fix everything

docs/source/classes/Jetscape/index.rst

@@ -8,4 +8,3 @@ Jetscape
     :members:
     :inherited-members:
 
-.. automethod:: Jetscape.create_loader

docs/source/classes/Oscar/index.rst

@@ -8,5 +8,3 @@ Oscar
     :members:
     :inherited-members:
 
-
-.. automethod:: Oscar.create_loader

docs/source/classes/loader/JetscapeLoader/index.rst

@@ -7,6 +7,3 @@ JetscapeLoader
 .. autoclass:: JetscapeLoader
     :members:
     :inherited-members:
-
-.. automethod:: JetscapeLoader._get_num_skip_lines
-.. automethod:: JetscapeLoader.event_end_lines

docs/source/classes/loader/OscarLoader/index.rst

@@ -8,6 +8,3 @@ OscarLoader
     :members:
     :inherited-members:
 
-
-.. automethod:: OscarLoader.oscar_format
-.. automethod:: OscarLoader.event_end_lines

src/sparkx/BaseStorer.py

@@ -10,6 +10,7 @@
 from sparkx.Filter import *
 import numpy as np
 from abc import ABC, abstractmethod
+from sparkx.Particle import Particle
 from typing import List, Union, Tuple, Optional
 from sparkx.loader.BaseLoader import BaseLoader
 
@@ -74,7 +75,7 @@ class BaseStorer(ABC):
     """
 
     def __init__(
-        self, path: Union[str, List[List["Particle"]]], **kwargs
+        self, path: Union[str, List[List[Particle]]], **kwargs
     ) -> None:
         """
         Parameters
@@ -94,7 +95,7 @@ def __init__(
         self.loader_: Optional[BaseLoader] = None
         self.num_output_per_event_: Optional[np.ndarray] = None
         self.num_events_: Optional[int] = None
-        self.particle_list_: Optional[List] = None
+        self.particle_list_: List[List[Particle]] = [[]]
         self.create_loader(path)
         if self.loader_ is not None:
             (
@@ -229,7 +230,6 @@ def uncharged_particles(self) -> "BaseStorer":
         self : BaseStorer object
             Containing uncharged particles in every event only
         """
-
         self.particle_list_ = uncharged_particles(self.particle_list_)
         self._update_num_output_per_event_after_filter()
 

src/sparkx/EventCharacteristics.py

@@ -397,8 +397,8 @@ def generate_eBQS_densities_Milne_from_OSCAR_IC(self,
             raise TypeError(
                 "The smearing function only works with EventCharacteristics derived from particles."
             )
-        if not isinstance(self.event_data_, (list, np.ndarray)):
-            raise TypeError("The input is not a list nor a numpy.ndarray.")
+        if not isinstance(self.event_data_, list):
+            raise TypeError("The input is not a list.")
 
         energy_density = Lattice3D(
             x_min,
@@ -628,8 +628,8 @@ def generate_eBQS_densities_Minkowski_from_OSCAR_IC(
             raise TypeError(
                 "The smearing function only works with EventCharacteristics derived from particles."
             )
-        if not isinstance(self.event_data_, (list, np.ndarray)):
-            raise TypeError("The input is not a list nor a numpy.ndarray.")
+        if not isinstance(self.event_data_, list):
+            raise TypeError("The input is not a list.")
 
         energy_density = Lattice3D(
             x_min,

src/sparkx/Filter.py

@@ -457,10 +457,10 @@ def spacetime_cut(particle_list: List[List[Particle]], dim: str,
     return updated_particle_list
 
 
-def pt_cut(particle_list: List[List[Particle]],
+def pT_cut(particle_list: List[List[Particle]],
            cut_value_tuple: Tuple[Optional[float], Optional[float]]) -> List[List[Particle]]:
     """
-    Apply p_t cut to all events by passing an acceptance range by
+    Apply p_T cut to all events by passing an acceptance range by
     ::code`cut_value_tuple`. All particles outside this range will
     be removed.
 

src/sparkx/Histogram.py

@@ -655,7 +655,7 @@ def average_weighted(self, weights: np.ndarray) -> 'Histogram':
             np.average(self.systematic_error_**2.0, axis=0, weights=weights)
         )
         self.histogram_raw_count_ = np.sum(self.histograms_raw_count_, axis=0)
-        self.scaling_ = self.scaling_[0]
+        self.scaling_ = np.asarray(self.scaling_[0])
 
         if self.scaling_.ndim == 1:
             self.scaling_ = self.scaling_.reshape(1, -1)
@@ -716,7 +716,7 @@ def average_weighted_by_error(self) -> 'Histogram':
             np.average(self.systematic_error_**2.0, axis=0, weights=weights)
         )
         self.histogram_raw_count_ = np.sum(self.histograms_raw_count_, axis=0)
-        self.scaling_ = self.scaling_[0]
+        self.scaling_ = np.asarray(self.scaling_[0])
 
         if self.scaling_.ndim == 1:
             self.scaling_ = self.scaling_.reshape(1, -1)

src/sparkx/JetAnalysis.py

@@ -143,12 +143,12 @@ def __init__(self) -> None:
         self.hadron_data_: Optional[List[List[Particle]]] = None
         self.jet_R_: Optional[float] = None
         self.jet_eta_range_: Optional[tuple] = None
-        self.jet_pt_range_: Optional[tuple] = None
+        self.jet_pT_range_: Optional[tuple] = None
         self.jet_data_: Optional[List[List[Any]]] = None
 
     def __initialize_and_check_parameters(self, hadron_data: List[List[Particle]], jet_R: float, 
                                           jet_eta_range: Tuple[Optional[float], Optional[float]], 
-                                          jet_pt_range: Tuple[Optional[float], Optional[float]]) -> None:
+                                          jet_pT_range: Tuple[Optional[float], Optional[float]]) -> None:
         """
         Initialize and check the parameters for jet analysis.
 
@@ -207,16 +207,16 @@ def __initialize_and_check_parameters(self, hadron_data: List[List[Particle]], j
                           "upper one. They are interchanged automatically.")
 
         # check the jet pt range
-        if not isinstance(jet_pt_range, tuple):
-            raise TypeError("jet_pt_range is not a tuple. " +
+        if not isinstance(jet_pT_range, tuple):
+            raise TypeError("jet_pT_range is not a tuple. " +
                             "It must contain either values or None.")
-        if len(jet_pt_range) != 2:
-            raise ValueError("jet_pt_range must contain exactly two values.")
-        if any(pt is not None and pt < 0 for pt in jet_pt_range):
-            raise ValueError("All values in jet_pt_range must be non-negative.")
+        if len(jet_pT_range) != 2:
+            raise ValueError("jet_pT_range must contain exactly two values.")
+        if any(pT is not None and pT < 0 for pT in jet_pT_range):
+            raise ValueError("All values in jet_pT_range must be non-negative.")
 
-        lower_cut = 0. if jet_pt_range[0] is None else jet_pt_range[0]
-        upper_cut = float('inf') if jet_pt_range[1] is None else jet_pt_range[1]
+        lower_cut = 0. if jet_pT_range[0] is None else jet_pT_range[0]
+        upper_cut = float('inf') if jet_pT_range[1] is None else jet_pT_range[1]
         if lower_cut < upper_cut:
             self.jet_pT_range_ = (lower_cut, upper_cut)
         else:
@@ -359,8 +359,8 @@ def write_jet_output(self, output_filename: str, jet: fj.PseudoJet,
         bool
             False if successful.
         """
-        if self.jet_pt_range_ is None:
-            raise TypeError("'jet_pt_range_' is None. It must be initialized before calling the 'write_jet_output' function.")
+        if self.jet_pT_range_ is None:
+            raise TypeError("'jet_pT_range_' is None. It must be initialized before calling the 'write_jet_output' function.")
 
         # jet data from reconstruction
         jet_status = 10
@@ -408,7 +408,7 @@ def write_jet_output(self, output_filename: str, jet: fj.PseudoJet,
 
     def perform_jet_finding(self, hadron_data: List[List[Particle]], jet_R: float,
             jet_eta_range: Tuple[Optional[float], Optional[float]],
-            jet_pt_range: Tuple[Optional[float], Optional[float]],
+            jet_pT_range: Tuple[Optional[float], Optional[float]],
             output_filename: str, assoc_only_charged: bool = True,
             jet_algorithm: fj = fj.antikt_algorithm) -> None:
         """
@@ -448,16 +448,16 @@ def perform_jet_finding(self, hadron_data: List[List[Particle]], jet_R: float,
         package is fixed here.
 
         """
+        self.__initialize_and_check_parameters(
+            hadron_data, jet_R, jet_eta_range, jet_pT_range
+        )
         if self.hadron_data_ is None:
             raise TypeError("'hadron_data_' is None. It must be initialized before calling the 'perform_jet_finding' function.")
         if self.jet_eta_range_ is None:
             raise TypeError("'jet_eta_range_' is None. It must be initialized before calling the 'perform_jet_finding' function.")
-        if self.jet_pt_range_ is None:
-            raise TypeError("'jet_pt_range_' is None. It must be initialized before calling the 'perform_jet_finding' function.")
+        if self.jet_pT_range_ is None:
+            raise TypeError("'jet_pT_range_' is None. It must be initialized before calling the 'perform_jet_finding' function.")
 
-        self.__initialize_and_check_parameters(
-            hadron_data, jet_R, jet_eta_range, jet_pT_range
-        )
         for event, hadron_data_event in enumerate(self.hadron_data_):
             new_file = False
             event_PseudoJets = self.create_fastjet_PseudoJets(hadron_data_event)
@@ -516,9 +516,6 @@ def read_jet_data(self, input_filename: str) -> None:
         input_filename: str
             Filename of the CSV file containing the jet data.
         """
-        if self.jet_data_ is None:
-            raise TypeError("'jet_data_' is None. It must be initialized before calling the 'read_jet_data' function.")
-
         jet_data = []
         current_jet: List[List[Any]] = []
         with open(input_filename, 'r', newline='') as f:

src/sparkx/Jetscape.py

@@ -10,6 +10,7 @@
 from sparkx.Filter import *
 import numpy as np
 from sparkx.loader.JetscapeLoader import JetscapeLoader
+from sparkx.Particle import Particle
 from sparkx.BaseStorer import BaseStorer
 from typing import List, Tuple, Union, Dict, Optional
 
@@ -181,18 +182,19 @@ def __init__(
         )
         self.last_line_: str = self.loader_.get_last_line(JETSCAPE_FILE)
         del self.loader_
+
     def create_loader(
-            self, JETSCAPE_FILE: Union[str, List[List["Particle"]]]
+            self, JETSCAPE_FILE: Union[str, List[List[Particle]]]
         ) -> None:
         """
         Creates a new JetscapeLoader object.
 
         This method initializes a new JetscapeLoader object with the specified JETSCAPE file
-        and assigns it to the loader_ attribute.
+        and assigns it to the loader attribute.
 
         Parameters
         ----------
-        JETSCAPE_FILE : Union[str, List[List["Particle"]]]
+        JETSCAPE_FILE : Union[str, List[List[Particle]]]
             The path to the JETSCAPE file to be loaded. Must be a string.
 
         Raises
@@ -210,7 +212,7 @@ def create_loader(
 
     # PRIVATE CLASS METHODS
     def _particle_as_list(
-        self, particle: "Particle"
+        self, particle: Particle
     ) -> List[Union[int, float]]:
         particle_list: List[Union[int, float]] = [0.0] * 7
         particle_list[0] = int(particle.ID)

src/sparkx/Lattice3D.py

@@ -266,8 +266,6 @@ def __get_index(self, value: Union[int, float],
             The value for which the index is to be determined.
         values : list or numpy.ndarray
             The list or array containing the range of values, sorted ascending.
-        num_points : int
-            The number of points in the range.
 
         Returns
         -------
@@ -1230,7 +1228,7 @@ def interpolate_to_lattice_new_extent(self, num_points_x: int, num_points_y: int
                         or z < self.z_min_
                         or z > self.z_max_
                     ):
-                        value = 0
+                        value = 0.0
                     else:
                         value = self.interpolate_value(x, y, z)
                     new_lattice.set_value_by_index(i, j, k, value)
@@ -1277,6 +1275,8 @@ def add_same_spaced_grid(self, other: 'Lattice3D', center_x: float, center_y: fl
             raise TypeError(
                 "Unsupported operand type. The operand must be of type 'Lattice3D'."
             )
+        if self.spacing_x_ is None or self.spacing_y_ is None or self.spacing_z_ is None:
+            raise TypeError("At least one of the 'spacing' is None.")
         # Check if both lattices have the same spacing
         if (
             (

src/sparkx/MultiParticlePtCorrelations.py

@@ -343,7 +343,7 @@ def _compute_mean_pT_correlations(
 
         return sum_numerator / sum_denominator
 
-    def mean_pt_correlations(self,
+    def mean_pT_correlations(self,
                              particle_list_all_events: List[List[Particle]],
                              compute_error: bool = True,
                              delete_fraction: float = 0.4,

src/sparkx/Oscar.py

@@ -172,7 +172,7 @@ def __init__(self, OSCAR_FILE: str, **kwargs: Any) -> None:
         self.PATH_OSCAR_: str = OSCAR_FILE
         if not isinstance(self.loader_, OscarLoader):
             raise TypeError("The loader must be an instance of OscarLoader.")
-        self.oscar_format_: Union[str | None] = self.loader_.oscar_format()
+        self.oscar_format_: Union[str, None] = self.loader_.oscar_format()
         self.event_end_lines_: List[str] = self.loader_.event_end_lines()
         del self.loader_
 
@@ -181,7 +181,7 @@ def create_loader(self, OSCAR_FILE: str) -> None:  # type: ignore[override]
         Creates a new OscarLoader object.
     
         This method initializes a new OscarLoader object with the specified OSCAR file
-        and assigns it to the loader_ attribute.
+        and assigns it to the loader attribute.
     
         Parameters
         ----------

src/sparkx/flow/EventPlaneFlow.py

@@ -98,7 +98,7 @@ class EventPlaneFlow(FlowInterface.FlowInterface):
 
     """
 
-    def __init__(self, n: int = 2, weight: str = "pt2", pseudorapidity_gap: float = 0.) -> None:
+    def __init__(self, n: int = 2, weight: str = "pT2", pseudorapidity_gap: float = 0.) -> None:
         """
         Initialize the ScalarProductFlow object.
 
@@ -107,7 +107,7 @@ def __init__(self, n: int = 2, weight: str = "pt2", pseudorapidity_gap: float =
         n : int, optional
             The value of the harmonic. Default is 2.
         weight : str, optional
-            The weight used for calculating the flow. Default is "pt2".
+            The weight used for calculating the flow. Default is "pT2".
         pseudorapidity_gap : float, optional
             The pseudorapidity gap used for dividing the particles into sub-events.
             Default is 0.0.
@@ -123,7 +123,7 @@ def __init__(self, n: int = 2, weight: str = "pt2", pseudorapidity_gap: float =
             self.n_ = n
         if not isinstance(weight, str):
             raise TypeError('weight has to be a string')
-        elif weight not in ["pt", "pt2", "ptn", "rapidity", "pseudorapidity"]:
+        elif weight not in ["pT", "pT2", "pTn", "rapidity", "pseudorapidity"]:
             raise ValueError(
                 "Invalid weight given, choose one of the following: 'pT', 'pT2', 'pTn', 'rapidity', 'pseudorapidity'"
             )
@@ -495,7 +495,7 @@ def differential_flow(
             raise TypeError('bins has to be list or np.ndarray')
         if not isinstance(flow_as_function_of, str):
             raise TypeError('flow_as_function_of is not a string')
-        if flow_as_function_of not in ["pt", "rapidity", "pseudorapidity"]:
+        if flow_as_function_of not in ["pT", "rapidity", "pseudorapidity"]:
             raise ValueError(
                 "flow_as_function_of must be either 'pT', 'rapidity', 'pseudorapidity'"
             )

src/sparkx/flow/GenerateFlow.py

@@ -188,7 +188,7 @@ def __thermal_distribution(self, temperature: float, mass: float) -> float:
             momentum_radial: float
                 The magnitude of the momentum.
         """
-        momentum_radial = 0
+        momentum_radial = 0.0
         energy = 0.0
         if temperature > 0.6 * mass:
             while True:
@@ -364,7 +364,7 @@ def __artificial_flow_pT_shape(self, pT: float, pT0_bis: float, pT_sat: float, v
 
         return value
 
-    def __distribution_function_pT_differential(self, phi: float, vn_pt_list: List[float]) -> float:
+    def __distribution_function_pT_differential(self, phi: float, vn_pT_list: List[float]) -> float:
         """
         Calculates the pT-differential distribution function for a given
         azimuthal angle.
@@ -433,7 +433,7 @@ def __create_k_particle_correlations(
         self.py_ = py
         self.pz_ = pz
 
-    def __generate_flow_realistic_pt_distribution(
+    def __generate_flow_realistic_pT_distribution(
             self, multiplicity: int, reaction_plane_angle: float) -> None:
         pTmax = 4.5
         pTmin = 0.1
@@ -568,7 +568,7 @@ def generate_dummy_JETSCAPE_file(
 
             output.write("#	sigmaGen	0.0	sigmaErr	0.0")
 
-    def generate_dummy_JETSCAPE_file_realistic_pt_shape(
+    def generate_dummy_JETSCAPE_file_realistic_pT_shape(
             self,
             output_path: str,
             number_events: int,
@@ -761,7 +761,7 @@ def generate_dummy_JETSCAPE_file_multi_particle_correlations(
 
             output.write("#	sigmaGen	0.0	sigmaErr	0.0")
 
-    def generate_dummy_JETSCAPE_file_realistic_pt_shape_multi_particle_correlations(
+    def generate_dummy_JETSCAPE_file_realistic_pT_shape_multi_particle_correlations(
             self,
             output_path: str,
             number_events: int,
@@ -962,7 +962,7 @@ def generate_dummy_OSCAR_file(
                 output.write(
                     f"# event {event} end 0 impact  -1.000 scattering_projectile_target no\n")
 
-    def generate_dummy_OSCAR_file_realistic_pt_shape(
+    def generate_dummy_OSCAR_file_realistic_pT_shape(
             self,
             output_path: str,
             number_events: int,
@@ -1172,7 +1172,7 @@ def generate_dummy_OSCAR_file_multi_particle_correlations(
                 output.write(
                     f"# event {event} end 0 impact  -1.000 scattering_projectile_target no\n")
 
-    def generate_dummy_OSCAR_file_realistic_pt_shape_multi_particle_correlations(
+    def generate_dummy_OSCAR_file_realistic_pT_shape_multi_particle_correlations(
             self,
             output_path: str,
             number_events: int,