diff --git a/conf/config_2pop.yml b/conf/config_2pop.yml new file mode 100644 index 0000000..aeba12f --- /dev/null +++ b/conf/config_2pop.yml @@ -0,0 +1,156 @@ +########################################## +# Simulation parameters +########################################## +# disable jit compilation +DISABLE_JIT: 0 +# number of threads for parallel processing +NUM_THREADS: 116 + +# output different prompts for debugging purpose +VERBOSE: 0 + +# 1 to save the data to REPO_ROOT/data/simul +SAVE_DATA: 1 + +# Time step in s +DT: 0.001 +# total simulation time in s +DURATION: 5.0 +# time to start saving simulation files +T_STEADY: 1.0 +# Saving to files every T_WINDOW +T_WINDOW: .250 + +########################################## +# Parameters for the stimulus presentation +########################################## +# stimulus as a cosine shape +# time for stimulus onset in s +T_STIM_ON: 2.0 +# time for stimulus offset in s +T_STIM_OFF: 2.5 +# amplitude of the 1st stimulus +I0: [2.0, 0.0] +# amplitude of the 2nd stimulus +I1: [0.0, 0.0] +# I1: [0.05, 0.0] +# Phase of the 1st stimulus +PHI0: 180.0 +# Tuning of the 1st stimulus +SIGMA0: 1.0 +# Phase difference between 1st/2nd stimuli +DPHI: 0.25 + +########################################## +# Network parameters +########################################## +# number of populations +N_POP: 2 +# number of neurons +N: 2000 +# number of average presynaptic input (set to 1 if all to all) +K: 1.0 +# fraction of neuron in each population (must sum to 1) +frac: [0.75, 0.25] + +########################################## +# Network Dynamic +########################################## +# Transfert Function +# set to 0 for threshold linear, 1 for sigmoid +TF_TYPE: 1 + +# Dynamics of the rates +# set to 0 if instantaneous rates, 1 if exponentially decaying +RATE_DYN: 1 +# rate time constants in s +TAU_MEM: [0.02, 0.02] + +# Dynamics of the recurrent inputs +# set to 0 if instantaneous, 1 if exponentially decaying +SYN_DYN: 0 +# Synaptic time constants for each population +TAU_SYN: [0.003, 0.002] + +# Adding NMDA currents +IF_NMDA: 0 +# NMDA time constants in s +TAU_NMDA: [0.2, 0.2] + +# Feedforward inputs dynamics +# set to 0 for instantaneous, 1 to exp decay, 2 adds gaussian noise +FF_DYN: 2 +# FF time constants in s +TAU_FF: [0.003, 0.003] +# Variance of the noise +VAR_FF: [1.0, 1.0] + +# Threshold dynamics +# set to 0 constant thresholds, 1 to add adaptative thresholds +THRESH_DYN: 0 +# threshold +THRESH: [15.00, 15.00] +# threshold time constants +TAU_THRESH: [0.1, 0.1] + +# Network's gain +GAIN: 1.0 + +# Synaptic strengths +Jab: [2.0, -1.5, 1.0, -1.0] +# External inputs strengths +Iext: [0.5, 0.25] +# External rate +M0: 1.0 + +# To add an attentional switch +# if BUMP_SWITCH[i] == 1 it sets Iext[i] to zero before stimulus presentation +BUMP_SWITCH: [1, 1] + +######################## +# Plasticity +######################## +# adds learning +IF_LEARNING: 0 +# adds short term plasticity +IF_STP: 0 + +############## +# Connectivity +############## +# load connectivity matrix +# from REPO_PATH/data/matrix +IF_LOAD_MAT: 0 + +# save connectivity matrix +IF_SAVE_MAT: 1 + +# seed for connectivity None or float +SEED: 1 +# connectivity type +# STRUCTURE can be 'all', 'all_cos', 'cos', 'spec_cos', 'None' + +# By default the matrix is a random sparse matrix Cij +# 'cos' gives a sparse matrix with strong cosine structure, +# Pij = (1 + 2 KAPPA cos(theta_ij) / sqrt(Kb)), Cij = 1 with proba Pij +# 'spec_cos' gives a sparse matrix with weak cosine structure, +# Pij = (1 + 2 KAPPA cos(theta_ij) / sqrt(Kb)) , Cij = 1 with proba Pij +# 'all' gives an all to all matrix, Cij = 1/N +# 'all_cos' gives an all to all with cosine shape, +# Cij = (1 + 2 KAPPA cos(theta_ij)) / N +# any other string gives a sparse matrix, +# Cij = 1 with proba Ka/Na, 0 otherwise + +# sets probabilities of connections' shape +STRUCTURE: ['all_cos', 'all_cos', 'all_cos', 'all_cos'] +# tuning of the recurrent connections +KAPPA: [0.6, 0.0, 0.6, 0.0] +# phase of the connectivity +PHASE: 0.0 + +# strength of the asymmetries if all to all +SIGMA: [0.0, 0.0, 0.0, 0.0] + +# parameters for computing the mean field +TOLERANCE: 1.e-12 +MAXITER: 100 diff --git a/notebooks/doc.ipynb b/notebooks/doc.ipynb deleted file mode 100644 index 8c93726..0000000 --- a/notebooks/doc.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"cell_type":"markdown","metadata":{},"source":"RNN numba package\n=================\n\n"},{"cell_type":"markdown","metadata":{},"source":["## notebook settings\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"The autoreload extension is already loaded. To reload it, use:\n %reload_ext autoreload\nPython exe\n/home/leon/mambaforge/envs/dual_data/bin/python"}],"source":["%load_ext autoreload\n%autoreload 2\n%reload_ext autoreload\n\n%run ../notebooks/setup.py\n%matplotlib inline\n%config InlineBackend.figure_format = 'png'"]},{"cell_type":"markdown","metadata":{},"source":["## Continuous Bump Attractor Model\n\n"]},{"cell_type":"markdown","metadata":{},"source":["### imports\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import sys\nsys.path.insert(0, '/home/leon/tmp/rnn_numba') # put here the path to the repo\nfrom src.model.rate_model import Network"]},{"cell_type":"markdown","metadata":{},"source":["### Single trial\n\n"]},{"cell_type":"markdown","metadata":{},"source":["#### Simulation\n\n"]},{"cell_type":"markdown","metadata":{},"source":["To run a simulation, first we need to define a network model.\nThe class Network takes two arguments:\n\n1. the name of the configuration file that defines the model. \n This file is well detailed (check configbump.yml or configEI.yml)\n2. the name of the output file that will contain the simulation data.\n The model writes all relevant data to a single dataframe stored in an h5 format\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"Loading config from /home/leon/tmp/rnn_numba/conf/config_bump.yml\nSaving data to /home/leon/tmp/rnn_numba/data/simul/bump.h5\nJab [[-2.75]]\nTuning, KAPPA [0.4]\nAsymmetry, SIGMA [0.]\nIext [14.]"}],"source":["REPO_ROOT = \"/home/leon/tmp/rnn_numba\"\nmodel = Network('config_bump.yml', 'bump', REPO_ROOT, VERBOSE=1)"]},{"cell_type":"markdown","metadata":{},"source":["Then one just runs the model with\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"#+begin_example\n Generating matrix Cij\n all to all connectivity\n with cosine structure\n Saving matrix to /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Parameters:\n N 1000 Na [1000] K 1.0 Ka [1.]\n Iext [14.] Jab [-2.75]\n Tuning, KAPPA [0.4]\n Asymmetry, SIGMA [0.]\n MF Rates: [5.09090909]\n Transfert Func Sigmoid\n Running simulation\n times (s) 0.5 rates (Hz) [2.18]\n times (s) 1.0 rates (Hz) [2.19]\n STIM ON\n times (s) 1.5 rates (Hz) [6.25]\n STIM OFF\n times (s) 2.0 rates (Hz) [5.9]\n times (s) 2.5 rates (Hz) [5.91]\n times (s) 3.0 rates (Hz) [5.87]\n times (s) 3.5 rates (Hz) [5.87]\n times (s) 4.0 rates (Hz) [5.89]\n saving data to /home/leon/tmp/rnn_numba/data/simul/bump.h5\n Elapsed (with compilation) = 7.23014812899055s\n#+end_example"}],"source":["model.run()"]},{"cell_type":"markdown","metadata":{},"source":["#### Analysis\n\n"]},{"cell_type":"markdown","metadata":{},"source":["##### Imports\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import pandas as pd\nfrom src.analysis.decode import decode_bump"]},{"cell_type":"markdown","metadata":{},"source":["##### Load data\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"rates ff h_E neurons time\n0 2.512678 -11.005349 -5.810748 0 0.499\n1 1.003620 -0.271863 -5.810921 1 0.499\n2 4.395283 4.921598 -5.811103 2 0.499\n3 1.868867 -2.958338 -5.811292 3 0.499\n4 2.314441 -5.003102 -5.811489 4 0.499"}],"source":["df = pd.read_hdf(REPO_ROOT + \"/data/simul/bump.h5\", mode=\"r\") \nprint(df.head())"]},{"cell_type":"markdown","metadata":{},"source":["##### Rates\n\n"]},{"cell_type":"markdown","metadata":{},"source":["###### raster\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots()\npt = pd.pivot_table(df, values=\"rates\", index=[\"neurons\"], columns=\"time\")\n\nsns.heatmap(pt, cmap=\"jet\", ax=ax, vmax=15, vmin=0)\nax.set_yticks([0, 500, 1000], [0, 500, 1000])\nax.set_xticks([0, 2, 4, 6, 8], [0, 1, 2, 3, 4])\nax.set_title('Excitatory')\n\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["###### histograms\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["mean_df = df.groupby(\"neurons\").mean()\nmean_df[mean_df.rates<.01] = np.nan\n\nsns.histplot(mean_df_E, x=mean_df_E.rates, kde=True, color='r')\nplt.xlabel(\"Rates (au)\")\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["##### Tuning\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"time m0 m1 phase\n0 0.499 2.182644 0.170818 0.151626\n1 0.999 2.189366 0.052484 2.583821\n2 1.499 6.248643 7.171486 3.136531\n3 1.999 5.900416 5.401989 3.128763\n4 2.499 5.910800 5.532978 3.094187"}],"source":["data = df.groupby(['time'])['rates'].apply(decode_bump).reset_index()\ndata[['m0', 'm1', 'phase']] = pd.DataFrame(data['rates'].tolist(), index=data.index)\ndata = data.drop(columns=['rates'])\n\nprint(data.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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ax = plt.subplots(1, 3, figsize=[2*width, height])\n\nsns.lineplot(data=data, x='time', y='m0', legend=False, lw=2, ax=ax[0])\nax[0].set_xlabel('Time (s)')\nax[0].set_ylabel('$\\mathcal{F}_0 (Hz)$')\nax[1].set_xticks([0, 1, 2, 3, 4])\n\nsns.lineplot(x=data['time'], y=data['m1']/data['m0'], legend=False, lw=2, ax=ax[1])\nax[1].set_xlabel('Time (s)')\nax[1].set_ylabel('$\\mathcal{F}_1 / \\mathcal{F}_0$')\nax[1].set_xticks([0, 1, 2, 3, 4])\n\nsns.lineplot(x=data['time'], y=data['phase']*180/np.pi, legend=False, lw=2, ax=ax[2])\nax[2].set_xlabel('Time (s)')\nax[2].set_ylabel('$\\phi$ (°)')\nax[2].set_xticks([0, 1, 2, 3, 4])\nax[2].set_yticks([0, 90, 180, 270, 360])\nplt.show()"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":[""]},{"cell_type":"markdown","metadata":{},"source":["### Multiple trials\n\n"]},{"cell_type":"markdown","metadata":{},"source":["#### Simulations\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"#+begin_example\n ##########################################\n trial 1\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_1.h5\n Generating matrix Cij\n Saving matrix to /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 53.97293146402808s\n ##########################################\n trial 2\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_2.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 56.96205114200711s\n ##########################################\n trial 3\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_3.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 46.552777758974116s\n ##########################################\n trial 4\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_4.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 57.053969001048245s\n ##########################################\n trial 5\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_5.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 54.42072479397757s\n ##########################################\n trial 6\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_6.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 50.73790435300907s\n ##########################################\n trial 7\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_7.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 51.30651221697917s\n ##########################################\n trial 8\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_8.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 48.36234194302233s\n ##########################################\n trial 9\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_9.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 52.83128838700941s\n#+end_example"}],"source":["ini_list = np.arange(1, 10)\n\nREPO_ROOT = \"/home/leon/tmp/rnn_numba\"\n\nIF_LOAD_MAT = 0\nIF_SAVE_MAT = 1\n\nfor ini in ini_list:\n print('##########################################')\n print(\"trial\", ini)\n print('##########################################')\n\n model = Network('config_EI.yml', 'bump_ini_%d' % ini, REPO_ROOT,\n IF_LOAD_MAT=IF_LOAD_MAT, IF_SAVE_MAT=IF_SAVE_MAT)\n\n model.run()\n\n IF_LOAD_MAT = 1\n IF_SAVE_MAT = 0"]},{"cell_type":"markdown","metadata":{},"source":["#### Analysis\n\n"]},{"cell_type":"markdown","metadata":{},"source":["##### Imports\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import pandas as pd\nfrom src.analysis.decode import decode_bump"]},{"cell_type":"markdown","metadata":{},"source":["##### Load data\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"rates ff h_E h_I neurons time trial\n0 0.620963 17.178619 7.837148 -24.014507 0 0.499 1\n1 0.348972 19.188986 8.049864 -25.528297 1 0.499 1\n2 0.044523 18.140488 8.291198 -27.459217 2 0.499 1\n3 0.051996 17.061010 7.774259 -26.545981 3 0.499 1\n4 0.396972 16.060816 8.087732 -25.197549 4 0.499 1"}],"source":["ini_list = np.arange(1, 10)\n\ndf_list = []\n\nfor ini in ini_list:\n df_i = pd.read_hdf(REPO_ROOT + \"/data/simul/bump_ini_%d.h5\" % ini, mode=\"r\")\n df_i['trial'] = ini\n df_list.append(df_i)\n\ndf = pd.concat(df_list, ignore_index=True)\nprint(df.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"time trial m0 m1 phase\n0 0.499 1 0.310010 0.436322 1.350543\n1 0.499 2 0.309471 0.435234 1.345035\n2 0.499 3 0.309075 0.434342 1.501287\n3 0.499 4 0.308214 0.433595 1.501947\n4 0.499 5 0.309797 0.435703 1.300236"}],"source":["data = df.groupby(['time', 'trial'])['rates'].apply(decode_bump).reset_index()\ndata[['m0', 'm1', 'phase']] = pd.DataFrame(data['rates'].tolist(), index=data.index)\ndata = data.drop(columns=['rates'])\nprint(data.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"time trial m0 m1 phase\n63 3.999 1 0.305413 0.429020 2.379814\n64 3.999 2 0.306242 0.430313 2.387125\n65 3.999 3 0.305628 0.429620 2.393247\n66 3.999 4 0.304745 0.428685 2.389969\n67 3.999 5 0.305512 0.429292 2.385865"}],"source":["end_point = data[data.time == data.time.iloc[-1]]\nprint(end_point.head())"]},{"cell_type":"markdown","metadata":{},"source":["##### Phases\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(1, 2, figsize=[2*width, height])\n\nsns.lineplot(data=data, x='time', y=data['phase']*180/np.pi, legend=False, lw=2, ax=ax[0], hue='trial')\nax[0].set_xlabel('Time (s)')\nax[0].set_ylabel('$\\phi$ (°)')\nax[0].set_xticks([0, 1, 2, 3, 4])\nax[0].set_yticks([0, 90, 180, 270, 360])\n\nsns.histplot(data=end_point, x=end_point['phase']*180/np.pi, legend=False, ax=ax[1], bins='auto', kde=True)\nax[1].set_xlabel('$\\phi$ (°)')\nax[1].set_ylabel('$Count$')\n# ax[1].set_xticks([0, 90, 180, 270, 360])\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["##### Precision Errors\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"#+begin_example\n time trial m0 m1 phase accuracy precision\n 63 3.999 1 0.305413 0.429020 2.379814 -0.761779 -0.000976\n 64 3.999 2 0.306242 0.430313 2.387125 -0.754468 0.006335\n 65 3.999 3 0.305628 0.429620 2.393247 -0.748345 0.012458\n 66 3.999 4 0.304745 0.428685 2.389969 -0.751623 0.009180\n 67 3.999 5 0.305512 0.429292 2.385865 -0.755728 0.005076\n /tmp/ipykernel_2966984/1857574883.py:4: SettingWithCopyWarning: \n A value is trying to be set on a copy of a slice from a DataFrame.\n Try using .loc[row_indexer,col_indexer] = value instead\n\n See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n end_point['accuracy'] = end_point.phase - stim_phase\n /tmp/ipykernel_2966984/1857574883.py:5: SettingWithCopyWarning: \n A value is trying to be set on a copy of a slice from a DataFrame.\n Try using .loc[row_indexer,col_indexer] = value instead\n\n See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n end_point['precision'] = end_point.phase - circmean(end_point.phase)\n#+end_example"}],"source":["from scipy.stats import circmean\nstim_phase = np.pi\n\nend_point['accuracy'] = end_point.phase - stim_phase\nend_point['precision'] = end_point.phase - circmean(end_point.phase)\nprint(end_point.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(1, 2, figsize=[2*width, height])\n\nsns.histplot(data=end_point, x=end_point['accuracy']*180/np.pi, legend=False, lw=2, ax=ax[0])\nax[0].set_xlabel('$\\phi - \\phi_{stim}$ (°)')\nax[0].set_ylabel('Count')\n\nsns.histplot(data=end_point, x=end_point['precision']*180/np.pi, legend=False, ax=ax[1], bins='auto', kde=True)\nax[1].set_xlabel('$\\phi - <\\phi>_{trials}$ (°)')\nax[1].set_ylabel('$Count$')\n\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["## Balanced EI Bump Attractor Model\n\n"]},{"cell_type":"markdown","metadata":{},"source":["### imports\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import sys\nsys.path.insert(0, '/home/leon/tmp/rnn_numba') # put here the path to the repo\nfrom src.model.rate_model import Network"]},{"cell_type":"markdown","metadata":{},"source":["### Single trial\n\n"]},{"cell_type":"markdown","metadata":{},"source":["#### Simulation\n\n"]},{"cell_type":"markdown","metadata":{},"source":["To run a simulation, first we need to define a network model.\nThe class Network takes two arguments:\n\n1. the name of the configuration file that defines the model. \n This file is well detailed (check configbump.yml or configEI.yml)\n2. the name of the output file that will contain the simulation data.\n The model writes all relevant data to a single dataframe stored in an h5 format\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\nSaving data to /home/leon/tmp/rnn_numba/data/simul/bump.h5\nJab [[ 1. -1.5]\n [ 1. -1. ]]\nTuning, KAPPA [5. 0. 0. 0.]\nAsymmetry, SIGMA [0. 0. 0. 0.]\nIext [0.5 0.25]"}],"source":["REPO_ROOT = \"/home/leon/tmp/rnn_numba\"\nmodel = Network('config_EI.yml', 'bump', REPO_ROOT, VERBOSE=1 , M0=1)"]},{"cell_type":"markdown","metadata":{},"source":["Then one just runs the model with\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"#+begin_example\n Generating matrix Cij\n sparse connectivity\n with spec cosine structure\n sparse connectivity\n sparse connectivity\n sparse connectivity\n Saving matrix to /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Parameters:\n N 10000 Na [7500 2500] K 500.0 Ka [500. 500.]\n Iext [11.18033989 5.59016994] Jab [ 0.04472136 -0.06708204 0.04472136 -0.04472136]\n Tuning, KAPPA [5. 0. 0. 0.]\n Asymmetry, SIGMA [0. 0. 0. 0.]\n MF Rates: [0.25 0.5 ]\n Transfert Func Sigmoid\n Running simulation\n times (s) 0.25 rates (Hz) [0.0, 0.29]\n times (s) 0.5 rates (Hz) [0.0, 0.29]\n times (s) 0.75 rates (Hz) [0.0, 0.29]\n times (s) 1.0 rates (Hz) [0.0, 0.29]\n STIM ON\n times (s) 1.25 rates (Hz) [0.54, 0.74]\n times (s) 1.5 rates (Hz) [0.54, 0.74]\n STIM OFF\n times (s) 1.75 rates (Hz) [0.37, 0.6]\n times (s) 2.0 rates (Hz) [0.37, 0.6]\n times (s) 2.25 rates (Hz) [0.37, 0.6]\n times (s) 2.5 rates (Hz) [0.37, 0.6]\n times (s) 2.75 rates (Hz) [0.37, 0.6]\n times (s) 3.0 rates (Hz) [0.37, 0.6]\n times (s) 3.25 rates (Hz) [0.37, 0.6]\n times (s) 3.5 rates (Hz) [0.37, 0.6]\n times (s) 3.75 rates (Hz) [0.37, 0.6]\n times (s) 4.0 rates (Hz) [0.37, 0.6]\n saving data to /home/leon/tmp/rnn_numba/data/simul/bump.h5\n Elapsed (with compilation) = 55.362914263037965s\n#+end_example"}],"source":["model.run()"]},{"cell_type":"markdown","metadata":{},"source":["#### Analysis\n\n"]},{"cell_type":"markdown","metadata":{},"source":["##### Imports\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import pandas as pd\nfrom src.analysis.decode import decode_bump"]},{"cell_type":"markdown","metadata":{},"source":["##### Load data\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"rates ff h_E h_I neurons time\n0 1.603719e-14 -1.237244 1.555830e-10 -9.824757 0 0.249\n1 1.068644e-15 -0.286277 2.175872e-10 -10.012830 1 0.249\n2 5.164796e-14 1.380938 3.022810e-10 -9.672483 2 0.249\n3 2.162490e-15 0.181033 7.054538e-11 -9.582123 3 0.249\n4 1.895197e-13 0.603522 2.518099e-10 -9.404711 4 0.249"}],"source":["df = pd.read_hdf(REPO_ROOT + \"/data/simul/bump.h5\", mode=\"r\")\ndf_E = df[df.neurons<7500]\ndf_I = df[df.neurons>=7500]\n\nprint(df.head())"]},{"cell_type":"markdown","metadata":{},"source":["##### Rates\n\n"]},{"cell_type":"markdown","metadata":{},"source":["###### raster\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(1, 2, figsize=[2*width, height])\npt = pd.pivot_table(df, values=\"rates\", index=[\"neurons\"], columns=\"time\")\n\nsns.heatmap(pt[:7500], cmap=\"jet\", ax=ax[0], vmax=1, vmin=0)\nax[0].set_yticks([0, 2500, 5000, 7500], [0, 2500, 5000, 7500])\nax[0].set_xticks([0, 2, 4, 6, 8], [0, 1, 2, 3, 4])\nax[0].set_title('Excitatory')\n\nsns.heatmap(pt[7500:], cmap=\"jet\", ax=ax[1], vmax=1, vmin=0)\nax[1].set_yticks([0, 625, 1250, 1875, 2500], [0, 625, 1250, 1875, 2500])\nax[1].set_xticks([0, 2, 4, 6, 8], [0, 1, 2, 3, 4])\nax[1].set_title('Inhibitory')\n\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["###### histograms\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["mean_df_E = df_E.groupby(\"neurons\").mean()\nmean_df_E[mean_df_E.rates<.01] = np.nan\n\nmean_df_I = df_I.groupby(\"neurons\").mean()\nmean_df_I[mean_df_I.rates<.01] = np.nan\n\nsns.histplot(mean_df_E, x=mean_df_E.rates, kde=True, color='r', label='E')\nsns.histplot(mean_df_I, x=mean_df_I.rates, kde=True, color='b', label='I')\nplt.legend(fontsize=12)\nplt.xlabel(\"Rates (au)\")\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["##### Tuning\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"time m0 m1 phase\n0 0.249 1.971564e-11 1.996778e-11 4.101198\n1 0.499 9.912278e-12 3.949440e-12 0.031584\n2 0.749 8.105434e-11 1.410955e-10 4.814738\n3 0.999 7.173168e-12 3.755936e-12 0.843219\n4 1.249 5.370993e-01 5.969055e-01 3.144594"}],"source":["data = df_E.groupby(['time'])['rates'].apply(decode_bump).reset_index()\ndata[['m0', 'm1', 'phase']] = pd.DataFrame(data['rates'].tolist(), index=data.index)\ndata = data.drop(columns=['rates'])\n\nprint(data.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(1, 3, figsize=[2*width, height])\n\nsns.lineplot(data=data, x='time', y='m0', legend=False, lw=2, ax=ax[0])\nax[0].set_xlabel('Time (s)')\nax[0].set_ylabel('$\\mathcal{F}_0 (Hz)$')\nax[1].set_xticks([0, 1, 2, 3, 4])\n\nsns.lineplot(x=data['time'], y=data['m1']/data['m0'], legend=False, lw=2, ax=ax[1])\nax[1].set_xlabel('Time (s)')\nax[1].set_ylabel('$\\mathcal{F}_1 / \\mathcal{F}_0$')\nax[1].set_xticks([0, 1, 2, 3, 4])\n\nsns.lineplot(x=data['time'], y=data['phase']*180/np.pi, legend=False, lw=2, ax=ax[2])\nax[2].set_xlabel('Time (s)')\nax[2].set_ylabel('$\\phi$ (°)')\nax[2].set_xticks([0, 1, 2, 3, 4])\nax[2].set_yticks([0, 90, 180, 270, 360])\nplt.show()"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":[""]},{"cell_type":"markdown","metadata":{},"source":["#### Parameter search\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"#+begin_example\n [0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1. ]\n ##########################################\n Ie 0.1\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.1.h5\n Generating matrix Cij\n Saving matrix to /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 57.59470825298922s\n ##########################################\n Ie 0.2\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.2.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 58.72569092398044s\n ##########################################\n Ie 0.30000000000000004\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.3.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 58.357797659002244s\n ##########################################\n Ie 0.4\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.4.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 58.12026895402232s\n ##########################################\n Ie 0.5\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.5.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 58.90326176898088s\n ##########################################\n Ie 0.6\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.6.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 58.6129756779992s\n ##########################################\n Ie 0.7000000000000001\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.7.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 58.70668443996692s\n ##########################################\n Ie 0.8\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.8.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 53.72524890798377s\n ##########################################\n Ie 0.9\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_0.9.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 57.952931727981195s\n ##########################################\n Ie 1.0\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_Ie_1.0.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 57.457209688960575s\n#+end_example"}],"source":["Ie_list = np.linspace(0.1, 1, 10)\nprint(Ie_list)\n\nREPO_ROOT = \"/home/leon/tmp/rnn_numba\"\n\nIF_LOAD_MAT = 0\nIF_SAVE_MAT = 1\n\nfor Ie in Ie_list:\n print('##########################################')\n print(\"Ie\", Ie)\n print('##########################################')\n\n model = Network('config_EI.yml', 'bump_Ie_%.1f' % Ie, REPO_ROOT,\n IF_LOAD_MAT=IF_LOAD_MAT, IF_SAVE_MAT=IF_SAVE_MAT,\n Gain=Ie)\n\n model.run()\n\n IF_LOAD_MAT = 1\n IF_SAVE_MAT = 0"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"rates ff h_E h_I neurons time Ie\n0 0.368926 12.781403 9.071170 -20.381302 0 0.249 0\n1 0.548235 12.137876 8.606775 -19.757314 1 0.249 0\n2 0.791355 12.516987 8.236397 -18.628502 2 0.249 0\n3 0.659268 10.232158 8.340149 -19.042084 3 0.249 0\n4 0.235941 8.420432 8.426077 -20.439227 4 0.249 0"}],"source":["Ie_list = np.linspace(0.1, 1.0, 10)\n\ndf_list = []\n\nfor i in range(Ie_list.shape[0]):\n df_i = pd.read_hdf(REPO_ROOT + \"/data/simul/bump_Ie_%.1f.h5\" % Ie_list[i], mode=\"r\")\n df_i['Ie'] = i\n df_list.append(df_i)\n\ndf = pd.concat(df_list, ignore_index=True)\ndf_E = df[df.neurons<7500]\nprint(df.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["trial = 0\nfig, ax = plt.subplots(1, 2, figsize=[2*width, height])\npt = pd.pivot_table(df[df.Ie==trial], values=\"rates\", index=[\"neurons\"], columns=\"time\")\n\nsns.heatmap(pt[:7500], cmap=\"jet\", ax=ax[0], vmax=1, vmin=0)\nax[0].set_yticks([0, 2500, 5000, 7500], [0, 2500, 5000, 7500])\nax[0].set_xticks([0, 2, 4, 6, 8], [0, 1, 2, 3, 4])\nax[0].set_title('Excitatory')\n\nsns.heatmap(pt[7500:], cmap=\"jet\", ax=ax[1], vmax=1, vmin=0)\nax[1].set_yticks([0, 625, 1250, 1875, 2500], [0, 625, 1250, 1875, 2500])\nax[1].set_xticks([0, 2, 4, 6, 8], [0, 1, 2, 3, 4])\nax[1].set_title('Inhibitory')\n\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["### Multiple trials\n\n"]},{"cell_type":"markdown","metadata":{},"source":["#### Simulations\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"#+begin_example\n ##########################################\n trial 1\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_1.h5\n Generating matrix Cij\n Saving matrix to /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 53.97293146402808s\n ##########################################\n trial 2\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_2.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 56.96205114200711s\n ##########################################\n trial 3\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_3.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 46.552777758974116s\n ##########################################\n trial 4\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_4.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 57.053969001048245s\n ##########################################\n trial 5\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_5.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 54.42072479397757s\n ##########################################\n trial 6\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_6.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 50.73790435300907s\n ##########################################\n trial 7\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_7.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 51.30651221697917s\n ##########################################\n trial 8\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_8.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 48.36234194302233s\n ##########################################\n trial 9\n ##########################################\n Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\n Saving data to /home/leon/tmp/rnn_numba/data/simul/bump_ini_9.h5\n Loading matrix from /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Running simulation\n Elapsed (with compilation) = 52.83128838700941s\n#+end_example"}],"source":["ini_list = np.arange(1, 10)\n\nREPO_ROOT = \"/home/leon/tmp/rnn_numba\"\n\nIF_LOAD_MAT = 0\nIF_SAVE_MAT = 1\n\nfor ini in ini_list:\n print('##########################################')\n print(\"trial\", ini)\n print('##########################################')\n\n model = Network('config_EI.yml', 'bump_ini_%d' % ini, REPO_ROOT,\n IF_LOAD_MAT=IF_LOAD_MAT, IF_SAVE_MAT=IF_SAVE_MAT)\n\n model.run()\n\n IF_LOAD_MAT = 1\n IF_SAVE_MAT = 0"]},{"cell_type":"markdown","metadata":{},"source":["#### Analysis\n\n"]},{"cell_type":"markdown","metadata":{},"source":["##### Imports\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import pandas as pd\nfrom src.analysis.decode import decode_bump"]},{"cell_type":"markdown","metadata":{},"source":["##### Load data\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"rates ff h_E h_I neurons time trial\n0 0.620963 17.178619 7.837148 -24.014507 0 0.499 1\n1 0.348972 19.188986 8.049864 -25.528297 1 0.499 1\n2 0.044523 18.140488 8.291198 -27.459217 2 0.499 1\n3 0.051996 17.061010 7.774259 -26.545981 3 0.499 1\n4 0.396972 16.060816 8.087732 -25.197549 4 0.499 1"}],"source":["ini_list = np.arange(1, 10)\n\ndf_list = []\n\nfor ini in ini_list:\n df_i = pd.read_hdf(REPO_ROOT + \"/data/simul/bump_ini_%d.h5\" % ini, mode=\"r\")\n df_i['trial'] = ini\n df_list.append(df_i)\n\ndf = pd.concat(df_list, ignore_index=True)\ndf_E = df[df.neurons<7500]\nprint(df.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"time trial m0 m1 phase\n0 0.499 1 0.310010 0.436322 1.350543\n1 0.499 2 0.309471 0.435234 1.345035\n2 0.499 3 0.309075 0.434342 1.501287\n3 0.499 4 0.308214 0.433595 1.501947\n4 0.499 5 0.309797 0.435703 1.300236"}],"source":["data = df_E.groupby(['time', 'trial'])['rates'].apply(decode_bump).reset_index()\ndata[['m0', 'm1', 'phase']] = pd.DataFrame(data['rates'].tolist(), index=data.index)\ndata = data.drop(columns=['rates'])\nprint(data.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"time trial m0 m1 phase\n63 3.999 1 0.305413 0.429020 2.379814\n64 3.999 2 0.306242 0.430313 2.387125\n65 3.999 3 0.305628 0.429620 2.393247\n66 3.999 4 0.304745 0.428685 2.389969\n67 3.999 5 0.305512 0.429292 2.385865"}],"source":["end_point = data[data.time == data.time.iloc[-1]]\nprint(end_point.head())"]},{"cell_type":"markdown","metadata":{},"source":["##### Phases\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(1, 2, figsize=[2*width, height])\n\nsns.lineplot(data=data, x='time', y=data['phase']*180/np.pi, legend=False, lw=2, ax=ax[0], hue='trial')\nax[0].set_xlabel('Time (s)')\nax[0].set_ylabel('$\\phi$ (°)')\nax[0].set_xticks([0, 1, 2, 3, 4])\nax[0].set_yticks([0, 90, 180, 270, 360])\n\nsns.histplot(data=end_point, x=end_point['phase']*180/np.pi, legend=False, ax=ax[1], bins='auto', kde=True)\nax[1].set_xlabel('$\\phi$ (°)')\nax[1].set_ylabel('$Count$')\n# ax[1].set_xticks([0, 90, 180, 270, 360])\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["##### Precision Errors\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"#+begin_example\n time trial m0 m1 phase accuracy precision\n 63 3.999 1 0.305413 0.429020 2.379814 -0.761779 -0.000976\n 64 3.999 2 0.306242 0.430313 2.387125 -0.754468 0.006335\n 65 3.999 3 0.305628 0.429620 2.393247 -0.748345 0.012458\n 66 3.999 4 0.304745 0.428685 2.389969 -0.751623 0.009180\n 67 3.999 5 0.305512 0.429292 2.385865 -0.755728 0.005076\n /tmp/ipykernel_2966984/1857574883.py:4: SettingWithCopyWarning: \n A value is trying to be set on a copy of a slice from a DataFrame.\n Try using .loc[row_indexer,col_indexer] = value instead\n\n See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n end_point['accuracy'] = end_point.phase - stim_phase\n /tmp/ipykernel_2966984/1857574883.py:5: SettingWithCopyWarning: \n A value is trying to be set on a copy of a slice from a DataFrame.\n Try using .loc[row_indexer,col_indexer] = value instead\n\n See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n end_point['precision'] = end_point.phase - circmean(end_point.phase)\n#+end_example"}],"source":["from scipy.stats import circmean\nstim_phase = np.pi\n\nend_point['accuracy'] = end_point.phase - stim_phase\nend_point['precision'] = end_point.phase - circmean(end_point.phase)\nprint(end_point.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(1, 2, figsize=[2*width, height])\n\nsns.histplot(data=end_point, x=end_point['accuracy']*180/np.pi, legend=False, lw=2, ax=ax[0])\nax[0].set_xlabel('$\\phi - \\phi_{stim}$ (°)')\nax[0].set_ylabel('Count')\n\nsns.histplot(data=end_point, x=end_point['precision']*180/np.pi, legend=False, ax=ax[1], bins='auto', kde=True)\nax[1].set_xlabel('$\\phi - <\\phi>_{trials}$ (°)')\nax[1].set_ylabel('$Count$')\n\nplt.show()"]}],"metadata":{"org":null,"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.5.2"}},"nbformat":4,"nbformat_minor":0} diff --git a/org/EI_bal.ipynb b/org/EI_bal.ipynb deleted file mode 100644 index ffbf05e..0000000 --- a/org/EI_bal.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"cell_type":"markdown","metadata":{},"source":"EI Bump Attractor Network Model\n===============================\n\n"},{"cell_type":"markdown","metadata":{},"source":["## notebook settings\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"The autoreload extension is already loaded. To reload it, use:\n %reload_ext autoreload\nPython exe\n/home/leon/mambaforge/envs/dual_data/bin/python"}],"source":["%load_ext autoreload\n%autoreload 2\n%reload_ext autoreload\n\n%run ../notebooks/setup.py\n%matplotlib inline\n%config InlineBackend.figure_format = 'png'"]},{"cell_type":"markdown","metadata":{},"source":["## EI Balanced Attractor Model\n\n"]},{"cell_type":"markdown","metadata":{},"source":["Here I implemented a balanced EI network that exhibits attractor dynamics.\n\n"]},{"cell_type":"markdown","metadata":{},"source":["### imports\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import sys\nsys.path.insert(0, '/home/leon/tmp/rnn_numba') # put here the path to the repo\nfrom src.model.rate_model import Network"]},{"cell_type":"markdown","metadata":{},"source":["### Single trial\n\n"]},{"cell_type":"markdown","metadata":{},"source":["#### Simulation\n\n"]},{"cell_type":"markdown","metadata":{},"source":["To run a simulation, first we need to define a network model.\nThe class Network takes three mandatory arguments:\n\n1. The name of the configuration file that defines the model,\n eg 'configEI.yml', these files are in ../conf/ and well detailed.\n\n2. The name of the output file that will contain the simulation data.\n eg 'bump'. Simulation results will be saved as a data frame to '../data/simul/bump.h5'.\n\n3. The path to the root of this repository.\n\nOne can also pass extra arguments to Network, basically any parameter that is in the config file so that it will be overwritten.\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"Loading config from /home/leon/tmp/rnn_numba/conf/config_EI.yml\nSaving data to /home/leon/tmp/rnn_numba/data/simul/bump.h5\nJab [[ 1. -1.5]\n [ 1. -1. ]]\nTuning, KAPPA [5. 0. 0. 0.]\nAsymmetry, SIGMA [0. 0. 0. 0.]\nIext [0.5 0.25]"}],"source":["REPO_ROOT = \"/home/leon/tmp/rnn_numba\"\nmodel = Network('config_EI.yml', 'bump', REPO_ROOT, VERBOSE=1)"]},{"cell_type":"markdown","metadata":{},"source":["Then one just runs the model with\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"#+begin_example\n Generating matrix Cij\n sparse connectivity\n with spec cosine structure\n sparse connectivity\n sparse connectivity\n sparse connectivity\n Saving matrix to /home/leon/tmp/rnn_numba/data/matrix/Cij.npy\n Parameters:\n N 10000 Na [7500 2500] K 500.0 Ka [500. 500.]\n Iext [11.18033989 5.59016994] Jab [ 0.04472136 -0.06708204 0.04472136 -0.04472136]\n Tuning, KAPPA [5. 0. 0. 0.]\n Asymmetry, SIGMA [0. 0. 0. 0.]\n MF Rates: [0.25 0.5 ]\n Transfert Func Sigmoid\n Running simulation\n times (s) 0.25 rates (Hz) [0.03, 0.12]\n times (s) 0.5 rates (Hz) [0.03, 0.12]\n times (s) 0.75 rates (Hz) [0.03, 0.11]\n times (s) 1.0 rates (Hz) [0.03, 0.12]\n STIM ON\n times (s) 1.25 rates (Hz) [0.53, 0.74]\n times (s) 1.5 rates (Hz) [0.53, 0.74]\n STIM OFF\n times (s) 1.75 rates (Hz) [0.36, 0.6]\n times (s) 2.0 rates (Hz) [0.36, 0.6]\n times (s) 2.25 rates (Hz) [0.36, 0.6]\n times (s) 2.5 rates (Hz) [0.36, 0.6]\n times (s) 2.75 rates (Hz) [0.36, 0.6]\n times (s) 3.0 rates (Hz) [0.36, 0.6]\n times (s) 3.25 rates (Hz) [0.36, 0.6]\n times (s) 3.5 rates (Hz) [0.36, 0.6]\n times (s) 3.75 rates (Hz) [0.36, 0.6]\n times (s) 4.0 rates (Hz) [0.36, 0.6]\n saving data to /home/leon/tmp/rnn_numba/data/simul/bump.h5\n Elapsed (with compilation) = 59.40574227599427s\n#+end_example"}],"source":["model.run()"]},{"cell_type":"markdown","metadata":{},"source":["#### Analysis\n\n"]},{"cell_type":"markdown","metadata":{},"source":["##### Imports\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import pandas as pd\nfrom src.analysis.decode import decode_bump"]},{"cell_type":"markdown","metadata":{},"source":["##### Load data\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"rates ff h_E h_I neurons time\n0 0.016484 0.516858 0.660207 -4.258005 0 0.249\n1 0.010508 0.068475 0.606468 -4.101016 1 0.249\n2 0.039072 0.148301 0.625659 -3.540477 2 0.249\n3 0.033662 1.185190 0.600276 -3.787884 3 0.249\n4 0.044454 -0.488017 0.634493 -3.749277 4 0.249"}],"source":["df = pd.read_hdf(REPO_ROOT + \"/data/simul/bump.h5\", mode=\"r\")\ndf_E = df[df.neurons<7500]\ndf_I = df[df.neurons>=7500]\n\nprint(df.head())"]},{"cell_type":"markdown","metadata":{},"source":["##### Rates\n\n"]},{"cell_type":"markdown","metadata":{},"source":["###### raster\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(1, 2, figsize=[2*width, height])\npt = pd.pivot_table(df, values=\"rates\", index=[\"neurons\"], columns=\"time\")\n\nsns.heatmap(pt[:7500], cmap=\"jet\", ax=ax[0], vmax=1, vmin=0)\nax[0].set_yticks([0, 2500, 5000, 7500], [0, 2500, 5000, 7500])\nax[0].set_xticks([0, 2, 4, 6, 8], [0, 1, 2, 3, 4])\nax[0].set_title('Excitatory')\n\nsns.heatmap(pt[7500:], cmap=\"jet\", ax=ax[1], vmax=1, vmin=0)\nax[1].set_yticks([0, 625, 1250, 1875, 2500], [0, 625, 1250, 1875, 2500])\nax[1].set_xticks([0, 2, 4, 6, 8], [0, 1, 2, 3, 4])\nax[1].set_title('Inhibitory')\n\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["###### histograms\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["mean_df_E = df_E.groupby(\"neurons\").mean()\nmean_df_E[mean_df_E.rates<.001] = np.nan\n\nmean_df_I = df_I.groupby(\"neurons\").mean()\nmean_df_I[mean_df_I.rates<.001] = np.nan\n\nsns.histplot(mean_df_E, x=mean_df_E.rates, kde=True, color='r', label='E')\nsns.histplot(mean_df_I, x=mean_df_I.rates, kde=True, color='b', label='I')\nplt.legend(fontsize=12)\nplt.xlabel(\"Rates (au)\")\nplt.show()"]},{"cell_type":"markdown","metadata":{},"source":["##### Tuning\n\n"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":"time m0 m1 phase\n0 0.249 0.026883 0.000102 6.019133\n1 0.499 0.026896 0.000113 3.882348\n2 0.749 0.026606 0.000504 0.829742\n3 0.999 0.027251 0.000305 2.127723\n4 1.249 0.534482 0.597531 3.139320"}],"source":["data = df_E.groupby(['time'])['rates'].apply(decode_bump).reset_index()\ndata[['m0', 'm1', 'phase']] = pd.DataFrame(data['rates'].tolist(), index=data.index)\ndata = data.drop(columns=['rates'])\n\nprint(data.head())"]},{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":""},"metadata":{},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(1, 3, figsize=[2*width, height])\n\nsns.lineplot(data=data, x='time', y='m0', legend=False, lw=2, ax=ax[0])\nax[0].set_xlabel('Time (s)')\nax[0].set_ylabel('$\\mathcal{F}_0 (Hz)$')\nax[1].set_xticks([0, 1, 2, 3, 4])\n\nsns.lineplot(x=data['time'], y=data['m1']/data['m0'], legend=False, lw=2, ax=ax[1])\nax[1].set_xlabel('Time (s)')\nax[1].set_ylabel('$\\mathcal{F}_1 / \\mathcal{F}_0$')\nax[1].set_xticks([0, 1, 2, 3, 4])\n\nsns.lineplot(x=data['time'], y=data['phase']*180/np.pi, legend=False, lw=2, ax=ax[2])\nax[2].set_xlabel('Time (s)')\nax[2].set_ylabel('$\\phi$ (°)')\nax[2].set_xticks([0, 1, 2, 3, 4])\nax[2].set_yticks([0, 90, 180, 270, 360])\nplt.show()"]}],"metadata":{"org":null,"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.5.2"}},"nbformat":4,"nbformat_minor":0}