dynamic_programming.viterbi¶
Functions¶
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Viterbi Algorithm, to find the most likely path of |
Module Contents¶
- dynamic_programming.viterbi._validate_dict(_object: Any, var_name: str, value_type: type, nested: bool = False) None¶
>>> _validate_dict({"b": 0.5}, "mock_name", float)
>>> _validate_dict("invalid", "mock_name", float) Traceback (most recent call last): ... ValueError: mock_name must be a dict >>> _validate_dict({"a": 8}, "mock_name", dict) Traceback (most recent call last): ... ValueError: mock_name all values must be dict >>> _validate_dict({2: 0.5}, "mock_name",float, True) Traceback (most recent call last): ... ValueError: mock_name all keys must be strings >>> _validate_dict({"b": 4}, "mock_name", float,True) Traceback (most recent call last): ... ValueError: mock_name nested dictionary all values must be float
- dynamic_programming.viterbi._validate_dicts(initial_probabilities: Any, transition_probabilities: Any, emission_probabilities: Any) None¶
>>> _validate_dicts({"c":0.5}, {"d": {"e": 0.6}}, {"f": {"g": 0.7}})
>>> _validate_dicts("invalid", {"d": {"e": 0.6}}, {"f": {"g": 0.7}}) Traceback (most recent call last): ... ValueError: initial_probabilities must be a dict >>> _validate_dicts({"c":0.5}, {2: {"e": 0.6}}, {"f": {"g": 0.7}}) Traceback (most recent call last): ... ValueError: transition_probabilities all keys must be strings >>> _validate_dicts({"c":0.5}, {"d": {"e": 0.6}}, {"f": {2: 0.7}}) Traceback (most recent call last): ... ValueError: emission_probabilities all keys must be strings >>> _validate_dicts({"c":0.5}, {"d": {"e": 0.6}}, {"f": {"g": "h"}}) Traceback (most recent call last): ... ValueError: emission_probabilities nested dictionary all values must be float
- dynamic_programming.viterbi._validate_list(_object: Any, var_name: str) None¶
>>> _validate_list(["a"], "mock_name")
>>> _validate_list("a", "mock_name") Traceback (most recent call last): ... ValueError: mock_name must be a list >>> _validate_list([0.5], "mock_name") Traceback (most recent call last): ... ValueError: mock_name must be a list of strings
- dynamic_programming.viterbi._validate_lists(observations_space: Any, states_space: Any) None¶
>>> _validate_lists(["a"], ["b"])
>>> _validate_lists(1234, ["b"]) Traceback (most recent call last): ... ValueError: observations_space must be a list
>>> _validate_lists(["a"], [3]) Traceback (most recent call last): ... ValueError: states_space must be a list of strings
- dynamic_programming.viterbi._validate_nested_dict(_object: Any, var_name: str) None¶
>>> _validate_nested_dict({"a":{"b": 0.5}}, "mock_name")
>>> _validate_nested_dict("invalid", "mock_name") Traceback (most recent call last): ... ValueError: mock_name must be a dict >>> _validate_nested_dict({"a": 8}, "mock_name") Traceback (most recent call last): ... ValueError: mock_name all values must be dict >>> _validate_nested_dict({"a":{2: 0.5}}, "mock_name") Traceback (most recent call last): ... ValueError: mock_name all keys must be strings >>> _validate_nested_dict({"a":{"b": 4}}, "mock_name") Traceback (most recent call last): ... ValueError: mock_name nested dictionary all values must be float
- dynamic_programming.viterbi._validate_not_empty(observations_space: Any, states_space: Any, initial_probabilities: Any, transition_probabilities: Any, emission_probabilities: Any) None¶
>>> _validate_not_empty(["a"], ["b"], {"c":0.5}, ... {"d": {"e": 0.6}}, {"f": {"g": 0.7}})
>>> _validate_not_empty(["a"], ["b"], {"c":0.5}, {}, {"f": {"g": 0.7}}) Traceback (most recent call last): ... ValueError: There's an empty parameter >>> _validate_not_empty(["a"], ["b"], None, {"d": {"e": 0.6}}, {"f": {"g": 0.7}}) Traceback (most recent call last): ... ValueError: There's an empty parameter
- dynamic_programming.viterbi._validation(observations_space: Any, states_space: Any, initial_probabilities: Any, transition_probabilities: Any, emission_probabilities: Any) None¶
>>> observations = ["normal", "cold", "dizzy"] >>> states = ["Healthy", "Fever"] >>> start_p = {"Healthy": 0.6, "Fever": 0.4} >>> trans_p = { ... "Healthy": {"Healthy": 0.7, "Fever": 0.3}, ... "Fever": {"Healthy": 0.4, "Fever": 0.6}, ... } >>> emit_p = { ... "Healthy": {"normal": 0.5, "cold": 0.4, "dizzy": 0.1}, ... "Fever": {"normal": 0.1, "cold": 0.3, "dizzy": 0.6}, ... } >>> _validation(observations, states, start_p, trans_p, emit_p)
>>> _validation([], states, start_p, trans_p, emit_p) Traceback (most recent call last): ... ValueError: There's an empty parameter
- dynamic_programming.viterbi.viterbi(observations_space: list, states_space: list, initial_probabilities: dict, transition_probabilities: dict, emission_probabilities: dict) list¶
Viterbi Algorithm, to find the most likely path of states from the start and the expected output. https://en.wikipedia.org/wiki/Viterbi_algorithm
- sdafads
Wikipedia example >>> observations = [“normal”, “cold”, “dizzy”] >>> states = [“Healthy”, “Fever”] >>> start_p = {“Healthy”: 0.6, “Fever”: 0.4} >>> trans_p = { … “Healthy”: {“Healthy”: 0.7, “Fever”: 0.3}, … “Fever”: {“Healthy”: 0.4, “Fever”: 0.6}, … } >>> emit_p = { … “Healthy”: {“normal”: 0.5, “cold”: 0.4, “dizzy”: 0.1}, … “Fever”: {“normal”: 0.1, “cold”: 0.3, “dizzy”: 0.6}, … } >>> viterbi(observations, states, start_p, trans_p, emit_p) [‘Healthy’, ‘Healthy’, ‘Fever’]
>>> viterbi((), states, start_p, trans_p, emit_p) Traceback (most recent call last): ... ValueError: There's an empty parameter
>>> viterbi(observations, (), start_p, trans_p, emit_p) Traceback (most recent call last): ... ValueError: There's an empty parameter
>>> viterbi(observations, states, {}, trans_p, emit_p) Traceback (most recent call last): ... ValueError: There's an empty parameter
>>> viterbi(observations, states, start_p, {}, emit_p) Traceback (most recent call last): ... ValueError: There's an empty parameter
>>> viterbi(observations, states, start_p, trans_p, {}) Traceback (most recent call last): ... ValueError: There's an empty parameter
>>> viterbi("invalid", states, start_p, trans_p, emit_p) Traceback (most recent call last): ... ValueError: observations_space must be a list
>>> viterbi(["valid", 123], states, start_p, trans_p, emit_p) Traceback (most recent call last): ... ValueError: observations_space must be a list of strings
>>> viterbi(observations, "invalid", start_p, trans_p, emit_p) Traceback (most recent call last): ... ValueError: states_space must be a list
>>> viterbi(observations, ["valid", 123], start_p, trans_p, emit_p) Traceback (most recent call last): ... ValueError: states_space must be a list of strings
>>> viterbi(observations, states, "invalid", trans_p, emit_p) Traceback (most recent call last): ... ValueError: initial_probabilities must be a dict
>>> viterbi(observations, states, {2:2}, trans_p, emit_p) Traceback (most recent call last): ... ValueError: initial_probabilities all keys must be strings
>>> viterbi(observations, states, {"a":2}, trans_p, emit_p) Traceback (most recent call last): ... ValueError: initial_probabilities all values must be float
>>> viterbi(observations, states, start_p, "invalid", emit_p) Traceback (most recent call last): ... ValueError: transition_probabilities must be a dict
>>> viterbi(observations, states, start_p, {"a":2}, emit_p) Traceback (most recent call last): ... ValueError: transition_probabilities all values must be dict
>>> viterbi(observations, states, start_p, {2:{2:2}}, emit_p) Traceback (most recent call last): ... ValueError: transition_probabilities all keys must be strings
>>> viterbi(observations, states, start_p, {"a":{2:2}}, emit_p) Traceback (most recent call last): ... ValueError: transition_probabilities all keys must be strings
>>> viterbi(observations, states, start_p, {"a":{"b":2}}, emit_p) Traceback (most recent call last): ... ValueError: transition_probabilities nested dictionary all values must be float
>>> viterbi(observations, states, start_p, trans_p, "invalid") Traceback (most recent call last): ... ValueError: emission_probabilities must be a dict
>>> viterbi(observations, states, start_p, trans_p, None) Traceback (most recent call last): ... ValueError: There's an empty parameter