def reload_cycle_scenario(request, tmp_path_factory, rc_data_size):
"""Set up a Platform with *rc_data_size* of random data."""
# Command-line option for the JVM memory limit
kwarg = dict()
jvm_mem_limit = int(request.config.getoption("--jvm-mem-limit"))
if jvm_mem_limit > 0:
kwarg["jvmargs"] = f"-Xmx{jvm_mem_limit}M"
# Path for this database
path = tmp_path_factory.mktemp("reload_cycle") / "base"
# Create the Platform. This should be the first in the process, so the
# jvmargs are used in :func:`.jdbc.start_jvm`.
mp = ixmp.Platform(backend="jdbc", driver="hsqldb", path=path, **kwarg)
s0 = ixmp.Scenario(mp, model="foo", scenario="bar 0", version="new")
# Add data
# currently omitted: time series data with *rc_data_size* elements
# s0.add_timeseries(random_ts_data(rc_data_size))
# A set named 'random_set' and parameter 'random_par' with *rc_data_size*
# elements
add_random_model_data(s0, rc_data_size)
s0.commit("")
yield s0
def reload_cycle_scenario(request, tmp_path_factory, rc_data_size):
"""Set up a Platform with *rc_data_size* of random data."""
# Command-line option for the JVM memory limit
kwarg = dict()
jvm_mem_limit = int(request.config.getoption('--jvm-mem-limit'))
if jvm_mem_limit > 0:
kwarg['jvmargs'] = f'-Xmx{jvm_mem_limit}M'
# Path for this database
path = tmp_path_factory.mktemp('reload_cycle') / 'base'
# Create the Platform. This should be the first in the process, so the
# jvmargs are used in :func:`.jdbc.start_jvm`.
mp = ixmp.Platform(backend='jdbc', driver='hsqldb', path=path, **kwarg)
s0 = ixmp.Scenario(mp, model='foo', scenario='bar 0', version='new')
# Add data
# currently omitted: time series data with *rc_data_size* elements
# s0.add_timeseries(random_ts_data(rc_data_size))
# A set named 'random_set' and parameter 'random_par' with *rc_data_size*
# elements
add_random_model_data(s0, rc_data_size)
s0.commit('')
yield s0
def test_read_excel_big(test_mp, tmp_path):
"""Excel files with model items split across sheets can be read.
https://github.com/iiasa/ixmp/pull/345.
"""
tmp_path /= 'output.xlsx'
# Write a 25-element parameter with max_row=10 → split across 3 sheets
scen = ixmp.Scenario(test_mp, **models['dantzig'], version="new")
add_random_model_data(scen, 25)
scen.to_excel(tmp_path, items=ixmp.ItemType.MODEL, max_row=10)
# Initialize target scenario for reading
scen_empty = ixmp.Scenario(test_mp, "foo", "bar", version="new")
scen_empty.init_set("random_set")
scen_empty.init_par("random_par", scen.idx_sets("random_par"),
scen.idx_names("random_par"))
# File can be read
scen_empty.read_excel(tmp_path)
assert len(scen_empty.par("random_par")) == 25