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[pre-commit.ci] pre-commit autoupdate #1295

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[pre-commit.ci] pre-commit autoupdate #1295

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d3086ed
[pre-commit.ci] pre-commit autoupdate
pre-commit-ci[bot] Dec 18, 2023
12a2053
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Dec 18, 2023
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4 changes: 2 additions & 2 deletions .pre-commit-config.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ repos:
- id: check-added-large-files

- repo: https://github.com/psf/black
rev: 23.11.0
rev: 23.12.0
hooks:
- id: black
args: [--safe, --line-length=100, --preview]
Expand All @@ -24,7 +24,7 @@ repos:
- id: docformatter

- repo: https://github.com/pre-commit/mirrors-mypy
rev: v1.7.0
rev: v1.7.1
hooks:
- id: mypy
additional_dependencies: [
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6 changes: 3 additions & 3 deletions bin/restrax
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Expand Up @@ -315,9 +315,9 @@ class ReStrax(daq_core.DataBases):
self.log.info("No new work, looking for previously failed runs")
# Look for work which we tried before (and has a restrax field)
query.pop("restrax")
query.update({
"restrax.n_tries": {"$lt": self.max_tries + 1}, "restrax.state": {"$ne": "done"}
})
query.update(
{"restrax.n_tries": {"$lt": self.max_tries + 1}, "restrax.state": {"$ne": "done"}}
)
run_doc = self.run_coll.find_one(query, **kw)

if run_doc is not None:
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6 changes: 3 additions & 3 deletions notebooks/tutorials/pulse_analysis.ipynb
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Expand Up @@ -767,9 +767,9 @@
"areas = rr[\"data\"][:, 40:70].sum(axis=1)\n",
"channels = rr[\"channel\"]\n",
"\n",
"gain_ests = np.array([\n",
" np.median(areas[channels == pmt]) for pmt in tqdm(np.arange(straxen.n_tpc_pmts))\n",
"])"
"gain_ests = np.array(\n",
" [np.median(areas[channels == pmt]) for pmt in tqdm(np.arange(straxen.n_tpc_pmts))]\n",
")"
]
},
{
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6 changes: 3 additions & 3 deletions straxen/analyses/event_display.py
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Expand Up @@ -244,9 +244,9 @@ def _event_display(
_scatter_rec(event)

# Fill panels with peak/event info
for it, (ax, labels_and_unit) in enumerate([
(ax_event_info, display_event_info), (ax_peak_info, display_peak_info)
]):
for it, (ax, labels_and_unit) in enumerate(
[(ax_event_info, display_event_info), (ax_peak_info, display_peak_info)]
):
if ax is not None:
for i, (_lab, _unit) in enumerate(labels_and_unit):
coord = 0.01, 0.9 - 0.9 * i / len(labels_and_unit)
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6 changes: 3 additions & 3 deletions straxen/analyses/posrec_comparison.py
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Expand Up @@ -71,9 +71,9 @@ def load_corrected_positions(
itp_tmp = straxen.InterpolatingMap(straxen.common.get_resource(map_tmp, fmt="binary"))
itp_tmp.scale_coordinates([1.0, 1.0, -drift_speed])

orig_pos = np.vstack([
events[f"{s2_pre}s2_x_{algo}"], events[f"{s2_pre}s2_y_{algo}"], z_obs
]).T
orig_pos = np.vstack(
[events[f"{s2_pre}s2_x_{algo}"], events[f"{s2_pre}s2_y_{algo}"], z_obs]
).T
r_obs = np.linalg.norm(orig_pos[:, :2], axis=1)
delta_r = itp_tmp(orig_pos)
z_obs = z_obs + drift_speed * drift_time_gate
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14 changes: 8 additions & 6 deletions straxen/contexts.py
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Expand Up @@ -291,12 +291,14 @@ def xenonnt_online(
# newer than 8796 are not affected. See:
# https://github.com/XENONnT/straxen/pull/166 and
# https://xe1t-wiki.lngs.infn.it/doku.php?id=xenon:xenonnt:dsg:daq:sector_swap
st.set_context_config({
"apply_data_function": (
straxen.remap_old,
straxen.check_loading_allowed,
)
})
st.set_context_config(
{
"apply_data_function": (
straxen.remap_old,
straxen.check_loading_allowed,
)
}
)
if _context_config_overwrite is not None:
warnings.warn(
f"_context_config_overwrite is deprecated, please pass to context as kwargs",
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12 changes: 5 additions & 7 deletions straxen/holoviews_utils.py
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Expand Up @@ -436,13 +436,11 @@ def _make_title(self, ind):
start_ns = start - (start // 10**9) * 10**9
end = self.df_event_time.loc[ind, "endtime"]
end_ns = end - start + start_ns
return "".join(
(
f"##Event {ind} from run {self.run_id}\n",
f"##Recorded at ({date[:10]} {date[10:]}) UTC ",
f"{start_ns} ns - {end_ns} ns",
)
)
return "".join((
f"##Event {ind} from run {self.run_id}\n",
f"##Recorded at ({date[:10]} {date[10:]}) UTC ",
f"{start_ns} ns - {end_ns} ns",
))


def plot_tpc_circle(radius):
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6 changes: 3 additions & 3 deletions straxen/mini_analysis.py
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Expand Up @@ -135,9 +135,9 @@ def wrapped_f(context: strax.Context, run_id: str, **kwargs):
if kwargs.get("time_range") is None:
scr = None
else:
scr = tuple([
(t - kwargs["t_reference"]) / int(1e9) for t in kwargs["time_range"]
])
scr = tuple(
[(t - kwargs["t_reference"]) / int(1e9) for t in kwargs["time_range"]]
)
kwargs.setdefault("seconds_range", scr)

kwargs.setdefault("run_id", run_id)
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6 changes: 3 additions & 3 deletions straxen/plugins/aqmon_hits/aqmon_hits.py
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Expand Up @@ -136,9 +136,9 @@ def find_aqmon_hits_per_channel(self, records):
aqmon_hits = strax.find_hits(records[~is_artificial], min_amplitude=aqmon_thresholds)

if np.sum(is_artificial):
aqmon_hits = np.concatenate([
aqmon_hits, self.get_deadtime_hits(records[is_artificial])
])
aqmon_hits = np.concatenate(
[aqmon_hits, self.get_deadtime_hits(records[is_artificial])]
)
return aqmon_hits

def get_deadtime_hits(self, artificial_deadtime):
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20 changes: 8 additions & 12 deletions straxen/plugins/events/event_ambience.py
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Expand Up @@ -24,18 +24,14 @@ def origin_dtype(self):
def infer_dtype(self):
dtype = []
for ambience in self.origin_dtype:
dtype.append(
(
(f"Number of {' '.join(ambience.split('_'))} main S1", f"s1_n_{ambience}"),
np.int16,
)
)
dtype.append(
(
(f"Number of {' '.join(ambience.split('_'))} main S2", f"s2_n_{ambience}"),
np.int16,
)
)
dtype.append((
(f"Number of {' '.join(ambience.split('_'))} main S1", f"s1_n_{ambience}"),
np.int16,
))
dtype.append((
(f"Number of {' '.join(ambience.split('_'))} main S2", f"s2_n_{ambience}"),
np.int16,
))
dtype += strax.time_fields
return dtype

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30 changes: 12 additions & 18 deletions straxen/plugins/events/event_area_per_channel.py
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Expand Up @@ -37,24 +37,18 @@ def infer_dtype(self):
# populating APC
ptypes = ["s1", "s2", "alt_s1", "alt_s2"]
for type_ in ptypes:
dtype += [
(
(f"Area per channel for {infoline[type_]}", f"{type_}_area_per_channel"),
pfields_["area_per_channel"][0],
)
]
dtype += [
(
(f"Length of the interval in samples for {infoline[type_]}", f"{type_}_length"),
pfields_["length"][0],
)
]
dtype += [
(
(f"Width of one sample for {infoline[type_]} [ns]", f"{type_}_dt"),
pfields_["dt"][0],
)
]
dtype += [(
(f"Area per channel for {infoline[type_]}", f"{type_}_area_per_channel"),
pfields_["area_per_channel"][0],
)]
dtype += [(
(f"Length of the interval in samples for {infoline[type_]}", f"{type_}_length"),
pfields_["length"][0],
)]
dtype += [(
(f"Width of one sample for {infoline[type_]} [ns]", f"{type_}_dt"),
pfields_["dt"][0],
)]
# populating S1 n channel properties
n_channel_dtype = [
(("Main S1 count of contributing PMTs", "s1_n_channels"), np.int16),
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67 changes: 27 additions & 40 deletions straxen/plugins/events/event_positions.py
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Expand Up @@ -87,50 +87,37 @@ def infer_dtype(self):
naive_pos = []
fdc_pos = []
for j in "r z".split():
naive_pos += [
(
f"{j}_naive",
np.float32,
f"Main interaction {j}-position with observed position (cm)",
)
]
fdc_pos += [
(
f"{j}_field_distortion_correction",
np.float32,
f"Correction added to {j}_naive for field distortion (cm)",
)
]
naive_pos += [(
f"{j}_naive",
np.float32,
f"Main interaction {j}-position with observed position (cm)",
)]
fdc_pos += [(
f"{j}_field_distortion_correction",
np.float32,
f"Correction added to {j}_naive for field distortion (cm)",
)]
for s_i in [1, 2]:
naive_pos += [
(
f"alt_s{s_i}_{j}_naive",
np.float32,
(
f"Alternative S{s_i} interaction (rel. main S{3 - s_i}) {j}-position"
" with observed position (cm)"
),
)
]
fdc_pos += [
(
f"alt_s{s_i}_{j}_field_distortion_correction",
np.float32,
f"Correction added to alt_s{s_i}_{j}_naive for field distortion (cm)",
)
]
dtype += naive_pos + fdc_pos
for s_i in [1, 2]:
dtype += [
(
f"alt_s{s_i}_theta",
naive_pos += [(
f"alt_s{s_i}_{j}_naive",
np.float32,
(
f"Alternative S{s_i} (rel. main S{3 - s_i}) interaction angular position"
" (radians)"
f"Alternative S{s_i} interaction (rel. main S{3 - s_i}) {j}-position"
" with observed position (cm)"
),
)
]
)]
fdc_pos += [(
f"alt_s{s_i}_{j}_field_distortion_correction",
np.float32,
f"Correction added to alt_s{s_i}_{j}_naive for field distortion (cm)",
)]
dtype += naive_pos + fdc_pos
for s_i in [1, 2]:
dtype += [(
f"alt_s{s_i}_theta",
np.float32,
f"Alternative S{s_i} (rel. main S{3 - s_i}) interaction angular position (radians)",
)]

dtype += [("theta", np.float32, f"Main interaction angular position (radians)")]
return dtype + strax.time_fields
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94 changes: 41 additions & 53 deletions straxen/plugins/events/event_shadow.py
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Expand Up @@ -25,80 +25,68 @@ def infer_dtype(self):
# previous S2 can cast both time & position shadow
for key in ["s1_time_shadow", "s2_time_shadow", "s2_position_shadow"]:
type_str, tp_desc, _ = key.split("_")
dtype.append(
dtype.append((
(
(
(
f"largest {tp_desc} shadow casting from previous {type_str} to"
f" {main_peak_desc} [PE/ns]"
),
f"{main_peak}shadow_{key}",
f"largest {tp_desc} shadow casting from previous {type_str} to"
f" {main_peak_desc} [PE/ns]"
),
np.float32,
)
)
dtype.append(
f"{main_peak}shadow_{key}",
),
np.float32,
))
dtype.append((
(
(
(
f"time difference from the previous {type_str} casting largest"
f" {tp_desc} shadow to {main_peak_desc} [ns]"
),
f"{main_peak}dt_{key}",
f"time difference from the previous {type_str} casting largest"
f" {tp_desc} shadow to {main_peak_desc} [ns]"
),
np.int64,
)
)
f"{main_peak}dt_{key}",
),
np.int64,
))
# Only previous S2 peaks have (x,y)
if "s2" in key:
dtype.append(
dtype.append((
(
(
(
f"x of previous s2 peak casting largest {tp_desc} shadow on"
f" {main_peak_desc} [cm]"
),
f"{main_peak}x_{key}",
f"x of previous s2 peak casting largest {tp_desc} shadow on"
f" {main_peak_desc} [cm]"
),
np.float32,
)
)
dtype.append(
f"{main_peak}x_{key}",
),
np.float32,
))
dtype.append((
(
(
(
f"y of previous s2 peak casting largest {tp_desc} shadow on"
f" {main_peak_desc} [cm]"
),
f"{main_peak}y_{key}",
f"y of previous s2 peak casting largest {tp_desc} shadow on"
f" {main_peak_desc} [cm]"
),
np.float32,
)
)
f"{main_peak}y_{key}",
),
np.float32,
))
# Only time shadow gives the nearest large peak
if "time" in key:
dtype.append(
dtype.append((
(
(
(
f"time difference from the nearest previous large {type_str} to"
f" {main_peak_desc} [ns]"
),
f"{main_peak}nearest_dt_{type_str}",
f"time difference from the nearest previous large {type_str} to"
f" {main_peak_desc} [ns]"
),
np.int64,
)
)
f"{main_peak}nearest_dt_{type_str}",
),
np.int64,
))
# Also record the PDF of HalfCauchy when calculating S2 position shadow
dtype.append(
dtype.append((
(
(
f"PDF describing correlation between previous s2 and {main_peak_desc}",
f"{main_peak}pdf_s2_position_shadow",
),
np.float32,
)
)
f"PDF describing correlation between previous s2 and {main_peak_desc}",
f"{main_peak}pdf_s2_position_shadow",
),
np.float32,
))
dtype += strax.time_fields
return dtype

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