{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d6a066dd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-09T12:20:26.286224Z",
     "iopub.status.busy": "2021-06-09T12:20:26.285751Z",
     "iopub.status.idle": "2021-06-09T12:20:26.315070Z",
     "shell.execute_reply": "2021-06-09T12:20:26.313736Z",
     "shell.execute_reply.started": "2021-06-09T12:20:26.286105Z"
    }
   },
   "outputs": [],
   "source": [
    "def minmax(x):\n",
    "    \"\"\"min max normalizes the given array\"\"\"\n",
    "    return (x - np.min(x))/(np.max(x)-np.min(x))\n",
    "\n",
    "def make_noise(num_traces=100,num_samples=4999):\n",
    "    \"\"\"Creates a noise trace used in generating spike rasters.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    num_traces : int, optional\n",
    "        number of noise traces to create (first dimension), by default 100\n",
    "    num_samples : int, optional\n",
    "        length of the trace (second dimension), by default 4999\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    np.array\n",
    "        noise trace\n",
    "    \"\"\"    \n",
    "    B = [0.049922035, -0.095993537, 0.050612699, -0.004408786]\n",
    "    A = [1, -2.494956002,   2.017265875,  -0.522189400]\n",
    "    invfn = np.zeros((num_traces,num_samples))\n",
    "    for i in np.arange(0,num_traces):\n",
    "        wn = np.random.normal(loc=1,\n",
    " \t\t\t   scale=0.5,size=num_samples+2000)\n",
    "        invfn[i,:] = minmax(ss.lfilter(B, A, wn)[2000:])+0.5                             # Create '1/f' Noise\n",
    "    return invfn\n",
    "\n",
    "def make_rhythmic_inh(writer, num_traces=100,T=1,DoM=0.1,f=8,P=0,C=[10.0,1.0],fs=1000):\n",
    "    \"\"\"Creates a sin wave trace used in generating spike rasters.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    num_traces : int, optional\n",
    "        number of noise traces to create (first dimension), by default 100\n",
    "    T : int, optional\n",
    "        length of the trace in seconds (second dimension), by default 5000\n",
    "    DoM : float, optional\n",
    "        depth of modulation = A/(A+C), by default 0.1\n",
    "    f : int, optional\n",
    "        frequency of sin wave in Hz, by default 8\n",
    "    P : int, optional\n",
    "        phase of sin wave, by default 0\n",
    "    C : List, optional\n",
    "        mean and std of offset (i.e. firing rate), by default [10.0, 1.0]\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    np.array\n",
    "        sin wave trace\n",
    "    \"\"\"\n",
    "    \n",
    "    t = np.arange(T * fs) / fs\n",
    "    fn = np.zeros((num_traces,T * fs))\n",
    "    for i in np.arange(0,num_traces):\n",
    "        offset = np.random.normal(C[0],C[1])\n",
    "        A = offset/((1/DoM)-1)\n",
    "        fn[i,:] = A*np.sin((2 * np.pi * f * t)+P) + offset\n",
    "        \n",
    "        rateProf=fn[i,:]\n",
    "        rateProf[rateProf<0] = 0#Can't have negate firing rates.\n",
    "    \n",
    "        normRateProf = rateProf\n",
    "\n",
    "\n",
    "        rate_temp=[];simSpks_temp=[]\n",
    "\n",
    "        rate_temp = normRateProf\n",
    "\n",
    "        numbPoints = scipy.stats.poisson(rate_temp/1000).rvs()#Poisson number of points\n",
    "\n",
    "        simSpks=np.where(numbPoints>0)[0]\n",
    "        \n",
    "        writer.append_repeat(ds = \"node_ids\", val=i, N=len(simSpks))\n",
    "        writer.append_ds(simSpks, \"timestamps\")\n",
    "    return fn\n",
    "\n",
    "class SonataWriter:\n",
    "    \"\"\"Class used to dynamically writing spike rasters to an h5 file.\n",
    "\n",
    "    Attributes\n",
    "    ----------\n",
    "    file : h5py.File\n",
    "        file object being worked on\n",
    "    group : h5py.Group\n",
    "        gropu where the datasets reside\n",
    "    datasets : dict\n",
    "        datasets that are saved to the file\n",
    "\n",
    "    Methods\n",
    "    -------\n",
    "    append_ds(vals, ds)\n",
    "        appends the given values to the end of the given dataset\n",
    "    append_repeat(ds, val, N)\n",
    "        appends the given value N times to the end of the given dataset\n",
    "    close()\n",
    "        close the h5py file\n",
    "    \"\"\"\n",
    "    def __init__(self, f_name, groups, datasets, types):\n",
    "        \"\"\"\n",
    "        Parameters\n",
    "        ----------\n",
    "        f_name : str\n",
    "            name of file location\n",
    "        groups : list\n",
    "            list of group names (str) that are layered into the h5py file\n",
    "            in the order given.\n",
    "        datasets : list\n",
    "            list of dataset names (str)\n",
    "        types : list\n",
    "            list of data types that corresponds to the datasets list\n",
    "        \"\"\"        \n",
    "        self.file = h5py.File(f_name, 'w')\n",
    "\n",
    "        self.group = self.file\n",
    "        for group in groups:\n",
    "            self.group = self.group.create_group(group)\n",
    "\n",
    "        self.datasets = {}\n",
    "        for i, ds in enumerate(datasets):\n",
    "            self.datasets[ds] = self.group.create_dataset(ds, data=[], dtype=types[i], chunks=True, maxshape=(None,))\n",
    "\n",
    "    def append_ds(self, vals, ds):\n",
    "        \"\"\"appends the given values to the end of the given dataset\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        vals : list\n",
    "            list of values to be appended to the dataset\n",
    "        ds : str\n",
    "            key of the dataset to append to\n",
    "        \"\"\"        \n",
    "        length = len(self.datasets[ds])\n",
    "        self.datasets[ds].resize((length + len(vals), ))\n",
    "        self.datasets[ds][length:] = vals\n",
    "\n",
    "    def append_repeat(self, ds, val, N):\n",
    "        \"\"\"appends the given value N times to the end of the given dataset\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        ds : str\n",
    "            key of the dataset to append to\n",
    "        val : [type]\n",
    "            value to be appended N times\n",
    "        N : int\n",
    "            number of vals to append to the dataset\n",
    "        \"\"\"        \n",
    "        self.append_ds([val for i in range(N)], ds)\n",
    "\n",
    "    def close(self):\n",
    "        \"\"\"Closes the h5py File\n",
    "        \"\"\"        \n",
    "        self.file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0ca5b4c5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-07T20:38:55.048723Z",
     "iopub.status.busy": "2021-06-07T20:38:55.048196Z",
     "iopub.status.idle": "2021-06-07T20:38:55.224445Z",
     "shell.execute_reply": "2021-06-07T20:38:55.223719Z",
     "shell.execute_reply.started": "2021-06-07T20:38:55.048666Z"
    }
   },
   "outputs": [],
   "source": [
    "writer = SonataWriter('rhythmic_inh.h5', [\"spikes\", \"prox_inh_stim\"], [\"timestamps\", \"node_ids\"], [np.float, np.int])\n",
    "f = make_rhythmic_inh(writer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "60a2bcfe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-07T20:38:56.795822Z",
     "iopub.status.busy": "2021-06-07T20:38:56.795352Z",
     "iopub.status.idle": "2021-06-07T20:38:57.036513Z",
     "shell.execute_reply": "2021-06-07T20:38:57.035882Z",
     "shell.execute_reply.started": "2021-06-07T20:38:56.795769Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fe150a90040>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(f[0,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8507e31d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-09T12:20:30.030413Z",
     "iopub.status.busy": "2021-06-09T12:20:30.029902Z",
     "iopub.status.idle": "2021-06-09T12:20:33.356033Z",
     "shell.execute_reply": "2021-06-09T12:20:33.355352Z",
     "shell.execute_reply.started": "2021-06-09T12:20:30.030356Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Matplotlib created a temporary config/cache directory at /tmp/matplotlib-aqi66ydf because the default path (/home/qs/.cache/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy\n",
    "import scipy.stats\n",
    "import h5py\n",
    "import scipy.signal as ss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "11f4bdc8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-09T12:20:59.093744Z",
     "iopub.status.busy": "2021-06-09T12:20:59.093280Z",
     "iopub.status.idle": "2021-06-09T12:20:59.102351Z",
     "shell.execute_reply": "2021-06-09T12:20:59.101210Z",
     "shell.execute_reply.started": "2021-06-09T12:20:59.093696Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2],\n",
       "       [0, 1, 2]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.tile(np.array([0,1,2]),(2,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "f1eb6ad3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-07T13:09:46.801466Z",
     "iopub.status.busy": "2021-06-07T13:09:46.800958Z",
     "iopub.status.idle": "2021-06-07T13:09:46.811045Z",
     "shell.execute_reply": "2021-06-07T13:09:46.809798Z",
     "shell.execute_reply.started": "2021-06-07T13:09:46.801409Z"
    }
   },
   "outputs": [],
   "source": [
    "DoM = .01\n",
    "A = C/((1/DoM)-1)\n",
    "f = 8\n",
    "t = np.arange(0,60,.001)\n",
    "P = 0\n",
    "C = 10\n",
    "W = A*np.sin(f*t+P) + C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "8059ca07",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-07T13:09:55.092622Z",
     "iopub.status.busy": "2021-06-07T13:09:55.092123Z",
     "iopub.status.idle": "2021-06-07T13:09:55.287307Z",
     "shell.execute_reply": "2021-06-07T13:09:55.286644Z",
     "shell.execute_reply.started": "2021-06-07T13:09:55.092568Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 10.0)"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(t,W)\n",
    "plt.xlim(0,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "4aea3e1e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-07T12:53:32.288789Z",
     "iopub.status.busy": "2021-06-07T12:53:32.288285Z",
     "iopub.status.idle": "2021-06-07T12:53:32.348107Z",
     "shell.execute_reply": "2021-06-07T12:53:32.347251Z",
     "shell.execute_reply.started": "2021-06-07T12:53:32.288733Z"
    }
   },
   "outputs": [],
   "source": [
    "rateProf=W\n",
    "rateProf[rateProf<0] = 0#Can't have negate firing rates.\n",
    "    \n",
    "normRateProf = rateProf\n",
    "\n",
    "numUnits = 10\n",
    "L = []\n",
    "for i in np.arange(0,numUnits):\n",
    "    rate_temp=[];simSpks_temp=[]\n",
    "\n",
    "    rate_temp = normRateProf\n",
    "    #rate_temp = normRateProf*dist()\n",
    "\n",
    "    numbPoints = scipy.stats.poisson(rate_temp/1000).rvs()#Poisson number of points\n",
    "\n",
    "    simSpks=np.where(numbPoints>0)[0]\n",
    "    L.append(simSpks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "7976f912",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-07T12:53:33.008931Z",
     "iopub.status.busy": "2021-06-07T12:53:33.008467Z",
     "iopub.status.idle": "2021-06-07T12:53:33.018161Z",
     "shell.execute_reply": "2021-06-07T12:53:33.016904Z",
     "shell.execute_reply.started": "2021-06-07T12:53:33.008880Z"
    }
   },
   "outputs": [],
   "source": [
    "flat_list = [item for sublist in L for item in sublist]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "cd701aca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-07T12:53:33.269957Z",
     "iopub.status.busy": "2021-06-07T12:53:33.269513Z",
     "iopub.status.idle": "2021-06-07T12:53:40.423078Z",
     "shell.execute_reply": "2021-06-07T12:53:40.422392Z",
     "shell.execute_reply.started": "2021-06-07T12:53:33.269907Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(flat_list,bins=np.arange(0,60000,10))\n",
    "plt.plot(np.arange(0,60000),W-C+1)\n",
    "plt.xlim(0,10000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "36066367",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-07T12:53:40.424161Z",
     "iopub.status.busy": "2021-06-07T12:53:40.424004Z",
     "iopub.status.idle": "2021-06-07T12:53:40.983450Z",
     "shell.execute_reply": "2021-06-07T12:53:40.982846Z",
     "shell.execute_reply.started": "2021-06-07T12:53:40.424143Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000.0, 20000.0)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(simSpks, 10*np.ones((simSpks.shape[0],)), '.')\n",
    "plt.plot(np.arange(0,60000),W)\n",
    "plt.xlim(10000,20000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "742974ec",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:.conda-ds-TaskRankingService]",
   "language": "python",
   "name": "conda-env-.conda-ds-TaskRankingService-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
