diff --git a/ml4gw/transforms/spline_interpolation.py b/ml4gw/transforms/spline_interpolation.py
index 6972560f..005b0c6f 100644
--- a/ml4gw/transforms/spline_interpolation.py
+++ b/ml4gw/transforms/spline_interpolation.py
@@ -263,7 +263,7 @@ def bivariate_spline_fit_natural(self, Z):
             return torch.linalg.solve(self.BxT_Bx, Z_Bx.mT).mT
 
         # Adding batch/channel dimension handling
-        # ByT @ Z @ Bx
+        # ByT @ Z @ BxW
         ByT_Z_Bx = torch.einsum("ij,bcik,kl->bcjl", self.By, Z, self.Bx)
         # (ByT @ By)^-1 @ (ByT @ Z @ Bx) = By^-1 @ Z @ Bx
         E = torch.linalg.solve(self.ByT_By, ByT_Z_Bx)
diff --git a/ml4gw/waveforms/cbc/phenom_d.py b/ml4gw/waveforms/cbc/phenom_d.py
index 9a883825..8b4911af 100644
--- a/ml4gw/waveforms/cbc/phenom_d.py
+++ b/ml4gw/waveforms/cbc/phenom_d.py
@@ -157,20 +157,30 @@ def phenom_d_amp(
         chi22,
         xi,
         distance,
+        fRD=None,  # used for passing ringdown frequency from phenom_p
+        fDM=None,  # used for passing damping frequency from phenom_p
     ):
         ins_amp, ins_Damp = self.phenom_d_inspiral_amp(
             Mf, eta, eta2, Seta, xi, chi1, chi2, chi12, chi22
         )
         int_amp, int_Damp = self.phenom_d_int_amp(
-            Mf, eta, eta2, Seta, chi1, chi2, chi12, chi22, xi
+            Mf, eta, eta2, Seta, chi1, chi2, chi12, chi22, xi, fRD, fDM
         )
         mrd_amp, mrd_Damp = self.phenom_d_mrd_amp(
-            Mf, eta, eta2, chi1, chi2, xi
+            Mf, eta, eta2, chi1, chi2, xi, fRD, fDM
         )
 
         gamma2 = self.gamma2_fun(eta, eta2, xi)
         gamma3 = self.gamma3_fun(eta, eta2, xi)
-        fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
+
+        # merger ringdown
+        if (fRD is None) != (fDM is None):
+            raise ValueError(
+                "Both fRD and fDM must either be provided or both be None"
+            )
+        if (fRD is None) and (fDM is None):
+            fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
+
         Mf_peak = self.fmaxCalc(fRD, fDM, gamma2, gamma3)
         # Geometric peak and joining frequencies
         Mf_peak = (torch.ones_like(Mf).mT * Mf_peak).mT
@@ -201,10 +211,27 @@ def phenom_d_amp(
         return amp, Damp
 
     def phenom_d_int_amp(
-        self, Mf, eta, eta2, Seta, chi1, chi2, chi12, chi22, xi
+        self,
+        Mf,
+        eta,
+        eta2,
+        Seta,
+        chi1,
+        chi2,
+        chi12,
+        chi22,
+        xi,
+        fRD=None,  # used for passing ringdown frequency from phenom_p
+        fDM=None,  # used for passing damping frequency from phenom_p
     ):
         # merger ringdown
-        fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
+        if (fRD is None) != (fDM is None):
+            raise ValueError(
+                "Both fRD and fDM must either be provided or both be None"
+            )
+        if (fRD is None) and (fDM is None):
+            fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
+
         # Geometric frequency definition from PhenomD header file
         AMP_fJoin_INS = 0.014
 
@@ -220,7 +247,9 @@ def phenom_d_int_amp(
         v1, d1 = self.phenom_d_inspiral_amp(
             Mf1, eta, eta2, Seta, xi, chi1, chi2, chi12, chi22
         )
-        v3, d2 = self.phenom_d_mrd_amp(Mf3, eta, eta2, chi1, chi2, xi)
+        v3, d2 = self.phenom_d_mrd_amp(
+            Mf3, eta, eta2, chi1, chi2, xi, fRD, fDM
+        )
         v2 = (
             torch.ones_like(Mf).mT * self.AmpIntColFitCoeff(eta, eta2, xi)
         ).mT
@@ -239,9 +268,18 @@ def phenom_d_int_amp(
         )
         return amp, Damp
 
-    def phenom_d_mrd_amp(self, Mf, eta, eta2, chi1, chi2, xi):
+    # fRD and fDM are to be passed for generating phenom_p waveforms
+    # and remain None for phenom_d
+    def phenom_d_mrd_amp(
+        self, Mf, eta, eta2, chi1, chi2, xi, fRD=None, fDM=None
+    ):
         # merger ringdown
-        fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
+        if (fRD is None) != (fDM is None):
+            raise ValueError(
+                "Both fRD and fDM must either be provided or both be None"
+            )
+        if (fRD is None) and (fDM is None):
+            fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
 
         gamma1 = self.gamma1_fun(eta, eta2, xi)
         gamma2 = self.gamma2_fun(eta, eta2, xi)
@@ -384,17 +422,26 @@ def phenom_d_inspiral_amp(
 
         return amp, Damp
 
-    def phenom_d_phase(self, Mf, mass_1, mass_2, eta, eta2, chi1, chi2, xi):
+    # fRD and fDM are to be passed for generating phenom_p waveforms
+    # and remain None for phenom_d
+    def phenom_d_phase(
+        self, Mf, mass_1, mass_2, eta, eta2, chi1, chi2, xi, fRD=None, fDM=None
+    ):
         ins_phase, ins_Dphase = self.phenom_d_inspiral_phase(
             Mf, mass_1, mass_2, eta, eta2, xi, chi1, chi2
         )
         int_phase, int_Dphase = self.phenom_d_int_phase(Mf, eta, eta2, xi)
         mrd_phase, mrd_Dphase = self.phenom_d_mrd_phase(
-            Mf, eta, eta2, chi1, chi2, xi
+            Mf, eta, eta2, chi1, chi2, xi, fRD, fDM
         )
 
         # merger ringdown
-        fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
+        if (fRD is None) != (fDM is None):
+            raise ValueError(
+                "Both fRD and fDM must either be provided or both be None"
+            )
+        if (fRD is None) and (fDM is None):
+            fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
         # definitions in Eq. (35) of arXiv:1508.07253
         # PHI_fJoin_INS in header LALSimIMRPhenomD.h
         # C1 continuity at intermediate region i.e. f_1
@@ -415,7 +462,7 @@ def phenom_d_phase(self, Mf, mass_1, mass_2, eta, eta2, chi1, chi2, xi):
             fRDJoin, eta, eta2, xi
         )
         mrd_phase_rd, mrd_Dphase_rd = self.phenom_d_mrd_phase(
-            fRDJoin, eta, eta2, chi1, chi2, xi
+            fRDJoin, eta, eta2, chi1, chi2, xi, fRD, fDM
         )
         PhiIntTempVal = (int_phase_rd.mT / eta).mT + C1Int + C2Int * fRDJoin
         # C2MRD = int_Dphase_rd - mrd_Dphase_rd
@@ -454,7 +501,11 @@ def phenom_d_phase(self, Mf, mass_1, mass_2, eta, eta2, chi1, chi2, xi):
 
         return phasing, Dphasing
 
-    def phenom_d_mrd_phase(self, Mf, eta, eta2, chi1, chi2, xi):
+    # fRD and fDM are to be passed for generating phenom_p waveforms
+    # and remain None for phenom_d
+    def phenom_d_mrd_phase(
+        self, Mf, eta, eta2, chi1, chi2, xi, fRD=None, fDM=None
+    ):
         alpha1 = self.alpha1Fit(eta, eta2, xi)
         alpha2 = self.alpha2Fit(eta, eta2, xi)
         alpha3 = self.alpha3Fit(eta, eta2, xi)
@@ -462,9 +513,14 @@ def phenom_d_mrd_phase(self, Mf, eta, eta2, chi1, chi2, xi):
         alpha5 = self.alpha5Fit(eta, eta2, xi)
 
         # merger ringdown
-        fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
-        f_minus_alpha5_fRD = (Mf.t() - alpha5 * fRD).t()
+        if (fRD is None) != (fDM is None):
+            raise ValueError(
+                "Both fRD and fDM must either be provided or both be None"
+            )
+        if (fRD is None) and (fDM is None):
+            fRD, fDM = self.fring_fdamp(eta, eta2, chi1, chi2)
 
+        f_minus_alpha5_fRD = (Mf.t() - alpha5 * fRD).t()
         # Leading 1/eta is not multiplied at this stage
         mrd_phasing = (Mf.t() * alpha1).t()
         mrd_phasing -= (1 / Mf.t() * alpha2).t()
diff --git a/ml4gw/waveforms/cbc/phenom_p.py b/ml4gw/waveforms/cbc/phenom_p.py
index df91ef2f..c1b2b0f1 100644
--- a/ml4gw/waveforms/cbc/phenom_p.py
+++ b/ml4gw/waveforms/cbc/phenom_p.py
@@ -1,13 +1,21 @@
+"""
+    Based on the JAX implementation of IMRPhenomPv2 from
+    https://github.com/tedwards2412/ripple/blob/main/src/ripplegw/waveforms/IMRPhenomPv2.py
+"""
+
 from typing import Dict, Optional, Tuple
 
 import torch
 from jaxtyping import Float
 from torch import Tensor
 
-from ml4gw.constants import MPC_SEC, MTSUN_SI, PI
-from ml4gw.types import BatchTensor, FrequencySeries1d
-from ml4gw.waveforms.conversion import rotate_y, rotate_z
-
+from ...constants import MPC_SEC, MTSUN_SI, PI
+from ...types import BatchTensor, FrequencySeries1d
+from ..conversion import (
+    chirp_mass_and_mass_ratio_to_components,
+    rotate_y,
+    rotate_z,
+)
 from .phenom_d import IMRPhenomD
 
 
@@ -75,15 +83,15 @@ def forward(
         if tc is None:
             tc = torch.zeros_like(chirp_mass)
 
-        m2 = chirp_mass * (1.0 + mass_ratio) ** 0.2 / mass_ratio**0.6
-        m1 = m2 * mass_ratio
+        m1, m2 = chirp_mass_and_mass_ratio_to_components(
+            chirp_mass, mass_ratio
+        )
 
         # # flip m1 m2. For some reason LAL uses this convention for PhenomPv2
         m1, m2 = m2, m1
         s1x, s2x = s2x, s1x
         s1y, s2y = s2y, s1y
         s1z, s2z = s2z, s1z
-
         (
             chi1_l,
             chi2_l,
@@ -320,42 +328,61 @@ def PhenomPOneFrequency(
         phic: Orbital phase at peak of the underlying non precessing model
         M: Total mass (Solar masses)
         """
-
         M_s = M * MTSUN_SI
         Mf = torch.outer(M_s, fs)
-        fRD, _ = self.phP_get_fRD_fdamp(m1, m2, chi1, chi2, chip)
+        fRD, fDM = self.phP_get_fRD_fdamp(m1, m2, chi1, chi2, chip)
+        # pass M_s * ringdown and M_s * damping frequency to PhenomD functions
+        MfRD, MfDM = M_s * fRD, M_s * fDM
 
-        phase, _ = self.phenom_d_phase(Mf, m1, m2, eta, eta2, chi1, chi2, xi)
+        phase, _ = self.phenom_d_phase(
+            Mf, m1, m2, eta, eta2, chi1, chi2, xi, MfRD, MfDM
+        )
         phase = (phase.mT - (phic + PI / 4.0)).mT
+        # why are they subtracting 2*phic?
+        # https://git.ligo.org/lscsoft/lalsuite/-/blob/master/lalsimulation/lib/LALSimIMRPhenomP.c#L1316
+
         Amp = self.phenom_d_amp(
-            Mf, m1, m2, eta, eta2, Seta, chi1, chi2, chi12, chi22, xi, distance
+            Mf,
+            m1,
+            m2,
+            eta,
+            eta2,
+            Seta,
+            chi1,
+            chi2,
+            chi12,
+            chi22,
+            xi,
+            distance,
+            MfRD,
+            MfDM,
         )[0]
         Amp0 = self.get_Amp0(Mf, eta)
         dist_s = distance * MPC_SEC
         Amp = ((Amp0 * Amp).mT * (M_s**2.0) / dist_s).mT
-        # phase -= 2. * phic; # line 1316 ???
+
         hPhenom = Amp * (torch.exp(-1j * phase))
 
-        fRDs = torch.outer(
-            fRD, torch.linspace(0.5, 1.5, 101, device=fRD.device)
-        )
-        delta_fRds = torch.median(torch.diff(fRDs, axis=1), axis=1)[0]
+        # calculating derivative of phase with frequency following
+        # https://git.ligo.org/lscsoft/lalsuite/-/blame/master/lalsimulation/lib/LALSimIMRPhenomP.c?page=2#L1057 # noqa: E501
+        n_fixed = 1000
+        x = torch.linspace(0.8, 1.2, n_fixed, device=fRD.device)
+        fRDs = torch.outer(fRD, x)
+        delta_fRds = (1.2 * fRD - 0.8 * fRD) / (n_fixed - 1)
         MfRDs = torch.zeros_like(fRDs)
         for i in range(fRD.shape[0]):
             MfRDs[i, :] = torch.outer(M_s, fRDs[i, :])[i, :]
         RD_phase = self.phenom_d_phase(
-            MfRDs, m1, m2, eta, eta2, chi1, chi2, xi
+            MfRDs, m1, m2, eta, eta2, chi1, chi2, xi, MfRD, MfDM
         )[0]
         diff = torch.diff(RD_phase, axis=1)
         diffRDphase = (diff[:, 1:] + diff[:, :-1]) / (
             2 * delta_fRds.unsqueeze(1)
         )
-        diffRDphase = -diffRDphase[:, 50]
-        # MfRD = torch.outer(M_s, fRD)
-        # Dphase = torch.diag(
-        #     -self.phenom_d_phase(
-        #         MfRD, m1, m2, eta, eta2, chi1, chi2, xi)[1] * M_s
-        # ).view(-1, 1)
+        # reshape x to have same shape as diffRDphase
+        x = x[1:-1].unsqueeze(0).expand(diffRDphase.shape)
+        # interpolate at x = 1, as thats the same as f = fRD
+        diffRDphase = -self.interpolate(torch.tensor([1]), x, diffRDphase)
         return hPhenom, diffRDphase
 
     # Utility functions
@@ -752,9 +779,9 @@ def FinalSpin_inplane(
         eta2 = eta * eta
         # m1 > m2, the convention used in phenomD
         # (not the convention of internal phenomP)
-        mass_ratio = m1 / m2
+        q_factor = m1 / M
         af_parallel = self.FinalSpin0815(eta, eta2, chi1_l, chi2_l)
-        Sperp = chip * mass_ratio * mass_ratio
+        Sperp = chip * q_factor * q_factor
         af = torch.copysign(
             torch.ones_like(af_parallel), af_parallel
         ) * torch.sqrt(Sperp * Sperp + af_parallel * af_parallel)
diff --git a/poetry.lock b/poetry.lock
index 535748e5..de0b4598 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -13,13 +13,13 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.5.0"
+version = "4.5.2"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "anyio-4.5.0-py3-none-any.whl", hash = "sha256:fdeb095b7cc5a5563175eedd926ec4ae55413bb4be5770c424af0ba46ccb4a78"},
-    {file = "anyio-4.5.0.tar.gz", hash = "sha256:c5a275fe5ca0afd788001f58fca1e69e29ce706d746e317d660e21f70c530ef9"},
+    {file = "anyio-4.5.2-py3-none-any.whl", hash = "sha256:c011ee36bc1e8ba40e5a81cb9df91925c218fe9b778554e0b56a21e1b5d4716f"},
+    {file = "anyio-4.5.2.tar.gz", hash = "sha256:23009af4ed04ce05991845451e11ef02fc7c5ed29179ac9a420e5ad0ac7ddc5b"},
 ]
 
 [package.dependencies]
@@ -30,7 +30,7 @@ typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
 trio = ["trio (>=0.26.1)"]
 
 [[package]]
@@ -175,21 +175,18 @@ test-all = ["coverage[toml]", "ipython (>=4.2)", "objgraph", "pytest (>=7.0)", "
 
 [[package]]
 name = "asttokens"
-version = "2.4.1"
+version = "3.0.0"
 description = "Annotate AST trees with source code positions"
 optional = false
-python-versions = "*"
+python-versions = ">=3.8"
 files = [
-    {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"},
-    {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"},
+    {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"},
+    {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"},
 ]
 
-[package.dependencies]
-six = ">=1.12.0"
-
 [package.extras]
-astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
-test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
+astroid = ["astroid (>=2,<4)"]
+test = ["astroid (>=2,<4)", "pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "async-lru"
@@ -207,19 +204,19 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
 
 [[package]]
 name = "attrs"
-version = "24.2.0"
+version = "24.3.0"
 description = "Classes Without Boilerplate"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"},
-    {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"},
+    {file = "attrs-24.3.0-py3-none-any.whl", hash = "sha256:ac96cd038792094f438ad1f6ff80837353805ac950cd2aa0e0625ef19850c308"},
+    {file = "attrs-24.3.0.tar.gz", hash = "sha256:8f5c07333d543103541ba7be0e2ce16eeee8130cb0b3f9238ab904ce1e85baff"},
 ]
 
 [package.extras]
 benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
-dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
 tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
@@ -275,13 +272,13 @@ lxml = ["lxml"]
 
 [[package]]
 name = "bilby"
-version = "2.2.2"
+version = "2.2.2.1"
 description = "A user-friendly Bayesian inference library"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "bilby-2.2.2-py3-none-any.whl", hash = "sha256:619cd5728272b4969e0eb413d9e2af38516e0906499c65d078e513faba98eaac"},
-    {file = "bilby-2.2.2.tar.gz", hash = "sha256:e28cff434ff3f197b57d30fabc915812bc1153e31177aca617ef8af1b0a0a6c8"},
+    {file = "bilby-2.2.2.1-py3-none-any.whl", hash = "sha256:5c1010a876a568b8b7628132ab0295547bd01d8de3ea48ca2e3438336c1ce921"},
+    {file = "bilby-2.2.2.1.tar.gz", hash = "sha256:832855233331592a23084ad0cec3673ffc845433517c77ef4b4513abbb2e8085"},
 ]
 
 [package.dependencies]
@@ -343,6 +340,7 @@ files = [
 
 [package.dependencies]
 six = ">=1.9.0"
+tinycss2 = {version = ">=1.1.0,<1.3", optional = true, markers = "extra == \"css\""}
 webencodings = "*"
 
 [package.extras]
@@ -350,13 +348,13 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
 
 [[package]]
 name = "certifi"
-version = "2024.8.30"
+version = "2024.12.14"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"},
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 [[package]]
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 [[package]]
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 [[package]]
 name = "cryptography"
-version = "43.0.1"
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 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -775,7 +775,7 @@ nox = ["nox"]
 pep8test = ["check-sdist", "click", "mypy", "ruff"]
 sdist = ["build"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi", "cryptography-vectors (==43.0.1)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
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 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -795,33 +795,37 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "debugpy"
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+    {file = "fonttools-4.55.3.tar.gz", hash = "sha256:3983313c2a04d6cc1fe9251f8fc647754cf49a61dac6cb1e7249ae67afaafc45"},
 ]
 
 [package.extras]
@@ -1074,13 +1080,13 @@ files = [
 
 [[package]]
 name = "fsspec"
-version = "2024.9.0"
+version = "2024.12.0"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fsspec-2024.9.0-py3-none-any.whl", hash = "sha256:a0947d552d8a6efa72cc2c730b12c41d043509156966cca4fb157b0f2a0c574b"},
-    {file = "fsspec-2024.9.0.tar.gz", hash = "sha256:4b0afb90c2f21832df142f292649035d80b421f60a9e1c027802e5a0da2b04e8"},
+    {file = "fsspec-2024.12.0-py3-none-any.whl", hash = "sha256:b520aed47ad9804237ff878b504267a3b0b441e97508bd6d2d8774e3db85cee2"},
+    {file = "fsspec-2024.12.0.tar.gz", hash = "sha256:670700c977ed2fb51e0d9f9253177ed20cbde4a3e5c0283cc5385b5870c8533f"},
 ]
 
 [package.extras]
@@ -1133,21 +1139,20 @@ test = ["pytest (>=2.8.0)", "pytest-cov", "requests-mock"]
 
 [[package]]
 name = "gwosc"
-version = "0.7.1"
+version = "0.7.2"
 description = "A python interface to the GW Open Science data archive"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.8"
 files = [
-    {file = "gwosc-0.7.1-py3-none-any.whl", hash = "sha256:4cb7598f9aaf8749c032e8913c723a391784a52127397989c9f733f8c3f99558"},
-    {file = "gwosc-0.7.1.tar.gz", hash = "sha256:5328223410081731ba4ef6f3be9f13ac4b3b9a43397fa04c1f50ddeb59895816"},
+    {file = "gwosc-0.7.2-py3-none-any.whl", hash = "sha256:53b42227ccb5a538068fb741fbb4b30cd346904ce993c6972f8da9dd67292d64"},
+    {file = "gwosc-0.7.2.tar.gz", hash = "sha256:32a7bd8096e0acfa6d57dc907dc36dc9034734a5c0a31cd902d132e09269f90a"},
 ]
 
 [package.dependencies]
 requests = ">=1.0.0"
 
 [package.extras]
-docs = ["sphinx", "sphinx-automodapi", "sphinx-rtd-theme"]
-lint = ["flake8 (<5.0.0a0)", "flake8-bandit"]
+docs = ["sphinx", "sphinx-automodapi", "sphinx-immaterial-igwn"]
 test = ["pytest (>=2.7.0)", "pytest-cov", "pytest-socket", "requests-mock (>=1.5.0)"]
 
 [[package]]
@@ -1227,13 +1232,13 @@ numpy = ">=1.17.3"
 
 [[package]]
 name = "httpcore"
-version = "1.0.5"
+version = "1.0.7"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
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+    {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"},
+    {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"},
 ]
 
 [package.dependencies]
@@ -1244,17 +1249,17 @@ h11 = ">=0.13,<0.15"
 asyncio = ["anyio (>=4.0,<5.0)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
-trio = ["trio (>=0.22.0,<0.26.0)"]
+trio = ["trio (>=0.22.0,<1.0)"]
 
 [[package]]
 name = "httpx"
-version = "0.27.2"
+version = "0.28.1"
 description = "The next generation HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"},
-    {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"},
+    {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"},
+    {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"},
 ]
 
 [package.dependencies]
@@ -1262,7 +1267,6 @@ anyio = "*"
 certifi = "*"
 httpcore = "==1.*"
 idna = "*"
-sniffio = "*"
 
 [package.extras]
 brotli = ["brotli", "brotlicffi"]
@@ -1513,32 +1517,32 @@ typing-extensions = ">=3.7.4.1"
 
 [[package]]
 name = "jedi"
-version = "0.19.1"
+version = "0.19.2"
 description = "An autocompletion tool for Python that can be used for text editors."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0"},
-    {file = "jedi-0.19.1.tar.gz", hash = "sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd"},
+    {file = "jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9"},
+    {file = "jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0"},
 ]
 
 [package.dependencies]
-parso = ">=0.8.3,<0.9.0"
+parso = ">=0.8.4,<0.9.0"
 
 [package.extras]
 docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
 qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
-testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
+testing = ["Django", "attrs", "colorama", "docopt", "pytest (<9.0.0)"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.4"
+version = "3.1.5"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
-    {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
+    {file = "jinja2-3.1.5-py3-none-any.whl", hash = "sha256:aba0f4dc9ed8013c424088f68a5c226f7d6097ed89b246d7749c2ec4175c6adb"},
+    {file = "jinja2-3.1.5.tar.gz", hash = "sha256:8fefff8dc3034e27bb80d67c671eb8a9bc424c0ef4c0826edbff304cceff43bb"},
 ]
 
 [package.dependencies]
@@ -1549,15 +1553,18 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "json5"
-version = "0.9.25"
+version = "0.10.0"
 description = "A Python implementation of the JSON5 data format."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.8.0"
 files = [
-    {file = "json5-0.9.25-py3-none-any.whl", hash = "sha256:34ed7d834b1341a86987ed52f3f76cd8ee184394906b6e22a1e0deb9ab294e8f"},
-    {file = "json5-0.9.25.tar.gz", hash = "sha256:548e41b9be043f9426776f05df8635a00fe06104ea51ed24b67f908856e151ae"},
+    {file = "json5-0.10.0-py3-none-any.whl", hash = "sha256:19b23410220a7271e8377f81ba8aacba2fdd56947fbb137ee5977cbe1f5e8dfa"},
+    {file = "json5-0.10.0.tar.gz", hash = "sha256:e66941c8f0a02026943c52c2eb34ebeb2a6f819a0be05920a6f5243cd30fd559"},
 ]
 
+[package.extras]
+dev = ["build (==1.2.2.post1)", "coverage (==7.5.3)", "mypy (==1.13.0)", "pip (==24.3.1)", "pylint (==3.2.3)", "ruff (==0.7.3)", "twine (==5.1.1)", "uv (==0.5.1)"]
+
 [[package]]
 name = "jsonpointer"
 version = "3.0.0"
@@ -1798,13 +1805,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.2.5"
+version = "4.3.4"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab-4.2.5-py3-none-any.whl", hash = "sha256:73b6e0775d41a9fee7ee756c80f58a6bed4040869ccc21411dc559818874d321"},
-    {file = "jupyterlab-4.2.5.tar.gz", hash = "sha256:ae7f3a1b8cb88b4f55009ce79fa7c06f99d70cd63601ee4aa91815d054f46f75"},
+    {file = "jupyterlab-4.3.4-py3-none-any.whl", hash = "sha256:b754c2601c5be6adf87cb5a1d8495d653ffb945f021939f77776acaa94dae952"},
+    {file = "jupyterlab-4.3.4.tar.gz", hash = "sha256:f0bb9b09a04766e3423cccc2fc23169aa2ffedcdf8713e9e0fb33cac0b6859d0"},
 ]
 
 [package.dependencies]
@@ -1820,15 +1827,15 @@ jupyter-server = ">=2.4.0,<3"
 jupyterlab-server = ">=2.27.1,<3"
 notebook-shim = ">=0.2"
 packaging = "*"
-setuptools = ">=40.1.0"
+setuptools = ">=40.8.0"
 tomli = {version = ">=1.2.2", markers = "python_version < \"3.11\""}
 tornado = ">=6.2.0"
 traitlets = "*"
 
 [package.extras]
-dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.3.5)"]
-docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"]
-docs-screenshots = ["altair (==5.3.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.2)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.1.post2)", "matplotlib (==3.8.3)", "nbconvert (>=7.0.0)", "pandas (==2.2.1)", "scipy (==1.12.0)", "vega-datasets (==0.9.0)"]
+dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.6.9)"]
+docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<8.1.0)", "sphinx-copybutton"]
+docs-screenshots = ["altair (==5.4.1)", "ipython (==8.16.1)", "ipywidgets (==8.1.5)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.2.post3)", "matplotlib (==3.9.2)", "nbconvert (>=7.0.0)", "pandas (==2.2.3)", "scipy (==1.14.1)", "vega-datasets (==0.9.0)"]
 test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
 upgrade-extension = ["copier (>=9,<10)", "jinja2-time (<0.3)", "pydantic (<3.0)", "pyyaml-include (<3.0)", "tomli-w (<2.0)"]
 
@@ -2306,15 +2313,18 @@ files = [
 
 [[package]]
 name = "mistune"
-version = "3.0.2"
+version = "3.1.0"
 description = "A sane and fast Markdown parser with useful plugins and renderers"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "mistune-3.0.2-py3-none-any.whl", hash = "sha256:71481854c30fdbc938963d3605b72501f5c10a9320ecd412c121c163a1c7d205"},
-    {file = "mistune-3.0.2.tar.gz", hash = "sha256:fc7f93ded930c92394ef2cb6f04a8aabab4117a91449e72dcc8dfa646a508be8"},
+    {file = "mistune-3.1.0-py3-none-any.whl", hash = "sha256:b05198cf6d671b3deba6c87ec6cf0d4eb7b72c524636eddb6dbf13823b52cee1"},
+    {file = "mistune-3.1.0.tar.gz", hash = "sha256:dbcac2f78292b9dc066cd03b7a3a26b62d85f8159f2ea5fd28e55df79908d667"},
 ]
 
+[package.dependencies]
+typing-extensions = {version = "*", markers = "python_version < \"3.11\""}
+
 [[package]]
 name = "mpmath"
 version = "1.3.0"
@@ -2360,13 +2370,13 @@ testing-docutils = ["pygments", "pytest (>=7,<8)", "pytest-param-files (>=0.3.4,
 
 [[package]]
 name = "nbclient"
-version = "0.10.0"
+version = "0.10.1"
 description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "nbclient-0.10.0-py3-none-any.whl", hash = "sha256:f13e3529332a1f1f81d82a53210322476a168bb7090a0289c795fe9cc11c9d3f"},
-    {file = "nbclient-0.10.0.tar.gz", hash = "sha256:4b3f1b7dba531e498449c4db4f53da339c91d449dc11e9af3a43b4eb5c5abb09"},
+    {file = "nbclient-0.10.1-py3-none-any.whl", hash = "sha256:949019b9240d66897e442888cfb618f69ef23dc71c01cb5fced8499c2cfc084d"},
+    {file = "nbclient-0.10.1.tar.gz", hash = "sha256:3e93e348ab27e712acd46fccd809139e356eb9a31aab641d1a7991a6eb4e6f68"},
 ]
 
 [package.dependencies]
@@ -2377,23 +2387,23 @@ traitlets = ">=5.4"
 
 [package.extras]
 dev = ["pre-commit"]
-docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling"]
+docs = ["autodoc-traits", "flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "mock", "moto", "myst-parser", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling", "testpath", "xmltodict"]
 test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"]
 
 [[package]]
 name = "nbconvert"
-version = "7.16.4"
+version = "7.16.5"
 description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "nbconvert-7.16.4-py3-none-any.whl", hash = "sha256:05873c620fe520b6322bf8a5ad562692343fe3452abda5765c7a34b7d1aa3eb3"},
-    {file = "nbconvert-7.16.4.tar.gz", hash = "sha256:86ca91ba266b0a448dc96fa6c5b9d98affabde2867b363258703536807f9f7f4"},
+    {file = "nbconvert-7.16.5-py3-none-any.whl", hash = "sha256:e12eac052d6fd03040af4166c563d76e7aeead2e9aadf5356db552a1784bd547"},
+    {file = "nbconvert-7.16.5.tar.gz", hash = "sha256:c83467bb5777fdfaac5ebbb8e864f300b277f68692ecc04d6dab72f2d8442344"},
 ]
 
 [package.dependencies]
 beautifulsoup4 = "*"
-bleach = "!=5.0.0"
+bleach = {version = "!=5.0.0", extras = ["css"]}
 defusedxml = "*"
 importlib-metadata = {version = ">=3.6", markers = "python_version < \"3.10\""}
 jinja2 = ">=3.0"
@@ -2406,7 +2416,6 @@ nbformat = ">=5.7"
 packaging = "*"
 pandocfilters = ">=1.4.1"
 pygments = ">=2.4.1"
-tinycss2 = "*"
 traitlets = ">=5.1"
 
 [package.extras]
@@ -2481,18 +2490,18 @@ files = [
 
 [[package]]
 name = "notebook"
-version = "7.2.2"
+version = "7.3.2"
 description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "notebook-7.2.2-py3-none-any.whl", hash = "sha256:c89264081f671bc02eec0ed470a627ed791b9156cad9285226b31611d3e9fe1c"},
-    {file = "notebook-7.2.2.tar.gz", hash = "sha256:2ef07d4220421623ad3fe88118d687bc0450055570cdd160814a59cf3a1c516e"},
+    {file = "notebook-7.3.2-py3-none-any.whl", hash = "sha256:e5f85fc59b69d3618d73cf27544418193ff8e8058d5bf61d315ce4f473556288"},
+    {file = "notebook-7.3.2.tar.gz", hash = "sha256:705e83a1785f45b383bf3ee13cb76680b92d24f56fb0c7d2136fe1d850cd3ca8"},
 ]
 
 [package.dependencies]
 jupyter-server = ">=2.4.0,<3"
-jupyterlab = ">=4.2.0,<4.3"
+jupyterlab = ">=4.3.4,<4.4"
 jupyterlab-server = ">=2.27.1,<3"
 notebook-shim = ">=0.2,<0.3"
 tornado = ">=6.2.0"
@@ -2558,46 +2567,50 @@ files = [
 
 [[package]]
 name = "nvidia-cublas-cu12"
-version = "12.1.3.1"
+version = "12.4.5.8"
 description = "CUBLAS native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:ee53ccca76a6fc08fb9701aa95b6ceb242cdaab118c3bb152af4e579af792728"},
-    {file = "nvidia_cublas_cu12-12.1.3.1-py3-none-win_amd64.whl", hash = "sha256:2b964d60e8cf11b5e1073d179d85fa340c120e99b3067558f3cf98dd69d02906"},
+    {file = "nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0f8aa1706812e00b9f19dfe0cdb3999b092ccb8ca168c0db5b8ea712456fd9b3"},
+    {file = "nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl", hash = "sha256:2fc8da60df463fdefa81e323eef2e36489e1c94335b5358bcb38360adf75ac9b"},
+    {file = "nvidia_cublas_cu12-12.4.5.8-py3-none-win_amd64.whl", hash = "sha256:5a796786da89203a0657eda402bcdcec6180254a8ac22d72213abc42069522dc"},
 ]
 
 [[package]]
 name = "nvidia-cuda-cupti-cu12"
-version = "12.1.105"
+version = "12.4.127"
 description = "CUDA profiling tools runtime libs."
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:e54fde3983165c624cb79254ae9818a456eb6e87a7fd4d56a2352c24ee542d7e"},
-    {file = "nvidia_cuda_cupti_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:bea8236d13a0ac7190bd2919c3e8e6ce1e402104276e6f9694479e48bb0eb2a4"},
+    {file = "nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:79279b35cf6f91da114182a5ce1864997fd52294a87a16179ce275773799458a"},
+    {file = "nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:9dec60f5ac126f7bb551c055072b69d85392b13311fcc1bcda2202d172df30fb"},
+    {file = "nvidia_cuda_cupti_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:5688d203301ab051449a2b1cb6690fbe90d2b372f411521c86018b950f3d7922"},
 ]
 
 [[package]]
 name = "nvidia-cuda-nvrtc-cu12"
-version = "12.1.105"
+version = "12.4.127"
 description = "NVRTC native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:339b385f50c309763ca65456ec75e17bbefcbbf2893f462cb8b90584cd27a1c2"},
-    {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:0a98a522d9ff138b96c010a65e145dc1b4850e9ecb75a0172371793752fd46ed"},
+    {file = "nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0eedf14185e04b76aa05b1fea04133e59f465b6f960c0cbf4e37c3cb6b0ea198"},
+    {file = "nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:a178759ebb095827bd30ef56598ec182b85547f1508941a3d560eb7ea1fbf338"},
+    {file = "nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:a961b2f1d5f17b14867c619ceb99ef6fcec12e46612711bcec78eb05068a60ec"},
 ]
 
 [[package]]
 name = "nvidia-cuda-runtime-cu12"
-version = "12.1.105"
+version = "12.4.127"
 description = "CUDA Runtime native Libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:6e258468ddf5796e25f1dc591a31029fa317d97a0a94ed93468fc86301d61e40"},
-    {file = "nvidia_cuda_runtime_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:dfb46ef84d73fababab44cf03e3b83f80700d27ca300e537f85f636fac474344"},
+    {file = "nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:961fe0e2e716a2a1d967aab7caee97512f71767f852f67432d572e36cb3a11f3"},
+    {file = "nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:64403288fa2136ee8e467cdc9c9427e0434110899d07c779f25b5c068934faa5"},
+    {file = "nvidia_cuda_runtime_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:09c2e35f48359752dfa822c09918211844a3d93c100a715d79b59591130c5e1e"},
 ]
 
 [[package]]
@@ -2616,35 +2629,41 @@ nvidia-cublas-cu12 = "*"
 
 [[package]]
 name = "nvidia-cufft-cu12"
-version = "11.0.2.54"
+version = "11.2.1.3"
 description = "CUFFT native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl", hash = "sha256:794e3948a1aa71fd817c3775866943936774d1c14e7628c74f6f7417224cdf56"},
-    {file = "nvidia_cufft_cu12-11.0.2.54-py3-none-win_amd64.whl", hash = "sha256:d9ac353f78ff89951da4af698f80870b1534ed69993f10a4cf1d96f21357e253"},
+    {file = "nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_aarch64.whl", hash = "sha256:5dad8008fc7f92f5ddfa2101430917ce2ffacd86824914c82e28990ad7f00399"},
+    {file = "nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl", hash = "sha256:f083fc24912aa410be21fa16d157fed2055dab1cc4b6934a0e03cba69eb242b9"},
+    {file = "nvidia_cufft_cu12-11.2.1.3-py3-none-win_amd64.whl", hash = "sha256:d802f4954291101186078ccbe22fc285a902136f974d369540fd4a5333d1440b"},
 ]
 
+[package.dependencies]
+nvidia-nvjitlink-cu12 = "*"
+
 [[package]]
 name = "nvidia-curand-cu12"
-version = "10.3.2.106"
+version = "10.3.5.147"
 description = "CURAND native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:9d264c5036dde4e64f1de8c50ae753237c12e0b1348738169cd0f8a536c0e1e0"},
-    {file = "nvidia_curand_cu12-10.3.2.106-py3-none-win_amd64.whl", hash = "sha256:75b6b0c574c0037839121317e17fd01f8a69fd2ef8e25853d826fec30bdba74a"},
+    {file = "nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1f173f09e3e3c76ab084aba0de819c49e56614feae5c12f69883f4ae9bb5fad9"},
+    {file = "nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl", hash = "sha256:a88f583d4e0bb643c49743469964103aa59f7f708d862c3ddb0fc07f851e3b8b"},
+    {file = "nvidia_curand_cu12-10.3.5.147-py3-none-win_amd64.whl", hash = "sha256:f307cc191f96efe9e8f05a87096abc20d08845a841889ef78cb06924437f6771"},
 ]
 
 [[package]]
 name = "nvidia-cusolver-cu12"
-version = "11.4.5.107"
+version = "11.6.1.9"
 description = "CUDA solver native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd"},
-    {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-win_amd64.whl", hash = "sha256:74e0c3a24c78612192a74fcd90dd117f1cf21dea4822e66d89e8ea80e3cd2da5"},
+    {file = "nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_aarch64.whl", hash = "sha256:d338f155f174f90724bbde3758b7ac375a70ce8e706d70b018dd3375545fc84e"},
+    {file = "nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl", hash = "sha256:19e33fa442bcfd085b3086c4ebf7e8debc07cfe01e11513cc6d332fd918ac260"},
+    {file = "nvidia_cusolver_cu12-11.6.1.9-py3-none-win_amd64.whl", hash = "sha256:e77314c9d7b694fcebc84f58989f3aa4fb4cb442f12ca1a9bde50f5e8f6d1b9c"},
 ]
 
 [package.dependencies]
@@ -2654,13 +2673,14 @@ nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
 name = "nvidia-cusparse-cu12"
-version = "12.1.0.106"
+version = "12.3.1.170"
 description = "CUSPARSE native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c"},
-    {file = "nvidia_cusparse_cu12-12.1.0.106-py3-none-win_amd64.whl", hash = "sha256:b798237e81b9719373e8fae8d4f091b70a0cf09d9d85c95a557e11df2d8e9a5a"},
+    {file = "nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_aarch64.whl", hash = "sha256:9d32f62896231ebe0480efd8a7f702e143c98cfaa0e8a76df3386c1ba2b54df3"},
+    {file = "nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl", hash = "sha256:ea4f11a2904e2a8dc4b1833cc1b5181cde564edd0d5cd33e3c168eff2d1863f1"},
+    {file = "nvidia_cusparse_cu12-12.3.1.170-py3-none-win_amd64.whl", hash = "sha256:9bc90fb087bc7b4c15641521f31c0371e9a612fc2ba12c338d3ae032e6b6797f"},
 ]
 
 [package.dependencies]
@@ -2668,36 +2688,36 @@ nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
 name = "nvidia-nccl-cu12"
-version = "2.20.5"
+version = "2.21.5"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1fc150d5c3250b170b29410ba682384b14581db722b2531b0d8d33c595f33d01"},
-    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:057f6bf9685f75215d0c53bf3ac4a10b3e6578351de307abad9e18a99182af56"},
+    {file = "nvidia_nccl_cu12-2.21.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:8579076d30a8c24988834445f8d633c697d42397e92ffc3f63fa26766d25e0a0"},
 ]
 
 [[package]]
 name = "nvidia-nvjitlink-cu12"
-version = "12.6.68"
+version = "12.4.127"
 description = "Nvidia JIT LTO Library"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nvjitlink_cu12-12.6.68-py3-none-manylinux2014_aarch64.whl", hash = "sha256:b3fd0779845f68b92063ab1393abab1ed0a23412fc520df79a8190d098b5cd6b"},
-    {file = "nvidia_nvjitlink_cu12-12.6.68-py3-none-manylinux2014_x86_64.whl", hash = "sha256:125a6c2a44e96386dda634e13d944e60b07a0402d391a070e8fb4104b34ea1ab"},
-    {file = "nvidia_nvjitlink_cu12-12.6.68-py3-none-win_amd64.whl", hash = "sha256:a55744c98d70317c5e23db14866a8cc2b733f7324509e941fc96276f9f37801d"},
+    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:4abe7fef64914ccfa909bc2ba39739670ecc9e820c83ccc7a6ed414122599b83"},
+    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:06b3b9b25bf3f8af351d664978ca26a16d2c5127dbd53c0497e28d1fb9611d57"},
+    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:fd9020c501d27d135f983c6d3e244b197a7ccad769e34df53a42e276b0e25fa1"},
 ]
 
 [[package]]
 name = "nvidia-nvtx-cu12"
-version = "12.1.105"
+version = "12.4.127"
 description = "NVIDIA Tools Extension"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:dc21cf308ca5691e7c04d962e213f8a4aa9bbfa23d95412f452254c2caeb09e5"},
-    {file = "nvidia_nvtx_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:65f4d98982b31b60026e0e6de73fbdfc09d08a96f4656dd3665ca616a11e1e82"},
+    {file = "nvidia_nvtx_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7959ad635db13edf4fc65c06a6e9f9e55fc2f92596db928d169c0bb031e88ef3"},
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 ]
 
 [[package]]
@@ -2713,13 +2733,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "24.1"
+version = "24.2"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -2759,8 +2779,8 @@ files = [
 [package.dependencies]
 numpy = [
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-    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
     {version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
+    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -2999,13 +3019,13 @@ virtualenv = ">=20.10.0"
 
 [[package]]
 name = "prometheus-client"
-version = "0.21.0"
+version = "0.21.1"
 description = "Python client for the Prometheus monitoring system."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "prometheus_client-0.21.1-py3-none-any.whl", hash = "sha256:594b45c410d6f4f8888940fe80b5cc2521b305a1fafe1c58609ef715a001f301"},
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 ]
 
 [package.extras]
@@ -3027,32 +3047,33 @@ wcwidth = "*"
 
 [[package]]
 name = "psutil"
-version = "6.0.0"
+version = "6.1.1"
 description = "Cross-platform lib for process and system monitoring in Python."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
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+    {file = "psutil-6.1.1.tar.gz", hash = "sha256:cf8496728c18f2d0b45198f06895be52f36611711746b7f30c464b422b50e2f5"},
 ]
 
 [package.extras]
-test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
+dev = ["abi3audit", "black", "check-manifest", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pytest-cov", "requests", "rstcheck", "ruff", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "virtualenv", "vulture", "wheel"]
+test = ["pytest", "pytest-xdist", "setuptools"]
 
 [[package]]
 name = "ptyprocess"
@@ -3148,13 +3169,13 @@ test = ["pytest", "pytest-doctestplus (>=0.7)"]
 
 [[package]]
 name = "pygments"
-version = "2.18.0"
+version = "2.19.1"
 description = "Pygments is a syntax highlighting package written in Python."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pygments-2.18.0-py3-none-any.whl", hash = "sha256:b8e6aca0523f3ab76fee51799c488e38782ac06eafcf95e7ba832985c8e7b13a"},
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 ]
 
 [package.extras]
@@ -3179,20 +3200,20 @@ tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"]
 
 [[package]]
 name = "pyopenssl"
-version = "24.2.1"
+version = "24.3.0"
 description = "Python wrapper module around the OpenSSL library"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
-cryptography = ">=41.0.5,<44"
+cryptography = ">=41.0.5,<45"
 
 [package.extras]
-docs = ["sphinx (!=5.2.0,!=5.2.0.post0,!=7.2.5)", "sphinx-rtd-theme"]
+docs = ["sphinx (!=5.2.0,!=5.2.0.post0,!=7.2.5)", "sphinx_rtd_theme"]
 test = ["pretend", "pytest (>=3.0.1)", "pytest-rerunfailures"]
 
 [[package]]
@@ -3247,15 +3268,21 @@ six = ">=1.5"
 
 [[package]]
 name = "python-json-logger"
-version = "2.0.7"
-description = "A python library adding a json log formatter"
+version = "3.2.1"
+description = "JSON Log Formatter for the Python Logging Package"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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+    {file = "python_json_logger-3.2.1.tar.gz", hash = "sha256:8eb0554ea17cb75b05d2848bc14fb02fbdbd9d6972120781b974380bfa162008"},
 ]
 
+[package.dependencies]
+typing_extensions = {version = "*", markers = "python_version < \"3.10\""}
+
+[package.extras]
+dev = ["backports.zoneinfo", "black", "build", "freezegun", "mdx_truly_sane_lists", "mike", "mkdocs", "mkdocs-awesome-pages-plugin", "mkdocs-gen-files", "mkdocs-literate-nav", "mkdocs-material (>=8.5)", "mkdocstrings[python]", "msgspec", "msgspec-python313-pre", "mypy", "orjson", "pylint", "pytest", "tzdata", "validate-pyproject[all]"]
+
 [[package]]
 name = "pytz"
 version = "2024.2"
@@ -3269,40 +3296,44 @@ files = [
 
 [[package]]
 name = "pywin32"
-version = "306"
+version = "308"
 description = "Python for Window Extensions"
 optional = false
 python-versions = "*"
 files = [
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+version = "75.7.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
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 [[package]]
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+version = "1.12.1"
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 [package.dependencies]
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 [[package]]
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 [package.dependencies]
@@ -4061,46 +4106,73 @@ webencodings = ">=0.4"
 
 [package.extras]
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-test = ["pytest", "ruff"]
+test = ["flake8", "isort", "pytest"]
 
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 ]
 
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 optional = false
 python-versions = ">=3.8.0"
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 ]
 
 [package.dependencies]
@@ -4108,94 +4180,95 @@ filelock = "*"
 fsspec = "*"
 jinja2 = "*"
 networkx = "*"
-nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cublas-cu12 = {version = "12.4.5.8", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-cupti-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-nvrtc-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-runtime-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cudnn-cu12 = {version = "9.1.0.70", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-setuptools = "*"
-sympy = "*"
-triton = {version = "3.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
+nvidia-cufft-cu12 = {version = "11.2.1.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-curand-cu12 = {version = "10.3.5.147", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusolver-cu12 = {version = "11.6.1.9", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusparse-cu12 = {version = "12.3.1.170", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nccl-cu12 = {version = "2.21.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nvjitlink-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nvtx-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+setuptools = {version = "*", markers = "python_version >= \"3.12\""}
+sympy = [
+    {version = "1.12.1", markers = "python_version == \"3.8\""},
+    {version = "1.13.1", markers = "python_version >= \"3.9\""},
+]
+triton = {version = "3.1.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
 typing-extensions = ">=4.8.0"
 
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
-optree = ["optree (>=0.11.0)"]
+optree = ["optree (>=0.12.0)"]
 
 [[package]]
 name = "torchaudio"
-version = "2.4.1"
+version = "2.5.1"
 description = "An audio package for PyTorch"
 optional = false
 python-versions = "*"
 files = [
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+    {file = "torchaudio-2.5.1-cp310-cp310-win_amd64.whl", hash = "sha256:4aead2d6b32426d0e657e243f6f5146f8d400bc8db9fe8a8000254baeec1202d"},
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+    {file = "torchaudio-2.5.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f1cbfdfd1bbdfbe7289d47a74f36ff6c5d87c3205606202fef5a7fb693f61cf0"},
+    {file = "torchaudio-2.5.1-cp312-cp312-manylinux1_x86_64.whl", hash = "sha256:9c8fb06fbd8d2016e7b7caf15a3231867c792a2e3b0f2f8f9013633e9c2ce412"},
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+    {file = "torchaudio-2.5.1-cp312-cp312-win_amd64.whl", hash = "sha256:ec8f12d6be12aed248a0d65a76c7bb341ee5eef969fe2e9dc3154c7cfba1bdf4"},
+    {file = "torchaudio-2.5.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a40a0e4b238564a19bf138c64d593c7b52d97c8737843d85d6ca09216241ae66"},
+    {file = "torchaudio-2.5.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:f2f0a4fa19137cad247087dcf4b85c56860f924c3ca4a89679299cf0e002ee33"},
+    {file = "torchaudio-2.5.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:d29349944955eb061e774fe4d9eea4681c5bc9ff42ea39a877f8f14de1e4ed00"},
+    {file = "torchaudio-2.5.1-cp39-cp39-win_amd64.whl", hash = "sha256:0be6d6f5127b17f9f1ac33fb02c8f1127bfea955de630c5cab6eb9daaef4db6d"},
 ]
 
 [package.dependencies]
-torch = "2.4.1"
+torch = "2.5.1"
 
 [[package]]
 name = "tornado"
-version = "6.4.1"
+version = "6.4.2"
 description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8"},
-    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14"},
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-    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3"},
-    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f"},
-    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4"},
-    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698"},
-    {file = "tornado-6.4.1-cp38-abi3-win32.whl", hash = "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d"},
-    {file = "tornado-6.4.1-cp38-abi3-win_amd64.whl", hash = "sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7"},
-    {file = "tornado-6.4.1.tar.gz", hash = "sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9"},
+    {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e828cce1123e9e44ae2a50a9de3055497ab1d0aeb440c5ac23064d9e44880da1"},
+    {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:072ce12ada169c5b00b7d92a99ba089447ccc993ea2143c9ede887e0937aa803"},
+    {file = "tornado-6.4.2-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a017d239bd1bb0919f72af256a970624241f070496635784d9bf0db640d3fec"},
+    {file = "tornado-6.4.2-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c36e62ce8f63409301537222faffcef7dfc5284f27eec227389f2ad11b09d946"},
+    {file = "tornado-6.4.2-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca9eb02196e789c9cb5c3c7c0f04fb447dc2adffd95265b2c7223a8a615ccbf"},
+    {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:304463bd0772442ff4d0f5149c6f1c2135a1fae045adf070821c6cdc76980634"},
+    {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:c82c46813ba483a385ab2a99caeaedf92585a1f90defb5693351fa7e4ea0bf73"},
+    {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:932d195ca9015956fa502c6b56af9eb06106140d844a335590c1ec7f5277d10c"},
+    {file = "tornado-6.4.2-cp38-abi3-win32.whl", hash = "sha256:2876cef82e6c5978fde1e0d5b1f919d756968d5b4282418f3146b79b58556482"},
+    {file = "tornado-6.4.2-cp38-abi3-win_amd64.whl", hash = "sha256:908b71bf3ff37d81073356a5fadcc660eb10c1476ee6e2725588626ce7e5ca38"},
+    {file = "tornado-6.4.2.tar.gz", hash = "sha256:92bad5b4746e9879fd7bf1eb21dce4e3fc5128d71601f80005afa39237ad620b"},
 ]
 
 [[package]]
 name = "tqdm"
-version = "4.66.5"
+version = "4.67.1"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
-    {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
+    {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"},
+    {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [package.extras]
-dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"]
+discord = ["requests"]
 notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
@@ -4217,16 +4290,16 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "triton"
-version = "3.0.0"
+version = "3.1.0"
 description = "A language and compiler for custom Deep Learning operations"
 optional = false
 python-versions = "*"
 files = [
-    {file = "triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1efef76935b2febc365bfadf74bcb65a6f959a9872e5bddf44cc9e0adce1e1a"},
-    {file = "triton-3.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5ce8520437c602fb633f1324cc3871c47bee3b67acf9756c1a66309b60e3216c"},
-    {file = "triton-3.0.0-1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:34e509deb77f1c067d8640725ef00c5cbfcb2052a1a3cb6a6d343841f92624eb"},
-    {file = "triton-3.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:bcbf3b1c48af6a28011a5c40a5b3b9b5330530c3827716b5fbf6d7adcc1e53e9"},
-    {file = "triton-3.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:6e5727202f7078c56f91ff13ad0c1abab14a0e7f2c87e91b12b6f64f3e8ae609"},
+    {file = "triton-3.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b0dd10a925263abbe9fa37dcde67a5e9b2383fc269fdf59f5657cac38c5d1d8"},
+    {file = "triton-3.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0f34f6e7885d1bf0eaaf7ba875a5f0ce6f3c13ba98f9503651c1e6dc6757ed5c"},
+    {file = "triton-3.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c8182f42fd8080a7d39d666814fa36c5e30cc00ea7eeeb1a2983dbb4c99a0fdc"},
+    {file = "triton-3.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6dadaca7fc24de34e180271b5cf864c16755702e9f63a16f62df714a8099126a"},
+    {file = "triton-3.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aafa9a20cd0d9fee523cd4504aa7131807a864cd77dcf6efe7e981f18b8c6c11"},
 ]
 
 [package.dependencies]
@@ -4239,13 +4312,13 @@ tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "typeguard"
-version = "4.3.0"
+version = "4.4.0"
 description = "Run-time type checker for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "typeguard-4.3.0-py3-none-any.whl", hash = "sha256:4d24c5b39a117f8a895b9da7a9b3114f04eb63bade45a4492de49b175b6f7dfa"},
-    {file = "typeguard-4.3.0.tar.gz", hash = "sha256:92ee6a0aec9135181eae6067ebd617fd9de8d75d714fb548728a4933b1dea651"},
+    {file = "typeguard-4.4.0-py3-none-any.whl", hash = "sha256:8ca34c14043f53b2caae7040549ba431770869bcd6287cfa8239db7ecb882b4a"},
+    {file = "typeguard-4.4.0.tar.gz", hash = "sha256:463bd8697a65a4aa576a63767c369b1ecfba8a5ba735edfe3223127b6ecfa28c"},
 ]
 
 [package.dependencies]
@@ -4258,13 +4331,13 @@ test = ["coverage[toml] (>=7)", "mypy (>=1.2.0)", "pytest (>=7)"]
 
 [[package]]
 name = "types-python-dateutil"
-version = "2.9.0.20240906"
+version = "2.9.0.20241206"
 description = "Typing stubs for python-dateutil"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-python-dateutil-2.9.0.20240906.tar.gz", hash = "sha256:9706c3b68284c25adffc47319ecc7947e5bb86b3773f843c73906fd598bc176e"},
-    {file = "types_python_dateutil-2.9.0.20240906-py3-none-any.whl", hash = "sha256:27c8cc2d058ccb14946eebcaaa503088f4f6dbc4fb6093d3d456a49aef2753f6"},
+    {file = "types_python_dateutil-2.9.0.20241206-py3-none-any.whl", hash = "sha256:e248a4bc70a486d3e3ec84d0dc30eec3a5f979d6e7ee4123ae043eedbb987f53"},
+    {file = "types_python_dateutil-2.9.0.20241206.tar.gz", hash = "sha256:18f493414c26ffba692a72369fea7a154c502646301ebfe3d56a04b3767284cb"},
 ]
 
 [[package]]
@@ -4322,13 +4395,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.26.6"
+version = "20.28.1"
 description = "Virtual Python Environment builder"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "virtualenv-20.26.6-py3-none-any.whl", hash = "sha256:7345cc5b25405607a624d8418154577459c3e0277f5466dd79c49d5e492995f2"},
-    {file = "virtualenv-20.26.6.tar.gz", hash = "sha256:280aede09a2a5c317e409a00102e7077c6432c5a38f0ef938e643805a7ad2c48"},
+    {file = "virtualenv-20.28.1-py3-none-any.whl", hash = "sha256:412773c85d4dab0409b83ec36f7a6499e72eaf08c80e81e9576bca61831c71cb"},
+    {file = "virtualenv-20.28.1.tar.gz", hash = "sha256:5d34ab240fdb5d21549b76f9e8ff3af28252f5499fb6d6f031adac4e5a8c5329"},
 ]
 
 [package.dependencies]
@@ -4426,4 +4499,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.8,<3.13"
-content-hash = "e79a66e4ce6dfe78a9f998c8d95be3ddc6338a40b02de275047123955cbac721"
+content-hash = "8a0cdbf2548734631da9fa8949f6fd55318868aa31dbe1d1f6168bc12de2d130"
diff --git a/pyproject.toml b/pyproject.toml
index 566371b4..15c216bc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "ml4gw"
-version = "0.6.1"
+version = "0.6.2"
 description = "Tools for training torch models on gravitational wave data"
 readme = "README.md"
 authors = [
@@ -29,7 +29,7 @@ gwpy = "^2.1"
 
 # versions >= 1.9. fix issue with median calculation 
 # https://github.com/scipy/scipy/issues/15601
-scipy = ">=1.9.0"
+scipy = ">=1.9.0,<1.15"
 
 Sphinx = ">5.0"
 sphinx-rtd-theme = "^2.0.0"
@@ -77,6 +77,7 @@ deps =
     bilby>=1.1,<2
     gwpy>=3.0
     numpy>=1,<2
+    scipy>=1.9,<1.15
 commands = pytest tests
 """
 
diff --git a/tests/transforms/test_spline_interpolation.py b/tests/transforms/test_spline_interpolation.py
index 5b997664..ee7663ae 100644
--- a/tests/transforms/test_spline_interpolation.py
+++ b/tests/transforms/test_spline_interpolation.py
@@ -42,7 +42,7 @@ def test_1d_interpolation(self, x_out_len):
         # interpolations is about 0.9990, with some minor fluctuations.
         # Would be nice to know why the torch interpolation is
         # consistently smaller
-        assert np.allclose(actual, expected, rtol=5e-3)
+        assert np.allclose(actual, expected, rtol=1e-2)
 
     def test_2d_interpolation(self, x_out_len, y_out_len):
         x_in = np.linspace(0, 10, 100)
diff --git a/tests/waveforms/cbc/test_cbc_waveforms.py b/tests/waveforms/cbc/test_cbc_waveforms.py
index b2542e96..0b0c68d6 100644
--- a/tests/waveforms/cbc/test_cbc_waveforms.py
+++ b/tests/waveforms/cbc/test_cbc_waveforms.py
@@ -7,7 +7,10 @@
 from torch.distributions import Uniform
 
 import ml4gw.waveforms as waveforms
-from ml4gw.waveforms.conversion import chirp_mass_and_mass_ratio_to_components
+from ml4gw.waveforms.conversion import (
+    bilby_spins_to_lalsim,
+    chirp_mass_and_mass_ratio_to_components,
+)
 
 
 @pytest.fixture(params=[256, 1024, 2048])
@@ -299,7 +302,6 @@ def test_phenom_d(
         )
 
         hc_ml4gw = hc_ml4gw[0]
-
         hp_ml4gw = hp_ml4gw[0]
 
         hp_lal_data = hp_lal.data.data[lal_mask]
@@ -322,41 +324,64 @@ def test_phenom_d(
         )
 
 
-def test_phenom_p():
-    chirp_mass = torch.tensor([15.0, 30.0])
-    mass_ratio = torch.tensor([0.99, 0.5])
-    chi1z = torch.tensor([0.0, 0.5])
-    chi2z = torch.tensor([-0.1, 0.1])
-    distance = torch.tensor([100.0, 1000.0])
-    sample_rate = 2048
-
-    mass_2 = chirp_mass * (1 + mass_ratio) ** 0.2 / mass_ratio**0.6
-    mass_1 = mass_2 * mass_ratio
+def test_phenom_p(
+    chirp_mass,
+    mass_ratio,
+    distance,
+    phase,
+    sample_rate,
+    f_ref,
+    theta_jn,
+    phi_jl,
+    tilt_1,
+    tilt_2,
+    phi_12,
+    a_1,
+    a_2,
+):
+    mass_1, mass_2 = chirp_mass_and_mass_ratio_to_components(
+        chirp_mass, mass_ratio
+    )
+    (
+        inclination,
+        chi1x,
+        chi1y,
+        chi1z,
+        chi2x,
+        chi2y,
+        chi2z,
+    ) = bilby_spins_to_lalsim(
+        theta_jn,
+        phi_jl,
+        tilt_1,
+        tilt_2,
+        phi_12,
+        a_1,
+        a_2,
+        mass_1,
+        mass_2,
+        f_ref,
+        phase,
+    )
 
-    f_ref = 20.0
-    phic = 0.0
     tc = 0.0
-    inclination = 0.0
 
-    for i in range(chirp_mass.shape[0]):
-        m1, m2 = mass_1[i], mass_2[i]
-        mr = mass_ratio[i]
-        if m2 > m1:
-            m1, m2 = m2, m1
-            mr = 1 / mr
+    # compare each waveform with lalsimulation
+    for i in range(len(chirp_mass)):
 
+        # construct lalinference params
         params = dict(
-            m1=m1.item() * lal.MSUN_SI,
-            m2=m2.item() * lal.MSUN_SI,
-            S1x=0,
-            S1y=0,
+            m1=mass_1[i].item() * lal.MSUN_SI,
+            m2=mass_2[i].item() * lal.MSUN_SI,
+            S1x=chi1x[i].item(),
+            S1y=chi1y[i].item(),
             S1z=chi1z[i].item(),
-            S2x=0,
-            S2y=0,
+            S2x=chi2x[i].item(),
+            S2y=chi2y[i].item(),
             S2z=chi2z[i].item(),
             distance=(distance[i].item() * u.Mpc).to("m").value,
-            inclination=inclination,
-            phiRef=phic,
+            inclination=inclination[i].item(),
+            phiRef=phase[i].item(),
             longAscNodes=0.0,
             eccentricity=0.0,
             meanPerAno=0.0,
@@ -388,16 +413,16 @@ def test_phenom_p():
         hc_ml4gw, hp_ml4gw = waveforms.IMRPhenomPv2()(
             torch_freqs,
             chirp_mass[i][None],
-            torch.tensor([mr]),
-            torch.tensor([0.0]),
-            torch.tensor([0.0]),
+            mass_ratio[i][None],
+            chi1x[i][None],
+            chi1y[i][None],
             chi1z[i][None],
-            torch.tensor([0.0]),
-            torch.tensor([0.0]),
+            chi2x[i][None],
+            chi2y[i][None],
             chi2z[i][None],
             distance[i][None],
-            torch.tensor([phic]),
-            torch.tensor([inclination]),
+            phase[i][None],
+            inclination[i][None],
             f_ref,
             torch.tensor([tc]),
         )
@@ -409,14 +434,14 @@ def test_phenom_p():
         hc_lal_data = hc_lal.data.data[lal_mask]
 
         assert np.allclose(
-            1e21 * hp_lal_data.real, 1e21 * hp_ml4gw.real.numpy(), atol=2e-3
+            1e21 * hp_lal_data.real, 1e21 * hp_ml4gw.real.numpy(), atol=1e-2
         )
         assert np.allclose(
-            1e21 * hp_lal_data.imag, 1e21 * hp_ml4gw.imag.numpy(), atol=2e-3
+            1e21 * hp_lal_data.imag, 1e21 * hp_ml4gw.imag.numpy(), atol=1e-2
         )
         assert np.allclose(
-            1e21 * hc_lal_data.real, 1e21 * hc_ml4gw.real.numpy(), atol=2e-3
+            1e21 * hc_lal_data.real, 1e21 * hc_ml4gw.real.numpy(), atol=1e-2
         )
         assert np.allclose(
-            1e21 * hc_lal_data.imag, 1e21 * hc_ml4gw.imag.numpy(), atol=2e-3
+            1e21 * hc_lal_data.imag, 1e21 * hc_ml4gw.imag.numpy(), atol=1e-2
         )