def test_filter_online(self):
runs = load_tracker_runs()
values = list(runs.reco.unique())
assert ["express", "online", "prompt", "rereco"] == values
filtered = filter_online(runs)
assert ["online"] == list(filtered.reco.unique())
def test_is_commissioning():
tracker_runs = load_tracker_runs()
add_is_commissioning(tracker_runs)
assert "is_commissioning" in tracker_runs
tracker_runs.set_index(["run_number", "reco"], inplace=True)
assert not tracker_runs.loc[(314848, "prompt"), "is_commissioning"]
assert not tracker_runs.loc[(314848, "express"), "is_commissioning"]
assert not tracker_runs.loc[(314848, "online"), "is_commissioning"]
assert not tracker_runs.loc[(321766, "prompt"), "is_commissioning"]
assert not tracker_runs.loc[(321766, "express"), "is_commissioning"]
assert not tracker_runs.loc[(321766, "online"), "is_commissioning"]
assert not tracker_runs.loc[(321773, "prompt"), "is_commissioning"]
assert not tracker_runs.loc[(321773, "express"), "is_commissioning"]
assert not tracker_runs.loc[(321773, "online"), "is_commissioning"]
assert tracker_runs.loc[(314472, "prompt"), "is_commissioning"]
assert tracker_runs.loc[(314472, "express"), "is_commissioning"]
assert tracker_runs.loc[(314472, "online"), "is_commissioning"]
assert tracker_runs.loc[(314541, "express"), "is_commissioning"]
assert tracker_runs.loc[(314541, "online"), "is_commissioning"]
def test_add_bad_reason():
runs = load_tracker_runs()
tkdqm_runs = load_tkdqmdoctor_runs()
runs = merge_runreg_tkdqmdoc(runs, tkdqm_runs)
runs = runs.pipe(filter_collisions)
print(runs.columns)
runs = runs.pipe(add_bad_reason)
runs = runs.loc[runs["tracking"] == "BAD", [
"run_number",
"bad_reason",
"pixel_comment",
"strip_comment",
"tracking_comment",
"comment",
], ]
setup_pandas_display(max_rows=200)
runs = runs.loc[~runs.bad_reason.isnull(), :]
pandas.set_option("display.max_colwidth", -1)
print(runs)
def test_add_status_summary():
runs = load_tracker_runs()
runs = runs.pipe(add_status_summary)
runs.set_index(["run_number", "reco"], inplace=True)
assert runs.loc[(313052, "express"), "status_summary"] == "Pixel Excluded"
assert runs.loc[(313084, "prompt"), "status_summary"] == "Good"
def test_plot_angular_entropy():
runs = (load_tracker_runs().pipe(filter_collisions).pipe(
filter_express).pipe(add_is_bad).pipe(add_is_special).pipe(
add_is_commissioning).pipe(add_is_heavy_ion).pipe(
exclude_commissioning).pipe(exclude_special).pipe(
filter_run_number_range, 317400,
317500).pipe(add_angular_entropy))
plot_angular_entropy(runs, show=SHOW_PLOTS, save=SHOW_PLOTS)
def test_filter_lumisections(self):
runs = load_tracker_runs()
assert not runs.empty
assert not runs[runs["lumisections"] < 30].empty
runs = filter_lumisections_gte(runs, 30)
assert not runs.empty
assert runs[runs["lumisections"] < 30].empty
def test_exclude_lumisections(self):
runs = load_tracker_runs()
assert not runs.empty
assert not runs[runs["lumisections"] >= 30].empty
runs = runs.pipe(exclude_lumisections_gte, 30)
assert not runs.empty
assert runs[runs["lumisections"] >= 30].empty
def test_load_all_runreg_runs(self):
tracker_runs = load_tracker_runs()
global_runs = load_global_runs()
all_runs = load_all_runreg_runs()
assert len(all_runs) == len(tracker_runs) + len(
global_runs
), "Increased line count"
assert len(list(all_runs)) == max(
len(list(tracker_runs)), len(list(global_runs))
), "Maximum column count"
def test_plot_reference_distribution():
tracker_runs = load_tracker_runs()
tkdqmdoctor_runs = load_tkdqmdoctor_runs()
runs = merge_runreg_tkdqmdoc(tracker_runs, tkdqmdoctor_runs)
runs = (runs.pipe(add_is_bad).pipe(exclude_online).pipe(
exclude_rereco).pipe(add_is_commissioning).pipe(add_is_special).pipe(
exclude_commissioning).pipe(exclude_special))
plot_reference_distribution(runs, show=SHOW_PLOTS)
def test_load_tracker_runs(self):
runs = load_tracker_runs()
assert "rda_cmp_pixel" not in runs
assert "rda_cmp_strip" not in runs
assert "rda_cmp_tracking" not in runs
assert "rda_cmp_pix" not in runs
assert "rda_cmp_track" not in runs
assert "pixel" in runs
assert "strip" in runs
assert "tracking" in runs
assert "csc" not in runs
def test_merge_runreg_histograms():
tracker_runs = load_tracker_runs()
histograms = load_all_histogram_folders()
runs = merge_runreg_histograms(tracker_runs, histograms)
runs.set_index(["run_number", "reco"], inplace=True)
assert runs.loc[(327564, "express"),
"Seeds.detachedTriplet.mean"] == 10507.7
assert runs.loc[(327564, "express"), "pixel"] == "GOOD"
assert pandas.isnull(runs.loc[(314472, "online"),
"Seeds.detachedTriplet.mean"])
def test_exclude_collisions(self):
runs = load_tracker_runs()
values = list(runs.run_class_name.unique())
assert [
"Cosmics18",
"Commissioning18",
"Collisions18",
"Collisions18SpecialRun",
] == values
collisions = exclude_collisions(runs)
assert ["Cosmics18",
"Commissioning18"] == list(collisions.run_class_name.unique())
def test_merge_runreg_tkdqmdoctor_runs():
tracker_runs = load_tracker_runs()
tkdqm = load_tkdqmdoctor_runs()
tracker_size = len(tracker_runs)
tracker_column_count = len(list(tracker_runs))
assert 36 == tracker_column_count
merged = merge_runreg_tkdqmdoc(tracker_runs, tkdqm)
merged_column_count = len(list(merged))
assert len(tracker_runs) == tracker_size, "No Change in Line count"
assert tracker_column_count + 6 == merged_column_count, "Increased Column count"
def test_add_reference_cost():
tracker_runs = load_tracker_runs()
tkdqmdoc_runs = load_tkdqmdoctor_runs()
runs = merge_runreg_tkdqmdoc(tracker_runs, tkdqmdoc_runs)
assert "reference_cost" not in runs
add_reference_cost(runs)
assert "reference_cost" in runs
runs.set_index(["run_number", "reco"], inplace=True)
assert math.isclose(runs.loc[(315322, "prompt"), "reference_cost"],
0.130825,
abs_tol=0.01)
def test_filter_run_number_range():
runs = load_tracker_runs().pipe(filter_run_number_range, 316199, 316216)
assert {
316199,
316200,
316201,
316202,
316204,
316205,
316207,
316208,
316209,
316210,
316213,
316214,
316216,
} == set(runs.run_number.unique())
def test_merge_runreg_oms():
tracker_runs = load_tracker_runs()
oms = load_oms_runs()
tracker_size = len(tracker_runs)
tracker_column_count = len(list(tracker_runs))
oms_column_count = len(list(oms))
assert 36 == tracker_column_count
assert 35 == oms_column_count
merged = merge_runreg_oms(tracker_runs, oms)
merged_column_count = len(list(merged))
assert len(tracker_runs) == tracker_size, "No Change in Line count"
assert (tracker_column_count + oms_column_count -
1 == merged_column_count), "Increased Column count"
def test_merge_runreg_runreg():
tracker_runs = load_tracker_runs()
global_runs = load_global_runs()
tracker_size = len(tracker_runs)
global_size = len(global_runs)
tracker_column_count = len(list(tracker_runs))
global_column_count = len(list(global_runs))
assert global_column_count > tracker_column_count
merged = merge_runreg_runreg(tracker_runs, global_runs)
assert len(merged) == tracker_size + global_size, "Line Count increased"
assert len(list(merged)) == global_column_count, "Column Count is maximum"
assert len(tracker_runs) == tracker_size, "Nothing changed in tracker runs"
assert len(global_runs) == global_size, "Nothing changed in global runs"
assert global_column_count > tracker_column_count
def test_reference_cost():
run_number = 315322
ref_run_number = 315705
expected_cost = 0.130825
tracker_runs = load_tracker_runs()
tkdqmdoctor_runs = load_tkdqmdoctor_runs()
runs = merge_runreg_tkdqmdoc(tracker_runs, tkdqmdoctor_runs)
runs.set_index(["run_number", "reco"], inplace=True)
assert runs.loc[(run_number, "prompt"),
"reference_run_number"] == ref_run_number
matrix = extract_tracking_map_content(
load_tracking_map(run_number, "prompt"))
ref_matrix = extract_tracking_map_content(
load_tracking_map(ref_run_number, "prompt"))
assert math.isclose(reference_cost(matrix, ref_matrix),
expected_cost,
abs_tol=0.01)
def test_run_numbers():
tracker_runs = load_tracker_runs()
runs = tracker_runs.pipe(filter_run_number_range, 313181, 313183)
assert set([313181, 313182, 313183]) == set(runs.pipe(extract_run_numbers))
def test_plot_pairs():
tracker_runs = load_tracker_runs()
plot_pairs(tracker_runs, show=SHOW_PLOTS)
