[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

.pre-commit-config.yaml

@@ -19,4 +19,3 @@ repos:
     - id: ruff
       args: [--fix, --exit-non-zero-on-fix]
     - id: ruff-format
-

.vscode/settings.json

@@ -4,4 +4,4 @@
     ],
     "python.testing.unittestEnabled": false,
     "python.testing.pytestEnabled": true,
-}
+}

docs/conf.py

@@ -4,6 +4,7 @@
 # https://www.sphinx-doc.org/en/master/usage/configuration.html
 import os
 import sys
+
 import versioningit
 
 sys.path.insert(0, os.path.abspath("../src"))
@@ -59,7 +60,9 @@
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
-html_theme = "alabaster"  # "sphinx_rtd_theme", please add corresponding package to environment.yml if you want to use it
+html_theme = (
+    "alabaster"  # "sphinx_rtd_theme", please add corresponding package to environment.yml if you want to use it
+)
 autosummary_generate = True
 
 # Napoleon settings

scripts/rez_loader.jl

@@ -6,4 +6,4 @@ scan0042 = pdata["scan0042"]
 rez_mat = read(scan0042, "rez_mat")
 
 scan0001 = fid["data"]["IPTS32124_CG4C_exp0424"]["scan0001"]
-read(scan0001["sample"], "unit_cell")
+read(scan0001["sample"], "unit_cell")

scripts/scans_rez.py

@@ -35,7 +35,6 @@
     rez_r0_list = []
 
     for i in range(len(ei_list)):
-
         rez = tas.cooper_nathans(
             ei=ei_list[i],
             ef=ef_list[i],

src/tavi/configuration.py

@@ -4,9 +4,9 @@
 
 import os
 import shutil
-
 from configparser import ConfigParser
 from pathlib import Path
+
 from mantid.kernel import Logger
 
 logger = Logger("PACKAGENAME")

src/tavi/data/fit.py

@@ -27,9 +27,7 @@
 
 
 class FitData1D(object):
-
     def __init__(self, x: np.ndarray, y: np.ndarray) -> None:
-
         self.x = x
         self.y = y
         self.fmt: dict = {}
@@ -212,14 +210,12 @@ def x_to_plot(self, num_of_pts: Optional[int]):
         return x_to_plot
 
     def eval(self, pars: Parameters, num_of_pts: Optional[int] = 100) -> FitData1D:
-
         x_to_plot = self.x_to_plot(num_of_pts)
         y_to_plot = self.model.eval(pars, x=x_to_plot)
 
         return FitData1D(x_to_plot, y_to_plot)
 
     def fit(self, pars: Parameters) -> ModelResult:
-
         result = self.model.fit(self.y, pars, x=self.x, weights=self.err)
         self.result = result
         return result

src/tavi/data/nxdict.py

@@ -301,7 +301,6 @@ def spice_scan_to_nxdict(
 
     if instrument_config_params is not None:
         if (coll_params := instrument_config_params.get("collimators")) is not None:
-
             try:
                 div_x = [
                     coll_params["h_pre_mono"],

src/tavi/data/scan.py

@@ -74,7 +74,6 @@ class Scan(object):
     """
 
     def __init__(self, name: str, nexus_dict: NexusEntry) -> None:
-
         self.name: str = name
         self._nexus_dict: NexusEntry = nexus_dict
         self.data: dict = self.get_data_columns()

src/tavi/data/scan_data.py

@@ -15,7 +15,6 @@ def __init__(
         y: np.ndarray,
         norm: Optional[np.ndarray] = None,
     ) -> None:
-
         # ind = np.argsort(x)
         # self.x = x[ind]
         # self.y = y[ind]
@@ -198,7 +197,6 @@ def rebin_grid(self, rebin_params: tuple):
         counts = np.zeros_like(x)
 
         for i, x0 in enumerate(self.x):
-
             # Return the indices of the maximum values in the specified axis ignoring NaNs.
             idx = np.nanargmax(x_boundary - ZERO > x0)
             if idx > 0:  # ignore first and last bin box
@@ -246,7 +244,6 @@ def rebin_grid_renorm(self, rebin_params: tuple, norm_col: Optional[np.ndarray]
 
 
 class ScanData2D(object):
-
     ZEROS = 1e-6
 
     def __init__(

src/tavi/data/scan_group.py

@@ -61,7 +61,6 @@ def _get_data_1d(
         norm_to: Optional[tuple[float, str]],
         **rebin_params_dict: Optional[tuple],
     ) -> ScanData1D:
-
         x_axis, y_axis = axes
         x_array = np.array([])
         y_array = np.array([])

src/tavi/data/spice_reader.py

@@ -71,7 +71,7 @@ def read_spice_ubconf(ub_file_name: str) -> dict:
     Returns:
     """
     ubconf: dict[str, Any] = {}
-    with open(ub_file_name, 'r', encoding="utf-8") as f:
+    with open(ub_file_name, "r", encoding="utf-8") as f:
         all_content = f.readlines()
 
     for idx, line in enumerate(all_content):
@@ -129,8 +129,8 @@ def _create_spicelogs(path_to_scan_file: str) -> dict:
 
     scan_path = os.path.abspath(path_to_scan_file)
     (*folder_path, _, _) = scan_path.split("/")
-    ub_file_path = os.path.join('/',*folder_path,"UBConf", metadata["ubconf"])
-    ub_temp_file_path = os.path.join('/',*folder_path,"UBConf", "temp", metadata["ubconf"])
+    ub_file_path = os.path.join("/", *folder_path, "UBConf", metadata["ubconf"])
+    ub_temp_file_path = os.path.join("/", *folder_path, "UBConf", "temp", metadata["ubconf"])
 
     if os.path.isfile(ub_file_path):
         ub_conf_dict = {"file_path": ub_file_path}

src/tavi/instrument/instrument_params/cg4c.json

@@ -70,4 +70,4 @@
         "v_post_sample": 600,
         "v_post_ana": 600
     }
-}
+}

src/tavi/instrument/instrument_params/hb1a.json

@@ -69,4 +69,4 @@
         "v_post_sample": 600,
         "v_post_ana": 600
     }
-}
+}

src/tavi/instrument/instrument_params/hb3.json

@@ -73,4 +73,4 @@
         "v_post_sample": 300,
         "v_post_ana": 600
     }
-}
+}

src/tavi/instrument/instrument_params/hb3_mnte.json

@@ -73,4 +73,4 @@
         "v_post_sample": 120,
         "v_post_ana": 120
     }
-}
+}

src/tavi/instrument/instrument_params/takin_test.json

@@ -72,4 +72,4 @@
         "v_post_sample": 30,
         "v_post_ana": 30
     }
-}
+}

src/tavi/instrument/resolution/cooper_nathans.py

@@ -209,7 +209,6 @@ def cooper_nathans(
         hkle_list = self._generate_hkle_list(hkl_list, ei, ef)
         rez_list = []
         for hkl, ei, ef in hkle_list:
-
             # q_lab = conv_mat @ hkl
             # q_mod = np.linalg.norm(q_lab)
             q_mod = np.linalg.norm(self.sample.b_mat @ hkl) * 2 * np.pi

src/tavi/instrument/resolution/ellipsoid.py

@@ -40,7 +40,6 @@ def __init__(
         sample: Xtal,
         projection: Optional[tuple] = ((1, 0, 0), (0, 1, 0), (0, 0, 1)),
     ) -> None:
-
         self.STATUS: bool
         self.q: tuple[float, float, float]
 
@@ -263,7 +262,6 @@ def plot_ellipses(self):
         fig = plt.figure(figsize=(10, 6))
 
         for i, indices in enumerate([(0, 3), (1, 3), (2, 3), (0, 1), (1, 2), (0, 2)]):
-
             ellipse_co = self.get_ellipse(axes=indices, PROJECTION=False)
             ellipse_inco = self.get_ellipse(axes=indices, PROJECTION=True)
 

src/tavi/instrument/tas.py

@@ -86,7 +86,7 @@ def calculate_ub_matrix(self, peaks: tuple[Peak, ...]):
         if not isinstance(self.sample, Xtal):
             raise ValueError("sample needs to be Xtal class for UB calculation.")
 
-        match (num_of_peaks := len(peaks)):
+        match num_of_peaks := len(peaks):
             case 2:
                 ubconf = self._find_u_from_two_peaks(peaks)
                 self.sample.set_orientation(ubconf)

src/tavi/plotter.py

@@ -136,7 +136,6 @@ def plot(self, ax):
 
 
 class Plot2D(object):
-
     def __init__(self) -> None:
         # self.ax = None
         self.contour_data: list[ScanData2D] = []
@@ -155,19 +154,16 @@ def __init__(self) -> None:
         self.LOG_Z = False
 
     def add_contour(self, contour_data: ScanData2D, **kwargs):
-
         for key, val in kwargs.items():
             contour_data.fmt.update({key: val})
         self.contour_data.append(contour_data)
 
     def add_curve(self, curve_data: ScanData1D, **kwargs):
-
         for key, val in kwargs.items():
             curve_data.fmt.update({key: val})
         self.curve_data.append(curve_data)
 
     def add_reso(self, reso_data: ResoEllipse, **kwargs):
-
         for key, val in kwargs.items():
             reso_data.fmt.update({key: val})
         self.reso_data.append(reso_data)

tests/test_fit.py

@@ -20,7 +20,6 @@ def fit_data():
 
 
 def test_fit_single_peak_external_model(fit_data):
-
     s1_scan, PLOT = fit_data
 
     f1 = Fit1D(s1_scan, fit_range=(0.5, 4.0))
@@ -94,7 +93,6 @@ def test_guess_initial(fit_data):
 
 
 def test_fit_single_peak_internal_model(fit_data):
-
     s1_scan, PLOT = fit_data
     f1 = Fit1D(s1_scan, fit_range=(0.5, 4.0))
 
@@ -116,7 +114,6 @@ def test_fit_single_peak_internal_model(fit_data):
 
 
 def test_fit_two_peak(fit_data):
-
     s1_scan, PLOT = fit_data
 
     f1 = Fit1D(s1_scan, fit_range=(0.0, 4.0), name="scan42_fit2peaks")

tests/test_nxentry.py

@@ -144,7 +144,6 @@ def test_get_from_daslogs():
 
 
 def test_spice_to_nexus_one():
-
     path_to_spice_folder = "./test_data/exp424"
     path_to_nexus = "./test_data/spice_to_nxdict_test_scan0034.h5"
     scan0034 = NexusEntry.from_spice(path_to_spice_folder, 34)
@@ -157,7 +156,6 @@ def test_spice_to_nexus_one():
 
 
 def test_spice_to_nexus_empty():
-
     path_to_spice_folder = "./test_data/exp815"
     path_to_nexus = "./test_data/spice_to_nxdict_test_empty.h5"
     scan0002 = NexusEntry.from_spice(path_to_spice_folder, 2)
@@ -191,7 +189,6 @@ def test_get_dataset_names():
 
 @pytest.fixture
 def nexus_entries():
-
     analyser = {
         "attrs": {"EX_required": "true", "NX_class": "NXcrystal", "type": "NX_CHAR"},
         "a1": {

tests/test_plotter.py

@@ -11,7 +11,6 @@
 
 
 def test_plot2d():
-
     # load data
     tavi = TAVI("./test_data/tavi_exp424.h5")
     scan_list = list(range(42, 49, 1)) + list(range(70, 76, 1))

tests/test_tavi_data.py

@@ -79,7 +79,6 @@ def tavi_exp0424():
 
 
 def test_get_scan(tavi_exp0424):
-
     scan0034 = tavi_exp0424.get_scan(scan_num=("IPTS32124_CG4C_exp0424", 34))
     assert scan0034.name == "scan0034"
     assert scan0034.scan_info.scan_num == 34