Merge branch 'develop' of ssh://kuhl-mann.de/jkuhl/corrlib into develop
This commit is contained in:
commit
05d4f904ae
19 changed files with 1452 additions and 171 deletions
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|
@ -1,15 +1,16 @@
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||||||
from typing import Optional
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from typing import Optional
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import typer
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import typer
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from corrlib import __app_name__
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from corrlib import __app_name__
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|
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from .initialization import create
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from .initialization import create
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from .toml import import_tomls, update_project, reimport_project
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from .toml import import_tomls, update_project, reimport_project
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from .find import find_record, list_projects
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from .find import find_record, list_projects, list_ensembles, get_stat
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from .tools import str2list
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from .tools import str2list
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from .main import update_aliases
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from .main import update_aliases
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from .meas_io import drop_cache as mio_drop_cache
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from .meas_io import drop_cache as mio_drop_cache
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from .meas_io import load_record as mio_load_record
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from .integrity import full_integrity_check
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import os
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import os
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from pyerrors import Corr
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from importlib.metadata import version
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from importlib.metadata import version
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from pathlib import Path
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from pathlib import Path
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@ -26,7 +27,7 @@ def _version_callback(value: bool) -> None:
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@app.command()
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@app.command()
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def update(
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def update(
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path: Path = typer.Option(
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path: Path = typer.Option(
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Path('./corrlib'),
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Path('.'),
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"--dataset",
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"--dataset",
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"-d",
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"-d",
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),
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),
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@ -42,7 +43,7 @@ def update(
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@app.command()
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@app.command()
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def lister(
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def lister(
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path: Path = typer.Option(
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path: Path = typer.Option(
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Path('./corrlib'),
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Path('.'),
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"--dataset",
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"--dataset",
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"-d",
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"-d",
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),
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),
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@ -53,15 +54,15 @@ def lister(
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"""
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"""
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if entities in ['ensembles', 'Ensembles','ENSEMBLES']:
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if entities in ['ensembles', 'Ensembles','ENSEMBLES']:
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print("Ensembles:")
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print("Ensembles:")
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for item in os.listdir(path / "archive"):
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ensemble_results = list_ensembles(path)
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if os.path.isdir(path / "archive" / item):
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for e in ensemble_results:
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print(item)
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print(e)
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elif entities == 'projects':
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elif entities == 'projects':
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results = list_projects(path)
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project_results = list_projects(path)
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print("Projects:")
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print("Projects:")
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header = "UUID".ljust(37) + "| Aliases"
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header = "UUID".ljust(37) + "| Aliases"
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print(header)
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print(header)
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for project in results:
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for project in project_results:
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if project[1] is not None:
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if project[1] is not None:
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aliases = " | ".join(str2list(project[1]))
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aliases = " | ".join(str2list(project[1]))
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else:
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else:
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@ -73,7 +74,7 @@ def lister(
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@app.command()
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@app.command()
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def alias_add(
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def alias_add(
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path: Path = typer.Option(
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path: Path = typer.Option(
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Path('./corrlib'),
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Path('.'),
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"--dataset",
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"--dataset",
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"-d",
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"-d",
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),
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),
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|
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@ -91,7 +92,7 @@ def alias_add(
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@app.command()
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@app.command()
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def find(
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def find(
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path: Path = typer.Option(
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path: Path = typer.Option(
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Path('./corrlib'),
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Path('.'),
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"--dataset",
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"--dataset",
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"-d",
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"-d",
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),
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),
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|
|
@ -105,12 +106,19 @@ def find(
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),
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),
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) -> None:
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) -> None:
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"""
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"""
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Find a record in the backlog at hand. Through specifying it's ensemble and the measured correlator.
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Find a record in the given backlog.
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"""
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"""
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results = find_record(path, ensemble, corr, code)
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results = find_record(path, ensemble, corr, code)
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if results.empty:
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|
return
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if arg == 'all':
|
if arg == 'all':
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print(results)
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print(results)
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else:
|
else:
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if arg == 'stat':
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for r in results['path'].values:
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stat = get_stat(path, r)
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print(stat)
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return
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for r in results[arg].values:
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for r in results[arg].values:
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print(r)
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print(r)
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|
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|
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@ -118,7 +126,7 @@ def find(
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@app.command()
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@app.command()
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def stat(
|
def stat(
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path: Path = typer.Option(
|
path: Path = typer.Option(
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Path('./corrlib'),
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Path('.'),
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"--dataset",
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"--dataset",
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"-d",
|
"-d",
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),
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),
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|
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@ -127,18 +135,28 @@ def stat(
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"""
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"""
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Show the statistics of a given record.
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Show the statistics of a given record.
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"""
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"""
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record = mio_load_record(path, record_id)
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statistics = get_stat(path, record_id)
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if isinstance(record, (list, Corr)):
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record = record[0]
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statistics = record.idl
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print(statistics)
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print(statistics)
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return
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return
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|
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|
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@app.command()
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def check(path: Path = typer.Option(
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|
Path('.'),
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"--dataset",
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|
"-d",
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|
),
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) -> None:
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|
"""
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Check the integrity of the repository.
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|
"""
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full_integrity_check(path)
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|
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@app.command()
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@app.command()
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def importer(
|
def importer(
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path: Path = typer.Option(
|
path: Path = typer.Option(
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Path('./corrlib'),
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Path('.'),
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"--dataset",
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"--dataset",
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"-d",
|
"-d",
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),
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),
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|
|
@ -155,13 +173,14 @@ def importer(
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"""
|
"""
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file_list = files.split(",")
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file_list = files.split(",")
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import_tomls(path, file_list, copy_file)
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import_tomls(path, file_list, copy_file)
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mio_drop_cache(path)
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return
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return
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|
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|
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@app.command()
|
@app.command()
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def reimporter(
|
def reimporter(
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path: Path = typer.Option(
|
path: Path = typer.Option(
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Path('./corrlib'),
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Path('.'),
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||||||
"--dataset",
|
"--dataset",
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||||||
"-d",
|
"-d",
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||||||
),
|
),
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|
|
@ -179,13 +198,14 @@ def reimporter(
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raise Exception("This file is not known for this project.")
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raise Exception("This file is not known for this project.")
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else:
|
else:
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reimport_project(path, uuid)
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reimport_project(path, uuid)
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|
mio_drop_cache(path)
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return
|
return
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|
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||||||
|
|
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@app.command()
|
@app.command()
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||||||
def init(
|
def init(
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path: Path = typer.Option(
|
path: Path = typer.Option(
|
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Path('./corrlib'),
|
Path('.'),
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||||||
"--dataset",
|
"--dataset",
|
||||||
"-d",
|
"-d",
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||||||
),
|
),
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|
|
@ -205,7 +225,7 @@ def init(
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@app.command()
|
@app.command()
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def drop_cache(
|
def drop_cache(
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path: Path = typer.Option(
|
path: Path = typer.Option(
|
||||||
Path('./corrlib'),
|
Path('.'),
|
||||||
"--dataset",
|
"--dataset",
|
||||||
"-d",
|
"-d",
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||||||
),
|
),
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|
|
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323
corrlib/find.py
323
corrlib/find.py
|
|
@ -6,11 +6,18 @@ import numpy as np
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from .input.implementations import codes
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from .input.implementations import codes
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from .tools import k2m, get_db_file
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from .tools import k2m, get_db_file
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from .tracker import get
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from .tracker import get
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|
from .integrity import has_valid_times
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|
from .sql import thin_sql_wrapper
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from typing import Any, Optional
|
from typing import Any, Optional
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from pathlib import Path
|
from pathlib import Path
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|
import datetime as dt
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|
from collections.abc import Callable
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|
import warnings
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||||||
|
from .meas_io import load_record
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|
from pyerrors import Corr, Obs
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|
|
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|
|
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def _project_lookup_by_alias(db: Path, alias: str) -> str:
|
def _project_lookup_by_alias(path: Path, alias: str) -> str:
|
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"""
|
"""
|
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Lookup a projects UUID by its (human-readable) alias.
|
Lookup a projects UUID by its (human-readable) alias.
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|
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|
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@ -26,11 +33,8 @@ def _project_lookup_by_alias(db: Path, alias: str) -> str:
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uuid: str
|
uuid: str
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The UUID of the project with the given alias.
|
The UUID of the project with the given alias.
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"""
|
"""
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conn = sqlite3.connect(db)
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stmt = f"SELECT * FROM 'projects' WHERE aliases = '{alias}'"
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c = conn.cursor()
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results = thin_sql_wrapper(path, stmt)
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c.execute(f"SELECT * FROM 'projects' WHERE aliases = '{alias}'")
|
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results = c.fetchall()
|
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conn.close()
|
|
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if len(results)>1:
|
if len(results)>1:
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print("Error: multiple projects found with alias " + alias)
|
print("Error: multiple projects found with alias " + alias)
|
||||||
elif len(results) == 0:
|
elif len(results) == 0:
|
||||||
|
|
@ -38,7 +42,7 @@ def _project_lookup_by_alias(db: Path, alias: str) -> str:
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return str(results[0][0])
|
return str(results[0][0])
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|
|
||||||
|
|
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def _project_lookup_by_id(db: Path, uuid: str) -> list[tuple[str, str]]:
|
def _project_lookup_by_id(path: Path, uuid: str) -> list[tuple[str, ...]]:
|
||||||
"""
|
"""
|
||||||
Return the project information available in the database by UUID.
|
Return the project information available in the database by UUID.
|
||||||
|
|
||||||
|
|
@ -54,16 +58,61 @@ def _project_lookup_by_id(db: Path, uuid: str) -> list[tuple[str, str]]:
|
||||||
results: list
|
results: list
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||||||
The row of the project in the database.
|
The row of the project in the database.
|
||||||
"""
|
"""
|
||||||
conn = sqlite3.connect(db)
|
stmt = f"SELECT * FROM 'projects' WHERE id = '{uuid}'"
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c = conn.cursor()
|
results = thin_sql_wrapper(path, stmt)
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c.execute(f"SELECT * FROM 'projects' WHERE id = '{uuid}'")
|
|
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results = c.fetchall()
|
|
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conn.close()
|
|
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return results
|
return results
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||||||
|
|
||||||
|
|
||||||
def _db_lookup(db: Path, ensemble: str, correlator_name: str, code: str, project: Optional[str]=None, parameters: Optional[str]=None,
|
def _time_filter(results: pd.DataFrame, created_before: Optional[str]=None, created_after: Optional[Any]=None, updated_before: Optional[Any]=None, updated_after: Optional[Any]=None) -> pd.DataFrame:
|
||||||
created_before: Optional[str]=None, created_after: Optional[Any]=None, updated_before: Optional[Any]=None, updated_after: Optional[Any]=None) -> pd.DataFrame:
|
"""
|
||||||
|
Filter the results from the database in terms of the creation and update times.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
results: pd.DataFrame
|
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|
The dataframe holding the unfilteres results from the database.
|
||||||
|
created_before: str
|
||||||
|
Contraint on the creation date in datetime.datetime.isoformat. Note that this is exclusive. The creation date has to be truly before the date and time given.
|
||||||
|
created_after: str
|
||||||
|
Contraint on the creation date in datetime.datetime.isoformat. Note that this is exclusive. The creation date has to be truly after the date and time given.
|
||||||
|
updated_before: str
|
||||||
|
Contraint on the creation date in datetime.datetime.isoformat. Note that this is exclusive. The date of the last update has to be truly before the date and time given.
|
||||||
|
updated_after: str
|
||||||
|
Contraint on the creation date in datetime.datetime.isoformat. Note that this is exclusive. The date of the last update has to be truly after the date and time given.
|
||||||
|
"""
|
||||||
|
drops = []
|
||||||
|
for ind in range(len(results)):
|
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|
result = results.iloc[ind]
|
||||||
|
created_at = dt.datetime.fromisoformat(result['created_at'])
|
||||||
|
updated_at = dt.datetime.fromisoformat(result['updated_at'])
|
||||||
|
db_times_valid = has_valid_times(result)
|
||||||
|
if not db_times_valid:
|
||||||
|
raise ValueError('Time stamps not valid for result with path', result["path"])
|
||||||
|
|
||||||
|
if created_before is not None:
|
||||||
|
date_created_before = dt.datetime.fromisoformat(created_before)
|
||||||
|
if date_created_before < created_at:
|
||||||
|
drops.append(ind)
|
||||||
|
continue
|
||||||
|
if created_after is not None:
|
||||||
|
date_created_after = dt.datetime.fromisoformat(created_after)
|
||||||
|
if date_created_after > created_at:
|
||||||
|
drops.append(ind)
|
||||||
|
continue
|
||||||
|
if updated_before is not None:
|
||||||
|
date_updated_before = dt.datetime.fromisoformat(updated_before)
|
||||||
|
if date_updated_before < updated_at:
|
||||||
|
drops.append(ind)
|
||||||
|
continue
|
||||||
|
if updated_after is not None:
|
||||||
|
date_updated_after = dt.datetime.fromisoformat(updated_after)
|
||||||
|
if date_updated_after > updated_at:
|
||||||
|
drops.append(ind)
|
||||||
|
continue
|
||||||
|
return results.drop(drops)
|
||||||
|
|
||||||
|
|
||||||
|
def _db_lookup(db: Path, ensemble: str, correlator_name: str, code: str, project: Optional[str]=None, parameters: Optional[str]=None) -> pd.DataFrame:
|
||||||
"""
|
"""
|
||||||
Look up a correlator record in the database by the data given to the method.
|
Look up a correlator record in the database by the data given to the method.
|
||||||
|
|
||||||
|
|
@ -105,20 +154,84 @@ def _db_lookup(db: Path, ensemble: str, correlator_name: str, code: str, project
|
||||||
search_expr += f" AND code = '{code}'"
|
search_expr += f" AND code = '{code}'"
|
||||||
if parameters:
|
if parameters:
|
||||||
search_expr += f" AND parameters = '{parameters}'"
|
search_expr += f" AND parameters = '{parameters}'"
|
||||||
if created_before:
|
|
||||||
search_expr += f" AND created_at < '{created_before}'"
|
|
||||||
if created_after:
|
|
||||||
search_expr += f" AND created_at > '{created_after}'"
|
|
||||||
if updated_before:
|
|
||||||
search_expr += f" AND updated_at < '{updated_before}'"
|
|
||||||
if updated_after:
|
|
||||||
search_expr += f" AND updated_at > '{updated_after}'"
|
|
||||||
conn = sqlite3.connect(db)
|
conn = sqlite3.connect(db)
|
||||||
results = pd.read_sql(search_expr, conn)
|
results = pd.read_sql(search_expr, conn)
|
||||||
conn.close()
|
conn.close()
|
||||||
return results
|
return results
|
||||||
|
|
||||||
|
|
||||||
|
def _sfcf_drop(param: dict[str, Any], **kwargs: Any) -> bool:
|
||||||
|
if 'offset' in kwargs:
|
||||||
|
if kwargs.get('offset') != param['offset']:
|
||||||
|
return True
|
||||||
|
if 'quark_kappas' in kwargs:
|
||||||
|
kappas = kwargs['quark_kappas']
|
||||||
|
if (not np.isclose(kappas[0], param['quarks'][0]['mass']) or not np.isclose(kappas[1], param['quarks'][1]['mass'])):
|
||||||
|
return True
|
||||||
|
if 'quark_masses' in kwargs:
|
||||||
|
masses = kwargs['quark_masses']
|
||||||
|
if (not np.isclose(masses[0], k2m(param['quarks'][0]['mass'])) or not np.isclose(masses[1], k2m(param['quarks'][1]['mass']))):
|
||||||
|
return True
|
||||||
|
if 'qk1' in kwargs:
|
||||||
|
quark_kappa1 = kwargs['qk1']
|
||||||
|
if not isinstance(quark_kappa1, list):
|
||||||
|
if (not np.isclose(quark_kappa1, param['quarks'][0]['mass'])):
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
if len(quark_kappa1) == 2:
|
||||||
|
if (quark_kappa1[0] > param['quarks'][0]['mass']) or (quark_kappa1[1] < param['quarks'][0]['mass']):
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
raise ValueError("quark_kappa1 has to have length 2")
|
||||||
|
if 'qk2' in kwargs:
|
||||||
|
quark_kappa2 = kwargs['qk2']
|
||||||
|
if not isinstance(quark_kappa2, list):
|
||||||
|
if (not np.isclose(quark_kappa2, param['quarks'][1]['mass'])):
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
if len(quark_kappa2) == 2:
|
||||||
|
if (quark_kappa2[0] > param['quarks'][1]['mass']) or (quark_kappa2[1] < param['quarks'][1]['mass']):
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
raise ValueError("quark_kappa2 has to have length 2")
|
||||||
|
if 'qm1' in kwargs:
|
||||||
|
quark_mass1 = kwargs['qm1']
|
||||||
|
if not isinstance(quark_mass1, list):
|
||||||
|
if (not np.isclose(quark_mass1, k2m(param['quarks'][0]['mass']))):
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
if len(quark_mass1) == 2:
|
||||||
|
if (quark_mass1[0] > k2m(param['quarks'][0]['mass'])) or (quark_mass1[1] < k2m(param['quarks'][0]['mass'])):
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
raise ValueError("quark_mass1 has to have length 2")
|
||||||
|
if 'qm2' in kwargs:
|
||||||
|
quark_mass2 = kwargs['qm2']
|
||||||
|
if not isinstance(quark_mass2, list):
|
||||||
|
if (not np.isclose(quark_mass2, k2m(param['quarks'][1]['mass']))):
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
if len(quark_mass2) == 2:
|
||||||
|
if (quark_mass2[0] > k2m(param['quarks'][1]['mass'])) or (quark_mass2[1] < k2m(param['quarks'][1]['mass'])):
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
raise ValueError("quark_mass2 has to have length 2")
|
||||||
|
if 'quark_thetas' in kwargs:
|
||||||
|
quark_thetas = kwargs['quark_thetas']
|
||||||
|
if (quark_thetas[0] != param['quarks'][0]['thetas'] and quark_thetas[1] != param['quarks'][1]['thetas']) or (quark_thetas[0] != param['quarks'][1]['thetas'] and quark_thetas[1] != param['quarks'][0]['thetas']):
|
||||||
|
return True
|
||||||
|
# careful, this is not save, when multiple contributions are present!
|
||||||
|
if 'wf1' in kwargs:
|
||||||
|
wf1 = kwargs['wf1']
|
||||||
|
if not (np.isclose(wf1[0][0], param['wf1'][0][0], 1e-8) and np.isclose(wf1[0][1][0], param['wf1'][0][1][0], 1e-8) and np.isclose(wf1[0][1][1], param['wf1'][0][1][1], 1e-8)):
|
||||||
|
return True
|
||||||
|
if 'wf2' in kwargs:
|
||||||
|
wf2 = kwargs['wf2']
|
||||||
|
if not (np.isclose(wf2[0][0], param['wf2'][0][0], 1e-8) and np.isclose(wf2[0][1][0], param['wf2'][0][1][0], 1e-8) and np.isclose(wf2[0][1][1], param['wf2'][0][1][1], 1e-8)):
|
||||||
|
return True
|
||||||
|
return False
|
||||||
|
|
||||||
|
|
||||||
def sfcf_filter(results: pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
|
def sfcf_filter(results: pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
|
||||||
r"""
|
r"""
|
||||||
Filter method for the Database entries holding SFCF calculations.
|
Filter method for the Database entries holding SFCF calculations.
|
||||||
|
|
@ -136,9 +249,9 @@ def sfcf_filter(results: pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
|
||||||
qk2: float, optional
|
qk2: float, optional
|
||||||
Mass parameter $\kappa_2$ of the first quark.
|
Mass parameter $\kappa_2$ of the first quark.
|
||||||
qm1: float, optional
|
qm1: float, optional
|
||||||
Bare quak mass $m_1$ of the first quark.
|
Bare quark mass $m_1$ of the first quark.
|
||||||
qm2: float, optional
|
qm2: float, optional
|
||||||
Bare quak mass $m_1$ of the first quark.
|
Bare quark mass $m_2$ of the first quark.
|
||||||
quarks_thetas: list[list[float]], optional
|
quarks_thetas: list[list[float]], optional
|
||||||
wf1: optional
|
wf1: optional
|
||||||
wf2: optional
|
wf2: optional
|
||||||
|
|
@ -148,101 +261,81 @@ def sfcf_filter(results: pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
|
||||||
results: pd.DataFrame
|
results: pd.DataFrame
|
||||||
The filtered DataFrame, only holding the records that fit to the parameters given.
|
The filtered DataFrame, only holding the records that fit to the parameters given.
|
||||||
"""
|
"""
|
||||||
|
|
||||||
drops = []
|
drops = []
|
||||||
for ind in range(len(results)):
|
for ind in range(len(results)):
|
||||||
result = results.iloc[ind]
|
result = results.iloc[ind]
|
||||||
param = json.loads(result['parameters'])
|
param = json.loads(result['parameters'])
|
||||||
if 'offset' in kwargs:
|
if _sfcf_drop(param, **kwargs):
|
||||||
if kwargs.get('offset') != param['offset']:
|
drops.append(ind)
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
if 'quark_kappas' in kwargs:
|
|
||||||
kappas = kwargs['quark_kappas']
|
|
||||||
if (not np.isclose(kappas[0], param['quarks'][0]['mass']) or not np.isclose(kappas[1], param['quarks'][1]['mass'])):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
if 'quark_masses' in kwargs:
|
|
||||||
masses = kwargs['quark_masses']
|
|
||||||
if (not np.isclose(masses[0], k2m(param['quarks'][0]['mass'])) or not np.isclose(masses[1], k2m(param['quarks'][1]['mass']))):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
if 'qk1' in kwargs:
|
|
||||||
quark_kappa1 = kwargs['qk1']
|
|
||||||
if not isinstance(quark_kappa1, list):
|
|
||||||
if (not np.isclose(quark_kappa1, param['quarks'][0]['mass'])):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
else:
|
|
||||||
if len(quark_kappa1) == 2:
|
|
||||||
if (quark_kappa1[0] > param['quarks'][0]['mass']) or (quark_kappa1[1] < param['quarks'][0]['mass']):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
if 'qk2' in kwargs:
|
|
||||||
quark_kappa2 = kwargs['qk2']
|
|
||||||
if not isinstance(quark_kappa2, list):
|
|
||||||
if (not np.isclose(quark_kappa2, param['quarks'][1]['mass'])):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
else:
|
|
||||||
if len(quark_kappa2) == 2:
|
|
||||||
if (quark_kappa2[0] > param['quarks'][1]['mass']) or (quark_kappa2[1] < param['quarks'][1]['mass']):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
if 'qm1' in kwargs:
|
|
||||||
quark_mass1 = kwargs['qm1']
|
|
||||||
if not isinstance(quark_mass1, list):
|
|
||||||
if (not np.isclose(quark_mass1, k2m(param['quarks'][0]['mass']))):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
else:
|
|
||||||
if len(quark_mass1) == 2:
|
|
||||||
if (quark_mass1[0] > k2m(param['quarks'][0]['mass'])) or (quark_mass1[1] < k2m(param['quarks'][0]['mass'])):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
if 'qm2' in kwargs:
|
|
||||||
quark_mass2 = kwargs['qm2']
|
|
||||||
if not isinstance(quark_mass2, list):
|
|
||||||
if (not np.isclose(quark_mass2, k2m(param['quarks'][1]['mass']))):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
else:
|
|
||||||
if len(quark_mass2) == 2:
|
|
||||||
if (quark_mass2[0] > k2m(param['quarks'][1]['mass'])) or (quark_mass2[1] < k2m(param['quarks'][1]['mass'])):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
if 'quark_thetas' in kwargs:
|
|
||||||
quark_thetas = kwargs['quark_thetas']
|
|
||||||
if (quark_thetas[0] != param['quarks'][0]['thetas'] and quark_thetas[1] != param['quarks'][1]['thetas']) or (quark_thetas[0] != param['quarks'][1]['thetas'] and quark_thetas[1] != param['quarks'][0]['thetas']):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
# careful, this is not save, when multiple contributions are present!
|
|
||||||
if 'wf1' in kwargs:
|
|
||||||
wf1 = kwargs['wf1']
|
|
||||||
if not (np.isclose(wf1[0][0], param['wf1'][0][0], 1e-8) and np.isclose(wf1[0][1][0], param['wf1'][0][1][0], 1e-8) and np.isclose(wf1[0][1][1], param['wf1'][0][1][1], 1e-8)):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
if 'wf2' in kwargs:
|
|
||||||
wf2 = kwargs['wf2']
|
|
||||||
if not (np.isclose(wf2[0][0], param['wf2'][0][0], 1e-8) and np.isclose(wf2[0][1][0], param['wf2'][0][1][0], 1e-8) and np.isclose(wf2[0][1][1], param['wf2'][0][1][1], 1e-8)):
|
|
||||||
drops.append(ind)
|
|
||||||
continue
|
|
||||||
return results.drop(drops)
|
return results.drop(drops)
|
||||||
|
|
||||||
|
|
||||||
|
def openQCD_filter(results:pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
|
||||||
|
"""
|
||||||
|
Filter for parameters of openQCD.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
results: pd.DataFrame
|
||||||
|
The unfiltered list of results from the database.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
results: pd.DataFrame
|
||||||
|
The filtered results.
|
||||||
|
|
||||||
|
"""
|
||||||
|
warnings.warn("A filter for openQCD parameters is no implemented yet.", Warning)
|
||||||
|
|
||||||
|
return results
|
||||||
|
|
||||||
|
|
||||||
|
def _code_filter(results: pd.DataFrame, code: str, **kwargs: Any) -> pd.DataFrame:
|
||||||
|
"""
|
||||||
|
Abstraction of the filters for the different codes that are available.
|
||||||
|
At the moment, only openQCD and SFCF are known.
|
||||||
|
The possible key words for the parameters can be seen in the descriptionso f the code-specific filters.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
results: pd.DataFrame
|
||||||
|
The unfiltered list of results from the database.
|
||||||
|
code: str
|
||||||
|
The name of the code that produced the record at hand.
|
||||||
|
kwargs:
|
||||||
|
The keyworkd args that are handed over to the code-specific filters.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
results: pd.DataFrame
|
||||||
|
The filtered results.
|
||||||
|
"""
|
||||||
|
if code == "sfcf":
|
||||||
|
return sfcf_filter(results, **kwargs)
|
||||||
|
elif code == "openQCD":
|
||||||
|
return openQCD_filter(results, **kwargs)
|
||||||
|
else:
|
||||||
|
raise ValueError(f"Code {code} is not known.")
|
||||||
|
|
||||||
|
|
||||||
def find_record(path: Path, ensemble: str, correlator_name: str, code: str, project: Optional[str]=None, parameters: Optional[str]=None,
|
def find_record(path: Path, ensemble: str, correlator_name: str, code: str, project: Optional[str]=None, parameters: Optional[str]=None,
|
||||||
created_before: Optional[str]=None, created_after: Optional[str]=None, updated_before: Optional[str]=None, updated_after: Optional[str]=None, revision: Optional[str]=None, **kwargs: Any) -> pd.DataFrame:
|
created_before: Optional[str]=None, created_after: Optional[str]=None, updated_before: Optional[str]=None, updated_after: Optional[str]=None,
|
||||||
|
revision: Optional[str]=None,
|
||||||
|
customFilter: Optional[Callable[[pd.DataFrame], pd.DataFrame]] = None,
|
||||||
|
**kwargs: Any) -> pd.DataFrame:
|
||||||
|
path = Path(path)
|
||||||
db_file = get_db_file(path)
|
db_file = get_db_file(path)
|
||||||
db = path / db_file
|
db = path / db_file
|
||||||
if code not in codes:
|
if code not in codes:
|
||||||
raise ValueError("Code " + code + "unknown, take one of the following:" + ", ".join(codes))
|
raise ValueError("Code " + code + "unknown, take one of the following:" + ", ".join(codes))
|
||||||
get(path, db_file)
|
get(path, db_file)
|
||||||
results = _db_lookup(db, ensemble, correlator_name,code, project, parameters=parameters, created_before=created_before, created_after=created_after, updated_before=updated_before, updated_after=updated_after)
|
results = _db_lookup(db, ensemble, correlator_name,code, project, parameters=parameters)
|
||||||
if code == "sfcf":
|
if any([arg is not None for arg in [created_before, created_after, updated_before, updated_after]]):
|
||||||
results = sfcf_filter(results, **kwargs)
|
results = _time_filter(results, created_before, created_after, updated_before, updated_after)
|
||||||
elif code == "openQCD":
|
results = _code_filter(results, code, **kwargs)
|
||||||
pass
|
if customFilter is not None:
|
||||||
else:
|
results = customFilter(results)
|
||||||
raise Exception
|
|
||||||
print("Found " + str(len(results)) + " result" + ("s" if len(results)>1 else ""))
|
print("Found " + str(len(results)) + " result" + ("s" if len(results)>1 else ""))
|
||||||
return results.reset_index()
|
return results.reset_index()
|
||||||
|
|
||||||
|
|
@ -265,7 +358,7 @@ def find_project(path: Path, name: str) -> str:
|
||||||
"""
|
"""
|
||||||
db_file = get_db_file(path)
|
db_file = get_db_file(path)
|
||||||
get(path, db_file)
|
get(path, db_file)
|
||||||
return _project_lookup_by_alias(path / db_file, name)
|
return _project_lookup_by_alias(path, name)
|
||||||
|
|
||||||
|
|
||||||
def list_projects(path: Path) -> list[tuple[str, str]]:
|
def list_projects(path: Path) -> list[tuple[str, str]]:
|
||||||
|
|
@ -291,3 +384,19 @@ def list_projects(path: Path) -> list[tuple[str, str]]:
|
||||||
conn.close()
|
conn.close()
|
||||||
return results
|
return results
|
||||||
|
|
||||||
|
|
||||||
|
def list_ensembles(path: Path) -> list[str]:
|
||||||
|
res = []
|
||||||
|
for item in os.listdir(path / "archive"):
|
||||||
|
if os.path.isdir(path / "archive" / item):
|
||||||
|
res.append(item)
|
||||||
|
return res
|
||||||
|
|
||||||
|
|
||||||
|
def get_stat(path: Path, record_id: str) -> Any:
|
||||||
|
loaded_record: Obs = load_record(path, record_id)
|
||||||
|
if isinstance(loaded_record, (list, Corr)):
|
||||||
|
record: Obs = loaded_record[0]
|
||||||
|
else:
|
||||||
|
record = loaded_record
|
||||||
|
return record.idl
|
||||||
|
|
|
||||||
|
|
@ -3,6 +3,7 @@ import sqlite3
|
||||||
import os
|
import os
|
||||||
from .tracker import save, init
|
from .tracker import save, init
|
||||||
from pathlib import Path
|
from pathlib import Path
|
||||||
|
from .tools import CONFIG_FILENAME
|
||||||
|
|
||||||
|
|
||||||
def _create_db(db: Path) -> None:
|
def _create_db(db: Path) -> None:
|
||||||
|
|
@ -87,7 +88,7 @@ def _write_config(path: Path, config: ConfigParser) -> None:
|
||||||
config: ConfigParser
|
config: ConfigParser
|
||||||
The configuration to be used as a ConfigParser, e.g. generated by _create_config.
|
The configuration to be used as a ConfigParser, e.g. generated by _create_config.
|
||||||
"""
|
"""
|
||||||
with open(os.path.join(path, '.corrlib'), 'w') as configfile:
|
with open(os.path.join(path, CONFIG_FILENAME), 'w') as configfile:
|
||||||
config.write(configfile)
|
config.write(configfile)
|
||||||
return
|
return
|
||||||
|
|
||||||
|
|
|
||||||
|
|
@ -4,9 +4,12 @@ import os
|
||||||
import fnmatch
|
import fnmatch
|
||||||
from typing import Any, Optional
|
from typing import Any, Optional
|
||||||
from pathlib import Path
|
from pathlib import Path
|
||||||
|
from ..pars.openQCD import ms1
|
||||||
|
from ..pars.openQCD import qcd2
|
||||||
|
|
||||||
|
|
||||||
def read_ms1_param(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
|
|
||||||
|
def load_ms1_infile(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
|
||||||
"""
|
"""
|
||||||
Read the parameters for ms1 measurements from a parameter file in the project.
|
Read the parameters for ms1 measurements from a parameter file in the project.
|
||||||
|
|
||||||
|
|
@ -70,7 +73,7 @@ def read_ms1_param(path: Path, project: str, file_in_project: str) -> dict[str,
|
||||||
return param
|
return param
|
||||||
|
|
||||||
|
|
||||||
def read_ms3_param(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
|
def load_ms3_infile(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
|
||||||
"""
|
"""
|
||||||
Read the parameters for ms3 measurements from a parameter file in the project.
|
Read the parameters for ms3 measurements from a parameter file in the project.
|
||||||
|
|
||||||
|
|
@ -161,7 +164,8 @@ def read_rwms(path: Path, project: str, dir_in_project: str, param: dict[str, An
|
||||||
return rw_dict
|
return rw_dict
|
||||||
|
|
||||||
|
|
||||||
def extract_t0(path: Path, project: str, dir_in_project: str, param: dict[str, Any], prefix: str, dtr_read: int, xmin: int, spatial_extent: int, fit_range: int = 5, postfix: str="", names: Optional[list[str]]=None, files: Optional[list[str]]=None) -> dict[str, Any]:
|
def extract_t0(path: Path, project: str, dir_in_project: str, param: dict[str, Any], prefix: str, dtr_read: int, xmin: int, spatial_extent: int, fit_range: int = 5, postfix: str="", names: Optional[list[str]]=None, files: Optional[list[str]]=None,
|
||||||
|
r_start: list[int]=[], r_stop: list[int]=[], r_step:int=1) -> dict[str, Any]:
|
||||||
"""
|
"""
|
||||||
Extract t0 measurements from the project.
|
Extract t0 measurements from the project.
|
||||||
|
|
||||||
|
|
@ -215,6 +219,11 @@ def extract_t0(path: Path, project: str, dir_in_project: str, param: dict[str, A
|
||||||
if postfix is not None:
|
if postfix is not None:
|
||||||
kwargs['postfix'] = postfix
|
kwargs['postfix'] = postfix
|
||||||
kwargs['plot_fit'] = False
|
kwargs['plot_fit'] = False
|
||||||
|
if not r_start == []:
|
||||||
|
kwargs['r_start'] = r_start
|
||||||
|
if not r_stop == []:
|
||||||
|
kwargs['r_stop'] = r_stop
|
||||||
|
kwargs['r_step'] = r_step
|
||||||
|
|
||||||
t0 = input.extract_t0(directory,
|
t0 = input.extract_t0(directory,
|
||||||
prefix,
|
prefix,
|
||||||
|
|
@ -235,7 +244,8 @@ def extract_t0(path: Path, project: str, dir_in_project: str, param: dict[str, A
|
||||||
return t0_dict
|
return t0_dict
|
||||||
|
|
||||||
|
|
||||||
def extract_t1(path: Path, project: str, dir_in_project: str, param: dict[str, Any], prefix: str, dtr_read: int, xmin: int, spatial_extent: int, fit_range: int = 5, postfix: str = "", names: Optional[list[str]]=None, files: Optional[list[str]]=None) -> dict[str, Any]:
|
def extract_t1(path: Path, project: str, dir_in_project: str, param: dict[str, Any], prefix: str, dtr_read: int, xmin: int, spatial_extent: int, fit_range: int = 5, postfix: str = "", names: Optional[list[str]]=None, files: Optional[list[str]]=None,
|
||||||
|
r_start: list[int]=[], r_stop: list[int]=[], r_step:int=1) -> dict[str, Any]:
|
||||||
"""
|
"""
|
||||||
Extract t1 measurements from the project.
|
Extract t1 measurements from the project.
|
||||||
|
|
||||||
|
|
@ -287,6 +297,11 @@ def extract_t1(path: Path, project: str, dir_in_project: str, param: dict[str, A
|
||||||
if postfix is not None:
|
if postfix is not None:
|
||||||
kwargs['postfix'] = postfix
|
kwargs['postfix'] = postfix
|
||||||
kwargs['plot_fit'] = False
|
kwargs['plot_fit'] = False
|
||||||
|
if not r_start == []:
|
||||||
|
kwargs['r_start'] = r_start
|
||||||
|
if not r_stop == []:
|
||||||
|
kwargs['r_stop'] = r_stop
|
||||||
|
kwargs['r_step'] = r_step
|
||||||
t0 = input.extract_t0(directory,
|
t0 = input.extract_t0(directory,
|
||||||
prefix,
|
prefix,
|
||||||
dtr_read,
|
dtr_read,
|
||||||
|
|
@ -304,3 +319,51 @@ def extract_t1(path: Path, project: str, dir_in_project: str, param: dict[str, A
|
||||||
t1_dict[param["type"]] = {}
|
t1_dict[param["type"]] = {}
|
||||||
t1_dict[param["type"]][pars] = t0
|
t1_dict[param["type"]][pars] = t0
|
||||||
return t1_dict
|
return t1_dict
|
||||||
|
|
||||||
|
|
||||||
|
def load_qcd2_pars(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
|
||||||
|
"""
|
||||||
|
Thin wrapper around read_qcd2_par_file, getting the file before reading.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path of the corrlib repository.
|
||||||
|
project: str
|
||||||
|
UUID of the project of the parameter-file.
|
||||||
|
file_in_project: str
|
||||||
|
The loaction of the file in the project directory.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
par_dict: dict
|
||||||
|
The dict with the parameters read from the .par-file.
|
||||||
|
"""
|
||||||
|
fname = path / "projects" / project / file_in_project
|
||||||
|
ds = os.path.join(path, "projects", project)
|
||||||
|
dl.get(fname, dataset=ds)
|
||||||
|
return qcd2.read_qcd2_par_file(fname)
|
||||||
|
|
||||||
|
|
||||||
|
def load_ms1_parfile(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
|
||||||
|
"""
|
||||||
|
Thin wrapper around read_qcd2_ms1_par_file, getting the file before reading.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path of the corrlib repository.
|
||||||
|
project: str
|
||||||
|
UUID of the project of the parameter-file.
|
||||||
|
file_in_project: str
|
||||||
|
The loaction of the file in the project directory.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
par_dict: dict
|
||||||
|
The dict with the parameters read from the .par-file.
|
||||||
|
"""
|
||||||
|
fname = path / "projects" / project / file_in_project
|
||||||
|
ds = os.path.join(path, "projects", project)
|
||||||
|
dl.get(fname, dataset=ds)
|
||||||
|
return ms1.read_qcd2_ms1_par_file(fname)
|
||||||
|
|
|
||||||
295
corrlib/integrity.py
Normal file
295
corrlib/integrity.py
Normal file
|
|
@ -0,0 +1,295 @@
|
||||||
|
import datetime as dt
|
||||||
|
from pathlib import Path
|
||||||
|
from .tools import get_db_file, CONFIG_FILENAME
|
||||||
|
import pandas as pd
|
||||||
|
import sqlite3
|
||||||
|
from .tracker import get
|
||||||
|
import pyerrors.input.json as pj
|
||||||
|
import os
|
||||||
|
from configparser import ConfigParser
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
|
||||||
|
path_opts = ['db', 'projects_path', 'archive_path', 'toml_imports_path', 'import_scripts_path']
|
||||||
|
|
||||||
|
|
||||||
|
def has_valid_times(result: pd.Series) -> bool:
|
||||||
|
"""
|
||||||
|
Check, whether the result at hand has time-stamps that are sensible:
|
||||||
|
A recored is created first, then updated, with both times laying in the past.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
result: pd.Series
|
||||||
|
The result to check
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
b: bool
|
||||||
|
True, if the timestamps make sense.
|
||||||
|
"""
|
||||||
|
# we expect created_at <= updated_at <= now
|
||||||
|
created_at = dt.datetime.fromisoformat(result['created_at'])
|
||||||
|
updated_at = dt.datetime.fromisoformat(result['updated_at'])
|
||||||
|
if created_at > updated_at:
|
||||||
|
return False
|
||||||
|
if updated_at > dt.datetime.now():
|
||||||
|
return False
|
||||||
|
return True
|
||||||
|
|
||||||
|
def are_keys_unique(db: Path, table: str, col: str) -> bool:
|
||||||
|
"""
|
||||||
|
Check whether the strings listed in a column of a given table are unique.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
db: Path
|
||||||
|
The database to check.
|
||||||
|
table: str
|
||||||
|
The table to check.
|
||||||
|
col: str
|
||||||
|
The column to be checked for uniqueness.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
b: bool
|
||||||
|
True, if the strings are unique.
|
||||||
|
"""
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
c = conn.cursor()
|
||||||
|
c.execute(f"SELECT COUNT( DISTINCT CAST({col} AS nvarchar(4000))), COUNT({col}) FROM {table};")
|
||||||
|
results = c.fetchall()[0]
|
||||||
|
conn.close()
|
||||||
|
res = bool(results[0] == results[1])
|
||||||
|
if not res:
|
||||||
|
print("Unique:", results[0], "All:", results[1])
|
||||||
|
return res
|
||||||
|
|
||||||
|
|
||||||
|
def _list_projects(path: Path) -> list[tuple[str, str]]:
|
||||||
|
"""
|
||||||
|
List all projects known to the library.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: str
|
||||||
|
The path of the library.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
results: list[Any]
|
||||||
|
The projects known to the library.
|
||||||
|
"""
|
||||||
|
db_file = get_db_file(path)
|
||||||
|
get(path, db_file)
|
||||||
|
conn = sqlite3.connect(os.path.join(path, db_file))
|
||||||
|
c = conn.cursor()
|
||||||
|
c.execute("SELECT id,aliases FROM projects")
|
||||||
|
results = c.fetchall()
|
||||||
|
conn.close()
|
||||||
|
return results
|
||||||
|
|
||||||
|
|
||||||
|
def _list_ensembles(path: Path) -> list[str]:
|
||||||
|
res = []
|
||||||
|
for item in os.listdir(path / "archive"):
|
||||||
|
if os.path.isdir(path / "archive" / item):
|
||||||
|
res.append(item)
|
||||||
|
return res
|
||||||
|
|
||||||
|
|
||||||
|
def check_path_format(result: pd.Series, ensembles: list[str], projects: list[str]) -> None:
|
||||||
|
"""
|
||||||
|
Check whether the path of the given result has the right format.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
result: pd.Series
|
||||||
|
The result to be checked.
|
||||||
|
"""
|
||||||
|
p = result['path']
|
||||||
|
if not p.startswith('archive'):
|
||||||
|
raise ValueError(f'The path {p} does not start correctly')
|
||||||
|
|
||||||
|
meas_key = p.split('::')[1]
|
||||||
|
ensemble = p.split('/')[1]
|
||||||
|
project = p.split('/')[3].split('.')[0]
|
||||||
|
if not len(meas_key) == 64:
|
||||||
|
raise ValueError(f'meas_key of {p} is scrambled')
|
||||||
|
if ensemble not in ensembles:
|
||||||
|
raise ValueError(f'meas_key of {p} points to an unknown ensemble')
|
||||||
|
if project not in projects:
|
||||||
|
raise ValueError(f'meas_key of {p} points to an unknown project id ({project})')
|
||||||
|
if not ensemble == result['ensemble']:
|
||||||
|
raise ValueError(f'Ensemble in database and file does not match for path {p}.')
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def check_db_integrity(path: Path) -> None:
|
||||||
|
"""
|
||||||
|
Check intergrity of the database by checking the uniqueness of the record keys used to load the records
|
||||||
|
and ensuring that the timestamps of each record is sensible. Throws an error, if issues are detected.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path to the backlog-library to check.
|
||||||
|
"""
|
||||||
|
db = get_db_file(path)
|
||||||
|
|
||||||
|
if not are_keys_unique(path / db, 'backlogs', 'path'):
|
||||||
|
raise Exception("The paths the backlog table of the database links are not unique.")
|
||||||
|
|
||||||
|
search_expr = "SELECT * FROM 'backlogs'"
|
||||||
|
conn = sqlite3.connect(path / db)
|
||||||
|
results = pd.read_sql(search_expr, conn)
|
||||||
|
ensembles = _list_ensembles(path)
|
||||||
|
projects = [p[0] for p in _list_projects(path)]
|
||||||
|
|
||||||
|
for _, result in results.iterrows():
|
||||||
|
if not has_valid_times(result):
|
||||||
|
raise ValueError(f"Result with id {result[id]} has wrong time signatures.")
|
||||||
|
check_path_format(result, ensembles, projects)
|
||||||
|
return
|
||||||
|
|
||||||
|
|
||||||
|
def _check_db2paths(path: Path, meas_paths: list[str]) -> None:
|
||||||
|
"""
|
||||||
|
Check whether for each record in the given by meas_paths, we can find the data in the file as we expect.
|
||||||
|
Also check, whether there are unreachable records in the files. If either of the issues arise, throws an error.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path to the backlog-library to check.
|
||||||
|
meas_paths: list[str]
|
||||||
|
List of measurement paths to check.
|
||||||
|
"""
|
||||||
|
needed_data: dict[str, list[str]] = {}
|
||||||
|
for mpath in meas_paths:
|
||||||
|
file = mpath.split("::")[0]
|
||||||
|
if file not in needed_data.keys():
|
||||||
|
needed_data[file] = []
|
||||||
|
key = mpath.split("::")[1]
|
||||||
|
needed_data[file].append(key)
|
||||||
|
|
||||||
|
totf = len(needed_data.keys())
|
||||||
|
for i, file in enumerate(needed_data.keys()):
|
||||||
|
print(f"Check against file {i}/{totf}: {file}")
|
||||||
|
get(path, Path(file))
|
||||||
|
filedict: dict[str, Any] = pj.load_json_dict(str(path / file))
|
||||||
|
if not set(filedict.keys()).issubset(needed_data[file]):
|
||||||
|
for key in filedict.keys():
|
||||||
|
if key not in needed_data[file]:
|
||||||
|
raise ValueError(f"Found unintended key {key} in file {file}.")
|
||||||
|
if not set(needed_data[file]).issubset(filedict.keys()):
|
||||||
|
for key in needed_data[file]:
|
||||||
|
if key not in filedict.keys():
|
||||||
|
raise ValueError(f"Did not find data for key {key} that should be in file {file}.")
|
||||||
|
return
|
||||||
|
|
||||||
|
|
||||||
|
def check_db_file_links(path: Path) -> None:
|
||||||
|
"""
|
||||||
|
Check whether for each record in the given correlator library, we can find the data in the file as we expect.
|
||||||
|
Also check, whether there are unreachable records in the files. If either of the issues arise, throws an error.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path to the backlog-library to check.
|
||||||
|
"""
|
||||||
|
db = get_db_file(path)
|
||||||
|
search_expr = "SELECT path FROM 'backlogs'"
|
||||||
|
conn = sqlite3.connect(path / db)
|
||||||
|
results = pd.read_sql(search_expr, conn)['path'].values
|
||||||
|
_check_db2paths(path, list(results))
|
||||||
|
|
||||||
|
|
||||||
|
def check_path_and_config(path: Path) -> None:
|
||||||
|
"""
|
||||||
|
Check whether the given path exists and the cinfigureation file can be found.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path to the backlog-library to check.
|
||||||
|
"""
|
||||||
|
if not os.path.exists(path):
|
||||||
|
raise FileNotFoundError(f"Corrlib path {path} does not exist.")
|
||||||
|
config_path = path / CONFIG_FILENAME
|
||||||
|
if not os.path.exists(config_path):
|
||||||
|
raise FileNotFoundError(f"Configuration file {config_path} not found.")
|
||||||
|
|
||||||
|
|
||||||
|
def check_config_validity(path: Path) -> None:
|
||||||
|
"""
|
||||||
|
Check whether the configuration file of the given corrlib-dataset path is valid.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path to the backlog-library to check.
|
||||||
|
"""
|
||||||
|
config = ConfigParser()
|
||||||
|
config_path = path / CONFIG_FILENAME
|
||||||
|
if os.path.exists(config_path):
|
||||||
|
config.read(config_path)
|
||||||
|
else:
|
||||||
|
raise FileNotFoundError("Configuration file not found.")
|
||||||
|
|
||||||
|
if config.has_section('core'):
|
||||||
|
core_opts = ['version', 'tracker', 'cached']
|
||||||
|
has_core_opts = [config.has_option('core', opt) for opt in core_opts]
|
||||||
|
if not all(has_core_opts):
|
||||||
|
raise ValueError("One of the options in the 'core' section ('version', 'tracker', 'cached') is missing.")
|
||||||
|
|
||||||
|
if config.has_section('paths'):
|
||||||
|
has_path_opts = [config.has_option('paths', opt) for opt in path_opts]
|
||||||
|
if not all(has_path_opts):
|
||||||
|
raise ValueError("One of the options in the 'path' section ('db', 'projects_path', 'archive_path', 'toml_imports_path', 'import_scripts_path') is missing.")
|
||||||
|
|
||||||
|
|
||||||
|
def check_paths(path: Path) -> None:
|
||||||
|
"""
|
||||||
|
Check whether all paths demanded by the 'paths' section of the configuration-file exist.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path to the backlog-library to check.
|
||||||
|
"""
|
||||||
|
config = ConfigParser()
|
||||||
|
config_path = path / CONFIG_FILENAME
|
||||||
|
if os.path.exists(config_path):
|
||||||
|
config.read(config_path)
|
||||||
|
else:
|
||||||
|
raise FileNotFoundError("Configuration file not found.")
|
||||||
|
has_paths = [os.path.exists(path / config.get('paths', opt)) for opt in path_opts]
|
||||||
|
if not all(has_paths):
|
||||||
|
raise FileNotFoundError("One of the paths specified in the configuration file is not present.")
|
||||||
|
|
||||||
|
|
||||||
|
def full_integrity_check(path: Path) -> None:
|
||||||
|
"""
|
||||||
|
Aggregate all checks for easy validation of the backlog-library.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
path: Path
|
||||||
|
Path to the backlog-library to check.
|
||||||
|
"""
|
||||||
|
print("Run full integrity check...")
|
||||||
|
check_path_and_config(path)
|
||||||
|
print("(1/5) Path and config-file exist: ✅")
|
||||||
|
check_config_validity(path)
|
||||||
|
print("(2/5) Configuration is valid: ✅")
|
||||||
|
check_paths(path)
|
||||||
|
print("(3/5) Needed paths exist: ✅")
|
||||||
|
check_db_integrity(path)
|
||||||
|
print("(4/5) Database is sane: ✅")
|
||||||
|
check_db_file_links(path)
|
||||||
|
print("(5/5) DB2File and File2DB-links are sound: ✅")
|
||||||
|
print("Full integrity check: ✅")
|
||||||
|
|
||||||
|
|
||||||
|
|
@ -27,7 +27,7 @@ def create_project(path: Path, uuid: str, owner: Union[str, None]=None, tags: Un
|
||||||
The code that was used to create the measurements.
|
The code that was used to create the measurements.
|
||||||
"""
|
"""
|
||||||
db_file = get_db_file(path)
|
db_file = get_db_file(path)
|
||||||
db = os.path.join(path, db_file)
|
db = path / db_file
|
||||||
get(path, db_file)
|
get(path, db_file)
|
||||||
conn = sqlite3.connect(db)
|
conn = sqlite3.connect(db)
|
||||||
c = conn.cursor()
|
c = conn.cursor()
|
||||||
|
|
@ -67,7 +67,7 @@ def update_project_data(path: Path, uuid: str, prop: str, value: Union[str, None
|
||||||
"""
|
"""
|
||||||
db_file = get_db_file(path)
|
db_file = get_db_file(path)
|
||||||
get(path, db_file)
|
get(path, db_file)
|
||||||
conn = sqlite3.connect(os.path.join(path, db_file))
|
conn = sqlite3.connect(path / db_file)
|
||||||
c = conn.cursor()
|
c = conn.cursor()
|
||||||
c.execute(f"UPDATE projects SET '{prop}' = '{value}' WHERE id == '{uuid}'")
|
c.execute(f"UPDATE projects SET '{prop}' = '{value}' WHERE id == '{uuid}'")
|
||||||
conn.commit()
|
conn.commit()
|
||||||
|
|
@ -77,9 +77,8 @@ def update_project_data(path: Path, uuid: str, prop: str, value: Union[str, None
|
||||||
|
|
||||||
def update_aliases(path: Path, uuid: str, aliases: list[str]) -> None:
|
def update_aliases(path: Path, uuid: str, aliases: list[str]) -> None:
|
||||||
db_file = get_db_file(path)
|
db_file = get_db_file(path)
|
||||||
db = path / db_file
|
|
||||||
get(path, db_file)
|
get(path, db_file)
|
||||||
known_data = _project_lookup_by_id(db, uuid)[0]
|
known_data = _project_lookup_by_id(path, uuid)[0]
|
||||||
known_aliases = known_data[1]
|
known_aliases = known_data[1]
|
||||||
|
|
||||||
if aliases is None:
|
if aliases is None:
|
||||||
|
|
|
||||||
|
|
@ -11,6 +11,7 @@ from .tracker import get, save, unlock
|
||||||
import shutil
|
import shutil
|
||||||
from typing import Any
|
from typing import Any
|
||||||
from pathlib import Path
|
from pathlib import Path
|
||||||
|
from .integrity import _check_db2paths
|
||||||
|
|
||||||
|
|
||||||
CACHE_DIR = ".cache"
|
CACHE_DIR = ".cache"
|
||||||
|
|
@ -36,6 +37,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
|
||||||
parameter_file: str
|
parameter_file: str
|
||||||
The parameter file used for the measurement.
|
The parameter file used for the measurement.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
db_file = get_db_file(path)
|
db_file = get_db_file(path)
|
||||||
db = path / db_file
|
db = path / db_file
|
||||||
|
|
||||||
|
|
@ -49,7 +51,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
|
||||||
c = conn.cursor()
|
c = conn.cursor()
|
||||||
for corr in measurement.keys():
|
for corr in measurement.keys():
|
||||||
file_in_archive = Path('.') / 'archive' / ensemble / corr / str(uuid + '.json.gz')
|
file_in_archive = Path('.') / 'archive' / ensemble / corr / str(uuid + '.json.gz')
|
||||||
file = path / file_in_archive
|
file = Path(path) / file_in_archive
|
||||||
known_meas = {}
|
known_meas = {}
|
||||||
if not os.path.exists(path / 'archive' / ensemble / corr):
|
if not os.path.exists(path / 'archive' / ensemble / corr):
|
||||||
os.makedirs(path / 'archive' / ensemble / corr)
|
os.makedirs(path / 'archive' / ensemble / corr)
|
||||||
|
|
@ -59,7 +61,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
|
||||||
if file not in files_to_save:
|
if file not in files_to_save:
|
||||||
unlock(path, file_in_archive)
|
unlock(path, file_in_archive)
|
||||||
files_to_save.append(file_in_archive)
|
files_to_save.append(file_in_archive)
|
||||||
known_meas = pj.load_json_dict(file, verbose=False)
|
known_meas = pj.load_json_dict(str(file), verbose=False)
|
||||||
if code == "sfcf":
|
if code == "sfcf":
|
||||||
if parameter_file is not None:
|
if parameter_file is not None:
|
||||||
parameters = sfcf.read_param(path, uuid, parameter_file)
|
parameters = sfcf.read_param(path, uuid, parameter_file)
|
||||||
|
|
@ -74,9 +76,24 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
|
||||||
ms_type = list(measurement.keys())[0]
|
ms_type = list(measurement.keys())[0]
|
||||||
if ms_type == 'ms1':
|
if ms_type == 'ms1':
|
||||||
if parameter_file is not None:
|
if parameter_file is not None:
|
||||||
parameters = openQCD.read_ms1_param(path, uuid, parameter_file)
|
if parameter_file.endswith(".ms1.in"):
|
||||||
|
parameters = openQCD.load_ms1_infile(path, uuid, parameter_file)
|
||||||
|
elif parameter_file.endswith(".ms1.par"):
|
||||||
|
parameters = openQCD.load_ms1_parfile(path, uuid, parameter_file)
|
||||||
else:
|
else:
|
||||||
raise Exception("Need parameter file for this code!")
|
# Temporary solution
|
||||||
|
parameters = {}
|
||||||
|
parameters["rand"] = {}
|
||||||
|
parameters["rw_fcts"] = [{}]
|
||||||
|
for nrw in range(1):
|
||||||
|
if "nsrc" not in parameters["rw_fcts"][nrw]:
|
||||||
|
parameters["rw_fcts"][nrw]["nsrc"] = 1
|
||||||
|
if "mu" not in parameters["rw_fcts"][nrw]:
|
||||||
|
parameters["rw_fcts"][nrw]["mu"] = "None"
|
||||||
|
if "np" not in parameters["rw_fcts"][nrw]:
|
||||||
|
parameters["rw_fcts"][nrw]["np"] = "None"
|
||||||
|
if "irp" not in parameters["rw_fcts"][nrw]:
|
||||||
|
parameters["rw_fcts"][nrw]["irp"] = "None"
|
||||||
pars = {}
|
pars = {}
|
||||||
subkeys = []
|
subkeys = []
|
||||||
for i in range(len(parameters["rw_fcts"])):
|
for i in range(len(parameters["rw_fcts"])):
|
||||||
|
|
@ -88,7 +105,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
|
||||||
pars[subkey] = json.dumps(parameters["rw_fcts"][i])
|
pars[subkey] = json.dumps(parameters["rw_fcts"][i])
|
||||||
elif ms_type in ['t0', 't1']:
|
elif ms_type in ['t0', 't1']:
|
||||||
if parameter_file is not None:
|
if parameter_file is not None:
|
||||||
parameters = openQCD.read_ms3_param(path, uuid, parameter_file)
|
parameters = openQCD.load_ms3_infile(path, uuid, parameter_file)
|
||||||
else:
|
else:
|
||||||
parameters = {}
|
parameters = {}
|
||||||
for rwp in ["integrator", "eps", "ntot", "dnms"]:
|
for rwp in ["integrator", "eps", "ntot", "dnms"]:
|
||||||
|
|
@ -113,7 +130,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
|
||||||
c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
(corr, ensemble, code, meas_path, uuid, pars[subkey], parameter_file))
|
(corr, ensemble, code, meas_path, uuid, pars[subkey], parameter_file))
|
||||||
conn.commit()
|
conn.commit()
|
||||||
pj.dump_dict_to_json(known_meas, file)
|
pj.dump_dict_to_json(known_meas, str(file))
|
||||||
conn.close()
|
conn.close()
|
||||||
save(path, message="Add measurements to database", files=files_to_save)
|
save(path, message="Add measurements to database", files=files_to_save)
|
||||||
return
|
return
|
||||||
|
|
@ -138,7 +155,7 @@ def load_record(path: Path, meas_path: str) -> Union[Corr, Obs]:
|
||||||
return load_records(path, [meas_path])[0]
|
return load_records(path, [meas_path])[0]
|
||||||
|
|
||||||
|
|
||||||
def load_records(path: Path, meas_paths: list[str], preloaded: dict[str, Any] = {}) -> list[Union[Corr, Obs]]:
|
def load_records(path: Path, meas_paths: list[str], preloaded: dict[str, Any] = {}, dry_run: bool = False) -> list[Union[Corr, Obs]]:
|
||||||
"""
|
"""
|
||||||
Load a list of records by their paths.
|
Load a list of records by their paths.
|
||||||
|
|
||||||
|
|
@ -148,14 +165,20 @@ def load_records(path: Path, meas_paths: list[str], preloaded: dict[str, Any] =
|
||||||
Path of the correlator library.
|
Path of the correlator library.
|
||||||
meas_paths: list[str]
|
meas_paths: list[str]
|
||||||
A list of the paths to the correlator in the backlog system.
|
A list of the paths to the correlator in the backlog system.
|
||||||
perloaded: dict[str, Any]
|
preloaded: dict[str, Any]
|
||||||
The data that is already prelaoded. Of interest if data has alread been loaded in the same script.
|
The data that is already preloaded. Of interest if data has alread been loaded in the same script.
|
||||||
|
dry_run: bool
|
||||||
|
Do not load datda, just check whether we can reach the data we are interested in.
|
||||||
|
|
||||||
Returns
|
Returns
|
||||||
-------
|
-------
|
||||||
retruned_data: list
|
returned_data: list
|
||||||
The loaded records.
|
The loaded records.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
|
if dry_run:
|
||||||
|
_check_db2paths(path, meas_paths)
|
||||||
|
return []
|
||||||
needed_data: dict[str, list[str]] = {}
|
needed_data: dict[str, list[str]] = {}
|
||||||
for mpath in meas_paths:
|
for mpath in meas_paths:
|
||||||
file = mpath.split("::")[0]
|
file = mpath.split("::")[0]
|
||||||
|
|
@ -175,7 +198,7 @@ def load_records(path: Path, meas_paths: list[str], preloaded: dict[str, Any] =
|
||||||
if cache_enabled(path):
|
if cache_enabled(path):
|
||||||
if not os.path.exists(cache_dir(path, file)):
|
if not os.path.exists(cache_dir(path, file)):
|
||||||
os.makedirs(cache_dir(path, file))
|
os.makedirs(cache_dir(path, file))
|
||||||
dump_object(preloaded[file][key], cache_path(path, file, key))
|
dump_object(preloaded[file][key], str(cache_path(path, file, key)))
|
||||||
return returned_data
|
return returned_data
|
||||||
|
|
||||||
|
|
||||||
|
|
@ -195,7 +218,7 @@ def cache_dir(path: Path, file: str) -> Path:
|
||||||
The path holding the cached data for the given file.
|
The path holding the cached data for the given file.
|
||||||
"""
|
"""
|
||||||
cache_path_list = file.split("/")[1:]
|
cache_path_list = file.split("/")[1:]
|
||||||
cache_path = path / CACHE_DIR
|
cache_path = Path(path) / CACHE_DIR
|
||||||
for directory in cache_path_list:
|
for directory in cache_path_list:
|
||||||
cache_path /= directory
|
cache_path /= directory
|
||||||
return cache_path
|
return cache_path
|
||||||
|
|
@ -217,6 +240,7 @@ def cache_path(path: Path, file: str, key: str) -> Path:
|
||||||
cache_path: str
|
cache_path: str
|
||||||
The path at which the measurement of the given file and key is cached.
|
The path at which the measurement of the given file and key is cached.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
cache_path = cache_dir(path, file) / key
|
cache_path = cache_dir(path, file) / key
|
||||||
return cache_path
|
return cache_path
|
||||||
|
|
||||||
|
|
@ -237,8 +261,9 @@ def preload(path: Path, file: Path) -> dict[str, Any]:
|
||||||
filedict: dict[str, Any]
|
filedict: dict[str, Any]
|
||||||
The data read from the file.
|
The data read from the file.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
get(path, file)
|
get(path, file)
|
||||||
filedict: dict[str, Any] = pj.load_json_dict(path / file)
|
filedict: dict[str, Any] = pj.load_json_dict(str(path / file))
|
||||||
print("> read file")
|
print("> read file")
|
||||||
return filedict
|
return filedict
|
||||||
|
|
||||||
|
|
@ -255,7 +280,7 @@ def drop_record(path: Path, meas_path: str) -> None:
|
||||||
The measurement path as noted in the database.
|
The measurement path as noted in the database.
|
||||||
"""
|
"""
|
||||||
file_in_archive = meas_path.split("::")[0]
|
file_in_archive = meas_path.split("::")[0]
|
||||||
file = path / file_in_archive
|
file = Path(path) / file_in_archive
|
||||||
db_file = get_db_file(path)
|
db_file = get_db_file(path)
|
||||||
db = path / db_file
|
db = path / db_file
|
||||||
get(path, db_file)
|
get(path, db_file)
|
||||||
|
|
@ -269,11 +294,11 @@ def drop_record(path: Path, meas_path: str) -> None:
|
||||||
raise ValueError("This measurement does not exist as an entry!")
|
raise ValueError("This measurement does not exist as an entry!")
|
||||||
|
|
||||||
conn.commit()
|
conn.commit()
|
||||||
known_meas = pj.load_json_dict(file)
|
known_meas = pj.load_json_dict(str(file))
|
||||||
if sub_key in known_meas:
|
if sub_key in known_meas:
|
||||||
del known_meas[sub_key]
|
del known_meas[sub_key]
|
||||||
unlock(path, Path(file_in_archive))
|
unlock(path, Path(file_in_archive))
|
||||||
pj.dump_dict_to_json(known_meas, file)
|
pj.dump_dict_to_json(known_meas, str(file))
|
||||||
save(path, message="Drop measurements to database", files=[db, file])
|
save(path, message="Drop measurements to database", files=[db, file])
|
||||||
return
|
return
|
||||||
else:
|
else:
|
||||||
|
|
@ -289,6 +314,7 @@ def drop_cache(path: Path) -> None:
|
||||||
path: str
|
path: str
|
||||||
The path of the library.
|
The path of the library.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
cache_dir = path / ".cache"
|
cache_dir = path / ".cache"
|
||||||
for f in os.listdir(cache_dir):
|
for f in os.listdir(cache_dir):
|
||||||
shutil.rmtree(cache_dir / f)
|
shutil.rmtree(cache_dir / f)
|
||||||
|
|
|
||||||
3
corrlib/pars/openQCD/__init__.py
Normal file
3
corrlib/pars/openQCD/__init__.py
Normal file
|
|
@ -0,0 +1,3 @@
|
||||||
|
|
||||||
|
from . import ms1 as ms1
|
||||||
|
from . import qcd2 as qcd2
|
||||||
59
corrlib/pars/openQCD/flags.py
Normal file
59
corrlib/pars/openQCD/flags.py
Normal file
|
|
@ -0,0 +1,59 @@
|
||||||
|
"""
|
||||||
|
Reconstruct the outputs of flags.
|
||||||
|
"""
|
||||||
|
|
||||||
|
import struct
|
||||||
|
from typing import Any, BinaryIO
|
||||||
|
|
||||||
|
# lat_parms.c
|
||||||
|
def lat_parms_write_lat_parms(fp: BinaryIO) -> dict[str, Any]:
|
||||||
|
"""
|
||||||
|
NOTE: This is a duplcation from qcd2.
|
||||||
|
Unpack the lattice parameters written by write_lat_parms.
|
||||||
|
"""
|
||||||
|
lat_pars = {}
|
||||||
|
t = fp.read(16)
|
||||||
|
lat_pars["N"] = list(struct.unpack('iiii', t)) # lattice extends
|
||||||
|
t = fp.read(8)
|
||||||
|
nk, isw = struct.unpack('ii', t) # number of kappas and isw parameter
|
||||||
|
lat_pars["nk"] = nk
|
||||||
|
lat_pars["isw"] = isw
|
||||||
|
t = fp.read(8)
|
||||||
|
lat_pars["beta"] = struct.unpack('d', t)[0] # beta
|
||||||
|
t = fp.read(8)
|
||||||
|
lat_pars["c0"] = struct.unpack('d', t)[0]
|
||||||
|
t = fp.read(8)
|
||||||
|
lat_pars["c1"] = struct.unpack('d', t)[0]
|
||||||
|
t = fp.read(8)
|
||||||
|
lat_pars["csw"] = struct.unpack('d', t)[0] # csw factor
|
||||||
|
kappas = []
|
||||||
|
m0s = []
|
||||||
|
# read kappas
|
||||||
|
for ik in range(nk):
|
||||||
|
t = fp.read(8)
|
||||||
|
kappas.append(struct.unpack('d', t)[0])
|
||||||
|
t = fp.read(8)
|
||||||
|
m0s.append(struct.unpack('d', t)[0])
|
||||||
|
lat_pars["kappas"] = kappas
|
||||||
|
lat_pars["m0s"] = m0s
|
||||||
|
return lat_pars
|
||||||
|
|
||||||
|
|
||||||
|
def lat_parms_write_bc_parms(fp: BinaryIO) -> dict[str, Any]:
|
||||||
|
"""
|
||||||
|
NOTE: This is a duplcation from qcd2.
|
||||||
|
Unpack the boundary parameters written by write_bc_parms.
|
||||||
|
"""
|
||||||
|
bc_pars: dict[str, Any] = {}
|
||||||
|
t = fp.read(4)
|
||||||
|
bc_pars["type"] = struct.unpack('i', t)[0] # type of hte boundaries
|
||||||
|
t = fp.read(104)
|
||||||
|
bc_parms = struct.unpack('d'*13, t)
|
||||||
|
bc_pars["cG"] = list(bc_parms[:2]) # boundary gauge field improvement
|
||||||
|
bc_pars["cF"] = list(bc_parms[2:4]) # boundary fermion field improvement
|
||||||
|
phi: list[list[float]] = [[], []]
|
||||||
|
phi[0] = list(bc_parms[4:7])
|
||||||
|
phi[1] = list(bc_parms[7:10])
|
||||||
|
bc_pars["phi"] = phi
|
||||||
|
bc_pars["theta"] = list(bc_parms[10:])
|
||||||
|
return bc_pars
|
||||||
30
corrlib/pars/openQCD/ms1.py
Normal file
30
corrlib/pars/openQCD/ms1.py
Normal file
|
|
@ -0,0 +1,30 @@
|
||||||
|
from . import flags
|
||||||
|
|
||||||
|
from typing import Any
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
|
||||||
|
def read_qcd2_ms1_par_file(fname: Path) -> dict[str, dict[str, Any]]:
|
||||||
|
"""
|
||||||
|
The subroutines written here have names according to the openQCD programs and functions that write out the data.
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
fname: Path
|
||||||
|
Location of the parameter file.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
par_dict: dict
|
||||||
|
Dictionary holding the parameters specified in the given file.
|
||||||
|
"""
|
||||||
|
|
||||||
|
with open(fname, "rb") as fp:
|
||||||
|
lat_par_dict = flags.lat_parms_write_lat_parms(fp)
|
||||||
|
bc_par_dict = flags.lat_parms_write_bc_parms(fp)
|
||||||
|
fp.close()
|
||||||
|
par_dict = {}
|
||||||
|
par_dict["lat"] = lat_par_dict
|
||||||
|
par_dict["bc"] = bc_par_dict
|
||||||
|
return par_dict
|
||||||
|
|
||||||
|
|
||||||
29
corrlib/pars/openQCD/qcd2.py
Normal file
29
corrlib/pars/openQCD/qcd2.py
Normal file
|
|
@ -0,0 +1,29 @@
|
||||||
|
from . import flags
|
||||||
|
|
||||||
|
from pathlib import Path
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
|
||||||
|
def read_qcd2_par_file(fname: Path) -> dict[str, dict[str, Any]]:
|
||||||
|
"""
|
||||||
|
The subroutines written here have names according to the openQCD programs and functions that write out the data.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
fname: Path
|
||||||
|
Location of the parameter file.
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
par_dict: dict
|
||||||
|
Dictionary holding the parameters specified in the given file.
|
||||||
|
"""
|
||||||
|
|
||||||
|
with open(fname, "rb") as fp:
|
||||||
|
lat_par_dict = flags.lat_parms_write_lat_parms(fp)
|
||||||
|
bc_par_dict = flags.lat_parms_write_bc_parms(fp)
|
||||||
|
fp.close()
|
||||||
|
par_dict = {}
|
||||||
|
par_dict["lat"] = lat_par_dict
|
||||||
|
par_dict["bc"] = bc_par_dict
|
||||||
|
return par_dict
|
||||||
17
corrlib/sql.py
Normal file
17
corrlib/sql.py
Normal file
|
|
@ -0,0 +1,17 @@
|
||||||
|
import sqlite3
|
||||||
|
from .tools import get_db_file
|
||||||
|
from pathlib import Path
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
|
||||||
|
def thin_sql_wrapper(path: Path, stmt: str) -> list[Any]:
|
||||||
|
db_file = get_db_file(path)
|
||||||
|
db = path / db_file
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
c = conn.cursor()
|
||||||
|
|
||||||
|
c.execute(stmt)
|
||||||
|
results = c.fetchall()
|
||||||
|
conn.commit()
|
||||||
|
conn.close()
|
||||||
|
return results
|
||||||
|
|
@ -158,6 +158,10 @@ def import_toml(path: Path, file: str, copy_file: bool=True) -> None:
|
||||||
copy_file: bool, optional
|
copy_file: bool, optional
|
||||||
Whether the toml-files will be copied into the library. Default is True.
|
Whether the toml-files will be copied into the library. Default is True.
|
||||||
"""
|
"""
|
||||||
|
if not os.path.exists(path):
|
||||||
|
raise FileNotFoundError(f"Corrlib path {path} does not exist.")
|
||||||
|
if not os.path.exists(file):
|
||||||
|
raise FileNotFoundError(f".toml-file {file} does not exist.")
|
||||||
print("Import project as decribed in " + file)
|
print("Import project as decribed in " + file)
|
||||||
with open(file, 'rb') as fp:
|
with open(file, 'rb') as fp:
|
||||||
toml_dict = toml.load(fp)
|
toml_dict = toml.load(fp)
|
||||||
|
|
@ -178,8 +182,10 @@ def import_toml(path: Path, file: str, copy_file: bool=True) -> None:
|
||||||
update_aliases(path, uuid, aliases)
|
update_aliases(path, uuid, aliases)
|
||||||
else:
|
else:
|
||||||
uuid = import_project(path, project['url'], aliases=aliases)
|
uuid = import_project(path, project['url'], aliases=aliases)
|
||||||
|
imeas = 1
|
||||||
|
nmeas = len(measurements.keys())
|
||||||
for mname, md in measurements.items():
|
for mname, md in measurements.items():
|
||||||
print("Import measurement: " + mname)
|
print(f"Import measurement {imeas}/{nmeas}: {mname}")
|
||||||
ensemble = md['ensemble']
|
ensemble = md['ensemble']
|
||||||
if project['code'] == 'sfcf':
|
if project['code'] == 'sfcf':
|
||||||
param = sfcf.read_param(path, uuid, md['param_file'])
|
param = sfcf.read_param(path, uuid, md['param_file'])
|
||||||
|
|
@ -192,26 +198,49 @@ def import_toml(path: Path, file: str, copy_file: bool=True) -> None:
|
||||||
|
|
||||||
elif project['code'] == 'openQCD':
|
elif project['code'] == 'openQCD':
|
||||||
if md['measurement'] == 'ms1':
|
if md['measurement'] == 'ms1':
|
||||||
param = openQCD.read_ms1_param(path, uuid, md['param_file'])
|
if 'param_file' in md.keys():
|
||||||
|
parameter_file = md['param_file']
|
||||||
|
if parameter_file.endswith(".ms1.in"):
|
||||||
|
param = openQCD.load_ms1_infile(path, uuid, parameter_file)
|
||||||
|
elif parameter_file.endswith(".ms1.par"):
|
||||||
|
param = openQCD.load_ms1_parfile(path, uuid, parameter_file)
|
||||||
|
else:
|
||||||
|
# Temporary solution
|
||||||
|
parameters: dict[str, Any] = {}
|
||||||
|
parameters["rand"] = {}
|
||||||
|
parameters["rw_fcts"] = [{}]
|
||||||
|
for nrw in range(1):
|
||||||
|
if "nsrc" not in parameters["rw_fcts"][nrw]:
|
||||||
|
parameters["rw_fcts"][nrw]["nsrc"] = 1
|
||||||
|
if "mu" not in parameters["rw_fcts"][nrw]:
|
||||||
|
parameters["rw_fcts"][nrw]["mu"] = "None"
|
||||||
|
if "np" not in parameters["rw_fcts"][nrw]:
|
||||||
|
parameters["rw_fcts"][nrw]["np"] = "None"
|
||||||
|
if "irp" not in parameters["rw_fcts"][nrw]:
|
||||||
|
parameters["rw_fcts"][nrw]["irp"] = "None"
|
||||||
|
param = parameters
|
||||||
param['type'] = 'ms1'
|
param['type'] = 'ms1'
|
||||||
measurement = openQCD.read_rwms(path, uuid, md['path'], param, md["prefix"], version=md["version"], names=md['names'], files=md['files'])
|
measurement = openQCD.read_rwms(path, uuid, md['path'], param, md["prefix"], version=md["version"], names=md['names'], files=md['files'])
|
||||||
elif md['measurement'] == 't0':
|
elif md['measurement'] == 't0':
|
||||||
if 'param_file' in md:
|
if 'param_file' in md:
|
||||||
param = openQCD.read_ms3_param(path, uuid, md['param_file'])
|
param = openQCD.load_ms3_infile(path, uuid, md['param_file'])
|
||||||
else:
|
else:
|
||||||
param = {}
|
param = {}
|
||||||
for rwp in ["integrator", "eps", "ntot", "dnms"]:
|
for rwp in ["integrator", "eps", "ntot", "dnms"]:
|
||||||
param[rwp] = "Unknown"
|
param[rwp] = "Unknown"
|
||||||
param['type'] = 't0'
|
param['type'] = 't0'
|
||||||
measurement = openQCD.extract_t0(path, uuid, md['path'], param, str(md["prefix"]), int(md["dtr_read"]), int(md["xmin"]), int(md["spatial_extent"]),
|
measurement = openQCD.extract_t0(path, uuid, md['path'], param, str(md["prefix"]), int(md["dtr_read"]), int(md["xmin"]), int(md["spatial_extent"]),
|
||||||
fit_range=int(md.get('fit_range', 5)), postfix=str(md.get('postfix', '')), names=md.get('names', []), files=md.get('files', []))
|
fit_range=int(md.get('fit_range', 5)), postfix=str(md.get('postfix', '')), names=md.get('names', []), files=md.get('files', []),
|
||||||
|
r_start=md.get('r_start', []), r_stop=md.get('r_stop', []), r_step=md.get('r_step', 1))
|
||||||
elif md['measurement'] == 't1':
|
elif md['measurement'] == 't1':
|
||||||
if 'param_file' in md:
|
if 'param_file' in md:
|
||||||
param = openQCD.read_ms3_param(path, uuid, md['param_file'])
|
param = openQCD.load_ms3_infile(path, uuid, md['param_file'])
|
||||||
param['type'] = 't1'
|
param['type'] = 't1'
|
||||||
measurement = openQCD.extract_t1(path, uuid, md['path'], param, str(md["prefix"]), int(md["dtr_read"]), int(md["xmin"]), int(md["spatial_extent"]),
|
measurement = openQCD.extract_t1(path, uuid, md['path'], param, str(md["prefix"]), int(md["dtr_read"]), int(md["xmin"]), int(md["spatial_extent"]),
|
||||||
fit_range=int(md.get('fit_range', 5)), postfix=str(md.get('postfix', '')), names=md.get('names', []), files=md.get('files', []))
|
fit_range=int(md.get('fit_range', 5)), postfix=str(md.get('postfix', '')), names=md.get('names', []), files=md.get('files', []),
|
||||||
|
r_start=md.get('r_start', []), r_stop=md.get('r_stop', []), r_step=md.get('r_step', 1))
|
||||||
write_measurement(path, ensemble, measurement, uuid, project['code'], (md['param_file'] if 'param_file' in md else None))
|
write_measurement(path, ensemble, measurement, uuid, project['code'], (md['param_file'] if 'param_file' in md else None))
|
||||||
|
imeas += 1
|
||||||
print(mname + " imported.")
|
print(mname + " imported.")
|
||||||
|
|
||||||
if not os.path.exists(path / "toml_imports" / uuid):
|
if not os.path.exists(path / "toml_imports" / uuid):
|
||||||
|
|
|
||||||
|
|
@ -89,7 +89,8 @@ def set_config(path: Path, section: str, option: str, value: Any) -> None:
|
||||||
value: Any
|
value: Any
|
||||||
The value we set the option to.
|
The value we set the option to.
|
||||||
"""
|
"""
|
||||||
config_path = os.path.join(path, CONFIG_FILENAME)
|
path = Path(path)
|
||||||
|
config_path = path / CONFIG_FILENAME
|
||||||
config = ConfigParser()
|
config = ConfigParser()
|
||||||
if os.path.exists(config_path):
|
if os.path.exists(config_path):
|
||||||
config.read(config_path)
|
config.read(config_path)
|
||||||
|
|
@ -115,7 +116,10 @@ def get_db_file(path: Path) -> Path:
|
||||||
db_file: str
|
db_file: str
|
||||||
The file holding the database.
|
The file holding the database.
|
||||||
"""
|
"""
|
||||||
config_path = os.path.join(path, CONFIG_FILENAME)
|
path = Path(path)
|
||||||
|
if not os.path.exists(path):
|
||||||
|
raise FileNotFoundError(f"Corrlib path {path} does not exist.")
|
||||||
|
config_path = path / CONFIG_FILENAME
|
||||||
config = ConfigParser()
|
config = ConfigParser()
|
||||||
if os.path.exists(config_path):
|
if os.path.exists(config_path):
|
||||||
config.read(config_path)
|
config.read(config_path)
|
||||||
|
|
@ -140,7 +144,8 @@ def cache_enabled(path: Path) -> bool:
|
||||||
cached_bool: bool
|
cached_bool: bool
|
||||||
Whether the given library is cached.
|
Whether the given library is cached.
|
||||||
"""
|
"""
|
||||||
config_path = os.path.join(path, CONFIG_FILENAME)
|
path = Path(path)
|
||||||
|
config_path = path / CONFIG_FILENAME
|
||||||
config = ConfigParser()
|
config = ConfigParser()
|
||||||
if os.path.exists(config_path):
|
if os.path.exists(config_path):
|
||||||
config.read(config_path)
|
config.read(config_path)
|
||||||
|
|
|
||||||
|
|
@ -3,7 +3,7 @@ from configparser import ConfigParser
|
||||||
import datalad.api as dl
|
import datalad.api as dl
|
||||||
from typing import Optional
|
from typing import Optional
|
||||||
import shutil
|
import shutil
|
||||||
from .tools import get_db_file
|
from .tools import get_db_file, CONFIG_FILENAME
|
||||||
from pathlib import Path
|
from pathlib import Path
|
||||||
|
|
||||||
|
|
||||||
|
|
@ -21,7 +21,8 @@ def get_tracker(path: Path) -> str:
|
||||||
tracker: str
|
tracker: str
|
||||||
The tracker used in the dataset.
|
The tracker used in the dataset.
|
||||||
"""
|
"""
|
||||||
config_path = os.path.join(path, '.corrlib')
|
path = Path(path)
|
||||||
|
config_path = path / CONFIG_FILENAME
|
||||||
config = ConfigParser()
|
config = ConfigParser()
|
||||||
if os.path.exists(config_path):
|
if os.path.exists(config_path):
|
||||||
config.read(config_path)
|
config.read(config_path)
|
||||||
|
|
@ -42,6 +43,7 @@ def get(path: Path, file: Path) -> None:
|
||||||
file: str
|
file: str
|
||||||
The file to get.
|
The file to get.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
tracker = get_tracker(path)
|
tracker = get_tracker(path)
|
||||||
if tracker == 'datalad':
|
if tracker == 'datalad':
|
||||||
if file == get_db_file(path):
|
if file == get_db_file(path):
|
||||||
|
|
@ -70,6 +72,7 @@ def save(path: Path, message: str, files: Optional[list[Path]]=None) -> None:
|
||||||
files: list[str], optional
|
files: list[str], optional
|
||||||
The files to save. If None, all changes are saved.
|
The files to save. If None, all changes are saved.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
tracker = get_tracker(path)
|
tracker = get_tracker(path)
|
||||||
if tracker == 'datalad':
|
if tracker == 'datalad':
|
||||||
if files is not None:
|
if files is not None:
|
||||||
|
|
@ -93,6 +96,7 @@ def init(path: Path, tracker: str='datalad') -> None:
|
||||||
tracker: str
|
tracker: str
|
||||||
The tracker to use. Currently only 'datalad' and 'None' are supported.
|
The tracker to use. Currently only 'datalad' and 'None' are supported.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
if tracker == 'datalad':
|
if tracker == 'datalad':
|
||||||
dl.create(path)
|
dl.create(path)
|
||||||
elif tracker == 'None':
|
elif tracker == 'None':
|
||||||
|
|
@ -113,6 +117,7 @@ def unlock(path: Path, file: Path) -> None:
|
||||||
file : str
|
file : str
|
||||||
The file to unlock.
|
The file to unlock.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
tracker = get_tracker(path)
|
tracker = get_tracker(path)
|
||||||
if tracker == 'datalad':
|
if tracker == 'datalad':
|
||||||
dl.unlock(os.path.join(path, file), dataset=path)
|
dl.unlock(os.path.join(path, file), dataset=path)
|
||||||
|
|
@ -136,6 +141,7 @@ def clone(path: Path, source: str, target: str) -> None:
|
||||||
target: str
|
target: str
|
||||||
The target path to clone the dataset to.
|
The target path to clone the dataset to.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
tracker = get_tracker(path)
|
tracker = get_tracker(path)
|
||||||
if tracker == 'datalad':
|
if tracker == 'datalad':
|
||||||
dl.clone(target=target, source=source, dataset=path)
|
dl.clone(target=target, source=source, dataset=path)
|
||||||
|
|
@ -159,6 +165,7 @@ def drop(path: Path, reckless: Optional[str]=None) -> None:
|
||||||
reckless: Optional[str]
|
reckless: Optional[str]
|
||||||
The datalad's reckless option for dropping data.
|
The datalad's reckless option for dropping data.
|
||||||
"""
|
"""
|
||||||
|
path = Path(path)
|
||||||
tracker = get_tracker(path)
|
tracker = get_tracker(path)
|
||||||
if tracker == 'datalad':
|
if tracker == 'datalad':
|
||||||
dl.drop(path, reckless=reckless)
|
dl.drop(path, reckless=reckless)
|
||||||
|
|
|
||||||
|
|
@ -1,5 +1,6 @@
|
||||||
# file generated by setuptools-scm
|
# file generated by vcs-versioning
|
||||||
# don't change, don't track in version control
|
# don't change, don't track in version control
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
__all__ = [
|
__all__ = [
|
||||||
"__version__",
|
"__version__",
|
||||||
|
|
@ -10,25 +11,14 @@ __all__ = [
|
||||||
"commit_id",
|
"commit_id",
|
||||||
]
|
]
|
||||||
|
|
||||||
TYPE_CHECKING = False
|
|
||||||
if TYPE_CHECKING:
|
|
||||||
from typing import Tuple
|
|
||||||
from typing import Union
|
|
||||||
|
|
||||||
VERSION_TUPLE = Tuple[Union[int, str], ...]
|
|
||||||
COMMIT_ID = Union[str, None]
|
|
||||||
else:
|
|
||||||
VERSION_TUPLE = object
|
|
||||||
COMMIT_ID = object
|
|
||||||
|
|
||||||
version: str
|
version: str
|
||||||
__version__: str
|
__version__: str
|
||||||
__version_tuple__: VERSION_TUPLE
|
__version_tuple__: tuple[int | str, ...]
|
||||||
version_tuple: VERSION_TUPLE
|
version_tuple: tuple[int | str, ...]
|
||||||
commit_id: COMMIT_ID
|
commit_id: str | None
|
||||||
__commit_id__: COMMIT_ID
|
__commit_id__: str | None
|
||||||
|
|
||||||
__version__ = version = '0.2.4.dev71+g5e712b64c.d20260213'
|
__version__ = version = '0.3.1.dev0+g08de17e6b.d20260507'
|
||||||
__version_tuple__ = version_tuple = (0, 2, 4, 'dev71', 'g5e712b64c.d20260213')
|
__version_tuple__ = version_tuple = (0, 3, 1, 'dev0', 'g08de17e6b.d20260507')
|
||||||
|
|
||||||
__commit_id__ = commit_id = 'g5e712b64c'
|
__commit_id__ = commit_id = 'g08de17e6b'
|
||||||
|
|
|
||||||
|
|
@ -3,14 +3,23 @@ import sqlite3
|
||||||
from pathlib import Path
|
from pathlib import Path
|
||||||
import corrlib.initialization as cinit
|
import corrlib.initialization as cinit
|
||||||
import pytest
|
import pytest
|
||||||
|
import pandas as pd
|
||||||
|
import datalad.api as dl
|
||||||
|
import datetime as dt
|
||||||
|
|
||||||
|
|
||||||
def make_sql(path: Path) -> Path:
|
def make_sql(path: Path) -> Path:
|
||||||
db = path / "test.db"
|
db = path / "backlogger.db"
|
||||||
cinit._create_db(db)
|
cinit._create_db(db)
|
||||||
return db
|
return db
|
||||||
|
|
||||||
|
|
||||||
|
def make_config(path: Path) -> None:
|
||||||
|
cinit._write_config(path, cinit._create_config(path, "datalad", False))
|
||||||
|
|
||||||
|
|
||||||
def test_find_lookup_by_one_alias(tmp_path: Path) -> None:
|
def test_find_lookup_by_one_alias(tmp_path: Path) -> None:
|
||||||
|
make_config(tmp_path)
|
||||||
db = make_sql(tmp_path)
|
db = make_sql(tmp_path)
|
||||||
conn = sqlite3.connect(db)
|
conn = sqlite3.connect(db)
|
||||||
c = conn.cursor()
|
c = conn.cursor()
|
||||||
|
|
@ -22,7 +31,7 @@ def test_find_lookup_by_one_alias(tmp_path: Path) -> None:
|
||||||
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
(uuid, alias_str, tag_str, owner, code))
|
(uuid, alias_str, tag_str, owner, code))
|
||||||
conn.commit()
|
conn.commit()
|
||||||
assert uuid == find._project_lookup_by_alias(db, "fun_project")
|
assert uuid == find._project_lookup_by_alias(tmp_path, "fun_project")
|
||||||
uuid = "test_uuid2"
|
uuid = "test_uuid2"
|
||||||
alias_str = "fun_project"
|
alias_str = "fun_project"
|
||||||
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
|
@ -31,3 +40,400 @@ def test_find_lookup_by_one_alias(tmp_path: Path) -> None:
|
||||||
with pytest.raises(Exception):
|
with pytest.raises(Exception):
|
||||||
assert uuid == find._project_lookup_by_alias(db, "fun_project")
|
assert uuid == find._project_lookup_by_alias(db, "fun_project")
|
||||||
conn.close()
|
conn.close()
|
||||||
|
|
||||||
|
|
||||||
|
def test_find_lookup_by_id(tmp_path: Path) -> None:
|
||||||
|
make_config(tmp_path)
|
||||||
|
db = make_sql(tmp_path)
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
c = conn.cursor()
|
||||||
|
uuid = "test_uuid"
|
||||||
|
alias_str = "fun_project"
|
||||||
|
tag_str = "tt"
|
||||||
|
owner = "tester"
|
||||||
|
code = "test_code"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(uuid, alias_str, tag_str, owner, code))
|
||||||
|
conn.commit()
|
||||||
|
conn.close()
|
||||||
|
result = find._project_lookup_by_id(tmp_path, uuid)[0]
|
||||||
|
assert uuid == result[0]
|
||||||
|
assert alias_str == result[1]
|
||||||
|
assert tag_str == result[2]
|
||||||
|
assert owner == result[3]
|
||||||
|
assert code == result[4]
|
||||||
|
|
||||||
|
|
||||||
|
def test_time_filter() -> None:
|
||||||
|
record_A = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf0", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966'] # only created
|
||||||
|
record_B = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf1", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-04-26 12:55:18.229966'] # created and updated
|
||||||
|
record_C = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2026-04-14 12:55:18.229966'] # created and updated later
|
||||||
|
record_D = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf3", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2026-03-27 12:55:18.229966']
|
||||||
|
record_E = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf4", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2024-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # only created, earlier
|
||||||
|
record_F = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf5", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # this is invalid...
|
||||||
|
record_G = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', str(dt.datetime.now() + dt.timedelta(days=2, hours=3, minutes=5, seconds=30))] # created and updated later
|
||||||
|
|
||||||
|
data = [record_A, record_B, record_C, record_D, record_E]
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
|
||||||
|
results = find._time_filter(df, created_before='2023-03-26 12:55:18.229966')
|
||||||
|
assert results.empty
|
||||||
|
results = find._time_filter(df, created_before='2027-03-26 12:55:18.229966')
|
||||||
|
assert len(results) == 5
|
||||||
|
results = find._time_filter(df, created_before='2026-03-25 12:55:18.229966')
|
||||||
|
assert len(results) == 3
|
||||||
|
results = find._time_filter(df, created_before='2026-03-26 12:55:18.229965')
|
||||||
|
assert len(results) == 3
|
||||||
|
results = find._time_filter(df, created_before='2025-03-04 12:55:18.229965')
|
||||||
|
assert len(results) == 1
|
||||||
|
|
||||||
|
results = find._time_filter(df, created_after='2023-03-26 12:55:18.229966')
|
||||||
|
assert len(results) == 5
|
||||||
|
results = find._time_filter(df, created_after='2027-03-26 12:55:18.229966')
|
||||||
|
assert results.empty
|
||||||
|
results = find._time_filter(df, created_after='2026-03-25 12:55:18.229966')
|
||||||
|
assert len(results) == 2
|
||||||
|
results = find._time_filter(df, created_after='2026-03-26 12:55:18.229965')
|
||||||
|
assert len(results) == 2
|
||||||
|
results = find._time_filter(df, created_after='2025-03-04 12:55:18.229965')
|
||||||
|
assert len(results) == 4
|
||||||
|
|
||||||
|
results = find._time_filter(df, updated_before='2023-03-26 12:55:18.229966')
|
||||||
|
assert results.empty
|
||||||
|
results = find._time_filter(df, updated_before='2027-03-26 12:55:18.229966')
|
||||||
|
assert len(results) == 5
|
||||||
|
results = find._time_filter(df, updated_before='2026-03-25 12:55:18.229966')
|
||||||
|
assert len(results) == 3
|
||||||
|
results = find._time_filter(df, updated_before='2026-03-26 12:55:18.229965')
|
||||||
|
assert len(results) == 3
|
||||||
|
results = find._time_filter(df, updated_before='2025-03-04 12:55:18.229965')
|
||||||
|
assert len(results) == 1
|
||||||
|
|
||||||
|
results = find._time_filter(df, updated_after='2023-03-26 12:55:18.229966')
|
||||||
|
assert len(results) == 5
|
||||||
|
results = find._time_filter(df, updated_after='2027-03-26 12:55:18.229966')
|
||||||
|
assert results.empty
|
||||||
|
results = find._time_filter(df, updated_after='2026-03-25 12:55:18.229966')
|
||||||
|
assert len(results) == 2
|
||||||
|
results = find._time_filter(df, updated_after='2026-03-26 12:55:18.229965')
|
||||||
|
assert len(results) == 2
|
||||||
|
results = find._time_filter(df, updated_after='2025-03-04 12:55:18.229965')
|
||||||
|
assert len(results) == 4
|
||||||
|
|
||||||
|
data = [record_A, record_B, record_C, record_D, record_F]
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
results = find._time_filter(df, created_before='2023-03-26 12:55:18.229966')
|
||||||
|
|
||||||
|
data = [record_A, record_B, record_C, record_D, record_G]
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
results = find._time_filter(df, created_before='2023-03-26 12:55:18.229966')
|
||||||
|
|
||||||
|
|
||||||
|
def test_db_lookup(tmp_path: Path) -> None:
|
||||||
|
db = make_sql(tmp_path)
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
c = conn.cursor()
|
||||||
|
|
||||||
|
corr = "f_A"
|
||||||
|
ensemble = "SF_A"
|
||||||
|
code = "openQCD"
|
||||||
|
meas_path = "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf"
|
||||||
|
uuid = "Project_A"
|
||||||
|
pars = "{par_A: 3.0, par_B: 5.0}"
|
||||||
|
parameter_file = "projects/Project_A/myinput.in"
|
||||||
|
c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(corr, ensemble, code, meas_path, uuid, pars, parameter_file))
|
||||||
|
conn.commit()
|
||||||
|
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code)
|
||||||
|
assert len(results) == 1
|
||||||
|
results = find._db_lookup(db, "SF_B", corr, code)
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, "g_A", code)
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, corr, "sfcf")
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code, project = "Project_A")
|
||||||
|
assert len(results) == 1
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code, project = "Project_B")
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code, parameters = pars)
|
||||||
|
assert len(results) == 1
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code, parameters = '{"par_A": 3.0, "par_B": 4.0}')
|
||||||
|
assert results.empty
|
||||||
|
|
||||||
|
corr = "g_A"
|
||||||
|
ensemble = "SF_A"
|
||||||
|
code = "openQCD"
|
||||||
|
meas_path = "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf"
|
||||||
|
uuid = "Project_A"
|
||||||
|
pars = '{"par_A": 3.0, "par_B": 4.0}'
|
||||||
|
parameter_file = "projects/Project_A/myinput.in"
|
||||||
|
c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(corr, ensemble, code, meas_path, uuid, pars, parameter_file))
|
||||||
|
conn.commit()
|
||||||
|
|
||||||
|
corr = "f_A"
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code)
|
||||||
|
assert len(results) == 1
|
||||||
|
results = find._db_lookup(db, "SF_B", corr, code)
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, "g_A", code)
|
||||||
|
assert len(results) == 1
|
||||||
|
results = find._db_lookup(db, ensemble, corr, "sfcf")
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code, project = "Project_A")
|
||||||
|
assert len(results) == 1
|
||||||
|
results = find._db_lookup(db, ensemble, "g_A", code, project = "Project_A")
|
||||||
|
assert len(results) == 1
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code, project = "Project_B")
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, "g_A", code, project = "Project_B")
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, corr, code, parameters = pars)
|
||||||
|
assert results.empty
|
||||||
|
results = find._db_lookup(db, ensemble, "g_A", code, parameters = '{"par_A": 3.0, "par_B": 4.0}')
|
||||||
|
assert len(results) == 1
|
||||||
|
|
||||||
|
conn.close()
|
||||||
|
|
||||||
|
|
||||||
|
def test_sfcf_drop() -> None:
|
||||||
|
parameters0 = {
|
||||||
|
'offset': [0,0,0],
|
||||||
|
'quarks': [{'mass': 1, 'thetas': [0,0,0]}, {'mass': 2, 'thetas': [0,0,1]}], # m0s = -3.5, -3.75
|
||||||
|
'wf1': [[1, [0, 0]], [0.5, [1, 0]], [.75, [.5, .5]]],
|
||||||
|
'wf2': [[1, [2, 1]], [2, [0.5, -0.5]], [.5, [.75, .72]]],
|
||||||
|
}
|
||||||
|
|
||||||
|
assert not find._sfcf_drop(parameters0, offset=[0,0,0])
|
||||||
|
assert find._sfcf_drop(parameters0, offset=[1,0,0])
|
||||||
|
|
||||||
|
assert not find._sfcf_drop(parameters0, quark_kappas = [1, 2])
|
||||||
|
assert find._sfcf_drop(parameters0, quark_kappas = [-3.1, -3.72])
|
||||||
|
|
||||||
|
assert not find._sfcf_drop(parameters0, quark_masses = [-3.5, -3.75])
|
||||||
|
assert find._sfcf_drop(parameters0, quark_masses = [-3.1, -3.72])
|
||||||
|
|
||||||
|
assert not find._sfcf_drop(parameters0, qk1 = 1)
|
||||||
|
assert not find._sfcf_drop(parameters0, qk2 = 2)
|
||||||
|
assert find._sfcf_drop(parameters0, qk1 = 2)
|
||||||
|
assert find._sfcf_drop(parameters0, qk2 = 1)
|
||||||
|
|
||||||
|
assert not find._sfcf_drop(parameters0, qk1 = [0.5,1.5])
|
||||||
|
assert not find._sfcf_drop(parameters0, qk2 = [1.5,2.5])
|
||||||
|
assert find._sfcf_drop(parameters0, qk1 = 2)
|
||||||
|
assert find._sfcf_drop(parameters0, qk2 = 1)
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
assert not find._sfcf_drop(parameters0, qk1 = [0.5,1,5])
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
assert not find._sfcf_drop(parameters0, qk2 = [1,5,2.5])
|
||||||
|
|
||||||
|
assert find._sfcf_drop(parameters0, qm1 = 1.2)
|
||||||
|
assert find._sfcf_drop(parameters0, qm2 = 2.2)
|
||||||
|
assert not find._sfcf_drop(parameters0, qm1 = -3.5)
|
||||||
|
assert not find._sfcf_drop(parameters0, qm2 = -3.75)
|
||||||
|
|
||||||
|
assert find._sfcf_drop(parameters0, qm2 = 1.2)
|
||||||
|
assert find._sfcf_drop(parameters0, qm1 = 2.2)
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
assert not find._sfcf_drop(parameters0, qm1 = [0.5,1,5])
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
assert not find._sfcf_drop(parameters0, qm2 = [1,5,2.5])
|
||||||
|
|
||||||
|
|
||||||
|
def test_openQCD_filter() -> None:
|
||||||
|
record_0 = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_1 = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_2 = ["f_P", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_3 = ["f_P", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
data = [
|
||||||
|
record_0,
|
||||||
|
record_1,
|
||||||
|
record_2,
|
||||||
|
record_3,
|
||||||
|
]
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
|
||||||
|
with pytest.warns(Warning):
|
||||||
|
find.openQCD_filter(df, a = "asdf")
|
||||||
|
|
||||||
|
|
||||||
|
def test_code_filter() -> None:
|
||||||
|
record_0 = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_1 = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_2 = ["f_P", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_3 = ["f_P", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_4 = ["f_A", "ensA", "openQCD", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_5 = ["f_A", "ensA", "openQCD", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_6 = ["f_P", "ensA", "openQCD", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_7 = ["f_P", "ensA", "openQCD", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
record_8 = ["f_P", "ensA", "openQCD", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966']
|
||||||
|
data = [
|
||||||
|
record_0,
|
||||||
|
record_1,
|
||||||
|
record_2,
|
||||||
|
record_3,
|
||||||
|
]
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
|
||||||
|
res = find._code_filter(df, "sfcf")
|
||||||
|
assert len(res) == 4
|
||||||
|
|
||||||
|
data = [
|
||||||
|
record_4,
|
||||||
|
record_5,
|
||||||
|
record_6,
|
||||||
|
record_7,
|
||||||
|
record_8,
|
||||||
|
]
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
|
||||||
|
res = find._code_filter(df, "openQCD")
|
||||||
|
assert len(res) == 5
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
res = find._code_filter(df, "asdf")
|
||||||
|
|
||||||
|
|
||||||
|
def test_find_record() -> None:
|
||||||
|
assert True
|
||||||
|
|
||||||
|
|
||||||
|
def test_find_project(tmp_path: Path) -> None:
|
||||||
|
cinit.create(tmp_path)
|
||||||
|
db = tmp_path / "backlogger.db"
|
||||||
|
dl.unlock(str(db), dataset=str(tmp_path))
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
c = conn.cursor()
|
||||||
|
uuid = "test_uuid"
|
||||||
|
alias_str = "fun_project"
|
||||||
|
tag_str = "tt"
|
||||||
|
owner = "tester"
|
||||||
|
code = "test_code"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(uuid, alias_str, tag_str, owner, code))
|
||||||
|
conn.commit()
|
||||||
|
|
||||||
|
assert uuid == find.find_project(tmp_path, "fun_project")
|
||||||
|
|
||||||
|
uuid = "test_uuid2"
|
||||||
|
alias_str = "fun_project"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(uuid, alias_str, tag_str, owner, code))
|
||||||
|
conn.commit()
|
||||||
|
|
||||||
|
with pytest.raises(Exception):
|
||||||
|
assert uuid == find._project_lookup_by_alias(tmp_path, "fun_project")
|
||||||
|
conn.close()
|
||||||
|
|
||||||
|
|
||||||
|
def test_list_projects(tmp_path: Path) -> None:
|
||||||
|
cinit.create(tmp_path)
|
||||||
|
db = tmp_path / "backlogger.db"
|
||||||
|
dl.unlock(str(db), dataset=str(tmp_path))
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
c = conn.cursor()
|
||||||
|
uuid = "test_uuid"
|
||||||
|
alias_str = "fun_project"
|
||||||
|
tag_str = "tt"
|
||||||
|
owner = "tester"
|
||||||
|
code = "test_code"
|
||||||
|
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(uuid, alias_str, tag_str, owner, code))
|
||||||
|
uuid = "test_uuid2"
|
||||||
|
alias_str = "fun_project2"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(uuid, alias_str, tag_str, owner, code))
|
||||||
|
uuid = "test_uuid3"
|
||||||
|
alias_str = "fun_project3"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(uuid, alias_str, tag_str, owner, code))
|
||||||
|
uuid = "test_uuid4"
|
||||||
|
alias_str = "fun_project4"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
|
||||||
|
(uuid, alias_str, tag_str, owner, code))
|
||||||
|
conn.commit()
|
||||||
|
conn.close()
|
||||||
|
results = find.list_projects(tmp_path)
|
||||||
|
assert len(results) == 4
|
||||||
|
for i in range(4):
|
||||||
|
assert len(results[i]) == 2
|
||||||
|
|
|
||||||
189
tests/integrity_test.py
Normal file
189
tests/integrity_test.py
Normal file
|
|
@ -0,0 +1,189 @@
|
||||||
|
import corrlib.integrity as integ
|
||||||
|
import corrlib.find as find
|
||||||
|
import datalad.api as dl
|
||||||
|
import corrlib.initialization as cinit
|
||||||
|
import sqlite3
|
||||||
|
from pathlib import Path
|
||||||
|
import os
|
||||||
|
import pandas as pd
|
||||||
|
import datetime as dt
|
||||||
|
import pytest
|
||||||
|
|
||||||
|
|
||||||
|
def test_list_ensembles(tmp_path: Path) -> None:
|
||||||
|
"""
|
||||||
|
Check against the implementation in find to check if they are the same.
|
||||||
|
"""
|
||||||
|
os.mkdir(tmp_path / 'archive')
|
||||||
|
os.mkdir(tmp_path / 'archive' / 'A')
|
||||||
|
os.mkdir(tmp_path / 'archive' / 'B')
|
||||||
|
os.mkdir(tmp_path / 'archive' / 'C')
|
||||||
|
integ_results = integ._list_ensembles(tmp_path)
|
||||||
|
assert len(integ_results) == 3
|
||||||
|
find_results = find.list_ensembles(tmp_path)
|
||||||
|
assert len(find_results) == 3
|
||||||
|
for f,i in zip(find_results, integ_results):
|
||||||
|
assert f == i
|
||||||
|
|
||||||
|
|
||||||
|
def test_list_projects(tmp_path: Path) -> None:
|
||||||
|
cinit.create(tmp_path)
|
||||||
|
db = tmp_path / "backlogger.db"
|
||||||
|
dl.unlock(str(db), dataset=str(tmp_path))
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
c = conn.cursor()
|
||||||
|
|
||||||
|
customTags = ""
|
||||||
|
owner = "owner"
|
||||||
|
code = "sfcf"
|
||||||
|
created_at = "today"
|
||||||
|
updated_at = "today"
|
||||||
|
|
||||||
|
id = "asdf1"
|
||||||
|
aliases = "a1,s1,d1,f1"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?,?,?,?,?,?,?)", (id, aliases, customTags, owner, code , created_at, updated_at))
|
||||||
|
id = "asdf2"
|
||||||
|
aliases = "a2,s2,d2,f2"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?,?,?,?,?,?,?)", (id, aliases, customTags, owner, code , created_at, updated_at))
|
||||||
|
id = "asdf3"
|
||||||
|
aliases = "a3,s3,d3,f3"
|
||||||
|
c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?,?,?,?,?,?,?)", (id, aliases, customTags, owner, code , created_at, updated_at))
|
||||||
|
conn.commit()
|
||||||
|
conn.close
|
||||||
|
integ_results = integ._list_projects(tmp_path)
|
||||||
|
assert len(integ_results) == 3
|
||||||
|
find_results = find.list_projects(tmp_path)
|
||||||
|
assert len(find_results) == 3
|
||||||
|
for f,i in zip(find_results, integ_results):
|
||||||
|
assert f == i
|
||||||
|
|
||||||
|
|
||||||
|
def test_has_valid_time() -> None:
|
||||||
|
record_A = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf0", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966'] # only created
|
||||||
|
record_B = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf1", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-04-26 12:55:18.229966'] # created and updated
|
||||||
|
record_C = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2026-04-14 12:55:18.229966'] # created and updated later
|
||||||
|
record_D = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf3", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2026-03-27 12:55:18.229966']
|
||||||
|
record_E = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf4", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2024-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # only created, earlier
|
||||||
|
record_F = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf5", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # this is invalid...
|
||||||
|
record_G = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', str(dt.datetime.now() + dt.timedelta(days=2, hours=3, minutes=5, seconds=30))] # created and updated later
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
data = [record_A, record_B, record_C, record_D, record_E]
|
||||||
|
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
for _, result in df.iterrows():
|
||||||
|
assert integ.has_valid_times(result)
|
||||||
|
data = [record_F, record_G]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
for _, result in df.iterrows():
|
||||||
|
assert not integ.has_valid_times(result)
|
||||||
|
|
||||||
|
|
||||||
|
def test_are_keys_unique(tmp_path: Path) -> None:
|
||||||
|
db = tmp_path / 'test_success.db'
|
||||||
|
|
||||||
|
record_A = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf0", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966'] # only created
|
||||||
|
record_B = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf1", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-04-26 12:55:18.229966'] # created and updated
|
||||||
|
record_C = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2026-04-14 12:55:18.229966'] # created and updated later
|
||||||
|
record_D = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf3", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2026-03-27 12:55:18.229966']
|
||||||
|
record_E = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf4", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2024-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # only created, earlier
|
||||||
|
record_F = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf5", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # this is invalid...
|
||||||
|
record_G = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', str(dt.datetime.now() + dt.timedelta(days=2, hours=3, minutes=5, seconds=30))] # created and updated later
|
||||||
|
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
|
||||||
|
data = [record_A, record_B, record_C, record_D, record_E, record_F]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
df.to_sql('backlogs', conn)
|
||||||
|
conn.close()
|
||||||
|
assert integ.are_keys_unique(db, 'backlogs', 'path')
|
||||||
|
|
||||||
|
db = tmp_path / 'test_fail.db'
|
||||||
|
data = [record_A, record_B, record_C, record_D, record_E, record_F, record_G]
|
||||||
|
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
conn = sqlite3.connect(db)
|
||||||
|
df.to_sql('backlogs', conn)
|
||||||
|
conn.close()
|
||||||
|
assert not integ.are_keys_unique(db, 'backlogs', 'path')
|
||||||
|
|
||||||
|
|
||||||
|
def test_check_path_format() -> None:
|
||||||
|
record_A = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_A.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966'] # only created
|
||||||
|
record_B = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_B.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2025-03-26 12:55:18.229966', '2025-04-26 12:55:18.229966'] # created and updated
|
||||||
|
record_C = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_A.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2026-04-14 12:55:18.229966'] # created and updated later
|
||||||
|
record_D = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_B.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2026-03-27 12:55:18.229966']
|
||||||
|
record_E = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_A.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2024-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # only created, earlier
|
||||||
|
record_F = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_B.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # this is invalid...
|
||||||
|
record_G = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_A.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfas", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
|
||||||
|
'2026-03-26 12:55:18.229966', str(dt.datetime.now() + dt.timedelta(days=2, hours=3, minutes=5, seconds=30))] # created and updated later
|
||||||
|
|
||||||
|
projects = ['Project_A', 'Project_B']
|
||||||
|
ensembles = ['ensA']
|
||||||
|
cols = ["name",
|
||||||
|
"ensemble",
|
||||||
|
"code",
|
||||||
|
"path",
|
||||||
|
"project",
|
||||||
|
"parameters",
|
||||||
|
"parameter_file",
|
||||||
|
"created_at",
|
||||||
|
"updated_at"]
|
||||||
|
|
||||||
|
data = [record_A, record_B, record_C, record_D, record_E, record_F]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
for _, result in df.iterrows():
|
||||||
|
integ.check_path_format(result, ensembles, projects)
|
||||||
|
|
||||||
|
projects = ['Project_A', 'Project_B']
|
||||||
|
ensembles = ['ensB']
|
||||||
|
for _, result in df.iterrows():
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
integ.check_path_format(result, ensembles, projects)
|
||||||
|
|
||||||
|
projects = ['Project_A', 'Project_B']
|
||||||
|
ensembles = ['ensA', 'ensB']
|
||||||
|
for _, result in df.iterrows():
|
||||||
|
integ.check_path_format(result, ensembles, projects)
|
||||||
|
|
||||||
|
data = [record_G]
|
||||||
|
df = pd.DataFrame(data,columns=cols)
|
||||||
|
for _, result in df.iterrows():
|
||||||
|
with pytest.raises(ValueError):
|
||||||
|
integ.check_path_format(result, ensembles, projects)
|
||||||
|
|
@ -69,6 +69,8 @@ def test_get_db_file(tmp_path: Path) -> None:
|
||||||
# config is not yet available
|
# config is not yet available
|
||||||
tl.set_config(tmp_path, section, option, value)
|
tl.set_config(tmp_path, section, option, value)
|
||||||
assert tl.get_db_file(tmp_path) == Path("test_value")
|
assert tl.get_db_file(tmp_path) == Path("test_value")
|
||||||
|
with pytest.raises(FileNotFoundError):
|
||||||
|
tl.get_db_file(tmp_path / "doesnotexist")
|
||||||
|
|
||||||
|
|
||||||
def test_cache_enabled(tmp_path: Path) -> None:
|
def test_cache_enabled(tmp_path: Path) -> None:
|
||||||
|
|
@ -82,3 +84,5 @@ def test_cache_enabled(tmp_path: Path) -> None:
|
||||||
tl.set_config(tmp_path, section, option, "lalala")
|
tl.set_config(tmp_path, section, option, "lalala")
|
||||||
with pytest.raises(ValueError):
|
with pytest.raises(ValueError):
|
||||||
tl.cache_enabled(tmp_path)
|
tl.cache_enabled(tmp_path)
|
||||||
|
with pytest.raises(FileNotFoundError):
|
||||||
|
tl.cache_enabled(tmp_path / "doesnotexist")
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue