Move log_linear_ells to generators

firecrown/generators/two_point.py

@@ -52,3 +52,19 @@ def generate(self) -> npt.NDArray[np.int64]:
         # Round the results to the nearest integer values.
         # N.B. the dtype of the result is np.dtype[float64]
         return np.unique(np.around(concatenated)).astype(np.int64)
+
+
+def log_linear_ells(
+    *, minimum: int, midpoint: int, maximum: int, n_log: int
+) -> npt.NDArray[np.int64]:
+    """Create an array of ells to sample the power spectrum.
+
+    This is used for for real-space predictions. The result will contain
+    each integral value from min to mid. Starting from mid, and going up
+    to max, there will be n_log logarithmically spaced values.
+
+    All values are rounded to the nearest integer.
+    """
+    return LogLinearElls(
+        minimum=minimum, midpoint=midpoint, maximum=maximum, n_log=n_log
+    ).generate()

firecrown/likelihood/two_point.py

@@ -16,7 +16,7 @@
 # firecrown is needed for backward compatibility; remove support for deprecated
 # directory structure is removed.
 import firecrown  # pylint: disable=unused-import # noqa: F401
-from firecrown.generators.two_point import LogLinearElls, ELL_FOR_XI_DEFAULTS
+from firecrown.generators.two_point import ELL_FOR_XI_DEFAULTS, log_linear_ells
 from firecrown.likelihood.source import Source, Tracer
 from firecrown.likelihood.weak_lensing import (
     WeakLensingFactory,
@@ -66,22 +66,6 @@
 }
 
 
-def log_linear_ells(
-    *, minimum: int, midpoint: int, maximum: int, n_log: int
-) -> npt.NDArray[np.int64]:
-    """Create an array of ells to sample the power spectrum.
-
-    This is used for for real-space predictions. The result will contain
-    each integral value from min to mid. Starting from mid, and going up
-    to max, there will be n_log logarithmically spaced values.
-
-    All values are rounded to the nearest integer.
-    """
-    return LogLinearElls(
-        minimum=minimum, midpoint=midpoint, maximum=maximum, n_log=n_log
-    ).generate()
-
-
 def generate_bin_centers(
     *, minimum: float, maximum: float, n: int, binning: str = "log"
 ) -> npt.NDArray[np.float64]:

tests/likelihood/gauss_family/statistic/test_two_point.py

@@ -21,7 +21,6 @@
 )
 from firecrown.likelihood.statistic import TheoryVector
 from firecrown.likelihood.two_point import (
-    log_linear_ells,
     generate_bin_centers,
     TwoPoint,
     TracerNames,
@@ -32,6 +31,7 @@
     WeakLensingFactory,
     NumberCountsFactory,
 )
+from firecrown.generators.two_point import log_linear_ells
 from firecrown.metadata_types import (
     Galaxies,
     InferredGalaxyZDist,