Merge pull request #19 from mj-will/add-mf-min-argument

Add option to specify `mf_min`

BBHX_Phenom.py

@@ -8,20 +8,24 @@
 from warnings import warn
 
 
-def get_waveform_genner(log_mf_min, run_phenomd=True):
+def get_waveform_genner(log_mf_min=None, mf_min=None, run_phenomd=True):
     # See below where this function is called for description of how we handle
     # log_mf_min.
-    mf_min = math.exp(log_mf_min/25.)
+    if mf_min is None:
+        mf_min = math.exp(log_mf_min/25.)
     wave_gen = BBHWaveformFD(
-        amp_phase_kwargs=dict(run_phenomd=run_phenomd, mf_min=mf_min),
+        amp_phase_kwargs=dict(
+            run_phenomd=run_phenomd,
+            mf_min=mf_min,
+        ),
     )
     return wave_gen
 
 
 @functools.lru_cache(maxsize=128)
-def cached_get_waveform_genner(log_mf_fin, run_phenomd=True):
+def cached_get_waveform_genner(*args, **kwargs):
     """Cached version of get_waveform_genner"""
-    return get_waveform_genner(log_mf_fin, run_phenomd)
+    return get_waveform_genner(*args, **kwargs)
 
 
 @functools.lru_cache(maxsize=10)
@@ -135,6 +139,7 @@ def _bbhx_fd(
     num_interp=100,
     interp_f_lower=1e-4,
     cache_generator=True,
+    mf_min=None,
     **params
 ):
 
@@ -163,8 +168,13 @@ def _bbhx_fd(
     interp_f_lower : float
         Lower frequency cutoff used for interpolation when computing the 
         chirp time.
+    mf_min : float, optional
+        Minimum frequency used by BBHx when performing interpolation. If
+        not specified, the value will be set based on the total mass and
+        minimum frequency.
     cache_generator : bool
-        If true, the BBHx waveform generator is cached based on 
+        If true, the BBHx waveform generator is cached based on the computed
+        ``mf_min``. Must be ``False`` if ``mf_min`` is specfied.
     
     Returns
     -------
@@ -200,6 +210,7 @@ def _bbhx_fd(
     num_interp = int(num_interp)
     length = int(length) if length is not None else None
     interp_f_lower = float(interp_f_lower)
+
 
     if ref_frame == 'LISA':
         t_ref_lisa = np.float64(params['tc']) + t_offset
@@ -279,14 +290,20 @@ def _bbhx_fd(
     # So we round down to the nearest 1/25 of the logarithm of the frequency
     log_mf_min = math.log(f_min*MTSUN_SI*(m1+m2)) * 25
     if cache_generator:
+        if mf_min is not None:
+            raise RuntimeError(
+                "Cannot use `cache_generator` when `mf_min` is specified"
+            )
         # Use int to round down
         wave_gen = cached_get_waveform_genner(
             int(log_mf_min),
+            mf_min=None,
             run_phenomd=run_phenomd,
         )
     else:
         wave_gen = get_waveform_genner(
             log_mf_min,
+            mf_min=mf_min,
             run_phenomd=run_phenomd,
         )