def historic_run():
"""Run the model."""
logger.info(f'Version: {VERSION}')
logger.info('Initialising cloud storage client ...')
client = init_azure_storage()
download_hydrology(client)
logger.info('Starting model run ...')
# Run the model
if not os.path.exists(OUT_DIR):
os.makedirs(OUT_DIR)
model = Model.load(MODEL_FILENAME)
# Add a storage recorder
TablesRecorder(model,
os.path.join(OUT_DIR, 'thames_output.h5'),
parameters=[p for p in model.parameters])
ProgressRecorder(model)
# Run the model
stats = model.run()
logger.info(stats)
# Upload the results
logger.info('Uploading outputs ...')
upload_outputs(client)
# Print stats
stats_df = stats.to_dataframe()
logger.info(stats_df)
def test_multiple_scenarios(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder
"""
from pywr.parameters import ConstantScenarioParameter
model = simple_linear_model
scA = Scenario(model, name='A', size=4)
scB = Scenario(model, name='B', size=2)
otpt = model.nodes['Output']
inpt = model.nodes['Input']
inpt.max_flow = ConstantScenarioParameter(model, scA, [10, 20, 30, 40])
otpt.max_flow = ConstantScenarioParameter(model, scB, [20, 40])
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
rec = TablesRecorder(model, h5f)
model.run()
for node_name in model.nodes.keys():
ca = h5f.get_node('/', node_name)
assert ca.shape == (365, 4, 2)
np.testing.assert_allclose(ca[0, ...], [[10, 10], [20, 20], [20, 30], [20, 40]])
scenarios = h5f.get_node('/scenarios')
for i, s in enumerate(model.scenarios.scenarios):
row = scenarios[i]
assert row['name'] == s.name.encode('utf-8')
assert row['size'] == s.size
def plot_res(ext, show):
end_year = "2105"
data = {}
for name, df in TablesRecorder.generate_dataframes("thames_output.h5"):
df.columns = ["Very low", "Low", "Central", "High", "Very high"]
data[name] = df
fig1, ax1 = plt.subplots(figsize=(16, 5), dpi=300)
data["reservoir1"].loc[:end_year, "Central"].plot(ax=ax1)
ax1.set_ylabel("Volume [$Mm^3$]")
plt.tight_layout()
fig2, ax2 = plt.subplots(figsize=(16, 5), dpi=300)
data["demand_saving_level"].loc[:end_year, "Central"].plot(ax=ax2)
ax2.set_ylabel("Demand saving level")
plt.tight_layout()
fig3, ax3 = plt.subplots(figsize=(16, 5), dpi=300)
data["demand_max_flow"].loc[:end_year, "Central"].plot(ax=ax3)
ax3.set_ylabel("Demand [$Mm^3/day$]")
plt.tight_layout()
for ax in (ax1, ax2, ax3):
ax.grid(True)
if ext is not None:
fig1.savefig(f"Reservoir.{ext}", dpi=300)
fig2.savefig(f"Demand saving level.{ext}", dpi=300)
fig3.savefig(f"Demand.{ext}", dpi=300)
if show:
plt.show()
def test_nodes_with_str(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder
"""
from pywr.parameters import ConstantParameter
model = simple_linear_model
otpt = model.nodes['Output']
inpt = model.nodes['Input']
agg_node = AggregatedNode(model, 'Sum', [otpt, inpt])
p = ConstantParameter(model, 10.0, name='max_flow')
inpt.max_flow = p
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
nodes = ['Output', 'Input', 'Sum']
where = "/agroup"
rec = TablesRecorder(model, h5f, nodes=nodes,
parameters=[p, ], where=where)
model.run()
for node_name in ['Output', 'Input', 'Sum', 'max_flow']:
ca = h5f.get_node("/agroup/" + node_name)
assert ca.shape == (365, 1)
if node_name == 'Sum':
np.testing.assert_allclose(ca, 20.0)
else:
np.testing.assert_allclose(ca, 10.0)
def test_parameters(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder
"""
from pywr.parameters import ConstantParameter
model = simple_linear_model
otpt = model.nodes['Output']
inpt = model.nodes['Input']
p = ConstantParameter(10.0, name='max_flow')
inpt.max_flow = p
agg_node = AggregatedNode(model, 'Sum', [otpt, inpt])
inpt.max_flow = 10.0
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
rec = TablesRecorder(model, h5f, parameters=[p, ])
model.run()
for node_name in model.nodes.keys():
ca = h5f.get_node('/', node_name)
assert ca.shape == (365, 1)
if node_name == 'Sum':
np.testing.assert_allclose(ca, 20.0)
else:
np.testing.assert_allclose(ca, 10.0)
def plot_res(ext, show):
end_year = '2105'
data = {}
for name, df in TablesRecorder.generate_dataframes('thames_output.h5'):
df.columns = ['Very low', 'Low', 'Central', 'High', 'Very high']
data[name] = df
fig1, ax1 = plt.subplots(figsize=(16, 5), dpi=300)
data['reservoir1'].loc[:end_year, 'Central'].plot(ax=ax1)
ax1.set_ylabel('Volume [$Mm^3$]')
plt.tight_layout()
fig2, ax2 = plt.subplots(figsize=(16, 5), dpi=300)
data['demand_saving_level'].loc[:end_year, 'Central'].plot(ax=ax2)
ax2.set_ylabel('Demand saving level')
plt.tight_layout()
fig3, ax3 = plt.subplots(figsize=(16, 5), dpi=300)
data['demand_max_flow'].loc[:end_year, 'Central'].plot(ax=ax3)
ax3.set_ylabel('Demand [$Mm^3/day$]')
plt.tight_layout()
for ax in (ax1, ax2, ax3):
ax.grid(True)
if ext is not None:
fig1.savefig(f'Reservoir.{ext}', dpi=300)
fig2.savefig(f'Demand saving level.{ext}', dpi=300)
fig3.savefig(f'Demand.{ext}', dpi=300)
if show:
plt.show()
def figures(ext, show):
for name, df in TablesRecorder.generate_dataframes('thames_output.h5'):
df.columns = ['Very low', 'Low', 'Central', 'High', 'Very high']
fig, (ax1, ax2) = plt.subplots(figsize=(12, 4),
ncols=2,
sharey='row',
gridspec_kw={'width_ratios': [3, 1]})
df['2100':'2125'].plot(ax=ax1)
df.quantile(np.linspace(0, 1)).plot(ax=ax2)
if name.startswith('reservoir'):
ax1.set_ylabel('Volume [$Mm^3$]')
else:
ax1.set_ylabel('Flow [$Mm^3/day$]')
for ax in (ax1, ax2):
ax.set_title(name)
ax.grid(True)
plt.tight_layout()
if ext is not None:
fig.savefig(f'{name}.{ext}', dpi=300)
if show:
plt.show()
def test_routes_multiple_scenarios(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder
"""
from pywr.parameters import ConstantScenarioParameter
model = simple_linear_model
scA = Scenario(model, name='A', size=4)
scB = Scenario(model, name='B', size=2)
otpt = model.nodes['Output']
inpt = model.nodes['Input']
inpt.max_flow = ConstantScenarioParameter(model, scA, [10, 20, 30, 40])
otpt.max_flow = ConstantScenarioParameter(model, scB, [20, 40])
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
rec = TablesRecorder(model, h5f, routes_flows='flows')
model.run()
flows = h5f.get_node('/flows')
assert flows.shape == (365, 1, 4, 2)
np.testing.assert_allclose(flows[0, 0], [[10, 10], [20, 20], [20, 30], [20, 40]])
def figures(ext, show):
for name, df in TablesRecorder.generate_dataframes("thames_output.h5"):
df.columns = ["Very low", "Low", "Central", "High", "Very high"]
fig, (ax1, ax2) = plt.subplots(
figsize=(12, 4), ncols=2, sharey="row", gridspec_kw={"width_ratios": [3, 1]}
)
df["2100":"2125"].plot(ax=ax1)
df.quantile(np.linspace(0, 1)).plot(ax=ax2)
if name.startswith("reservoir"):
ax1.set_ylabel("Volume [$Mm^3$]")
else:
ax1.set_ylabel("Flow [$Mm^3/day$]")
for ax in (ax1, ax2):
ax.set_title(name)
ax.grid(True)
plt.tight_layout()
if ext is not None:
fig.savefig(f"{name}.{ext}", dpi=300)
if show:
plt.show()
def test_routes(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder
"""
model = simple_linear_model
otpt = model.nodes['Output']
inpt = model.nodes['Input']
agg_node = AggregatedNode(model, 'Sum', [otpt, inpt])
inpt.max_flow = 10.0
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
rec = TablesRecorder(model, h5f, routes_flows='flows')
model.run()
flows = h5f.get_node('/flows')
assert flows.shape == (365, 1, 1)
np.testing.assert_allclose(flows.read(), np.ones((365, 1, 1))*10)
routes = h5f.get_node('/routes')
assert routes.shape[0] == 1
row = routes[0]
row['start'] = "Input"
row['end'] = "Output"
from datetime import date, timedelta
d = date(2015, 1, 1)
time = h5f.get_node('/time')
for i in range(len(model.timestepper)):
row = time[i]
assert row['year'] == d.year
assert row['month'] == d.month
assert row['day'] == d.day
d += timedelta(1)
scenarios = h5f.get_node('/scenarios')
for s in model.scenarios.scenarios:
row = scenarios[i]
assert row['name'] == s.name
assert row['size'] == s.size
model.reset()
model.run()
time = h5f.get_node('/time')
assert len(time) == len(model.timestepper)
def test_nodes(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder
"""
model = simple_linear_model
otpt = model.nodes['Output']
inpt = model.nodes['Input']
agg_node = AggregatedNode(model, 'Sum', [otpt, inpt])
inpt.max_flow = 10.0
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
rec = TablesRecorder(model, h5f)
model.run()
for node_name in model.nodes.keys():
ca = h5f.get_node('/', node_name)
assert ca.shape == (365, 1)
if node_name == 'Sum':
np.testing.assert_allclose(ca, 20.0)
else:
np.testing.assert_allclose(ca, 10.0)
from datetime import date, timedelta
d = date(2015, 1, 1)
time = h5f.get_node('/time')
for i in range(len(model.timestepper)):
row = time[i]
assert row['year'] == d.year
assert row['month'] == d.month
assert row['day'] == d.day
d += timedelta(1)
scenarios = h5f.get_node('/scenarios')
for i, s in enumerate(model.scenarios.scenarios):
row = scenarios[i]
assert row['name'] == s.name.encode('utf-8')
assert row['size'] == s.size
model.reset()
model.run()
time = h5f.get_node('/time')
assert len(time) == len(model.timestepper)
def test_parameters(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder
"""
from pywr.parameters import ConstantParameter
model = simple_linear_model
otpt = model.nodes['Output']
inpt = model.nodes['Input']
p = ConstantParameter(model, 10.0, name='max_flow')
inpt.max_flow = p
# ensure TablesRecorder can handle parameters with a / in the name
p_slash = ConstantParameter(model, 0.0, name='name with a / in it')
inpt.min_flow = p_slash
agg_node = AggregatedNode(model, 'Sum', [otpt, inpt])
inpt.max_flow = 10.0
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
with pytest.warns(ParameterNameWarning):
rec = TablesRecorder(model, h5f, parameters=[p, p_slash])
# check parameters have been added to the component tree
# this is particularly important for parameters which update their
# values in `after`, e.g. DeficitParameter (see #465)
assert(not model.find_orphaned_parameters())
assert(p in rec.children)
assert(p_slash in rec.children)
with pytest.warns(tables.NaturalNameWarning):
model.run()
for node_name in model.nodes.keys():
ca = h5f.get_node('/', node_name)
assert ca.shape == (365, 1)
if node_name == 'Sum':
np.testing.assert_allclose(ca, 20.0)
elif "name with a" in node_name:
assert(node_name == "name with a _ in it")
np.testing.assert_allclose(ca, 0.0)
else:
np.testing.assert_allclose(ca, 10.0)
def test_demand_saving_with_indexed_array(self, solver, tmpdir):
"""Test recording various items from demand saving example
"""
model = load_model("demand_saving2.json", solver=solver)
model.timestepper.end = "2016-01-31"
model.check()
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
nodes = [
('/outputs/demand', 'Demand'),
('/storage/reservoir', 'Reservoir'),
]
parameters = [
('/parameters/demand_saving_level', 'demand_saving_level'),
]
rec = TablesRecorder(model, h5f, nodes=nodes, parameters=parameters)
model.run()
max_volume = model.nodes["Reservoir"].max_volume
rec_demand = h5f.get_node('/outputs/demand', 'Demand').read()
rec_storage = h5f.get_node('/storage/reservoir', 'Reservoir').read()
# model starts with no demand saving
demand_baseline = 50.0
demand_factor = 0.9 # jan-apr
demand_saving = 1.0
assert_allclose(rec_demand[0, 0], demand_baseline * demand_factor * demand_saving)
# first control curve breached
demand_saving = 0.95
assert (rec_storage[4, 0] < (0.8 * max_volume))
assert_allclose(rec_demand[5, 0], demand_baseline * demand_factor * demand_saving)
# second control curve breached
demand_saving = 0.5
assert (rec_storage[11, 0] < (0.5 * max_volume))
assert_allclose(rec_demand[12, 0], demand_baseline * demand_factor * demand_saving)
def test_create_directory(self, simple_linear_model, tmpdir):
""" Test TablesRecorder to create a new directory """
model = simple_linear_model
otpt = model.nodes['Output']
inpt = model.nodes['Input']
agg_node = AggregatedNode(model, 'Sum', [otpt, inpt])
inpt.max_flow = 10.0
otpt.cost = -2.0
# Make a path with a new directory
folder = tmpdir.join('outputs')
h5file = folder.join('output.h5')
assert(not folder.exists())
rec = TablesRecorder(model, str(h5file), create_directories=True)
model.run()
assert(folder.exists())
assert(h5file.exists())
def plot_res2(ext, show):
end_year = "2105"
data = {}
for name, df in TablesRecorder.generate_dataframes("thames_output.h5"):
df.columns = ["Very low", "Low", "Central", "High", "Very high"]
data[name] = df
fig1, ax1 = plt.subplots(figsize=(16, 5), dpi=300)
data["reservoir1"].loc[:end_year].plot(ax=ax1)
ax1.set_ylabel("Volume [$Mm^3$]")
plt.legend()
plt.tight_layout()
fig2, ax2 = plt.subplots(figsize=(16, 5), dpi=300)
data["reservoir1"].quantile(np.linspace(0, 1)).plot(ax=ax2)
ax2.set_ylabel("Volume [$Mm^3$]")
ax2.set_xlabel("Quantile")
plt.tight_layout()
fig3, ax3 = plt.subplots(figsize=(16, 5), dpi=300)
df = data["demand_saving_level"].apply(pandas.Series.value_counts)
df /= df.sum(axis=0)
df.plot.bar(ax=ax3)
ax3.set_ylabel("Proportion of time.")
ax3.set_xlabel("Demand saving level")
plt.tight_layout()
for ax in (ax1, ax2, ax3):
ax.grid(True)
if ext is not None:
fig1.savefig(f"Reservoir (scenarios).{ext}", dpi=300)
fig2.savefig(f"Reservoir SDC (scenarios).{ext}", dpi=300)
fig3.savefig(f"Demand saving level count (scenarios).{ext}", dpi=300)
if show:
plt.show()
def plot_res2(ext, show):
end_year = '2105'
data = {}
for name, df in TablesRecorder.generate_dataframes('thames_output.h5'):
df.columns = ['Very low', 'Low', 'Central', 'High', 'Very high']
data[name] = df
fig1, ax1 = plt.subplots(figsize=(16, 5), dpi=300)
data['reservoir1'].loc[:end_year].plot(ax=ax1)
ax1.set_ylabel('Volume [$Mm^3$]')
plt.legend()
plt.tight_layout()
fig2, ax2 = plt.subplots(figsize=(16, 5), dpi=300)
data['reservoir1'].quantile(np.linspace(0, 1)).plot(ax=ax2)
ax2.set_ylabel('Volume [$Mm^3$]')
ax2.set_xlabel('Quantile')
plt.tight_layout()
fig3, ax3 = plt.subplots(figsize=(16, 5), dpi=300)
df = data['demand_saving_level'].apply(pandas.Series.value_counts)
df /= df.sum(axis=0)
df.plot.bar(ax=ax3)
ax3.set_ylabel('Proportion of time.')
ax3.set_xlabel('Demand saving level')
plt.tight_layout()
for ax in (ax1, ax2, ax3):
ax.grid(True)
if ext is not None:
fig1.savefig(f'Reservoir (scenarios).{ext}', dpi=300)
fig2.savefig(f'Reservoir SDC (scenarios).{ext}', dpi=300)
fig3.savefig(f'Demand saving level count (scenarios).{ext}', dpi=300)
if show:
plt.show()
def test_user_scenarios(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder with user defined scenario subset
"""
from pywr.parameters import ConstantScenarioParameter
model = simple_linear_model
scA = Scenario(model, name='A', size=4)
scB = Scenario(model, name='B', size=2)
# Use first and last combinations
model.scenarios.user_combinations = [[0, 0], [3, 1]]
otpt = model.nodes['Output']
inpt = model.nodes['Input']
inpt.max_flow = ConstantScenarioParameter(model, scA, [10, 20, 30, 40])
otpt.max_flow = ConstantScenarioParameter(model, scB, [20, 40])
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
rec = TablesRecorder(model, h5f)
model.run()
for node_name in model.nodes.keys():
ca = h5f.get_node('/', node_name)
assert ca.shape == (365, 2)
np.testing.assert_allclose(ca[0, ...], [10, 40])
# check combinations table exists
combinations = h5f.get_node('/scenario_combinations')
for i, comb in enumerate(model.scenarios.user_combinations):
row = combinations[i]
assert row['A'] == comb[0]
assert row['B'] == comb[1]
def test_routes_user_scenarios(self, simple_linear_model, tmpdir):
"""
Test the TablesRecorder with user defined scenario subset
"""
from pywr.parameters import ConstantScenarioParameter
model = simple_linear_model
scA = Scenario(model, name='A', size=4)
scB = Scenario(model, name='B', size=2)
# Use first and last combinations
model.scenarios.user_combinations = [[0, 0], [3, 1]]
otpt = model.nodes['Output']
inpt = model.nodes['Input']
inpt.max_flow = ConstantScenarioParameter(model, scA, [10, 20, 30, 40])
otpt.max_flow = ConstantScenarioParameter(model, scB, [20, 40])
otpt.cost = -2.0
h5file = tmpdir.join('output.h5')
import tables
with tables.open_file(str(h5file), 'w') as h5f:
rec = TablesRecorder(model, h5f, routes_flows='flows')
model.run()
flows = h5f.get_node('/flows')
assert flows.shape == (365, 1, 2)
np.testing.assert_allclose(flows[0, 0], [10, 40])
# check combinations table exists
combinations = h5f.get_node('/scenario_combinations')
for i, comb in enumerate(model.scenarios.user_combinations):
row = combinations[i]
assert row['A'] == comb[0]
assert row['B'] == comb[1]
# This part of the test requires IPython (see `pywr.notebook`)
pytest.importorskip("IPython") # triggers a skip of the test if IPython not found.
from pywr.notebook.sankey import routes_to_sankey_links
links = routes_to_sankey_links(str(h5file), 'flows')
# Value is mean of 10 and 40
link = links[0]
assert link['source'] == 'Input'
assert link['target'] == 'Output'
np.testing.assert_allclose(link['value'], 25.0)
links = routes_to_sankey_links(str(h5file), 'flows', scenario_slice=0)
link = links[0]
assert link['source'] == 'Input'
assert link['target'] == 'Output'
np.testing.assert_allclose(link['value'], 10.0)
links = routes_to_sankey_links(str(h5file), 'flows', scenario_slice=1, time_slice=0)
link = links[0]
assert link['source'] == 'Input'
assert link['target'] == 'Output'
np.testing.assert_allclose(link['value'], 40.0)
def run():
# Run the model
model = Model.load(MODEL_FILENAME)
# Add a storage recorder
TablesRecorder(model, "thames_output.h5", parameters=[p for p in model.parameters])
# Run the model
stats = model.run()
print(stats)
stats_df = stats.to_dataframe()
print(stats_df)
keys_to_plot = (
"time_taken_before",
"solver_stats.bounds_update_nonstorage",
"solver_stats.bounds_update_storage",
"solver_stats.objective_update",
"solver_stats.lp_solve",
"solver_stats.result_update",
"time_taken_after",
)
keys_to_tabulate = (
"timesteps",
"time_taken",
"solver",
"num_scenarios",
"speed",
"solver_name" "solver_stats.total",
"solver_stats.number_of_rows",
"solver_stats.number_of_cols",
"solver_stats.number_of_nonzero",
"solver_stats.number_of_routes",
"solver_stats.number_of_nodes",
)
values = []
labels = []
explode = []
solver_sub_total = 0.0
for k in keys_to_plot:
v = stats_df.loc[k][0]
values.append(v)
label = k.split(".", 1)[-1].replace("_", " ").capitalize()
explode.append(0.0)
if k.startswith("solver_stats"):
labels.append("Solver - {}".format(label))
solver_sub_total += v
else:
labels.append(label)
values.append(stats_df.loc["solver_stats.total"][0] - solver_sub_total)
labels.append("Solver - Other")
explode.append(0.0)
values.append(stats_df.loc["time_taken"][0] - sum(values))
values = np.array(values) / sum(values)
labels.append("Other")
explode.append(0.0)
fig, (ax1, ax2) = plt.subplots(
figsize=(12, 4), ncols=2, sharey="row", gridspec_kw={"width_ratios": [2, 1]}
)
print(values, labels)
ax1.pie(values, explode=explode, labels=labels, autopct="%1.1f%%", startangle=90)
ax1.axis("equal") # Equal aspect ratio ensures that pie is drawn as a circle.
cell_text = []
for index, value in stats_df.iterrows():
if index not in keys_to_tabulate:
continue
v = value[0]
if isinstance(v, (float, np.float64, np.float32)):
v = f"{v:.2f}"
cell_text.append([index, v])
tbl = ax2.table(cellText=cell_text, colLabels=["Statistic", "Value"], loc="center")
tbl.scale(1.5, 1.5) # may help
tbl.set_fontsize(14)
ax2.axis("off")
fig.savefig("run_statistics_w_tables.png", dpi=300)
fig.savefig("run_statistics_w_tables.eps")
plt.show()
def run():
# Run the model
model = Model.load(MODEL_FILENAME)
# Add a storage recorder
TablesRecorder(model,
'thames_output.h5',
parameters=[p for p in model.parameters])
# Run the model
stats = model.run()
print(stats)
stats_df = stats.to_dataframe()
print(stats_df)
keys_to_plot = (
'time_taken_before',
'solver_stats.bounds_update_nonstorage',
'solver_stats.bounds_update_storage',
'solver_stats.objective_update',
'solver_stats.lp_solve',
'solver_stats.result_update',
'time_taken_after',
)
keys_to_tabulate = (
'timesteps',
'time_taken',
'solver',
'num_scenarios',
'speed',
'solver_name'
'solver_stats.total',
'solver_stats.number_of_rows',
'solver_stats.number_of_cols',
'solver_stats.number_of_nonzero',
'solver_stats.number_of_routes',
'solver_stats.number_of_nodes',
)
values = []
labels = []
explode = []
solver_sub_total = 0.0
for k in keys_to_plot:
v = stats_df.loc[k][0]
values.append(v)
label = k.split('.', 1)[-1].replace('_', ' ').capitalize()
explode.append(0.0)
if k.startswith('solver_stats'):
labels.append('Solver - {}'.format(label))
solver_sub_total += v
else:
labels.append(label)
values.append(stats_df.loc['solver_stats.total'][0] - solver_sub_total)
labels.append('Solver - Other')
explode.append(0.0)
values.append(stats_df.loc['time_taken'][0] - sum(values))
values = np.array(values) / sum(values)
labels.append('Other')
explode.append(0.0)
fig, (ax1, ax2) = plt.subplots(figsize=(12, 4),
ncols=2,
sharey='row',
gridspec_kw={'width_ratios': [2, 1]})
print(values, labels)
ax1.pie(values,
explode=explode,
labels=labels,
autopct='%1.1f%%',
startangle=90)
ax1.axis(
'equal') # Equal aspect ratio ensures that pie is drawn as a circle.
cell_text = []
for index, value in stats_df.iterrows():
if index not in keys_to_tabulate:
continue
v = value[0]
if isinstance(v, (float, np.float64, np.float32)):
v = f'{v:.2f}'
cell_text.append([index, v])
tbl = ax2.table(cellText=cell_text,
colLabels=['Statistic', 'Value'],
loc='center')
tbl.scale(1.5, 1.5) # may help
tbl.set_fontsize(14)
ax2.axis('off')
fig.savefig('run_statistics_w_tables.png', dpi=300)
fig.savefig('run_statistics_w_tables.eps')
plt.show()