diff --git a/.gitignore b/.gitignore index 7e4b7d14..572b6ab7 100644 --- a/.gitignore +++ b/.gitignore @@ -5,3 +5,4 @@ __pycache__/ *.pyc node_modules/ +.DS_Store \ No newline at end of file diff --git a/docs/FAQ.md b/docs/FAQ.md index 961210fc..f132abf8 100644 --- a/docs/FAQ.md +++ b/docs/FAQ.md @@ -21,7 +21,7 @@ The Openscope Databook is a great place to demonstrate the capabilities and some As described in [This Jupyter blog post](https://blog.jupyter.org/mybinder-org-reducing-capacity-c93ccfc6413f), Binder no longer has the support of Google, and therefore shows reduced performance. Launches may fail or take a long time. There is no working solution to this except trying to launch again. An alternative would be to launch Databook notebooks with Google Colab. **How can I store my work on the Databook and come back to it later?**\ -You can fork the [GitHub repository](https://github.com/AllenInstitute/openscope_databook), and clone the repository to your local machine or [Dandihub](https://hub.dandiarchive.org). Running files locally and on Dandihub are explained in further detail on the [front page](https://alleninstitute.github.io/openscope_databook/intro.html). As you are working, be sure to commit your changes and push them to GitHub. +You can fork the [GitHub repository](https://github.com/AllenInstitute/openscope_databook), and clone the repository to your local machine. Running files locally is explained in further detail on the [front page](https://alleninstitute.github.io/openscope_databook/intro.html). As you are working, be sure to commit your changes and push them to GitHub. **How do you recommend using the Databook?**\ The Databook can be used to reproduce analysis on files, as a starting point for investigating a dataset, or as an educational resource to get more familiar with NWB files or particular kinds of data. In all of these cases, the code can be modified, copied, and interactively run to gain a better understanding of the data. For educational use, the databook may be run remotely with Thebe, Binder, or Google Colab as simple demonstrations. For more advanced usage and analysis, it may behoove you to download an individual notebook and run it locally. diff --git a/docs/higher-order/GLM_pynapple_nemos.ipynb b/docs/higher-order/GLM_pynapple_nemos.ipynb index a065047c..802d2666 100644 --- a/docs/higher-order/GLM_pynapple_nemos.ipynb +++ b/docs/higher-order/GLM_pynapple_nemos.ipynb @@ -41,7 +41,7 @@ "\n", "
GLM(\n",
+ " observation_model=PoissonObservations(),\n",
+ " inverse_link_function=exp,\n",
+ " regularizer=Ridge(),\n",
+ " regularizer_strength=7.745e-06,\n",
+ " solver_name='LBFGS',\n",
+ " solver_kwargs={'maxiter': 5000}\n",
+ ")In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | \n", + " | observation_model | \n", + "PoissonObservations() | \n", + "
| \n", + " | inverse_link_function | \n", + "<function exp at 0x11680aa20> | \n", + "
| \n", + " | regularizer | \n", + "Ridge() | \n", + "
| \n", + " | regularizer_strength | \n", + "7.745e-06 | \n", + "
| \n", + " | solver_name | \n", + "'LBFGS' | \n", + "
| \n", + " | solver_kwargs | \n", + "{'maxiter': 5000} | \n", + "
| Name | \n", + "Type | \n", + "Value | \n", + "
|---|---|---|
| aux_ | \n", + "NoneType | \n", + "None | \n", + "\n", + "\n", + "
| coef_ | \n", + "ArrayImpl[float32](30,) | \n", + "Array([ 0.956...dtype=float32) | \n", + "\n", + "\n", + "
| dof_resid_ | \n", + "ArrayImpl[float32](1,) | \n", + "Array([24969.], dtype=float32) | \n", + "\n", + "\n", + "
| intercept_ | \n", + "ArrayImpl[float32](1,) | \n", + "Array([-3.892...dtype=float32) | \n", + "\n", + "\n", + "
| scale_ | \n", + "ArrayImpl[float32](1,) | \n", + "Array([1.], dtype=float32) | \n", + "\n", + "\n", + "
| solver_state_ | \n", + "OptimistixAdapterState | \n", + "OptimistixAda...k_bool[]\n", + " )\n", + ") | \n", + "\n", + "\n", + "
PopulationGLM(\n",
+ " observation_model=PoissonObservations(),\n",
+ " inverse_link_function=exp,\n",
+ " regularizer=Ridge(),\n",
+ " regularizer_strength=7.745e-06,\n",
+ " solver_name='LBFGS',\n",
+ " solver_kwargs={'maxiter': 5000}\n",
+ ")In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | \n", + " | observation_model | \n", + "PoissonObservations() | \n", + "
| \n", + " | inverse_link_function | \n", + "<function exp at 0x11680aa20> | \n", + "
| \n", + " | regularizer | \n", + "Ridge() | \n", + "
| \n", + " | regularizer_strength | \n", + "7.745e-06 | \n", + "
| \n", + " | solver_name | \n", + "'LBFGS' | \n", + "
| \n", + " | solver_kwargs | \n", + "{'maxiter': 5000} | \n", + "
| \n", + " | feature_mask | \n", + "None | \n", + "
| Name | \n", + "Type | \n", + "Value | \n", + "
|---|---|---|
| aux_ | \n", + "NoneType | \n", + "None | \n", + "\n", + "\n", + "
| coef_ | \n", + "ArrayImpl[float32](30, 19) | \n", + "Array([[-1.58...dtype=float32) | \n", + "\n", + "\n", + "
| dof_resid_ | \n", + "ArrayImpl[float32](19,) | \n", + "Array([24969....dtype=float32) | \n", + "\n", + "\n", + "
| intercept_ | \n", + "ArrayImpl[float32](19,) | \n", + "Array([-4.329...dtype=float32) | \n", + "\n", + "\n", + "
| scale_ | \n", + "ArrayImpl[float32](19,) | \n", + "Array([1., 1....dtype=float32) | \n", + "\n", + "\n", + "
| solver_state_ | \n", + "OptimistixAdapterState | \n", + "OptimistixAda...k_bool[]\n", + " )\n", + ") | \n", + "\n", + "\n", + "
PopulationGLM(\n", + " observation_model=PoissonObservations(),\n", + " inverse_link_function=exp,\n", + " regularizer=Ridge(),\n", + " regularizer_strength=0.005,\n", + " solver_name='LBFGS'\n", + ")In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
| \n", + " | observation_model | \n", + "PoissonObservations() | \n", + "
| \n", + " | inverse_link_function | \n", + "<function exp at 0x11680aa20> | \n", + "
| \n", + " | regularizer | \n", + "Ridge() | \n", + "
| \n", + " | regularizer_strength | \n", + "0.005 | \n", + "
| \n", + " | solver_name | \n", + "'LBFGS' | \n", + "
| \n", + " | solver_kwargs | \n", + "{} | \n", + "
| \n", + " | feature_mask | \n", + "None | \n", + "
| Name | \n", + "Type | \n", + "Value | \n", + "
|---|---|---|
| aux_ | \n", + "NoneType | \n", + "None | \n", + "\n", + "\n", + "
| coef_ | \n", + "ArrayImpl[float32](182, 19) | \n", + "Array([[-0.00...dtype=float32) | \n", + "\n", + "\n", + "
| dof_resid_ | \n", + "ArrayImpl[float32](19,) | \n", + "Array([24817....dtype=float32) | \n", + "\n", + "\n", + "
| intercept_ | \n", + "ArrayImpl[float32](19,) | \n", + "Array([-4.673...dtype=float32) | \n", + "\n", + "\n", + "
| scale_ | \n", + "ArrayImpl[float32](19,) | \n", + "Array([1., 1....dtype=float32) | \n", + "\n", + "\n", + "
| solver_state_ | \n", + "OptimistixAdapterState | \n", + "OptimistixAda...k_bool[]\n", + " )\n", + ") | \n", + "\n", + "\n", + "