terms. The model used here is the same as the one deployed on the neuroquery website ( https://neuroquery.saclay.inria.fr ), and this example shows how to easily reproduce the website's functionality in a Python script. You can run this example on binder: https://mybinder.org/v2/gh/neuroquery/neuroquery.git/master?filepath=examples """ ###################################################################### # Download the vocabulary and learned coefficients of a NeuroQuery model # ---------------------------------------------------------------------- from neuroquery import fetch_neuroquery_model neuroquery_data = fetch_neuroquery_model() print(neuroquery_data) ###################################################################### # Load the NeuroQuery model # ------------------------- from neuroquery import NeuroQueryModel encoder = NeuroQueryModel.from_data_dir(neuroquery_data) ###################################################################### # Query the model and display the results # --------------------------------------- # taken from Wikipedia
""" Minimal example: encoding with NeuroQuery ========================================= The model used here is the same as the one deployed on the neuroquery website ( https://neuroquery.saclay.inria.fr ). """ ###################################################################### # Encode a query into a statistical map of the brain # -------------------------------------------------- from neuroquery import fetch_neuroquery_model, NeuroQueryModel from nilearn.plotting import view_img encoder = NeuroQueryModel.from_data_dir(fetch_neuroquery_model()) ###################################################################### query = """Huntington's disease""" result = encoder(query) view_img(result["z_map"], threshold=3.1) ###################################################################### # (drag the mouse on this interactive plot to see other slices) # # Note: if you are not using a jupyter notebook, use `.open_in_browser()` to # open the plot above: view_img(result["z_map"], threshold=3.1).open_in_browser() ###################################################################### # Display some relevant terms:
from neuroquery.tokenization import get_html_highlighted_text
from nilearn.plotting import plot_img, view_img
import ipywidgets as widgets
from IPython.display import display, display_html, Markdown
import utils
EXAMPLE_QUERY = (
"Theory of mind is the ability to attribute mental states — beliefs, "
"intents, desires, emotions, knowledge, etc. — to oneself, and to others, "
"and to understand that others have beliefs, desires, intentions, and "
"perspectives that are different from one's own. (from wikipedia)")
# %%capture
encoder = SimpleEncoder.from_data_dir(
fetch_neuroquery_model(model_name="ensemble_model_2020-02-12"))
query = widgets.Textarea(value=EXAMPLE_QUERY)
button = widgets.Button(description="Run query")
display(widgets.HBox([query, button]))
output = widgets.Output()
display(output)
def run_and_display_query(_):
result = encoder(query.value)
with output:
output.clear_output()
display_html(get_html_highlighted_text(result["highlighted_text"]),
raw=True)
display_html(view_img(result["brain_map"],