Skip to content

Commit

Permalink
notebooks
Browse files Browse the repository at this point in the history
  • Loading branch information
@LegrandNico
LegrandNico committed Oct 2, 2023
1 parent 04d1e7a commit eef13f7
Show file tree
Hide file tree
Showing 8 changed files with 50 additions and 50 deletions.
6 changes: 3 additions & 3 deletions docs/source/notebooks/0-Creating_networks.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,7 @@
"outputs": [],
"source": [
"from pyhgf.typing import Indexes\n",
"parameters = {\"mu\": 0.0, \"pi\": 1.0}\n",
"parameters = {\"mean\": 0.0, \"precision\": 1.0}\n",
"\n",
"attributes = (parameters, parameters, parameters)\n",
"edges = (\n",
Expand All @@ -99,7 +99,7 @@
"id": "54c60f31-3554-48d5-906f-484f7b209545",
"metadata": {},
"source": [
"The code above illustrate the creation of a probabilistic network of 3 nodes with simple parameters sets $(\\mu=0.0, \\pi=1.0)$. Node 2 is the value parent of node 1. Node 3 is the value parent of node 2 and has no parents."
"The code above illustrates creating a probabilistic network of 3 nodes with simple parameter sets $(mean = 0.0, precision = 1.0)$. Node 2 is the value parent of node 1. Node 3 is the value parent of node 2 and has no parents."
]
},
{
Expand Down Expand Up @@ -218,7 +218,7 @@
"metadata": {},
"outputs": [],
"source": [
"hgf.attributes[3][\"pi\"] = 5.0"
"hgf.attributes[3][\"precision\"] = 5.0"
]
},
{
Expand Down
8 changes: 4 additions & 4 deletions docs/source/notebooks/0-Creating_networks.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@ jupytext:
extension: .md
format_name: myst
format_version: 0.13
jupytext_version: 1.14.7
jupytext_version: 1.15.1
kernelspec:
display_name: Python 3 (ipykernel)
language: python
Expand Down Expand Up @@ -66,7 +66,7 @@ One of the advantages of reasoning this way is that it dissociates variables tha

```{code-cell} ipython3
from pyhgf.typing import Indexes
parameters = {"mu": 0.0, "pi": 1.0}
parameters = {"mean": 0.0, "precision": 1.0}
attributes = (parameters, parameters, parameters)
edges = (
Expand All @@ -76,7 +76,7 @@ edges = (
)
```

The code above illustrate the creation of a probabilistic network of 3 nodes with simple parameters sets $(\mu=0.0, \pi=1.0)$. Node 2 is the value parent of node 1. Node 3 is the value parent of node 2 and has no parents.
The code above illustrates creating a probabilistic network of 3 nodes with simple parameter sets $(mean = 0.0, precision = 1.0)$. Node 2 is the value parent of node 1. Node 3 is the value parent of node 2 and has no parents.

+++

Expand All @@ -95,7 +95,7 @@ hgf.plot_network()
The simpler change we can make on a network is to change the values of some of its parameters. The parameters are stored in the `attributes` variable as a dictionary where the key (integers) are node indexes. Therefore, modifying the expected precision of the third node in the previous example is as simple as:

```{code-cell} ipython3
hgf.attributes[3]["pi"] = 5.0
hgf.attributes[3]["precision"] = 5.0
```

However, modifying parameters values *manually* should not be that common as this is something we want the model to perform dynamically as we present new observations, but this can be used for example to generate prior predictive by sampling some parameter values from a distribution.
Expand Down
6 changes: 3 additions & 3 deletions docs/source/notebooks/2-Using_custom_response_functions.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -158,9 +158,9 @@
"agent = HGF(\n",
" n_levels=2,\n",
" model_type=\"binary\",\n",
" initial_mu={\"1\": .0, \"2\": .5},\n",
" initial_pi={\"1\": .0, \"2\": 1e4},\n",
" omega={\"2\": -4.0},\n",
" initial_mean={\"1\": .0, \"2\": .5},\n",
" initial_precision={\"1\": .0, \"2\": 1e4},\n",
" tonic_volatility={\"2\": -4.0},\n",
").input_data(input_data=u)"
]
},
Expand Down
12 changes: 6 additions & 6 deletions docs/source/notebooks/2-Using_custom_response_functions.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -86,9 +86,9 @@ slideshow:
agent = HGF(
n_levels=2,
model_type="binary",
initial_mu={"1": .0, "2": .5},
initial_pi={"1": .0, "2": 1e4},
omega={"2": -4.0},
initial_mean={"1": .0, "2": .5},
initial_precision={"1": .0, "2": 1e4},
tonic_volatility={"2": -4.0},
).input_data(input_data=u)
```

Expand Down Expand Up @@ -121,7 +121,7 @@ slideshow:
---
# a simple decision rule using the first level of the HGF
np.random.seed(1)
responses = np.random.binomial(p=agent.node_trajectories[1]["muhat"], n=1)
responses = np.random.binomial(p=agent.node_trajectories[1]["expected_mean"], n=1)
```

+++ {"editable": true, "slideshow": {"slide_type": ""}}
Expand All @@ -139,7 +139,7 @@ plt.figure(figsize=(12, 3))
jitter = responses * .1 + (1-responses) * -.1
plt.scatter(np.arange(len(u)), u, label="Observations", color="#4c72b0", edgecolor="k", alpha=.2)
plt.scatter(np.arange(len(responses)), responses + jitter, label="Responses", color="#c44e52", alpha=.2, edgecolor="k")
plt.plot(agent.node_trajectories[1]["muhat"], label="Beliefs", linestyle="--")
plt.plot(agent.node_trajectories[1]["expected_mean"], label="Beliefs", linestyle="--")
plt.legend()
plt.xlabel("Trials")
```
Expand Down Expand Up @@ -205,7 +205,7 @@ def response_function(hgf, response_function_parameters):
responses = response_function_parameters[0]
# the expected values at the first level of the HGF
beliefs = hgf.node_trajectories[1]["muhat"]
beliefs = hgf.node_trajectories[1]["expected_mean"]
return jnp.sum(jnp.where(responses, -jnp.log(beliefs), -jnp.log(1.0 - beliefs)))
```
Expand Down
10 changes: 5 additions & 5 deletions docs/source/notebooks/Example_1_Heart_rate_variability.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -753,11 +753,11 @@
"hgf = HGF(\n",
" n_levels=2,\n",
" model_type=\"continuous\",\n",
" initial_mu={\"1\": rr[0], \"2\": -4.0},\n",
" initial_pi={\"1\": 1e4, \"2\": 1e1},\n",
" omega={\"1\": -4.0, \"2\": omega_2},\n",
" rho={\"1\": 0.0, \"2\": 0.0},\n",
" kappas={\"1\": 1.0}).input_data(input_data=rr)"
" initial_mean={\"1\": rr[0], \"2\": -4.0},\n",
" initial_precision={\"1\": 1e4, \"2\": 1e1},\n",
" tonic_volatility={\"1\": -4.0, \"2\": omega_2},\n",
" tonic_drift={\"1\": 0.0, \"2\": 0.0},\n",
" volatility_coupling={\"1\": 1.0}).input_data(input_data=rr)"
]
},
{
Expand Down
10 changes: 5 additions & 5 deletions docs/source/notebooks/Example_1_Heart_rate_variability.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -127,11 +127,11 @@ omega_2 = az.summary(idata)["mean"]["omega_2"]
hgf = HGF(
n_levels=2,
model_type="continuous",
initial_mu={"1": rr[0], "2": -4.0},
initial_pi={"1": 1e4, "2": 1e1},
omega={"1": -4.0, "2": omega_2},
rho={"1": 0.0, "2": 0.0},
kappas={"1": 1.0}).input_data(input_data=rr)
initial_mean={"1": rr[0], "2": -4.0},
initial_precision={"1": 1e4, "2": 1e1},
tonic_volatility={"1": -4.0, "2": omega_2},
tonic_drift={"1": 0.0, "2": 0.0},
volatility_coupling={"1": 1.0}).input_data(input_data=rr)
```

```{code-cell} ipython3
Expand Down
24 changes: 12 additions & 12 deletions docs/source/notebooks/Exercise_1_Using_the_HGF.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -222,9 +222,9 @@
"two_levels_continuous_hgf = HGF(\n",
" n_levels=2,\n",
" model_type=\"continuous\",\n",
" initial_mu={\"1\": 1.04, \"2\": 0.0},\n",
" initial_pi={\"1\": 1e4, \"2\": 1e1},\n",
" omega={\"1\": -8.0, \"2\": -1.0},\n",
" initial_mean={\"1\": 1.04, \"2\": 0.0},\n",
" initial_precision={\"1\": 1e4, \"2\": 1e1},\n",
" tonic_volatility={\"1\": -8.0, \"2\": -1.0},\n",
")"
]
},
Expand Down Expand Up @@ -875,9 +875,9 @@
"hgf = HGF(\n",
" n_levels=2,\n",
" model_type=\"continuous\",\n",
" initial_mu={\"1\": timeserie[0], \"2\": .5},\n",
" initial_pi={\"1\": 1e4, \"2\": 1e1},\n",
" omega={\"1\":-6.0, \"2\": -3.0},\n",
" initial_mean={\"1\": timeserie[0], \"2\": .5},\n",
" initial_precision={\"1\": 1e4, \"2\": 1e1},\n",
" tonic_volatility={\"1\":-6.0, \"2\": -3.0},\n",
")\n",
"\n",
"# add new observations\n",
Expand Down Expand Up @@ -975,9 +975,9 @@
"two_levels_hgf = HGF(\n",
" n_levels=2,\n",
" model_type=\"binary\",\n",
" initial_mu={\"1\": .0, \"2\": 0.0},\n",
" initial_pi={\"1\": np.nan, \"2\": 1.0},\n",
" omega={\"2\": -5},\n",
" initial_mean={\"1\": .0, \"2\": 0.0},\n",
" initial_precision={\"1\": np.nan, \"2\": 1.0},\n",
" tonic_volatility={\"2\": -5},\n",
")"
]
},
Expand Down Expand Up @@ -2334,9 +2334,9 @@
" three_levels_df = HGF(\n",
" n_levels=3,\n",
" model_type=\"binary\",\n",
" initial_mu={\"1\": .0, \"2\": 0.0, \"3\": 1.0},\n",
" initial_pi={\"1\": .0, \"2\": 1.0, \"3\": 1.0},\n",
" omega={\"2\": omega_2, \"3\": -6.0},\n",
" initial_mean={\"1\": .0, \"2\": 0.0, \"3\": 1.0},\n",
" initial_precision={\"1\": .0, \"2\": 1.0, \"3\": 1.0},\n",
" tonic_volatility={\"2\": omega_2, \"3\": -6.0},\n",
" verbose=False\n",
" ).input_data(input_data=u).to_pandas()\n",
" \n",
Expand Down
24 changes: 12 additions & 12 deletions docs/source/notebooks/Exercise_1_Using_the_HGF.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -143,9 +143,9 @@ This requires propagating updates on sufficient statistics and sending precision
two_levels_continuous_hgf = HGF(
n_levels=2,
model_type="continuous",
initial_mu={"1": 1.04, "2": 0.0},
initial_pi={"1": 1e4, "2": 1e1},
omega={"1": -8.0, "2": -1.0},
initial_mean={"1": 1.04, "2": 0.0},
initial_precision={"1": 1e4, "2": 1e1},
tonic_volatility={"1": -8.0, "2": -1.0},
)
```

Expand Down Expand Up @@ -280,9 +280,9 @@ timeserie = aarhus_weather_df["t2m"][:24*30].to_numpy()
hgf = HGF(
n_levels=2,
model_type="continuous",
initial_mu={"1": timeserie[0], "2": .5},
initial_pi={"1": 1e4, "2": 1e1},
omega={"1":-6.0, "2": -3.0},
initial_mean={"1": timeserie[0], "2": .5},
initial_precision={"1": 1e4, "2": 1e1},
tonic_volatility={"1":-6.0, "2": -3.0},
)
# add new observations
Expand Down Expand Up @@ -325,9 +325,9 @@ Fitting data to a binary HGF is quite similar to the continuous one (note that `
two_levels_hgf = HGF(
n_levels=2,
model_type="binary",
initial_mu={"1": .0, "2": 0.0},
initial_pi={"1": np.nan, "2": 1.0},
omega={"2": -5},
initial_mean={"1": .0, "2": 0.0},
initial_precision={"1": np.nan, "2": 1.0},
tonic_volatility={"2": -5},
)
```

Expand Down Expand Up @@ -743,9 +743,9 @@ for _ in range(20):
three_levels_df = HGF(
n_levels=3,
model_type="binary",
initial_mu={"1": .0, "2": 0.0, "3": 1.0},
initial_pi={"1": .0, "2": 1.0, "3": 1.0},
omega={"2": omega_2, "3": -6.0},
initial_mean={"1": .0, "2": 0.0, "3": 1.0},
initial_precision={"1": .0, "2": 1.0, "3": 1.0},
tonic_volatility={"2": omega_2, "3": -6.0},
verbose=False
).input_data(input_data=u).to_pandas()
Expand Down

0 comments on commit eef13f7

Please sign in to comment.