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a/_modules/index.html b/_modules/index.html index 7a1223c4e..fd45e3fa8 100644 --- a/_modules/index.html +++ b/_modules/index.html @@ -438,7 +438,6 @@

    All modules for which code is available

    diff --git a/_modules/pyhgf/networks.html b/_modules/pyhgf/utils.html similarity index 98% rename from _modules/pyhgf/networks.html rename to _modules/pyhgf/utils.html index 3248b25d8..203f1a8d8 100644 --- a/_modules/pyhgf/networks.html +++ b/_modules/pyhgf/utils.html @@ -7,7 +7,7 @@ - pyhgf.networks — pyhgf 0.0.18 documentation + pyhgf.utils — pyhgf 0.0.18 documentation @@ -48,7 +48,7 @@ - + @@ -420,7 +420,7 @@ - + @@ -437,7 +437,7 @@
    -

    Source code for pyhgf.networks

    +  

    Source code for pyhgf.utils

     # Author: Nicolas Legrand <nicolas.legrand@cas.au.dk>
     
     from functools import partial
    @@ -477,7 +477,7 @@ 

    Source code for pyhgf.networks

     
     
     
    -[docs] +[docs] @partial(jit, static_argnames=("update_sequence", "structure")) def beliefs_propagation( attributes: Attributes, @@ -551,7 +551,7 @@

    Source code for pyhgf.networks

     
     
     
    -[docs] +[docs] def trim_sequence( exclude_node_idxs: List, update_sequence: UpdateSequence, edges: Tuple ) -> UpdateSequence: @@ -587,7 +587,7 @@

    Source code for pyhgf.networks

     
     
     
    -[docs] +[docs] def list_branches(node_idxs: List, edges: Tuple, branch_list: List = []) -> List: """Return the branch of a network from a given set of root nodes. @@ -647,7 +647,7 @@

    Source code for pyhgf.networks

     
     
     
    -[docs] +[docs] def fill_categorical_state_node( network: "Network", node_idx: int, @@ -730,7 +730,7 @@

    Source code for pyhgf.networks

     
     
     
    -[docs] +[docs] def get_update_sequence(network: "Network", update_type: str) -> List: """Generate an update sequence from the network's structure. diff --git a/_sources/api.rst.txt b/_sources/api.rst.txt index c09fddf83..8802acd68 100644 --- a/_sources/api.rst.txt +++ b/_sources/api.rst.txt @@ -203,15 +203,15 @@ least the HGF instance as input after observation and returning surprise. binary_softmax binary_softmax_inverse_temperature -Networks -******** +Utils +***** -Utilities for manipulating networks of probabilistic nodes. +Utilities for manipulating neural networks. -.. currentmodule:: pyhgf.networks +.. currentmodule:: pyhgf.utils .. autosummary:: - :toctree: generated/pyhgf.networks + :toctree: generated/pyhgf.utils beliefs_propagation trim_sequence diff --git a/_sources/generated/pyhgf.networks/pyhgf.networks.beliefs_propagation.rst.txt b/_sources/generated/pyhgf.networks/pyhgf.networks.beliefs_propagation.rst.txt deleted file mode 100644 index cb2ecbd36..000000000 --- a/_sources/generated/pyhgf.networks/pyhgf.networks.beliefs_propagation.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -pyhgf.networks.beliefs\_propagation -=================================== - -.. currentmodule:: pyhgf.networks - -.. autofunction:: beliefs_propagation \ No newline at end of file diff --git a/_sources/generated/pyhgf.networks/pyhgf.networks.fill_categorical_state_node.rst.txt b/_sources/generated/pyhgf.networks/pyhgf.networks.fill_categorical_state_node.rst.txt deleted file mode 100644 index c5147f3ca..000000000 --- a/_sources/generated/pyhgf.networks/pyhgf.networks.fill_categorical_state_node.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -pyhgf.networks.fill\_categorical\_state\_node -============================================= - -.. currentmodule:: pyhgf.networks - -.. autofunction:: fill_categorical_state_node \ No newline at end of file diff --git a/_sources/generated/pyhgf.networks/pyhgf.networks.get_update_sequence.rst.txt b/_sources/generated/pyhgf.networks/pyhgf.networks.get_update_sequence.rst.txt deleted file mode 100644 index 2f43b4ee2..000000000 --- a/_sources/generated/pyhgf.networks/pyhgf.networks.get_update_sequence.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -pyhgf.networks.get\_update\_sequence -==================================== - -.. currentmodule:: pyhgf.networks - -.. autofunction:: get_update_sequence \ No newline at end of file diff --git a/_sources/generated/pyhgf.networks/pyhgf.networks.list_branches.rst.txt b/_sources/generated/pyhgf.networks/pyhgf.networks.list_branches.rst.txt deleted file mode 100644 index c25afbd3b..000000000 --- a/_sources/generated/pyhgf.networks/pyhgf.networks.list_branches.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -pyhgf.networks.list\_branches -============================= - -.. currentmodule:: pyhgf.networks - -.. autofunction:: list_branches \ No newline at end of file diff --git a/_sources/generated/pyhgf.networks/pyhgf.networks.trim_sequence.rst.txt b/_sources/generated/pyhgf.networks/pyhgf.networks.trim_sequence.rst.txt deleted file mode 100644 index 3bd08cd12..000000000 --- a/_sources/generated/pyhgf.networks/pyhgf.networks.trim_sequence.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -pyhgf.networks.trim\_sequence -============================= - -.. currentmodule:: pyhgf.networks - -.. autofunction:: trim_sequence \ No newline at end of file diff --git a/_sources/generated/pyhgf.utils/pyhgf.utils.beliefs_propagation.rst.txt b/_sources/generated/pyhgf.utils/pyhgf.utils.beliefs_propagation.rst.txt new file mode 100644 index 000000000..494978e3f --- /dev/null +++ b/_sources/generated/pyhgf.utils/pyhgf.utils.beliefs_propagation.rst.txt @@ -0,0 +1,6 @@ +pyhgf.utils.beliefs\_propagation +================================ + +.. currentmodule:: pyhgf.utils + +.. autofunction:: beliefs_propagation \ No newline at end of file diff --git a/_sources/generated/pyhgf.utils/pyhgf.utils.fill_categorical_state_node.rst.txt b/_sources/generated/pyhgf.utils/pyhgf.utils.fill_categorical_state_node.rst.txt new file mode 100644 index 000000000..81450f4bf --- /dev/null +++ b/_sources/generated/pyhgf.utils/pyhgf.utils.fill_categorical_state_node.rst.txt @@ -0,0 +1,6 @@ +pyhgf.utils.fill\_categorical\_state\_node +========================================== + +.. currentmodule:: pyhgf.utils + +.. autofunction:: fill_categorical_state_node \ No newline at end of file diff --git a/_sources/generated/pyhgf.utils/pyhgf.utils.get_update_sequence.rst.txt b/_sources/generated/pyhgf.utils/pyhgf.utils.get_update_sequence.rst.txt new file mode 100644 index 000000000..bbe8607ae --- /dev/null +++ b/_sources/generated/pyhgf.utils/pyhgf.utils.get_update_sequence.rst.txt @@ -0,0 +1,6 @@ +pyhgf.utils.get\_update\_sequence +================================= + +.. currentmodule:: pyhgf.utils + +.. autofunction:: get_update_sequence \ No newline at end of file diff --git a/_sources/generated/pyhgf.utils/pyhgf.utils.list_branches.rst.txt b/_sources/generated/pyhgf.utils/pyhgf.utils.list_branches.rst.txt new file mode 100644 index 000000000..65a4d1c60 --- /dev/null +++ b/_sources/generated/pyhgf.utils/pyhgf.utils.list_branches.rst.txt @@ -0,0 +1,6 @@ +pyhgf.utils.list\_branches +========================== + +.. currentmodule:: pyhgf.utils + +.. autofunction:: list_branches \ No newline at end of file diff --git a/_sources/generated/pyhgf.utils/pyhgf.utils.trim_sequence.rst.txt b/_sources/generated/pyhgf.utils/pyhgf.utils.trim_sequence.rst.txt new file mode 100644 index 000000000..da88dd6e2 --- /dev/null +++ b/_sources/generated/pyhgf.utils/pyhgf.utils.trim_sequence.rst.txt @@ -0,0 +1,6 @@ +pyhgf.utils.trim\_sequence +========================== + +.. currentmodule:: pyhgf.utils + +.. autofunction:: trim_sequence \ No newline at end of file diff --git a/_sources/notebooks/0.3-Generalised_filtering.ipynb.txt b/_sources/notebooks/0.3-Generalised_filtering.ipynb.txt index 3ae750155..edc1a9f73 100644 --- a/_sources/notebooks/0.3-Generalised_filtering.ipynb.txt +++ b/_sources/notebooks/0.3-Generalised_filtering.ipynb.txt @@ -38,7 +38,7 @@ "from matplotlib.ticker import MultipleLocator\n", "from pyhgf.math import MultivariateNormal, Normal, gaussian_predictive_distribution\n", "from pyhgf.model import HGF\n", - "from pyhgf.networks import beliefs_propagation\n", + "from pyhgf.utils import beliefs_propagation\n", "from scipy.special import gammaln\n", "from scipy.stats import norm, t\n", "\n", diff --git a/_sources/notebooks/Example_3_Multi_armed_bandit.ipynb.txt b/_sources/notebooks/Example_3_Multi_armed_bandit.ipynb.txt index a63967026..1317b2413 100644 --- a/_sources/notebooks/Example_3_Multi_armed_bandit.ipynb.txt +++ b/_sources/notebooks/Example_3_Multi_armed_bandit.ipynb.txt @@ -942,7 +942,7 @@ "metadata": {}, "outputs": [], "source": [ - "from pyhgf.networks import beliefs_propagation" + "from pyhgf.utils import beliefs_propagation" ] }, { diff --git a/api.html b/api.html index 5ab3b0bc5..f3242540c 100644 --- a/api.html +++ b/api.html @@ -483,7 +483,7 @@
  • Model

  • Plots

  • Response

  • -
  • Networks

  • +
  • Utils

  • Math

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  • @@ -713,24 +713,24 @@

    Response -
    -

    Networks#

    -

    Utilities for manipulating networks of probabilistic nodes.

    +
    +

    Utils#

    +

    Utilities for manipulating neural networks.

    - + - + - + - + - + @@ -850,7 +850,7 @@

    MathModel
  • Plots
  • Response
  • -
  • Networks
  • +
  • Utils
  • Math
  • diff --git a/generated/pyhgf.distribution/pyhgf.distribution.HGFDistribution.html b/generated/pyhgf.distribution/pyhgf.distribution.HGFDistribution.html index 0f8e2de9e..de508059e 100644 --- a/generated/pyhgf.distribution/pyhgf.distribution.HGFDistribution.html +++ b/generated/pyhgf.distribution/pyhgf.distribution.HGFDistribution.html @@ -455,11 +455,11 @@
  • pyhgf.response.binary_softmax_inverse_temperature
  • @@ -528,11 +528,11 @@
    -
    -

    pyhgf.networks.beliefs_propagation#

    +
    +

    pyhgf.utils.beliefs_propagation#

    -
    -pyhgf.networks.beliefs_propagation(attributes: Dict[int, Dict], input_data: Array | ndarray | bool_ | number | bool | int | float | complex, update_sequence: Tuple[Tuple[int, Callable], ...], structure: Tuple[Inputs, Tuple[AdjacencyLists, ...]]) Tuple[Dict, Dict][source]#
    +
    +pyhgf.utils.beliefs_propagation(attributes: Dict[int, Dict], input_data: Array | ndarray | bool_ | number | bool | int | float | complex, update_sequence: Tuple[Tuple[int, Callable], ...], structure: Tuple[Inputs, Tuple[AdjacencyLists, ...]]) Tuple[Dict, Dict][source]#

    Update the network’s parameters after observing new data point(s).

    This function performs the beliefs propagation step at a time t triggered by the observation of a new batch of value(s). The way beliefs propagate is defined by the @@ -589,11 +589,11 @@

    pyhgf.networks.beliefs_propagation

    next

    -

    pyhgf.networks.trim_sequence

    +

    pyhgf.utils.trim_sequence

    @@ -615,14 +615,14 @@

    pyhgf.networks.beliefs_propagation @@ -528,11 +528,11 @@
    -
    -

    pyhgf.networks.fill_categorical_state_node#

    +
    +

    pyhgf.utils.fill_categorical_state_node#

    -
    -pyhgf.networks.fill_categorical_state_node(network: Network, node_idx: int, binary_input_idxs: List[int], binary_parameters: Dict) Network[source]#
    +
    +pyhgf.utils.fill_categorical_state_node(network: Network, node_idx: int, binary_input_idxs: List[int], binary_parameters: Dict) Network[source]#

    Generate a binary network implied by categorical state(-transition) nodes.

    Parameters:
    @@ -569,20 +569,20 @@

    pyhgf.networks.fill_categorical_state_node

    previous

    -

    pyhgf.networks.list_branches

    +

    pyhgf.utils.list_branches

    next

    -

    pyhgf.networks.get_update_sequence

    +

    pyhgf.utils.get_update_sequence

    @@ -604,14 +604,14 @@

    pyhgf.networks.fill_categorical_state_node @@ -528,11 +528,11 @@
    -
    -

    pyhgf.networks.get_update_sequence#

    +
    +

    pyhgf.utils.get_update_sequence#

    -
    -pyhgf.networks.get_update_sequence(network: Network, update_type: str) List[source]#
    +
    +pyhgf.utils.get_update_sequence(network: Network, update_type: str) List[source]#

    Generate an update sequence from the network’s structure.

    This function return an optimized update sequence considering the edges of the network. The function ensures that the following principles apply: @@ -577,12 +577,12 @@

    pyhgf.networks.get_update_sequence

    previous

    -

    pyhgf.networks.fill_categorical_state_node

    +

    pyhgf.utils.fill_categorical_state_node

    pyhgf.networks.get_update_sequence @@ -528,11 +528,11 @@
    -
    -

    pyhgf.networks.list_branches#

    +
    +

    pyhgf.utils.list_branches#

    -
    -pyhgf.networks.list_branches(node_idxs: List, edges: Tuple, branch_list: List = []) List[source]#
    +
    +pyhgf.utils.list_branches(node_idxs: List, edges: Tuple, branch_list: List = []) List[source]#

    Return the branch of a network from a given set of root nodes.

    This function searches recursively and lists the parents above a given node. If all the children of a given parent are on the exclusion list, this parent is also @@ -571,20 +571,20 @@

    pyhgf.networks.list_branches

    previous

    -

    pyhgf.networks.trim_sequence

    +

    pyhgf.utils.trim_sequence

    next

    -

    pyhgf.networks.fill_categorical_state_node

    +

    pyhgf.utils.fill_categorical_state_node

    @@ -606,14 +606,14 @@

    pyhgf.networks.list_branches @@ -528,11 +528,11 @@
    -
    -

    pyhgf.networks.trim_sequence#

    +
    +

    pyhgf.utils.trim_sequence#

    -
    -pyhgf.networks.trim_sequence(exclude_node_idxs: List, update_sequence: Tuple[Tuple[int, Callable], ...], edges: Tuple) Tuple[Tuple[int, Callable], ...][source]#
    +
    +pyhgf.utils.trim_sequence(exclude_node_idxs: List, update_sequence: Tuple[Tuple[int, Callable], ...], edges: Tuple) Tuple[Tuple[int, Callable], ...][source]#

    Remove steps from an update sequence that depends on a set of nodes.

    Parameters:
    @@ -569,20 +569,20 @@

    pyhgf.networks.trim_sequence

    previous

    -

    pyhgf.networks.beliefs_propagation

    +

    pyhgf.utils.beliefs_propagation

    next

    -

    pyhgf.networks.list_branches

    +

    pyhgf.utils.list_branches

    @@ -604,14 +604,14 @@

    pyhgf.networks.trim_sequence

    beliefs_propagation(attributes, input_data, ...)

    beliefs_propagation(attributes, input_data, ...)

    Update the network's parameters after observing new data point(s).

    trim_sequence(exclude_node_idxs, ...)

    trim_sequence(exclude_node_idxs, ...)

    Remove steps from an update sequence that depends on a set of nodes.

    list_branches(node_idxs, edges[, branch_list])

    list_branches(node_idxs, edges[, branch_list])

    Return the branch of a network from a given set of root nodes.

    fill_categorical_state_node(network, ...)

    fill_categorical_state_node(network, ...)

    Generate a binary network implied by categorical state(-transition) nodes.

    get_update_sequence(network, update_type)

    get_update_sequence(network, update_type)

    Generate an update sequence from the network's structure.

    diff --git a/notebooks/0.1-Theory.html b/notebooks/0.1-Theory.html index 50c60ec75..0248a4153 100644 --- a/notebooks/0.1-Theory.html +++ b/notebooks/0.1-Theory.html @@ -903,7 +903,7 @@

    System configuration
    -
    -
    Last updated: Thu May 23 2024
    +
     
    -
    Last updated: Thu May 23 2024
    +
    Last updated: Fri May 24 2024
     
     Python implementation: CPython
     Python version       : 3.12.3
    diff --git a/notebooks/1.1-Binary_HGF.html b/notebooks/1.1-Binary_HGF.html
    index 4b0be9102..669b3d4b4 100644
    --- a/notebooks/1.1-Binary_HGF.html
    +++ b/notebooks/1.1-Binary_HGF.html
    @@ -51,7 +51,7 @@
         
         
         
    -    
    +    
         
         
         
    @@ -792,19 +792,22 @@ 

    Sampling self.pid = os.fork()

    -
    -../_images/f2a4964ebba623b68f69bf0648e47b01f16cf56116c8edc7a12fe1b6b40aded9.png +../_images/1dc70311198250c983a638d2c1d50fb69da11820aa3a529a49793e9245e81330.png

    @@ -853,7 +856,7 @@

    Using the learned parameters -../_images/0338347516b69db9fbb7fd68de9936ee04c135283f4891a80839db1f98bafe19.png +../_images/a8da50c1a0b0b4b2f24551820095b2bd32e47462dc0951880adae3b8d4e192e7.png

    @@ -944,7 +947,11 @@

    Sampling# self.pid = os.fork() -

    @@ -1002,7 +1009,7 @@

    Using the learned parameters -../_images/e8d64ae897cd750329a324b1cf1290d9cb37c7c1532b70e75f19c22fd6d6e8d6.png +../_images/248b4b53ded9a8deaead9f14a8c327dca3af86e7a2b8ce7a5823d86c4ca608d7.png
    @@ -1012,7 +1019,7 @@

    Using the learned parameters -
    -
    -
    Last updated: Thu May 23 2024
    +
    diff --git a/notebooks/1.3-Continuous_HGF.html b/notebooks/1.3-Continuous_HGF.html index 2fbb590b4..35fc29fac 100644 --- a/notebooks/1.3-Continuous_HGF.html +++ b/notebooks/1.3-Continuous_HGF.html @@ -51,7 +51,7 @@ - + @@ -846,7 +846,7 @@

    Sampling self.pid = os.fork()

    -
    -../_images/6870c878dfa8be2a489ffd7c0a9945c167260725be27e94b8c323d315acd9f16.png +../_images/fc9c9d0ad7db3f8618a8fab2954880ab258dbe4672cdeda6d28e830f0e0fb36a.png
    @@ -904,7 +904,7 @@

    Using the learned parameters -../_images/99baaf96994441c801b09e398badaa2fec3fa62b5da6d4541c28b2374857cc78.png +../_images/912fffdcd2054c64eed5d2aa8bf4727c5e1de8d1da7009137538546b84545cba.png

    - @@ -1046,7 +1050,7 @@

    Using the learned parameters -../_images/ec45c913dddfe05083a32f5a73116e68992ff0978b7f3ba77f4ba143eea09cc0.png +../_images/16b6d00f943b9b8f127662c2a34f0a6eb4a54ae97fd7dfe4473a11ab262bc786.png
    @@ -1056,7 +1060,7 @@

    Using the learned parameters -
    -
    Last updated: Thu May 23 2024
    +
    Last updated: Fri May 24 2024
     
     Python implementation: CPython
     Python version       : 3.12.3
    @@ -1084,9 +1088,9 @@ 

    System configurationvar togglebuttonSelector = '.toggle, .admonition.dropdown'; - + @@ -888,13 +888,13 @@

    Recovering HGF parameters from the observed behaviors
    NUTS: [tonic_volatility_2]
     

    -
    
    +
    
     
     
    -
    
    +
    
     
     
    -
    +
    ../_images/2c05c24fd9a88f8b89577d0ca0dcd551e04308054d1b82ff87bc5e37b12d75bb.png +

    ../_images/0539b59bce54e24aa674cfd43a8494bed83174f6ce6c90341820bfbf525e1f23.png

    The results above indicate that given the responses provided by the participant, the most likely values for the parameter \(\omega_2\) are between -4.9 and -3.1, with a mean at -3.9 (you can find slightly different values if you sample different actions from the decisions function). We can consider this as an excellent estimate given the sparsity of the data, and the complexity of the model.

    @@ -977,7 +977,7 @@

    System configuration
    -
    Last updated: Thu May 23 2024
    +
    diff --git a/notebooks/3-Multilevel_HGF.html b/notebooks/3-Multilevel_HGF.html index 79f31f78e..88108fd81 100644 --- a/notebooks/3-Multilevel_HGF.html +++ b/notebooks/3-Multilevel_HGF.html @@ -51,7 +51,7 @@ - + @@ -707,7 +707,7 @@

    Plot the computational graph -../_images/696a07dc07aeeb78568195b4cd27da10c346b2f3696efa9446d59734f805f924.svg

    +../_images/0b97b076146b6fa4943dcd3dec35240d123dfd9ae79c99489d37f4c1181370f8.svg
    @@ -732,10 +732,10 @@

    Sampling
    NUTS: [mu_volatility, sigma_volatility, volatility, mu_temperature, sigma_temperature, inverse_temperature]
     
    -
    
    +
    
     
     
    -
    +

    @@ -748,7 +748,7 @@

    Visualization of the posterior distributions -../_images/9dd169223f849709d0e96f9e2b359b7e54bb489c486433223b1de934ec60675d.png +../_images/d2c8100ed99add21a983cd1ff589d723b8f399879fe56560c344134d58ba7733.png

    The reference values on both posterior distributions indicate the mean of the distribution used for simulation.

    @@ -764,7 +764,7 @@

    System configuration
    -
    Last updated: Thu May 23 2024
    +
    Last updated: Fri May 24 2024
     
     Python implementation: CPython
     Python version       : 3.12.3
    @@ -774,10 +774,10 @@ 

    System configurationvar togglebuttonSelector = '.toggle, .admonition.dropdown'; - + @@ -664,10 +664,10 @@

    Inference from the simulated behaviours
    NUTS: [censored_volatility, inverse_temperature]
     

    -
    
    +
    
     
     
    -
    +

    @@ -723,7 +723,7 @@

    Visualizing parameters recovery -../_images/8e13d3fa71ea9b734811483035e21406ecf61b532e57f8699aebe920d35e0fb9.png +../_images/e8375c0bab4b282f149e887dfc886c14e315fc329203e713d139911df5fa8147.png

    @@ -738,7 +738,7 @@

    System configuration
    -
    Last updated: Thu May 23 2024
    +
    diff --git a/notebooks/Example_1_Heart_rate_variability.html b/notebooks/Example_1_Heart_rate_variability.html index 1064b2bbc..c4f2b00a5 100644 --- a/notebooks/Example_1_Heart_rate_variability.html +++ b/notebooks/Example_1_Heart_rate_variability.html @@ -49,7 +49,7 @@ - + @@ -555,16 +555,16 @@

    Loading and preprocessing physiological recording
    Downloading ECG channel:   0%|          | 0/2 [00:00<?, ?it/s]
     

    -
    Downloading ECG channel:  50%|█████     | 1/2 [00:00<00:00,  1.45it/s]
    +
    Downloading ECG channel:  50%|█████     | 1/2 [00:00<00:00,  1.72it/s]
     
    -
    Downloading Respiration channel:  50%|█████     | 1/2 [00:00<00:00,  1.45it/s]
    +
    Downloading Respiration channel:  50%|█████     | 1/2 [00:00<00:00,  1.72it/s]
     
    -
    -
    -../_images/d612078ec9c0e0c6a3eedf48161006c61eca0e356ff0b881f6efc2e834dfa9e3.png +../_images/8493898cebfecbc8f291a4b7247f316d2edd76667ee28805648395d96146231f.png
    -../_images/bf3cf6b3bd9ee098f466293af2af94a39e55178a860be856e5be6e7aee72346e.png +../_images/7dfea04c749d084b7f2f78506c67509c43f70475026a98ef0a7073888e3358f2.png
    @@ -734,7 +734,7 @@

    System configuration

    -
    Last updated: Thu May 23 2024
    +
     
    -
    Last updated: Thu May 23 2024
    +
    diff --git a/notebooks/Example_3_Multi_armed_bandit.html b/notebooks/Example_3_Multi_armed_bandit.html index e6aa3d1cd..3da28bb5e 100644 --- a/notebooks/Example_3_Multi_armed_bandit.html +++ b/notebooks/Example_3_Multi_armed_bandit.html @@ -51,7 +51,7 @@ - + @@ -821,10 +821,10 @@

    Parameter recovery

    Real-time decision and belief updating#

    -

    We can implement this process using the pyhgf.networks.beliefs_propagation() function. In other models, this step is called sequentially in a jax.lax.scan() loop, but we can also use it for a single-step update.

    +

    We can implement this process using the pyhgf.networks.beliefs_propagation() function. In other models, this step is called sequentially in a jax.lax.scan() loop, but we can also use it for a single-step update.

    -
    from pyhgf.networks import beliefs_propagation
    +
    from pyhgf.utils import beliefs_propagation
     
    @@ -1081,16 +1081,16 @@

    Bayesian inference
    NUTS: [omega]
     

    -
    
    +
    
     
     
    -
    
    +
    
     
     
    -
    Sampling 2 chains for 1_000 tune and 1_000 draw iterations (2_000 + 2_000 draws total) took 25 seconds.
    +
    Sampling 2 chains for 1_000 tune and 1_000 draw iterations (2_000 + 2_000 draws total) took 26 seconds.
     
    -
    -
    Last updated: Thu May 23 2024
    +
    diff --git a/notebooks/Exercise_1_Using_the_HGF.html b/notebooks/Exercise_1_Using_the_HGF.html index 4d3cb7189..0ffa953ab 100644 --- a/notebooks/Exercise_1_Using_the_HGF.html +++ b/notebooks/Exercise_1_Using_the_HGF.html @@ -51,7 +51,7 @@ - + @@ -758,7 +758,7 @@

    Parameters optimization

    -
    @@ -813,15 +813,15 @@

    Parameters optimization tonic_volatility_1 - -5.988 - 0.919 - -7.608 - -4.236 - 0.027 - 0.019 - 1255.0 - 1111.0 - 1.0 + -5.943 + 0.946 + -7.714 + -4.169 + 0.03 + 0.022 + 1079.0 + 718.0 + 1.01 @@ -1160,19 +1160,11 @@

    Biased random{"version_major": 2, "version_minor": 0, "model_id": "6b990c3878b142398abc7fde6e6859b8"}
    /opt/hostedtoolcache/Python/3.12.3/x64/lib/python3.12/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.
    +
    /opt/hostedtoolcache/Python/3.12.3/x64/lib/python3.12/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.
       self.pid = os.fork()
     
    -
    
    -
    -
    -
    Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 35 seconds.
    -
    -
    -
    -

    Assess model fitting, here using leave-one-out cross-validation from the Arviz library.

    @@ -1196,8 +1188,8 @@

    Biased random

    @@ -1501,7 +1486,7 @@

    Two-level HGF - @@ -1832,7 +1817,7 @@

    System configuration

    -
    Last updated: Thu May 23 2024
    +
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