From 06bf971abe4392c3e2ef2aae41b592e51ece30ab Mon Sep 17 00:00:00 2001 From: ninamiolane Date: Tue, 26 Nov 2024 18:52:01 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20main=20from=20@=20geometric-in?= =?UTF-8?q?telligence/neurometry@564b576679bfb7d873733c193baf5ad62e134fc1?= =?UTF-8?q?=20=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- neurometry/.buildinfo | 4 +- neurometry/.doctrees/environment.pickle | Bin 246890 -> 247573 bytes .../01_methods_create_synthetic_data.ipynb | 86 +- ..._01_methods_create_synthetic_data_13_0.png | Bin 0 -> 61381 bytes ..._01_methods_create_synthetic_data_16_0.png | Bin 0 -> 41858 bytes ..._01_methods_create_synthetic_data_19_1.png | Bin 0 -> 36761 bytes ...s_01_methods_create_synthetic_data_9_2.png | Bin 0 -> 117190 bytes .../01_methods_create_synthetic_data.doctree | Bin 8673621 -> 8674085 bytes ...01_methods_create_synthetic_data.ipynb.txt | 1272 +++++++++-------- 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Topology

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Warping#< -
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Warping#<

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Warping#<

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Warping#<

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🦾 Getting Started
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🦾 Getting Started - + +

diff --git a/neurometry/notebooks/01_methods_create_synthetic_data.html b/neurometry/notebooks/01_methods_create_synthetic_data.html index 7e1e646..65e3860 100644 --- a/neurometry/notebooks/01_methods_create_synthetic_data.html +++ b/neurometry/notebooks/01_methods_create_synthetic_data.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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Create Synthetic Neural Manifolds#

This notebook explains how to use the module synthetic to generate points on neural manifolds in neural state space.

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Neural manifolds can be chosen among the following options: - Ring - Torus - Hypersphere - Klein bottle.

Set-up#

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Synthetic Neural Activity Encoding: Van der Pol Oscillator
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Synthetic Neural Activity Encoding: Van der Pol Oscillator - + +

diff --git a/neurometry/notebooks/01_methods_create_synthetic_data.ipynb b/neurometry/notebooks/01_methods_create_synthetic_data.ipynb index 11de294..e151d13 100644 --- a/neurometry/notebooks/01_methods_create_synthetic_data.ipynb +++ b/neurometry/notebooks/01_methods_create_synthetic_data.ipynb @@ -6,7 +6,13 @@ "source": [ "# Create Synthetic Neural Manifolds\n", "\n", - "This notebook explains how to use the module `synthetic` to generate points on neural manifolds in neural state space." + "This notebook explains how to use the module `synthetic` to generate points on neural manifolds in neural state space.\n", + "\n", + "Neural manifolds can be chosen among the following options:\n", + "- Ring\n", + "- Torus\n", + "- Hypersphere\n", + "- Klein bottle." ] }, { @@ -18395,6 +18401,7 @@ "yref": "paper" } ], + "autosize": true, "margin": { "b": 0, "l": 0, @@ -18403,6 +18410,11 @@ }, "scene": { "aspectmode": "cube", + "aspectratio": { + "x": 1, + "y": 1, + "z": 1 + }, "domain": { "x": [ 0, @@ -18420,7 +18432,8 @@ ], "title": { "text": "Feature 1" - } + }, + "type": "linear" }, "yaxis": { "range": [ @@ -18429,7 +18442,8 @@ ], "title": { "text": "Feature 2" - } + }, + "type": "linear" }, "zaxis": { "range": [ @@ -18438,11 +18452,17 @@ ], "title": { "text": "" - } + }, + "type": "linear" } }, "scene2": { "aspectmode": "cube", + "aspectratio": { + "x": 1, + "y": 1, + "z": 1 + }, "domain": { "x": [ 0.55, @@ -18460,7 +18480,8 @@ ], "title": { "text": "Neuron 1 firing rate" - } + }, + "type": "linear" }, "yaxis": { "range": [ @@ -18469,7 +18490,8 @@ ], "title": { "text": "Neuron 2 firing rate" - } + }, + "type": "linear" }, "zaxis": { "range": [ @@ -18478,7 +18500,8 @@ ], "title": { "text": "Neuron 3 firing rate" - } + }, + "type": "linear" } }, "template": { @@ -19302,6 +19325,7 @@ } } }, + "image/png": 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PLS approach
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PLS approach - + +

diff --git a/neurometry/notebooks/03_methods_estimate_manifold_topology.html b/neurometry/notebooks/03_methods_estimate_manifold_topology.html index ba0decc..4c81fc8 100644 --- a/neurometry/notebooks/03_methods_estimate_manifold_topology.html +++ b/neurometry/notebooks/03_methods_estimate_manifold_topology.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/04_explore_hyperbolic_geometry.html b/neurometry/notebooks/04_explore_hyperbolic_geometry.html index 5e9afd8..315a48f 100644 --- a/neurometry/notebooks/04_explore_hyperbolic_geometry.html +++ b/neurometry/notebooks/04_explore_hyperbolic_geometry.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/04_methods_estimate_manifold_geometry.html b/neurometry/notebooks/04_methods_estimate_manifold_geometry.html index f7cdcbe..fee1281 100644 --- a/neurometry/notebooks/04_methods_estimate_manifold_geometry.html +++ b/neurometry/notebooks/04_methods_estimate_manifold_geometry.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/05_explore_diffeomorphisms_of_space.html b/neurometry/notebooks/05_explore_diffeomorphisms_of_space.html index 91e2465..26a95a5 100644 --- a/neurometry/notebooks/05_explore_diffeomorphisms_of_space.html +++ b/neurometry/notebooks/05_explore_diffeomorphisms_of_space.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/071_application_dual_agent_rnns.html b/neurometry/notebooks/071_application_dual_agent_rnns.html index 80f3798..2df78f0 100644 --- a/neurometry/notebooks/071_application_dual_agent_rnns.html +++ b/neurometry/notebooks/071_application_dual_agent_rnns.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/09_application_rnns_grid_cells_xu.html b/neurometry/notebooks/09_application_rnns_grid_cells_xu.html index 1a83c18..72c5bb6 100644 --- a/neurometry/notebooks/09_application_rnns_grid_cells_xu.html +++ b/neurometry/notebooks/09_application_rnns_grid_cells_xu.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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Compute scores, scales, orientation of rate maps (TODO: clean!)
+ +
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Compute scores, scales, orientation of rate maps (TODO: clean!) - + +

diff --git a/neurometry/notebooks/10_methods_estimate_manifold_curvature.html b/neurometry/notebooks/10_methods_estimate_manifold_curvature.html index 83c9921..770391d 100644 --- a/neurometry/notebooks/10_methods_estimate_manifold_curvature.html +++ b/neurometry/notebooks/10_methods_estimate_manifold_curvature.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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Compute extrinsic curvature
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Compute extrinsic curvature - + +

diff --git a/neurometry/notebooks/11_visualize_rnn.html b/neurometry/notebooks/11_visualize_rnn.html index c0494fe..1224a24 100644 --- a/neurometry/notebooks/11_visualize_rnn.html +++ b/neurometry/notebooks/11_visualize_rnn.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -51,7 +54,8 @@ - + + @@ -67,19 +71,8 @@ Back to top - - - - - - -
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Load evaluation data (trajectories)
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Load evaluation data (trajectories) - + +

diff --git a/neurometry/notebooks/12_application_digitaltwin_v4.html b/neurometry/notebooks/12_application_digitaltwin_v4.html index 72b12a4..306d949 100644 --- a/neurometry/notebooks/12_application_digitaltwin_v4.html +++ b/neurometry/notebooks/12_application_digitaltwin_v4.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -50,7 +53,8 @@ - + + @@ -66,19 +70,8 @@ Back to top - - - - - - -
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Load model - + +

diff --git a/neurometry/notebooks/old_curvature/30_reparameterization_invariant_torus.html b/neurometry/notebooks/old_curvature/30_reparameterization_invariant_torus.html index cd94ea3..2a402d7 100644 --- a/neurometry/notebooks/old_curvature/30_reparameterization_invariant_torus.html +++ b/neurometry/notebooks/old_curvature/30_reparameterization_invariant_torus.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Plot curvature shapes, polar
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Plot curvature shapes, polar - + +

diff --git a/neurometry/notebooks/old_curvature/31_reparameterization_invariant_circle.html b/neurometry/notebooks/old_curvature/31_reparameterization_invariant_circle.html index af3e7ab..6209d54 100644 --- a/neurometry/notebooks/old_curvature/31_reparameterization_invariant_circle.html +++ b/neurometry/notebooks/old_curvature/31_reparameterization_invariant_circle.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Plot curvature shapes, polar - + +

diff --git a/neurometry/notebooks/other/17_simulated_place_cells.html b/neurometry/notebooks/other/17_simulated_place_cells.html index b65514f..89d3fef 100644 --- a/neurometry/notebooks/other/17_simulated_place_cells.html +++ b/neurometry/notebooks/other/17_simulated_place_cells.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Imports#< -
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Imports#<

- - + +
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Imports#<

- Created using Sphinx 8.0.2. + Created using Sphinx 8.1.3.

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Imports#<

- Built with the PyData Sphinx Theme 0.15.4. + Built with the PyData Sphinx Theme 0.16.0.

diff --git a/neurometry/notebooks/other/18_xor_geometry.html b/neurometry/notebooks/other/18_xor_geometry.html index 88f920d..48f1411 100644 --- a/neurometry/notebooks/other/18_xor_geometry.html +++ b/neurometry/notebooks/other/18_xor_geometry.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Imports#< -
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Imports#<

- Created using Sphinx 8.0.2. + Created using Sphinx 8.1.3.

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Imports#<

- Built with the PyData Sphinx Theme 0.15.4. + Built with the PyData Sphinx Theme 0.16.0.

diff --git a/neurometry/notebooks/other/29_grid_cells_var_orientation.html b/neurometry/notebooks/other/29_grid_cells_var_orientation.html index 8ef672e..0d572aa 100644 --- a/neurometry/notebooks/other/29_grid_cells_var_orientation.html +++ b/neurometry/notebooks/other/29_grid_cells_var_orientation.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Functions
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Functions - + +

diff --git a/neurometry/notebooks/place_cells/13_synthetic_place_cells_3neurons.html b/neurometry/notebooks/place_cells/13_synthetic_place_cells_3neurons.html index ab963df..8a92910 100644 --- a/neurometry/notebooks/place_cells/13_synthetic_place_cells_3neurons.html +++ b/neurometry/notebooks/place_cells/13_synthetic_place_cells_3neurons.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Verify that the function incorporated in synthetic.py generates correct data -
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Verify that the function incorporated in synthetic.py generates correct data

- - + +
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Verify that the function incorporated in synthetic.py generates correct data

- Created using Sphinx 8.0.2. + Created using Sphinx 8.1.3.

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Verify that the function incorporated in synthetic.py generates correct data

- Built with the PyData Sphinx Theme 0.15.4. + Built with the PyData Sphinx Theme 0.16.0.

diff --git a/neurometry/notebooks/place_cells/14_preprocess_ca1_hippocampus_data.html b/neurometry/notebooks/place_cells/14_preprocess_ca1_hippocampus_data.html index dc6ebc5..e20f6c0 100644 --- a/neurometry/notebooks/place_cells/14_preprocess_ca1_hippocampus_data.html +++ b/neurometry/notebooks/place_cells/14_preprocess_ca1_hippocampus_data.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Visualize 3D projection of neural state space (3 neurons with adjacent place -
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Visualize 3D projection of neural state space (3 neurons with adjacent place

- - + +
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Visualize 3D projection of neural state space (3 neurons with adjacent place

- Created using Sphinx 8.0.2. + Created using Sphinx 8.1.3.

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Visualize 3D projection of neural state space (3 neurons with adjacent place

- Built with the PyData Sphinx Theme 0.15.4. + Built with the PyData Sphinx Theme 0.16.0.

diff --git a/neurometry/notebooks/place_cells/16_decode_ca1_hippocampus_data.html b/neurometry/notebooks/place_cells/16_decode_ca1_hippocampus_data.html index a391ffb..3429088 100644 --- a/neurometry/notebooks/place_cells/16_decode_ca1_hippocampus_data.html +++ b/neurometry/notebooks/place_cells/16_decode_ca1_hippocampus_data.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Bayesian Decoder (GPT4) – Fix
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Bayesian Decoder (GPT4) – Fix - + +

diff --git a/neurometry/notebooks/place_cells/20_explore_raw_experimental_place_cells.html b/neurometry/notebooks/place_cells/20_explore_raw_experimental_place_cells.html index 6b4bacb..bb6e6f8 100644 --- a/neurometry/notebooks/place_cells/20_explore_raw_experimental_place_cells.html +++ b/neurometry/notebooks/place_cells/20_explore_raw_experimental_place_cells.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/place_cells/21_explore_binned_experimental_place_cells.html b/neurometry/notebooks/place_cells/21_explore_binned_experimental_place_cells.html index fe86969..e5b5b06 100644 --- a/neurometry/notebooks/place_cells/21_explore_binned_experimental_place_cells.html +++ b/neurometry/notebooks/place_cells/21_explore_binned_experimental_place_cells.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/place_cells/23_inspect_reconstructed_experimental_place_cells.html b/neurometry/notebooks/place_cells/23_inspect_reconstructed_experimental_place_cells.html index eca0335..3249c72 100644 --- a/neurometry/notebooks/place_cells/23_inspect_reconstructed_experimental_place_cells.html +++ b/neurometry/notebooks/place_cells/23_inspect_reconstructed_experimental_place_cells.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Plot Place
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diff --git a/neurometry/notebooks/place_cells/24_inspect_results_in_phase_space.html b/neurometry/notebooks/place_cells/24_inspect_results_in_phase_space.html index 52f2337..d402050 100644 --- a/neurometry/notebooks/place_cells/24_inspect_results_in_phase_space.html +++ b/neurometry/notebooks/place_cells/24_inspect_results_in_phase_space.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; - - - - - + + - - - - + + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/place_cells/25_evaluate_curvature_estimation.html b/neurometry/notebooks/place_cells/25_evaluate_curvature_estimation.html index 7a9d4a6..9ce66be 100644 --- a/neurometry/notebooks/place_cells/25_evaluate_curvature_estimation.html +++ b/neurometry/notebooks/place_cells/25_evaluate_curvature_estimation.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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diff --git a/neurometry/notebooks/place_cells/26_decode_gain_from_curvature.html b/neurometry/notebooks/place_cells/26_decode_gain_from_curvature.html index 7b9de64..5505d65 100644 --- a/neurometry/notebooks/place_cells/26_decode_gain_from_curvature.html +++ b/neurometry/notebooks/place_cells/26_decode_gain_from_curvature.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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TODO#
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TODO# - - + +

diff --git a/neurometry/notebooks/place_cells/27_plot_neural_manifolds.html b/neurometry/notebooks/place_cells/27_plot_neural_manifolds.html index d717a2f..516603b 100644 --- a/neurometry/notebooks/place_cells/27_plot_neural_manifolds.html +++ b/neurometry/notebooks/place_cells/27_plot_neural_manifolds.html @@ -16,29 +16,32 @@ document.documentElement.dataset.mode = localStorage.getItem("mode") || ""; document.documentElement.dataset.theme = localStorage.getItem("theme") || ""; + + - - - - - - - - - + + + + - - - + + - + @@ -49,7 +52,8 @@ - + + @@ -65,19 +69,8 @@ Back to top - - - - - - -
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Towards Parameterization invariance
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Isolation Forest - + +

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Python Module Index

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Python Module Index

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"Compute-Persistent-Homology-using-\\texttt{giotto-tda}"]], "Compute Spatial Autocorrelation + UMAP": [[15, "Compute-Spatial-Autocorrelation-+-UMAP"]], "Compute Topological Distance between Persistence Diagrams": [[9, "Compute-Topological-Distance-between-Persistence-Diagrams"]], "Compute extrinsic curvature": [[18, "Compute-extrinsic-curvature"]], "Compute grid scores, spatial autocorrelations (SACs)": [[17, "Compute-grid-scores,-spatial-autocorrelations-(SACs)"]], "Compute learned curvature": [[21, "Compute-learned-curvature"], [22, "Compute-learned-curvature"]], "Compute pairwise topological distance (\u201clandscape\u201d)": [[15, "Compute-pairwise-topological-distance-(%22landscape%22)"]], "Compute pull-back metric (\\varphi^*g)_{ij} = \\partial_{i}\\varphi^{a}\\partial_{j}\\varphi^{b}g_{ab}": [[16, "Compute-pull-back-metric-(\\varphi^*g)_{ij}-=-\\partial_{i}\\varphi^{a}\\partial_{j}\\varphi^{b}g_{ab}"]], "Compute pullback metric": [[12, "Compute-pullback-metric"]], "Compute scores, scales, orientation of rate maps (TODO: clean!)": [[17, "Compute-scores,-scales,-orientation-of-rate-maps-(TODO:-clean!)"]], "Compute true curvature": [[21, "Compute-true-curvature"], [22, "Compute-true-curvature"]], "Correlation between curvature and velocity": [[35, "Correlation-between-curvature-and-velocity"]], "Create Synthetic Neural Manifolds": [[7, null]], "Create and visualize synthetic place cells (3 neurons)": [[26, null]], "Create example torus point cloud": [[9, "Create-example-torus-point-cloud"]], "Create grid + deformed grid": [[16, "Create-grid-+-deformed-grid"]], "Curvature": [[0, null]], "Curvature computation": [[17, "Curvature-computation"]], "Cylinder (\\mathcal{S}^1 \\times [0,1]) in Neural State Space \\mathbb{R}^3": [[7, "Cylinder-(\\mathcal{S}^1-\\times-[0,1])-in-Neural-State-Space-\\mathbb{R}^3"]], "Datasets": [[1, null]], "Decode single and multiple gains": [[34, null]], "Define Parameters for Experiments": [[8, "Define-Parameters-for-Experiments"]], "Define diffeomorphism \\varphi: \\mathbb{R}^2 \\to \\mathbb{R}^2": [[16, "Define-diffeomorphism-\\varphi:-\\mathbb{R}^2-\\to-\\mathbb{R}^2"]], "Define experimental variables": [[27, "Define-experimental-variables"]], "Define subpolations based on UMAP on spatial autocorrelation scores": [[17, "Define-subpolations-based-on-UMAP-on-spatial-autocorrelation-scores"]], "Dimension": [[2, null]], "Dimensionality Estimation": [[17, "Dimensionality-Estimation"]], "Discover \u201cmodules\u201d through clustering / dim reduction? 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