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Draft: Port HMM to pomegranate 1.0 #20

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Draft: Port HMM to pomegranate 1.0 #20

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740d2ab
First tests
AKuederle Apr 18, 2023
cc5e216
Potentially fixed huge bug with model initialization, which was not c…
AKuederle Nov 9, 2023
e56d2b3
Returned parameter to original state
AKuederle Nov 9, 2023
7663d1a
Changed how priors are treated
AKuederle Nov 9, 2023
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2 changes: 1 addition & 1 deletion examples/stride_segmentation/roth_hmm_stride_segmentation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -133,7 +133,7 @@
ax2.plot(hidden_state_sequence_feature_space, color="tab:green")
ax2.tick_params(axis="y", labelcolor="tab:green")

plt.xlim([0, 500])
# plt.xlim([0, 500])
fig.tight_layout()
plt.show()

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13 changes: 3 additions & 10 deletions examples/stride_segmentation/segmentation_hmm_training.py
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Expand Up @@ -88,23 +88,19 @@
stride_model = SimpleHmm(
n_states=20,
n_gmm_components=6,
algo_train="baum-welch",
stop_threshold=1e-9,
max_iterations=5,
architecture="left-right-strict",
verbose=True,
name="stride_model",
)

transition_model = SimpleHmm(
n_states=5,
n_gmm_components=3,
algo_train="baum-welch",
stop_threshold=1e-9,
max_iterations=5,
architecture="left-right-loose",
verbose=True,
name="transition_model",
)

# %%
Expand All @@ -121,13 +117,10 @@
stride_model=stride_model,
transition_model=transition_model,
feature_transform=feature_transform,
algo_predict="viterbi",
algo_train="baum-welch",
stop_threshold=1e-9,
max_iterations=1,
initialization="labels",
verbose=True,
name="segmentation_model",
)

# %%
Expand Down Expand Up @@ -170,9 +163,9 @@

np.set_printoptions(precision=3, linewidth=180, suppress=True)

print(segmentation_model.model.dense_transition_matrix()[0:-2, 0:-2])
print(np.e**segmentation_model.model.edges)

print(segmentation_model.model.states[10])
print(segmentation_model.model.distributions[segmentation_model.n_states - 1])

# %%
# Applying the Model to a Sequence
Expand Down Expand Up @@ -208,6 +201,6 @@
axs[1].set_ylabel("Hidden State [N]")

axs[1].set_xlabel("Samples @ %d Hz" % sampling_rate_hz)
plt.xlim([6000, 7200])
# plt.xlim([6000, 7200])
fig.tight_layout()
plt.show()
16 changes: 7 additions & 9 deletions gaitmap_mad/gaitmap_mad/stride_segmentation/hmm/_hmm_stride_segmentation.py
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@@ -1,7 +1,5 @@
"""HMM based stride segmentation by Roth et al. 2021."""
from contextlib import suppress
from importlib.resources import open_text
from pathlib import Path
from typing import Dict, Generic, Optional, TypeVar, Union

import numpy as np
Expand Down Expand Up @@ -39,13 +37,13 @@ class PreTrainedRothSegmentationModel(RothSegmentationHmm):

"""

def __new__(cls):
# try to load models
with open_text(
"gaitmap_mad.stride_segmentation.hmm._pre_trained_models", "fallriskpd_at_lab_model.json"
) as test_data, Path(test_data.name).open(encoding="utf8") as f:
model_json = f.read()
return RothSegmentationHmm.from_json(model_json)
# def __new__(cls):
# # try to load models
# with open_text(
# "gaitmap_mad.stride_segmentation.hmm._pre_trained_models", "fallriskpd_at_lab_model.json"
# ) as test_data, Path(test_data.name).open(encoding="utf8") as f:
# model_json = f.read()
# return RothSegmentationHmm.from_json(model_json)


BaseSegmentationHmmT = TypeVar("BaseSegmentationHmmT", bound=BaseSegmentationHmm)
Expand Down
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