggregated = 0
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if lv_load_area.is_aggregated:
peak_load_aggregated += lv_load_area.peak_load
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openego/ding0 | ding0/core/structure/regions.py | LVLoadAreaDing0.lv_grid_districts | def lv_grid_districts(self):
"""Returns a generator for iterating over LV grid districts
Yields
------
int
generator for iterating over LV grid districts
"""
for lv_grid_district in sorted(self._lv_grid_districts, key=lambda _: repr(_)):
y... | python | def lv_grid_districts(self):
"""Returns a generator for iterating over LV grid districts
Yields
------
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generator for iterating over LV grid districts
"""
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openego/ding0 | ding0/core/structure/regions.py | LVLoadAreaDing0.add_lv_grid_district | def add_lv_grid_district(self, lv_grid_district):
# TODO: check docstring
"""Adds a LV grid district to _lv_grid_districts if not already existing
Args
----
lv_grid_district: :shapely:`Shapely Polygon object<polygons>`
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# TODO: check docstring
"""Adds a LV grid district to _lv_grid_districts if not already existing
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lv_grid_district: :shapely:`Shapely Polygon object<polygons>`
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openego/ding0 | ding0/core/structure/regions.py | LVLoadAreaDing0.peak_generation | def peak_generation(self):
"""Cumulative peak generation of generators connected to LV grids of
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"""
cum_peak_generation = 0
for lv_grid_district in self._lv_grid_districts:
cum_peak_generation += lv_grid_district.lv_grid.station().peak_generation
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"""Cumulative peak generation of generators connected to LV grids of
underlying LVGDs
"""
cum_peak_generation = 0
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cum_peak_generation += lv_grid_district.lv_grid.station().peak_generation
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openego/ding0 | ding0/grid/mv_grid/solvers/base.py | BaseSolution.get_pair | def get_pair(self, pair):
"""get pair description
Parameters
----------
pair : :any:`list` of nodes
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Returns
-------
type
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"""
i, j = pair
return (self._nodes[i.name()], self._nodes[j.... | python | def get_pair(self, pair):
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Parameters
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pair : :any:`list` of nodes
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openego/ding0 | ding0/grid/mv_grid/solvers/base.py | BaseSolution.is_complete | def is_complete(self):
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Returns
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True if all nodes are llocated.
"""
return all(
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openego/ding0 | ding0/grid/mv_grid/solvers/base.py | BaseSolution.clone | def clone(self):
"""Returns a deep copy of self
Function clones:
* route
* allocation
* nodes
Returns
-------
type
Deep copy of self
"""
new_solution = self.__class__(self._problem, len(self._routes))
... | python | def clone(self):
"""Returns a deep copy of self
Function clones:
* route
* allocation
* nodes
Returns
-------
type
Deep copy of self
"""
new_solution = self.__class__(self._problem, len(self._routes))
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openego/ding0 | ding0/grid/mv_grid/solvers/base.py | BaseSolution.length | def length(self):
"""Returns the solution length (or cost)
Returns
-------
float
Solution length (or cost).
"""
length = 0
for r in self._routes:
length = length + r.length()
return length | python | def length(self):
"""Returns the solution length (or cost)
Returns
-------
float
Solution length (or cost).
"""
length = 0
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openego/ding0 | ding0/grid/mv_grid/solvers/base.py | BaseSolution.draw_network | def draw_network(self, anim):
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Parameters
----------
AnimationDing0
AnimationDing0 object
"""
g = nx.Graph()
ntemp = []
nodes_pos = {}
demands = {}
demands_pos = {}
... | python | def draw_network(self, anim):
"""Draws solution's graph using networkx
Parameters
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AnimationDing0
AnimationDing0 object
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openego/ding0 | ding0/tools/geo.py | calc_geo_branches_in_polygon | def calc_geo_branches_in_polygon(mv_grid, polygon, mode, proj):
""" Calculate geographical branches in polygon.
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openego/ding0 | ding0/tools/geo.py | calc_geo_branches_in_buffer | def calc_geo_branches_in_buffer(node, mv_grid, radius, radius_inc, proj):
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openego/ding0 | ding0/tools/geo.py | calc_geo_dist_vincenty | def calc_geo_dist_vincenty(node_source, node_target):
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incorporating the detour factor specified in :file:`ding0/ding0/config/config_calc.cfg`.
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openego/ding0 | ding0/tools/geo.py | calc_geo_dist_matrix_vincenty | def calc_geo_dist_matrix_vincenty(nodes_pos):
""" Calculates the geodesic distance between all nodes in `nodes_pos` incorporating the detour factor in config_calc.cfg.
For every two points/coord it uses geopy's vincenty function (formula devised by Thaddeus Vincenty,
with an accurate ellipsoidal m... | python | def calc_geo_dist_matrix_vincenty(nodes_pos):
""" Calculates the geodesic distance between all nodes in `nodes_pos` incorporating the detour factor in config_calc.cfg.
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openego/ding0 | ding0/tools/geo.py | calc_geo_centre_point | def calc_geo_centre_point(node_source, node_target):
""" Calculates the geodesic distance between `node_source` and `node_target`
incorporating the detour factor specified in config_calc.cfg.
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node_source: LVStationDing0, GeneratorDing0, or CableDistributorDing0
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openego/ding0 | ding0/grid/mv_grid/mv_connect.py | find_nearest_conn_objects | def find_nearest_conn_objects(node_shp, branches, proj, conn_dist_weight, debug, branches_only=False):
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openego/ding0 | ding0/grid/mv_grid/mv_connect.py | find_connection_point | def find_connection_point(node, node_shp, graph, proj, conn_objects_min_stack, conn_dist_ring_mod, debug):
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openego/ding0 | ding0/grid/mv_grid/mv_connect.py | connect_node | def connect_node(node, node_shp, mv_grid, target_obj, proj, graph, conn_dist_ring_mod, debug):
""" Connects `node` to `target_obj`.
Args
----
node: LVLoadAreaCentreDing0, i.e.
Origin node - Ding0 graph object (e.g. LVLoadAreaCentreDing0)
node_shp: :shapely:`Shapely Point object<points>`
... | python | def connect_node(node, node_shp, mv_grid, target_obj, proj, graph, conn_dist_ring_mod, debug):
""" Connects `node` to `target_obj`.
Args
----
node: LVLoadAreaCentreDing0, i.e.
Origin node - Ding0 graph object (e.g. LVLoadAreaCentreDing0)
node_shp: :shapely:`Shapely Point object<points>`
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openego/ding0 | ding0/grid/mv_grid/mv_connect.py | disconnect_node | def disconnect_node(node, target_obj_result, graph, debug):
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----
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Args
----
node: LVLoadAreaCentreDing0, i.e.
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openego/ding0 | ding0/grid/mv_grid/mv_connect.py | parametrize_lines | def parametrize_lines(mv_grid):
""" Set unparametrized branches to default branch type
Args
----
mv_grid: MVGridDing0
MV grid instance
Notes
-----
During the connection process of satellites, new branches are created -
these have to be parametrized.
"""
for branch... | python | def parametrize_lines(mv_grid):
""" Set unparametrized branches to default branch type
Args
----
mv_grid: MVGridDing0
MV grid instance
Notes
-----
During the connection process of satellites, new branches are created -
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openego/ding0 | ding0/grid/mv_grid/mv_connect.py | mv_connect_satellites | def mv_connect_satellites(mv_grid, graph, mode='normal', debug=False):
""" Connect satellites (small Load Areas) to MV grid
Args
----
mv_grid: MVGridDing0
MV grid instance
graph: :networkx:`NetworkX Graph Obj< >`
NetworkX graph object with nodes
mode: str, defaults to 'normal'
... | python | def mv_connect_satellites(mv_grid, graph, mode='normal', debug=False):
""" Connect satellites (small Load Areas) to MV grid
Args
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mv_grid: MVGridDing0
MV grid instance
graph: :networkx:`NetworkX Graph Obj< >`
NetworkX graph object with nodes
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openego/ding0 | ding0/grid/mv_grid/mv_connect.py | mv_connect_stations | def mv_connect_stations(mv_grid_district, graph, debug=False):
""" Connect LV stations to MV grid
Args
----
mv_grid_district: MVGridDistrictDing0
MVGridDistrictDing0 object for which the connection process has to be done
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""" Connect LV stations to MV grid
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----
mv_grid_district: MVGridDistrictDing0
MVGridDistrictDing0 object for which the connection process has to be done
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openego/ding0 | ding0/grid/mv_grid/mv_connect.py | mv_connect_generators | def mv_connect_generators(mv_grid_district, graph, debug=False):
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Args
----
mv_grid_district: MVGridDistrictDing0
MVGridDistrictDing0 object for which the connection process has to be
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Args
----
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MVGridDistrictDing0 object for which the connection process has to be
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openego/ding0 | ding0/grid/mv_grid/mv_routing.py | ding0_graph_to_routing_specs | def ding0_graph_to_routing_specs(graph):
""" Build data dictionary from graph nodes for routing (translation)
Args
----
graph: :networkx:`NetworkX Graph Obj< >`
NetworkX graph object with nodes
Returns
-------
:obj:`dict`
Data dictionary for routing.
See Also
... | python | def ding0_graph_to_routing_specs(graph):
""" Build data dictionary from graph nodes for routing (translation)
Args
----
graph: :networkx:`NetworkX Graph Obj< >`
NetworkX graph object with nodes
Returns
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:obj:`dict`
Data dictionary for routing.
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openego/ding0 | ding0/grid/mv_grid/mv_routing.py | routing_solution_to_ding0_graph | def routing_solution_to_ding0_graph(graph, solution):
""" Insert `solution` from routing into `graph`
Args
----
graph: :networkx:`NetworkX Graph Obj< >`
NetworkX graph object with nodes
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NetworkX graph object with nodes
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openego/ding0 | ding0/grid/mv_grid/mv_routing.py | solve | def solve(graph, debug=False, anim=None):
# TODO: check docstring
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Translate data from node objects to appropriate format before.
Args
----
graph: :networkx:`NetworkX Graph Obj< >`
NetworkX graph object with nodes
debug: bool, defaul... | python | def solve(graph, debug=False, anim=None):
# TODO: check docstring
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openego/ding0 | ding0/grid/tools.py | cable_type | def cable_type(nom_power, nom_voltage, avail_cables):
"""Determine suitable type of cable for given nominal power
Based on maximum occurring current which is derived from nominal power
(either peak load or max. generation capacity) a suitable cable type is
chosen. Thus, no line overloading issues shoul... | python | def cable_type(nom_power, nom_voltage, avail_cables):
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openego/ding0 | ding0/grid/lv_grid/lv_connect.py | lv_connect_generators | def lv_connect_generators(lv_grid_district, graph, debug=False):
""" Connect LV generators to LV grid
Args
----
lv_grid_district: LVGridDistrictDing0
LVGridDistrictDing0 object for which the connection process has to be done
graph: :networkx:`NetworkX Graph Obj< >`
NetworkX gra... | python | def lv_connect_generators(lv_grid_district, graph, debug=False):
""" Connect LV generators to LV grid
Args
----
lv_grid_district: LVGridDistrictDing0
LVGridDistrictDing0 object for which the connection process has to be done
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openego/ding0 | ding0/grid/mv_grid/tools.py | set_circuit_breakers | def set_circuit_breakers(mv_grid, mode='load', debug=False):
""" Calculates the optimal position of a circuit breaker on all routes of mv_grid, adds and connects them to graph.
Args
----
mv_grid: MVGridDing0
Description#TODO
debug: bool, defaults to False
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""" Calculates the optimal position of a circuit breaker on all routes of mv_grid, adds and connects them to graph.
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----
mv_grid: MVGridDing0
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joytunes/JTLocalize | localization_flow/jtlocalize/core/handle_duplicates_in_localization.py | handle_duplications | def handle_duplications(file_path):
""" Omits the duplications in the strings files.
Keys that appear more than once, will be joined to one appearance and the omit will be documented.
Args:
file_path (str): The path to the strings file.
"""
logging.info('Handling duplications for "%s"'... | python | def handle_duplications(file_path):
""" Omits the duplications in the strings files.
Keys that appear more than once, will be joined to one appearance and the omit will be documented.
Args:
file_path (str): The path to the strings file.
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onecodex/onecodex | onecodex/viz/_heatmap.py | VizHeatmapMixin.plot_heatmap | def plot_heatmap(
self,
rank="auto",
normalize="auto",
top_n="auto",
threshold="auto",
title=None,
xlabel=None,
ylabel=None,
tooltip=None,
return_chart=False,
linkage="average",
haxis=None,
metric="euclidean",
... | python | def plot_heatmap(
self,
rank="auto",
normalize="auto",
top_n="auto",
threshold="auto",
title=None,
xlabel=None,
ylabel=None,
tooltip=None,
return_chart=False,
linkage="average",
haxis=None,
metric="euclidean",
... | [
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Parameters
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rank : {'auto', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'}, optional
Analysis will be restricted to abundances of taxa at the specified level.
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onecodex/onecodex | onecodex/api.py | Api._copy_resources | def _copy_resources(self):
"""
Copy all of the resources over to the toplevel client
-return: populates self with a pointer to each ._client.Resource
"""
for resource in self._client._resources:
# set the name param, the keys now have / in them
potion_re... | python | def _copy_resources(self):
"""
Copy all of the resources over to the toplevel client
-return: populates self with a pointer to each ._client.Resource
"""
for resource in self._client._resources:
# set the name param, the keys now have / in them
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onecodex/onecodex | onecodex/auth.py | login_uname_pwd | def login_uname_pwd(server, api_key=None):
"""
Prompts user for username and password, gets API key from server
if not provided.
"""
username = click.prompt("Please enter your One Codex (email)")
if api_key is not None:
return username, api_key
password = click.prompt("Please enter ... | python | def login_uname_pwd(server, api_key=None):
"""
Prompts user for username and password, gets API key from server
if not provided.
"""
username = click.prompt("Please enter your One Codex (email)")
if api_key is not None:
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password = click.prompt("Please enter ... | [
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onecodex/onecodex | onecodex/auth.py | _login | def _login(server, creds_file=None, api_key=None, silent=False):
"""
Login main function
"""
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if server[-1] != "/":
server = server + "/"
# creds file path setup
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creds_file = os.path.expanduser... | python | def _login(server, creds_file=None, api_key=None, silent=False):
"""
Login main function
"""
# fetch_api_key and check_version expect server to end in /
if server[-1] != "/":
server = server + "/"
# creds file path setup
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onecodex/onecodex | onecodex/auth.py | _remove_creds | def _remove_creds(creds_file=None):
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Remove ~/.onecodex file, returning True if successul or False if the file didn't exist
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except Exception as e:
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"""
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onecodex/onecodex | onecodex/auth.py | _logout | def _logout(creds_file=None):
"""
Logout main function, just rm ~/.onecodex more or less
"""
if _remove_creds(creds_file=creds_file):
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"""
Logout main function, just rm ~/.onecodex more or less
"""
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onecodex/onecodex | onecodex/auth.py | login_required | def login_required(fn):
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Notes
-----
Different means of authentication will be attempted in this order:
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onecodex/onecodex | onecodex/models/analysis.py | Classifications.results | def results(self, json=True):
"""
Returns the complete results table for the classification.
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json : bool, optional
Return result as JSON? Default True.
Returns
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table : dict | DataFrame
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Returns the complete results table for the classification.
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json : bool, optional
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onecodex/onecodex | onecodex/models/analysis.py | Classifications.abundances | def abundances(self, ids=None):
"""
Query the results table to get abundance data for all or some tax ids
"""
# TODO: Consider removing this method... since it's kind of trivial
# May want to replace with something that actually gets genome-size adjusted
# abu... | python | def abundances(self, ids=None):
"""
Query the results table to get abundance data for all or some tax ids
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onecodex/onecodex | onecodex/models/sample.py | Samples.save | def save(self):
"""
Persist changes on this Samples object back to the One Codex server along with any changes
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"""
super(Samples, self).save()
if self.metadata is not None:
self.metadata.save() | python | def save(self):
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Persist changes on this Samples object back to the One Codex server along with any changes
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onecodex/onecodex | onecodex/models/sample.py | Samples.upload | def upload(
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):
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Parameters
----------
files : `string` or `tuple`
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joytunes/JTLocalize | localization_flow/jtlocalize/core/localization_objects.py | LocalizationEntry.add_comments | def add_comments(self, comments):
""" Add comments to the localization entry
Args:
comments (list of str): The comments to be added to the localization entry.
"""
for comment in comments:
if comment not in self.comments and len(comment) > 0:
self.... | python | def add_comments(self, comments):
""" Add comments to the localization entry
Args:
comments (list of str): The comments to be added to the localization entry.
"""
for comment in comments:
if comment not in self.comments and len(comment) > 0:
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joytunes/JTLocalize | localization_flow/jtlocalize/merge_translations.py | merge_translations | def merge_translations(localization_bundle_path):
""" Merges the new translation with the old one.
The translated files are saved as '.translated' file, and are merged with old translated file.
Args:
localization_bundle_path (str): The path to the localization bundle.
"""
logging.info("Me... | python | def merge_translations(localization_bundle_path):
""" Merges the new translation with the old one.
The translated files are saved as '.translated' file, and are merged with old translated file.
Args:
localization_bundle_path (str): The path to the localization bundle.
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onecodex/onecodex | onecodex/viz/_bargraph.py | VizBargraphMixin.plot_bargraph | def plot_bargraph(
self,
rank="auto",
normalize="auto",
top_n="auto",
threshold="auto",
title=None,
xlabel=None,
ylabel=None,
tooltip=None,
return_chart=False,
haxis=None,
legend="auto",
label=None,
):
""... | python | def plot_bargraph(
self,
rank="auto",
normalize="auto",
top_n="auto",
threshold="auto",
title=None,
xlabel=None,
ylabel=None,
tooltip=None,
return_chart=False,
haxis=None,
legend="auto",
label=None,
):
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rank : {'auto', 'kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species'}, optional
Analysis will be restricted to abundances of taxa at the specified level.
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onecodex/onecodex | onecodex/exceptions.py | raise_api_error | def raise_api_error(resp, state=None):
"""Raise an exception with a pretty message in various states of upload"""
# TODO: Refactor into an Exception class
error_code = resp.status_code
if error_code == 402:
error_message = (
"Please add a payment method to upload more samples. If yo... | python | def raise_api_error(resp, state=None):
"""Raise an exception with a pretty message in various states of upload"""
# TODO: Refactor into an Exception class
error_code = resp.status_code
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error_message = (
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onecodex/onecodex | onecodex/viz/_pca.py | VizPCAMixin.plot_pca | def plot_pca(
self,
rank="auto",
normalize="auto",
org_vectors=0,
org_vectors_scale=None,
title=None,
xlabel=None,
ylabel=None,
color=None,
size=None,
tooltip=None,
return_chart=False,
label=None,
):
"""P... | python | def plot_pca(
self,
rank="auto",
normalize="auto",
org_vectors=0,
org_vectors_scale=None,
title=None,
xlabel=None,
ylabel=None,
color=None,
size=None,
tooltip=None,
return_chart=False,
label=None,
):
"""P... | [
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Analysis will be restricted to abundances of taxa at the specified level.
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onecodex/onecodex | onecodex/models/__init__.py | pretty_print_error | def pretty_print_error(err_json):
"""Pretty print Flask-Potion error messages for the user."""
# Special case validation errors
if len(err_json) == 1 and "validationOf" in err_json[0]:
required_fields = ", ".join(err_json[0]["validationOf"]["required"])
return "Validation error. Requires pro... | python | def pretty_print_error(err_json):
"""Pretty print Flask-Potion error messages for the user."""
# Special case validation errors
if len(err_json) == 1 and "validationOf" in err_json[0]:
required_fields = ", ".join(err_json[0]["validationOf"]["required"])
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onecodex/onecodex | onecodex/models/__init__.py | OneCodexBase._to_json | def _to_json(self, include_references=True):
"""Convert the model to JSON using the PotionJSONEncode and automatically
resolving the resource as needed (`_properties` call handles this).
"""
if include_references:
return json.dumps(self._resource._properties, cls=PotionJSONEn... | python | def _to_json(self, include_references=True):
"""Convert the model to JSON using the PotionJSONEncode and automatically
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if include_references:
return json.dumps(self._resource._properties, cls=PotionJSONEn... | [
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onecodex/onecodex | onecodex/models/__init__.py | OneCodexBase.all | def all(cls, sort=None, limit=None):
"""Returns all objects of this type. Alias for where() (without filter arguments).
See `where` for documentation on the `sort` and `limit` parameters.
"""
return cls.where(sort=sort, limit=limit) | python | def all(cls, sort=None, limit=None):
"""Returns all objects of this type. Alias for where() (without filter arguments).
See `where` for documentation on the `sort` and `limit` parameters.
"""
return cls.where(sort=sort, limit=limit) | [
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onecodex/onecodex | onecodex/models/__init__.py | OneCodexBase.where | def where(cls, *filters, **keyword_filters):
"""Retrieves objects (Samples, Classifications, etc.) from the One Codex server.
Parameters
----------
filters : objects
Advanced filters to use (not implemented)
sort : string | list, optional
Sort the results... | python | def where(cls, *filters, **keyword_filters):
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filters : objects
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onecodex/onecodex | onecodex/models/__init__.py | OneCodexBase.get | def get(cls, uuid):
"""Retrieve one specific object from the server by its UUID (unique 16-character id). UUIDs
can be found in the web browser's address bar while viewing analyses and other objects.
Parameters
----------
uuid : string
UUID of the object to retrieve.... | python | def get(cls, uuid):
"""Retrieve one specific object from the server by its UUID (unique 16-character id). UUIDs
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Parameters
----------
uuid : string
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onecodex/onecodex | onecodex/models/__init__.py | OneCodexBase.delete | def delete(self):
"""Delete this object from the One Codex server."""
check_bind(self)
if self.id is None:
raise ServerError("{} object does not exist yet".format(self.__class__.name))
elif not self.__class__._has_schema_method("destroy"):
raise MethodNotSupported... | python | def delete(self):
"""Delete this object from the One Codex server."""
check_bind(self)
if self.id is None:
raise ServerError("{} object does not exist yet".format(self.__class__.name))
elif not self.__class__._has_schema_method("destroy"):
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onecodex/onecodex | onecodex/models/__init__.py | OneCodexBase.save | def save(self):
"""Either create or persist changes on this object back to the One Codex server."""
check_bind(self)
creating = self.id is None
if creating and not self.__class__._has_schema_method("create"):
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"""Either create or persist changes on this object back to the One Codex server."""
check_bind(self)
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