diff --git a/acquire.py b/acquire.py index 396519a..022bff4 100644 --- a/acquire.py +++ b/acquire.py @@ -10,8 +10,8 @@ print('Connected to ' + IP) wave_form = 'sine' -freq = 200 -ampl = 0.9 +freq = 100 +ampl = 0.5 # Reset Generation and Acquisition rp_s.tx_txt('GEN:RST') @@ -49,7 +49,7 @@ # function for Data Acquisition data = rp_s.acq_data(1, convert=True) -plt.plot(10*data) +plt.plot(data) plt.ylabel('Amplitude [V]') plt.xlabel('Samples') plt.show() \ No newline at end of file diff --git a/acquire_automatic.py b/acquire_automatic.py new file mode 100644 index 0000000..21cf9b9 --- /dev/null +++ b/acquire_automatic.py @@ -0,0 +1,136 @@ +#!/usr/bin/env python3 + +import os +import sys +import time +import matplotlib.pyplot as plt +import redpitaya_scpi as scpi +import numpy as np +from scipy.fftpack import fft +import math +import util + +IP = 'rp-f0c04a.local' +rp_s = scpi.scpi(IP) +print('Connected to ' + IP) + +def run_one_shot(start_freq=1, end_freq=1000, decimation=8192, store_data=False, plot_data=False): + """Runs one shot of driving the speaker with a waveform and collecting the relevant data. + + Args: + start_freq (int, optional): the lower bound of the valid frequency range. Defaults to 1. + end_freq (int, optional): the upper bound of the valid frequency range. Defaults to 1000. + decimation (int, optional): Decimation that determines sample rate, should be power of 2. Defaults to 8192. + store_data (bool, optional): Whether to store data in h5py file. Defaults to False. + plot_data (bool, optional): Whether to plot data after acquisition. Defaults to False. + """ + ##### Create Waveform ##### + + N = 16384 # Number of samples in buffer + SMPL_RATE_DEC1 = 125e6 # sample rate for decimation=1 in Samples/s (Hz) + smpl_rate = SMPL_RATE_DEC1//decimation + burst_time = N / smpl_rate + + wave_form = 'ARBITRARY' + freq = 1 / burst_time + ampl = 0.1 # good range 0-0.6V + + t, y = util.bounded_frequency_waveform(start_freq, end_freq, length=N, sample_rate=smpl_rate) + y = util.linear_convert(y) # convert range of waveform to [-1, 1] to properly set ampl + if plot_data: + plt.plot(t, y) + plt.show() + + ##### Reset Generation and Acquisition ###### + rp_s.tx_txt('GEN:RST') + rp_s.tx_txt('ACQ:RST') + + ##### Generation ##### + # Function for configuring Source + rp_s.sour_set(1, wave_form, ampl, freq, data=y) + + # Enable output + rp_s.tx_txt('OUTPUT1:STATE ON') + rp_s.tx_txt('SOUR1:TRig:INT') + + ##### Acqusition ##### + # Function for configuring Acquisition + rp_s.acq_set(dec=decimation, trig_delay=0) + rp_s.tx_txt('ACQ:START') + time.sleep(1) + rp_s.tx_txt('ACQ:TRig CH2_PE') + time.sleep(1) + + # Wait for trigger + while 1: + rp_s.tx_txt('ACQ:TRig:STAT?') # Get Trigger Status + print('got status') + if rp_s.rx_txt() == 'TD': # Triggered? + break + print('triggered') + ## ! OS 2.00 or higher only ! ## + while 1: + rp_s.tx_txt('ACQ:TRig:FILL?') + if rp_s.rx_txt() == '1': + break + + ##### Analaysis ##### + # Read data and plot function for Data Acquisition + pd_data = np.array(rp_s.acq_data(chan=1, convert=True)) # Volts + speaker_data = np.array(rp_s.acq_data(chan=2, convert=True)) # Volts + velocity_data, converted_signal, freq = util.velocity_waveform(speaker_data, smpl_rate) + displ_data, _, _ = util.displacement_waveform(speaker_data, smpl_rate) + y_vel, y_converted, _ = util.velocity_waveform(ampl*y, smpl_rate) + time_data = np.linspace(0, N-1, num=N) / smpl_rate + + if plot_data: + fig, ax = plt.subplots(nrows=3) + + ax[0].plot(time_data, pd_data, color='blue', label='Observed PD') + ax[0].plot(time_data, speaker_data, color='black', label='Observed Drive') + ax[0].plot(time_data, ampl*y, label='Drive Output') + ax[0].legend() + ax[0].set_ylabel('Amplitude (V)') + ax[0].set_xlabel('Time (s)') + + ax[1].plot(freq, np.abs(fft(speaker_data)), color='black', label='Observed Drive') + ax[1].plot(freq, np.abs(converted_signal), color='green', label='Expected Observed Vel') + ax[1].plot(freq, np.abs(fft(ampl*y)), color='blue', label='Expected Drive') + ax[1].plot(freq, np.abs(y_converted), color='orange', label='Expected Ideal Vel') + ax[1].loglog() + ax[1].set_xlabel('Frequency (Hz)') + ax[1].set_ylabel('$|\^{V}|$') + ax[1].legend() + + ax[2].plot(time_data, velocity_data, color='black', label='Observed Drive') + ax[2].plot(time_data, y_vel, label='Drive Output') + ax[2].set_ylabel('Expected Vel (Microns/s)') + ax[2].set_xlabel('Time (s)') + ax[2].legend() + plt.tight_layout() + plt.show() + + if store_data: + # Store data in h5py file + path = "/Users/angelajia/Code/College/SMI/data/" + filename = "data.h5py" + file_path = os.path.join(path, filename) + + entries = { + 'Time (s)': time_data, + 'Speaker (V)': speaker_data, + 'Speaker (Microns/s)': velocity_data, + 'PD (V)': pd_data, + 'Speaker (Microns)': displ_data + } + + util.write_data(file_path, entries) + + ##### Reset when closing program ##### + rp_s.tx_txt('GEN:RST') + rp_s.tx_txt('ACQ:RST') + + +num_shots = 1 +for i in range(num_shots): + run_one_shot(store_data=False, plot_data=True) \ No newline at end of file diff --git a/acquire_continuous.py b/acquire_continuous.py new file mode 100644 index 0000000..6292be4 --- /dev/null +++ b/acquire_continuous.py @@ -0,0 +1,76 @@ +#!/usr/bin/env python3 + +import sys +import time +import matplotlib.pyplot as plt +import redpitaya_scpi as scpi +import numpy as np +import matplotlib.ticker as ticker + +IP = 'rp-f0c04a.local' +rp_s = scpi.scpi(IP) +print('Connected to ' + IP) + +wave_form = "SINE" +freq = 1000 +ampl = 0.1 + +N = 16384 # Number of samples in buffer +SMPL_RATE_DEC1 = 125e6 # sample rate for decimation=1 in Samples/s (Hz) +decimation = 32 +smpl_rate = SMPL_RATE_DEC1//decimation + +# Reset Generation and Acquisition +rp_s.tx_txt('GEN:RST') +rp_s.tx_txt('ACQ:RST') + +##### Generation ##### +# Function for configuring Source +rp_s.sour_set(1, wave_form, ampl, freq) + +# Enable output +rp_s.tx_txt('OUTPUT1:STATE ON') +rp_s.tx_txt('SOUR1:TRig:INT') + +##### Acqusition ##### +# Function for configuring Acquisition +rp_s.acq_set(dec=decimation, trig_delay=0) +rp_s.tx_txt('ACQ:START') +time.sleep(1) +rp_s.tx_txt('ACQ:TRig CH2_PE') +time.sleep(1) + +# Wait for trigger +while 1: + rp_s.tx_txt('ACQ:TRig:STAT?') # Get Trigger Status + print('got status') + if rp_s.rx_txt() == 'TD': # Triggerd? + break +print('triggered') +## ! OS 2.00 or higher only ! ## +while 1: + rp_s.tx_txt('ACQ:TRig:FILL?') + if rp_s.rx_txt() == '1': + break + +# Read data and plot +# function for Data Acquisition +time_data = np.linspace(-(N-1)/2, (N-1)/2, num=N) / smpl_rate +pd_data = rp_s.acq_data(chan=1, convert=True) +speaker_data = rp_s.acq_data(chan=2, convert=True) + +print(f"vpp: {np.max(speaker_data) - np.min(speaker_data)}") + +fig, ax = plt.subplots(nrows=1) +ax.plot(time_data, pd_data, color='blue', label='Observed PD') +ax.plot(time_data, speaker_data, color='black', label='Observed Drive') +ax.xaxis.set_major_locator(ticker.MultipleLocator(0.001)) +ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.0001)) + +plt.ylabel('Amplitude (V)') +plt.xlabel('Time (s)') +plt.show() + +##### Reset when closing program ##### +rp_s.tx_txt('GEN:RST') +rp_s.tx_txt('ACQ:RST') \ No newline at end of file diff --git a/calibration_rp.ipynb b/calibration_rp.ipynb new file mode 100644 index 0000000..5cd6ba7 --- /dev/null +++ b/calibration_rp.ipynb @@ -0,0 +1,380 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "id": "5e3c1deb", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import scipy\n", + "import pandas as pd\n", + "import lmfit" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a2845a38", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Index(['Frequency (Hz)', 'Vpp (V)', 'Displacement (Microns)',\n", + " 'Displacement (Microns) / Vampl (V)', 'A Uncertainty (V/microns)',\n", + " 'Phase (Radians)', 'Uncertainty (Radians)'],\n", + " dtype='object')\n" + ] + } + ], + "source": [ + "df = pd.read_csv('../calibrationdata/RPRPData.csv')\n", + "data = df.to_numpy()\n", + "\n", + "print(df.columns)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "03446f09", + "metadata": {}, + "outputs": [], + "source": [ + "freq = data[:, 0]\n", + "vpp = data[:, 1]\n", + "displ = data[:, 2]\n", + "a = data[:, 3]\n", + "a_sigma = data[:, 4]\n", + "phases = data[:, 5]\n", + "phases_sigma = data[:, 6]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "292e1321", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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mY2NTZp233noLjRs3Rq9eveDp6YlRo0apukGU1KhRI7Xn1tbWcHNz0+jLX9KKFSvQsmVLmJubo06dOnB2dsbWrVuRkpKiqnPr1i24u7vD0dGxzOPcuHEDgiCgUaNGcHZ2VntcvXpVNfC9iKenp8bYFzs7O7VZsorKAKi6wjx8+BBPnjzB0qVLNc4zcuRIANA4l7e3t9pzBwcHtWM+y9atW9GzZ0+NGZ6GDh2KjIwM/PXXXwCAo0eP4s6dO2rdrLKysjBjxgx4eXlBLpfDyckJzs7OePLkidprXFasRT9/aa9LafGXfB8AQOPGjZ/5PijN4MGDkZWVpRonkJ6ejm3btmHgwIGq312XLl0wYMAAzJ49G05OTnjppZf0Mp1y586dERISono8//zzatt9fX3Vnt+4cQNAwVitku+LXbt2qd4TRddzaa9TaX9bKuLmzZsQBAHTp0/XOHdRMq7te7IoUfD39y/33IMHD4ZcLlclXikpKdiyZQuGDh3KtUqoWjP6WaHee+89vPnmm2jatKnYoRDVCkFBQapZoYxR0YDa8qatrVu3Ls6fP4+dO3di+/bt2L59O3799VcMHz4cK1as0DmG3377DSNGjEC/fv3w/vvvo27duqrxK8U/Aa0IpVIJiUSC7du3q32SXKTk1KGl1SmvXCgcK1I0He/rr7+OiIiIUuu2bNlSq2OWJzMzEwcOHMAPP/ygsa1v376ws7PDmjVr8Nprr2HNmjWQyWRqLTETJ07Er7/+infeeQft27eHnZ0dJBIJXn311VKnFtbmdalI/Lpo164dfHx88Oeff+K1117D33//jaysLAwePFhVRyKRYN26dTh+/Dj+/vtv1XTK33zzDY4fP67xe9eX4i1BwNP3xapVq+Dq6qpRvzLT/pZ1Y140aL3kud97770yPxwpeZ3r8p4szsHBAX379sXq1asxY8YMrFu3Djk5OXj99de1Og6RoRl9YvHXX3/h22+/RXBwMN58800MHjyY09sRGVC9evUAANevX1fNIFXk+vXrqu1A2TcEzzpu/fr1VeW5ubmIjo5GSEiILmGXqWjgbXmtNEBBy0lYWBjCwsKgVCrx1ltv4ccff8T06dPVblZu3LiBbt26qZ6np6cjLi5ObcBxSevWrUP9+vWxYcMGtdesZJenBg0aYOfOnUhOTi6z1aJBgwYQBAG+vr6qbkBVwdnZGTY2NlAoFHr93ZT1ntm3bx9ycnLQq1cvjW1yuRyvvPIKVq5ciYSEBKxduxbdu3dXu7Fdt24dIiIi8M0336jKsrOzNQaz60vRJ/fF/ffff5Ve0X3QoEH47rvvkJqaiqioKPj4+KBdu3Ya9dq1a4d27drh888/x5o1azB06FD88ccfePPNNyt1Xm01aNAAQEEyXt77ouh6L+11un79utrzolaEkr+rkq2YRX83TE1N9faeLPp5Ll++/Mw1c4YPH46XXnoJp06dwurVq9GqVSs0b95cL3EQVRWj7goFFPwR2r9/Pxo3boy3334brq6uGDVqFI4ePSp2aERGoU2bNqhbty6WLFmi1s1i+/btuHr1Kvr06aMqK0r6K3LzFhISAjMzMyxcuFDt08JffvkFKSkpasfVlzVr1uDnn39G+/bt0aNHjzLrPXr0SO25VCpVfRpfsqvJ0qVL1fq4//DDD8jPzy/1hrhI0aemxX/uEydO4NixY2r1BgwYAEEQMHv2bI1jFO378ssvQyaTYfbs2RqfugqCoPGzVJZMJsOAAQOwfv36UqdRLW3qzYqwsrIqtWvStm3b0KZNG7i4uJS639ChQ5GXl4exY8fi4cOHGmtXyGQyjddj0aJFGp9668umTZvU+vOfPHkSJ06cKPd9UJ7BgwcjJycHK1aswI4dOzBo0CC17Y8fP9b4+QIDAwGov0dv3bqldSuYNkJDQ2Fra4svvvii1LEeRe8LNzc3BAYGYsWKFWq/7927d+PKlStq+9SrVw8ymQwHDx5UK//+++/VntetWxddu3bFjz/+iLi4uDLPrY2ePXvCxsYGc+bM0ZgytuTr3atXLzg5OeHLL7/EP//8w9YKqhGMvsUCKOjz2blzZ0RGRiIqKgq//vorOnbsiCZNmuCNN97AsGHDyvznQ0S6MTU1xZdffomRI0eiS5cuGDJkCBISEvDdd9/Bx8dHbWxT69atAQCTJk1CaGioRveU4pydnTFt2jTMnj0bL774IsLDw3H9+nV8//33aNu2rc7/pNetWwdra2vk5uaqVt4+cuQIAgICsHbt2nL3ffPNN5GcnIzu3bvD09MTd+/exaJFixAYGIhmzZqp1c3NzUWPHj0waNAgVfwdO3ZEeHh4mcfv27cvNmzYgP79+6NPnz6Ijo7GkiVL4OfnpzZgt1u3bhg2bBgWLlyIGzdu4MUXX4RSqcShQ4fQrVs3TJgwAQ0aNMBnn32GadOm4c6dO+jXrx9sbGwQHR2NjRs3YsyYMXjvvfd0ei2LzJ07F/v370dwcDBGjx4NPz8/JCcn4+zZs9izZw+Sk5O1Pmbr1q0RFRWFyZMno23btrC2tkZYWBi2bdumGrtRmi5dusDT0xN//fUXLCwsNKYg7tu3L1atWgU7Ozv4+fnh2LFj2LNnT7nTKuuiYcOG6NixI8aNG4ecnBwsWLAAderUwZQpUyp1vOeeew4NGzbERx99hJycHLVuUEDBGJ3vv/8e/fv3R4MGDZCWloaffvoJtra2aq1lRQl0ZcZ6VIStrS1++OEHDBs2DM899xxeffVVODs7IyYmBlu3bsXzzz+PxYsXAwDmzJmDPn36oGPHjhg1ahSSk5OxaNEiNG/eXO19b2dnh4EDB2LRokWQSCRo0KABtmzZojFeAigYM9axY0e0aNECo0ePRv369ZGQkIBjx47h3r17uHDhgtY/z7fffos333wTbdu2xWuvvQYHBwdcuHABmZmZal0hTU1N8eqrr2Lx4sWQyWTVdoFRIjWGnYSq5rhx44bw4YcfCo6OjoKZmZnY4RBVe0XTLT5resqypnqMiooSWrVqJcjlcsHR0VEYOnSo2vSaglAwHefEiRMFZ2dnQSKRVGjq2cWLFwtNmzYVTE1NBRcXF2HcuHHC48eP1epUZrrZooe5ubng6ekp9O3bV1i2bJnatJRFSk43u27dOqFnz55C3bp1BTMzM8Hb21sYO3asEBcXp6pT9Hr+888/wpgxYwQHBwfB2tpaGDp0qPDo0SO145ecblapVApffPGFUK9ePUEulwutWrUStmzZohGHIBS8pl999ZXQtGlTwczMTHB2dhZ69eolnDlzRq3e+vXrhY4dOwpWVlaClZWV0LRpU2H8+PGq6VeL4mjevLnGz1+vXj2hT58+GuUAhPHjx6uVJSQkCOPHjxe8vLwEU1NTwdXVVejRo4ewdOlSVZ2i99DatWvV9i1tutD09HThtddeE+zt7VXTjl6+fFkAIJw8eVIjpuLef/99AYAwaNAgjW2PHz8WRo4cKTg5OQnW1tZCaGiocO3aNaFevXpCRESEql5Z10VZ77mIiAjByspK42f66quvhG+++Ubw8vIS5HK50KlTJ+HChQulHrOiPvroIwGA0LBhQ41tZ8+eFYYMGSJ4e3sLcrlcqFu3rtC3b1/h9OnTavXq1atX5nS+Ffl5izzr78f+/fuF0NBQwc7OTjA3NxcaNGggjBgxQiOe9evXC82aNRPkcrng5+cnbNiwodT3/cOHD4UBAwYIlpaWgoODgzB27FjV+6L4+0cQBOHWrVvC8OHDBVdXV8HU1FTw8PAQ+vbtK6xbt+6Z8Zf1927z5s1Chw4dBAsLC8HW1lYICgoSfv/9d42f++TJkwIAoWfPnqW+LkTVjUQQqniUWA2UkZGBP//8E7/88guOHj2KJk2a4OrVq2KHRURGZPny5Rg5ciROnTpl1IPhq8K8efMwf/58xMXFVfsZdu7cuQNfX1989dVXemsZMjYjRozAgQMHqqxVpSpduHABgYGBWLlypWrxTaLqzOjHWBR3+PBhjBo1Cm5ubpg0aRIaN26MQ4cOMakgIqpFfHx88O2331b7pILop59+grW1tUZXPKLqyujHWMTFxWHFihVYvnw5/vvvP7Rr1w7z589XLexFRES1S8mBykTVzd9//40rV65g6dKlmDBhAmerpBrD6BMLLy8v1KlTB8OGDcMbb7yhMXCSiIiIyJAmTpyIhIQE9O7du9RZ24iqK6MfY7FhwwaEh4dXapEdIiIiIiIqYNSJRUZGhlbNi9rWJyIiIiIyFkY9eLthw4aYO3duqQvfFBEEAbt370avXr2wcOFCA0ZHRERERFRzGHWLxfXr1/Hhhx9i69atCAgIQJs2beDu7g5zc3M8fvwYV65cwbFjx2BiYoJp06Zh7NixqhVtqzOlUokHDx7AxsaGs54QERERUaUJgoC0tDS4u7tDKi2/TcKoE4siMTExWLt2LQ4dOoS7d+8iKysLTk5OaNWqFUJDQ9GrV68akVAUuXfvHry8vMQOg4iIiIhqidjYWHh6epZbh4lFLZSSkgJ7e3vExsbC1tZW7HCIiIiIqIZKTU2Fl5cXnjx5Ajs7u3LrciqkWqio+5OtrS0TCyIiIiLSWUW61xv14G0iIiIiItIPJhZEREREtVBcShaO3kpCXEqW2KGQkWBXqFokMjISkZGRUCgUYodCREREIoo6FYNpGy5BKQBSCTDn5RYY3NZb7LColuPg7VooNTUVdnZ2SElJ4RgLIiIiIxOXkoXn5+6DstgdnkwiweGp3eBmZyFeYFQjaXNfadQtFhcvXqxw3ZYtW1ZhJERERET6cTMxXS2pAACFIOBOUiYTC6pSRp1YBAYGQiKRoKxGm6JtEomE3YuIiIioRth07r5GmUwigY+TpQjRkDEx6sQiOjpa7BCIiIiI9GbF0TtYf7YgsZBIgKLPTqf1bsrWCqpyRp1Y1KtXT+wQiIiIiPRi//VEzP77XwDA1F5N8VKgOwYtOYbYx1lwsTUXOToyBpxutpjr169jwoQJ6NGjB3r06IEJEybg+vXrYodFREREVK7r8WmYuOYclAIwqI0nxnauDzc7C/Rs7goAOHIzSeQIyRgwsSi0fv16+Pv748yZMwgICEBAQADOnj0Lf39/rF+/XuzwKiQyMhJ+fn5o27at2KEQERGRgTxMy8Go5aeQnpOPYF9HfNavhWqV5I4NnQAAR24xsaCqx+lmCzVo0ABDhw7FJ598olY+c+ZM/Pbbb7h165ZIkWmP080SEREZh+w8BYb8dBznYp7A18kKG8Z1gIOVmWp7Rk4+AmbvQr5SwMH3u8G7Dgdwk3a0ua9ki0WhuLg4DB8+XKP89ddfR1xcnAgREREREZXtwZNMjFp+CudinsDOwhS/RLRRSyoAwEpugkAvewBstaCqx8SiUNeuXXHo0CGN8sOHD6NTp04iRERERERUuqhTMXh+7n4cvfUIQMG4ivrO1qXWfb6oOxTHWVAVM+pZoYoLDw/HBx98gDNnzqBdu3YAgOPHj2Pt2rWYPXs2Nm/erFaXiIiISAxxKVmYuuESivdlX3b4DkZ19C11StnnGzrhu703cOzWIyiVAqRSieGCJaPCMRaFpNKKNd7UhMXyOMaCiIio9jp6Kwmv/XRCo/z30e3QvkEdjfLcfCUCZu9CVp4C2yZ1gp877w2o4jjGohKUSmWFHtU9qSAiIqLazdpMs8NJeStrm5lIEVzfEUBBUkJUVZhYEBEREdUgB288VHsuk0jwxcv+5a6s/XwDjrOgqscxFsWcOnUK+/fvR2JiIpRKpdq2+fPnixQVERERUQGlUkDU6VgAwMd9mqG5ux18nCzLTSqApwO4T0QnIzdfCTMTfrZM+sfEotAXX3yBjz/+GE2aNIGLi4tqYRkAat9XZ5GRkYiMjGR3LSIiolrq6K1HiE3Ogo25CYYG14OFmaxC+zV1tYGjlRmSM3Jx4d4TtPVxrOJIyRgxsSj03XffYdmyZRgxYoTYoVTa+PHjMX78eNUgGyIiIqpdfj8VAwDoF+hR4aQCAKRSCdo3qIOtF+Pwx8kYeDpYPLOVg0hbbAcrJJVK8fzzz4sdBhEREVGprsalYsflgkV7B7f10np/eWH3p/Vn7+P5ufsQVZikEOkLE4tC7777LiIjI8UOg4iIiEhD1KkY9P7uEBSFQ0D/fZCi1f5xKVnYdO6+6rlSAD7ccBlxKVn6DJOMHLtCFXrvvffQp08fNGjQAH5+fjA1NVXbvmHDBpEiIyIiImMWl5KFaSUWxPtww2V0buxc4e5M0UkZUJZYuUwhCLiTlMkuUaQ3TCwKTZo0Cfv370e3bt1Qp06dGjNgm4iIiGo3fSQFvk5WkEqgdhyZBGWufUFUGUwsCq1YsQLr169Hnz59xA6FiIiISMVMpvlhZ3kL4pXGzc4Cc15ugWkbLqmSixHP+7K1gvSKYywKOTo6okGDBmKHQURERKQSdSoGA5ccVyuryIJ4pRnc1htHpnZHaHMXAMDdRxl6i5MIYGKhMmvWLMycOROZmZlih0JERERU6tgKKYANb7XH4LbelTqmm50FPnixKQBgz9VEbDp3nwO4SW/YFarQwoULcevWLbi4uMDHx0dj8PbZs2dFioyIiIiM0ek7yRpjK5QAMnOVOh23vrM1GrlY40ZCOt6JOg+pBJjzcotKJytERZhYFOrXr5/YIaiJjY3FsGHDkJiYCBMTE0yfPh0DBw4UOywiIiIygKhTMfhg/SWNcm3HVpQmLiULNxPTVc+Lpp7VZpYpotIwsSg0c+ZMsUNQY2JiggULFiAwMBDx8fFo3bo1evfuDSsrK7FDIyIioip0IfYxppaSVEglqNTYipKikzIgcOpZqgJMLKopNzc3uLm5AQBcXV3h5OSE5ORkJhZERES1WNSpGExdrz6uosjCV1uhb4C7zucobepZKaeeJT3g4O1CCoUCX3/9NYKCguDq6gpHR0e1h7YOHjyIsLAwuLu7QyKRYNOmTRp1IiMj4ePjA3NzcwQHB+PkyZOlHuvMmTNQKBTw8vLSOg4iIiKqGUobrF1EJpGgtY+DXs5TNPWstNgsti8/58nWCtIZE4tCs2fPxvz58zF48GCkpKRg8uTJePnllyGVSjFr1iytj5eRkYGAgABERkaWuj0qKgqTJ0/GzJkzcfbsWQQEBCA0NBSJiYlq9ZKTkzF8+HAsXbq0Mj8WERER1RBn7j7WGKwN6K8LVHFFU88ODS740PLk7Uc4fCOJM0SRTiSCULKXnXFq0KABFi5ciD59+sDGxgbnz59XlR0/fhxr1qyp9LElEgk2btyoNkA8ODgYbdu2xeLFiwEASqUSXl5emDhxIqZOnQoAyMnJwQsvvIDRo0dj2LBhZR4/JycHOTk5quepqanw8vJCSkoKbG1tKx03ERERGUZZg7WlADaO74AAL/20VpSUnpOPtp/tQVaeouB8nCGKSkhNTYWdnV2F7ivZYlEoPj4eLVq0AABYW1sjJSUFANC3b19s3bpVr+fKzc3FmTNnEBISoiqTSqUICQnBsWPHAACCIGDEiBHo3r17uUkFAMyZMwd2dnaqB7tMERER1RwxyRllDtaeM6BFlSUVAJCWnYfswqQCeDpDFFsuqDKYWBTy9PREXFwcgILWi127dgEATp06BblcrtdzJSUlQaFQwMXFRa3cxcUF8fHxAIAjR44gKioKmzZtQmBgIAIDA3HpkuYfHQCYNm0aUlJSVI/Y2Fi9xktERET6F5eSha0XH2DkslNlDtau6paD6KQMjXMXzRBFpC3OClWof//+2Lt3L4KDgzFx4kS8/vrr+OWXXxATE4N3333X4PF07NgRSmXFFsCRy+WQy+WIjIxEZGQkFArFs3ciIiIi0USdisHUDZc0pn0tos/B2uXhDFGkT0afWCxevBivv/465s6dqyobPHgwvL29cezYMTRq1AhhYWF6PaeTkxNkMhkSEhLUyhMSEuDq6lrp444fPx7jx49X9YUjIiKi6icuJUtjSlkJAEnhDb5MItH7YO2yFM0QNW3DJVVyEeTryBmiqFKMvivURx99BHd3dwwdOhT79u1Tlbdv3x6TJ0/We1IBAGZmZmjdujX27t2rKlMqldi7dy/at2+v9/MRERFR9aBQCvjk7ysa3Y8EFHR9+n10Oxye2s2gg6eLZoj6uE8zAMCJ6GRcvPfEYOen2sPoE4v4+HgsWbIEDx48wAsvvABfX198+umnOo9TSE9Px/nz53H+/HkAQHR0NM6fP4+YmBgAwOTJk/HTTz9hxYoVuHr1KsaNG4eMjAyMHDmy0ueMjIyEn58f2rZtq1PsREREpF9xKVnYfy0BEctOYvvleI3tRV2f2jeoI0prgZudBd7sVB/9At0hCMD0TZehKG3uW6JycLrZYm7fvo3ly5dj5cqVuHfvHkJCQvDGG2+gX79+MDU11epYBw4cQLdu3TTKIyIisHz5cgAF3bC++uorxMfHIzAwEAsXLkRwcLDOP4c204IRERGR/sWlZCE6KQO+TlbYfy0RH226rBpPIZNKMLiNF6JOxUIhCKquT9VhitfEtGz0+PofpOXk47N+/ni9XT2xQyKRaXNfycSiFIIgYM+ePVi+fDk2bdoEKysrjYXrqjMmFkREROJZc+KuWiJRklQCHJnaHQBwJykTPk6W1WpMw4qjdzBz87+wNTfBvve6wslav7NjUs3CdSx0JJFIYGJiAolEAkEQkJeXJ3ZIFcKuUEREROKJTsrAR5su4cONZScVQMEA7TtJmXCzsxCt61N5Xm9XD83dbZGanY85266JHQ7VIEwsiomNjcUnn3yC+vXr44UXXsCDBw/w008/qda3qO7Gjx+PK1eu4NSpU2KHQkREZBRy8hX46/x9DFl6HN2+PoDVx2OeuY9MIqnW07nKpBJ81s8fEgmw/uw9nLj9SOyQqIYw+ulmc3NzsWHDBixbtgz79u2Dm5sbIiIiMGrUKNSvX1/s8IiIiKgaupmYht9PxmLD2Xt4nFnQs0EiAdr5OuL47eRqMZWsLlp5O2BIkDfWnIjB9L8uY+ukTjCV8fNoKp/RJxaurq7IyMhAWFgY/v77b4SGhkIq5YVDRERE6rLzFNh6MQ5/nIrBqTuPVeVuduYY1MYLg9p6wcPeAlGnYvDhhstqA7M7N3auluMpyjMltAl2XI7Hfwnp+PVINMZ0biB2SFTNGf3g7Xnz5mHUqFFwcnISOxSdFV95+7///uPgbSIiokoqPqvTk8w8/HEyBhvO3Udadj6Agu5C3ZvWxZAgL3RpXBcyqURj/5qWSJRm7elYvL/uIsxNpfjqlQC08XGo0T8PaY+zQmnB2toaPj4+CA8Px0svvaSX6V7FxlmhiIiIKi/qVIzaStTFeTpY4NW2XhjYxgsutuaGD87AlEoB3b4+gLvJmQAKZrSa83KLajE1LhmGNveVRt8VKikpCbt378Zff/2Fl156CRKJBH379kV4eDheeOEFmJvX/j8aRERExiorV4FbD9MLHxm4fD8F+65pTjHfrakzRnbwRceGTpCWaJ2ozRLSshHzOFP1XCkAH264jM6NndlyQRqMPrEwNzdHWFgYwsLCIAgCjh07hs2bN+ODDz7AkCFDEBISgvDwcISFhcHZ2VnscImIiKgUxbsulbzhFQQBjzJycTOxMIFIzMDNh+m4lZiO+0+yKnT8MZ0aoH2DOlURerUWnZShMXWuQhBU0+USFWf0iUVxEokEHTp0QIcOHTB37lzcuHEDmzdvxvLlyzFu3DjMnz8f48ePFzvMMhUfY0FERGQsinddkkqAYe3qwd3eArcephcmExlIySp7TSpHKzM0cLZCA2dr1LWRY9H+m2o309V9etiq5OtkBWnhjFbFHbuVZJSJFpXP6MdYVNSjR4+QnJyMRo0aiR3KM3GMBRER1XaCIOD+kyzsvZaImX/9+8z6Egng5WCpSiAa1rVGg7rWaOBsDUcrM7W6pc3qZMxjCoq/HhJANZXuuyGNMalHQ0gkxtM1zBhx8HYl5OTk4MSJE7h79y4yMzPh7OyMVq1awdfXV+zQtMbEgoiIapvsPAX+fZCCs3ef4GzMY5y5+xiJaTll1m/foA6CfR0LEghna/g6WcHcVFbh89WWWZ30pfjrsf7MPXy96z8AwNjO9TG1V1MmF7UYB29r4ciRI/juu+/w999/Iy8vD3Z2drCwsEBycjJycnJQv359jB49GuPGjYONjY3Y4RIREdVKJcdIxKVk4ezdJzhz9zHOxjzGlQepyFUo1fYxkUrQsK41rsenqS1IJ5NIMH9QgE4JgZudBROKYoq/HhO6N4KFmQk+3XIFPx68jYzcfHwS7m9Ug9qpdEadWISHh+Ps2bN47bXXsGvXLrRp0wYWFk//iNy+fRuHDh3C77//jm+//RYrV67ECy+8IGLERERENYMgCMhXCsjJVyInT1HwNV+JnHwFcvLUv99/PRFrTsSokgM7CxOkZOVrHNPJ2gytvB3wnLcDnvO2R0tPe1iYyUrtusSkoGq90dEXVmYyTNt4Cb8dj0FmrgLzBrSECVfnNmpG3RXqxx9/xKhRo2BqavrMuleuXEFcXBx69OhhgMgqhwvkEVVv5c1aUxsZ28+rb7q+ftrc2Ku+f1bdfGXh84rVKW0diIqSSoBmbrZ4ztsBresVJBNejhZldrlh1yVx/HX+Pib/eQEKpYDeLVyxYHArmJkwuahNOMbCyHGMBVHVUygFZOcpkJ2nQFaeAtl5SmTnKZCTX/B9Vq4C2flPy4/deoRtl+IgAJAACPFzQQsPO5S8RSp5z1SRfssa+5Q4quZ23fbXPH+J+gDOxTzGlotPf96+Ld3QytsBpf3Deda/odI2CyWOVHod/RxHM56qP/flBynYdzVR9fq1q+8Ib0erCt/QZ+vhxl7fzGRSyE2kkJtKITeRQW4ihZmJFHkKJW49zNCov3xkW3RtUleESElbO/+Nx8Q155CrUKJbE2f88HprrcazUPXGxKISYmNjIZFI4OnpCQA4efIk1qxZAz8/P4wZM0bk6LQjVmLBTydJW/p8zyiVArLzFYU39ErVTX92XsEnsMVv/ovf8BevV7CtICkouDlT3ycrt+BY2fkK5Cn4p5NqlrJu7OWmBd8XPGSF25/WKV5fXoH65mr1C7abyaRl9r+PS8nC83P3qSVBMokEh6d24/+SGuSf/x5i7KrTyM5Ton39Ovg5og2s5Ebd477WYGJRCZ06dcKYMWMwbNgwxMfHo0mTJmjevDlu3LiBiRMnYsaMGWKHWGFiJBZRp2IwdcMlCELBp2tDg73xfEMng5ybaqYjN5OwurBPddEn2s3cbZFdSmKQVfh9Tp6yMCnQLC85qNOQzEykMDeRwtxUVvgo/r0MmTn5OH33scZ+3ZvWhYutXK2s5F/kynzKXnqrQPnHKG0nzU/dhWdsL/ialJ6Do7ceaRyvQ4M6cLKWl9oCotmKotkK8qydSra0FByn/POUXqcCx9Goor9zx6dkY/fVBI26g9t6oVFda73f2FcHnN61djhx+xHeWHEa6Tn5eM7bHr+ODIKdxbO7m1P1xsSiEhwcHHD8+HE0adIECxcuRFRUFI4cOYJdu3bh//7v/3D79m2xQ6wwQycWpX3aRCQmM1nBp6yqm3yTght8C1NZsXKZKhmwMCv4Xl4sMbAoniSYyAq3FS+XqW7gZM+4YTO2T2SN7efVN2N9/ThGona4EPsEw5edREpWHvzcbLHqjSDUsZY/e0eqtjjdbCXk5eVBLi944+/Zswfh4eEAgKZNmyIuLk7M0Kq96KSMUpOKJi7WsOUnFVSK1Kw8XE9I1yjv3NgJ3o6Wajfv8qKbf43WgIKbegsz9STB3PTZN/qG5mZngTkvtzCaWWuM7efVN2N9/Ti9a+0Q4GWPP8a0w7BfTuBKXCoGLz2O1W8Gw8XWXOzQyADYYlEoODgY3bp1Q58+fdCzZ08cP34cAQEBOH78OF555RXcu3dP7BArrDq0WBjDp2tUecb6njG2T2SN7efVN75+VJPdepiO138+gbiUbHg7WmL1m8HwcrQUOyyqBG3uKzkfWKEvv/wSP/74I7p27YohQ4YgICAAALB582YEBQWJHF3FREZGws/PD23btjXoeYs+XZMVdhY2lk/XqPKM9T3jZmeB9g3q1Pqfs4ix/bz6xteParIGztb4c2x7eDtaIiY5E4N+PIYTtx/h6K0kxKVkiR0eVRG2WBSjUCiQmpoKBwcHVdmdO3dgaWmJunVrzpR3Ys4KxU/XSBt8zxAR1W4JqdkY+vMJ3Ex82v1VKgHmvNyCA/RrCA7eNnJcx4KIiIiqiysPUtB74WG1MmPo/lpbsCtUJSQkJGDYsGFwd3eHiYkJZDKZ2oOIiIiItPckK0+jTCEIuJOkuTAi1WycFarQiBEjEBMTg+nTp8PNza1Cq90SERERUfl8nawglUBjBsmoU7FoXc8RZib8nLu2YFeoQjY2Njh06BACAwPFDkVn7ApFRERE1UnxRRAleLrAZpCvI34Y+hzXuqjGuI5FJXh5eWmsKktEREREuhvc1hudGzurJuy4FpeGSb+fw8noZLwUeQQ/DW+DZm78MLSmY9tToQULFmDq1Km4c+eO2KEQERER1TrFp1Du1rQuNo7vAJ86lrj3OAsDfjiKHZfjxQ6RdMSuUIUcHByQmZmJ/Px8WFpawtRUfcXo5ORkkSLTHrtCERERUU3wJDMXE9acw+GbSQCAyS80xsTuDTnWtRphV6hKWLBggdgh6CwyMhKRkZFQKBRih0JERET0TPaWZlg+si0+23oVy4/ewfzd/+F6fBq+GtgSlma8Ta1p2GJRC7HFgoiIiGqaP07GYPpfl5GnENDc3RZLh7eBhz3XuRAbF8irJIVCgU2bNuHq1asAgObNmyM8PLzGrWPBxIKIiIhqolN3kvF/q87gUUYunKzN8OOw1mhdz1HssIwaE4tKuHnzJnr37o379++jSZMmAIDr16/Dy8sLW7duRYMGDUSOsOKYWBAREVFNde9xJkavPIOrcakwlUnwef8WGNTGS+ywjBZX3q6ESZMmoUGDBoiNjcXZs2dx9uxZxMTEwNfXF5MmTRI7PCIiIiKj4OlgifXj2qOXvyvyFAKmrLuIT7dcQb5CKXZo9AxssShkZWWF48ePo0WLFmrlFy5cwPPPP4/09HSRItMeWyyIiIioplMqBSzcdwML9twAAHRq5ITFQ56DnaXpM/YkfWKLRSXI5XKkpaVplKenp8PMzEyEiIiIiIiMl1QqwTshjfHD0OdgYSrDoRtJ6P/9Edx6WHM+7DU2TCwK9e3bF2PGjMGJEycgCAIEQcDx48fxf//3fwgPDxc7PCIiIiKj1KuFG9aP6wAPewvcTspAv8gj2HE5Dj5Tt8Jn6lbcZqJRbbArVKEnT54gIiICf//9t2pxvPz8fISHh2P58uWws7MTOcKKY1coIiIiqm2S0nMw7rczOHXnMSQAim5gpRJgzsstMLitt5jh1VqcFUpLgiAgNjYWzs7OuH//vmq62WbNmqFhw4YiR6c9JhZERERUG+XmK/He2vPYfCFOrVwmkeDw1G5ws+O6F/rGMRZaEgQBDRs2xL1799CwYUOEhYUhLCxM9KSif//+cHBwwCuvvCJqHERERETVgZmJFK+W0jKhEAQcuZEkQkRUHBMLAFKpFI0aNcKjR4/EDkXN22+/jZUrV4odBhEREVG14etsBalEs/z9dRfx3toLuPc40/BBEQAmFipz587F+++/j8uXL4sdikrXrl1hY2MjdhhERERE1YabnQVmhzdXPZdKgObuthAArDtzD92//gezNv+LpPQc8YI0UkwsCg0fPhwnT55EQEAALCws4OjoqPbQ1sGDBxEWFgZ3d3dIJBJs2rRJo05kZCR8fHxgbm6O4OBgnDx5Ug8/CREREVHtNqy9D45N647fR7fDkandsXVSJ2x8qwM6NKiDXIUSy4/eQed5+zF/13WkZueJHa7RMBE7gOpiwYIFej1eRkYGAgICMGrUKLz88ssa26OiojB58mQsWbIEwcHBWLBgAUJDQ3H9+nXUrVtXr7EQERER1TZudhZqg7VbeTtgzeh2OHwjCfN2XsPFeylYuO8mVh6/i7e6NsDw9j4wN5WJGHHtx1mhDEAikWDjxo3o16+fqiw4OBht27bF4sWLAQBKpRJeXl6YOHEipk6dqqp34MABLF68GOvWrSvz+Dk5OcjJedrcl5qaCi8vL84KRUREREZJEATs/DceX+28jlsPMwAArrbmeDukEQa29oSJjJ12KoqzQlXCtm3bsHPnTo3yXbt2Yfv27Xo9V25uLs6cOYOQkBBVmVQqRUhICI4dO6b18ebMmQM7OzvVw8vLS5/hEhEREdUoEokEL/q7Yec7nTHvlZbwsLdAfGo2pm24hBe+PYi/LzyAUsnP1vWNiUWhqVOnQqFQaJQrlUq1FgR9SEpKgkKhgIuLi1q5i4sL4uPjVc9DQkIwcOBAbNu2DZ6enmUmHdOmTUNKSorqERsbq9d4iYiIiGoiE5kUg9p4Yd97XTCjrx/qWJkhOikDE38/h7DFh3HgeiLYeUd/OMai0I0bN+Dn56dR3rRpU9y8eVOEiIA9e/ZUqJ5cLodcLkdkZCQiIyNLTZCIiIiIjJXcRIZRHX0xqK0XfjkUjZ8O3ca/D1Ix4tdTCPJ1xAcvNkHretpP1kPq2GJRyM7ODrdv39Yov3nzJqysrPR6LicnJ8hkMiQkJKiVJyQkwNXVtdLHHT9+PK5cuYJTp07pGiIRERFRrWMtN8HbIY1wcEo3jO7kCzMTKU5GJ2PAD8fwxvJTuBqXKnaINRoTi0IvvfQS3nnnHdy6dUtVdvPmTfzvf/9DeHi4Xs9lZmaG1q1bY+/evaoypVKJvXv3on379no9FxERERGpc7Qyw0d9/HDgva54ta0XZFIJ9l5LRO+Fh/DOH+cQ84iL7FUGE4tC8+bNg5WVFZo2bQpfX1/4+vqiWbNmqFOnDr7++mutj5eeno7z58/j/PnzAIDo6GicP38eMTExAIDJkyfjp59+wooVK3D16lWMGzcOGRkZGDlyZKV/hsjISPj5+aFt27aVPgYRERGRsXC3t8DcAS2x+93O6NPSDYIAbDr/AN2/OYCPN11CYmq22CHWKJxuthhBELB7925cuHABFhYWaNmyJTp37lypYx04cADdunXTKI+IiMDy5csBAIsXL8ZXX32F+Ph4BAYGYuHChQgODtblRwCg3bRgRERERFTg8v0UzNt5HQf/ewgAMDeVYuTzvvi/zg1gZ2kqcnTi0Oa+kolFLcTEgoiIiKjyjt9+hHk7ruFszBMAgK25CcZ2aYCRz/vA0sy45j5iYlFBCxcuxJgxY2Bubo6FCxeWW3fSpEkGiqryis8K9d9//zGxICIiIqokQRCw92oivtp5HdcT0gAAzjZyTOzeEK+29YaZiXGMKGBiUUG+vr44ffo06tSpA19f3zLrSSSSUmeMqq7YYkFERESkHwqlgM0X7mP+7v8Qm5wFAPBytMDkFxojPMADMqlE5AirFhMLI8fEgoiIiEi/cvOViDoVg4X7buJhWg4AoImLDd4PbYIezepCIqmdCQYTCyPHxIKIiIioamTm5mP50TtYcuAWUrPzAQDPedtjyotN0a5+HZGj0z8mFpUgCALWrVuH/fv3IzExEUqlUm37hg0bRIqs4jjGgoiIiMgwUjLzsOTgLfx6JBrZeQX3jZ0bO2NKaBP4e9iJHJ3+MLGohLfffhs//vgjunXrBhcXF43mrF9//VWkyLTHFgsiIiIiw0hMzcaifTfx+8kY5CsLbqv7tHTD/15ojPrO1iJHpzsmFpXg6OiI3377Db179xY7FJ0xsSAiIiIyrLuPMvDt7v/w14UHEARAJpVgYGtPvB3SCG52FmKHV2na3FcaxzxZFWBnZ4f69euLHQYRERER1UD16lhhwautsG1SJ4Q0qwuFUsAfp2LR5asD+HzrFSRn5IodYpVji0WhFStWYMeOHVi2bBksLGpmVskxFkRERETVw5m7yfhyx3WcjE4GAFjLTTC6U3280ckX1vKas8geu0JVQlZWFvr3748jR47Ax8cHpqbqy7afPXtWpMi0x65QREREROITBAH//PcQX+28jn8fpAIA6liZYXy3hhjazhtyE1mFjpOZmw+/GTsBAFc+CTXo6t/a3FfWnHSpikVERODMmTN4/fXXSx28TURERESkDYlEgq5N6qJzI2dsvRSH+bv/Q3RSBj7ZcgW/HI7G2yGN8HIrD5jIasfoBCYWhbZu3YqdO3eiY8eOYodCRERERLWIVCpBWIA7XvR3xboz9/Ddnhu4/yQLU9ZdxI//3ML7oU0Q2ty1xn+wXTvSIz3w8vJityEiIiIiqjKmMimGBHnjwPtd8WHvprC3NMWthxn4v9/Ool/kERy+kSR2iDphYlHom2++wZQpU3Dnzh2xQ6m0yMhI+Pn5oW3btmKHQkRERERlMDeVYUznBjg4pRsmdW8ISzMZLtxLweu/nMBrPx3H+dgnYodYKRy8XcjBwQGZmZnIz8+HpaWlxuDt5ORkkSLTHgdvExEREdUcSek5iNx/E6uPxyBXUbCKd2hzF7zXswkaudhw8HZNs2DBArFDICIiIiIj5GQtx8yw5nijoy8W7LmBDWfvYee/Cdh9JQH9W3ni/7o8XWstPiW72q7ozRaLWogtFkREREQ1142ENHyz6z/s+DceACCVAMrCO3apBJjzcgsMbuttkFi48nYFZWRkVGl9IiIiIiJtNXKxwZJhrbFp/PNo42OvSiqAggTjww2XEZeSJV6AZTDqxKJhw4aYO3cu4uLiyqwjCAJ2796NXr16YeHChQaMjoiIiIiMWaCXPSa/0ESjXCEIuJOUKUJE5TPqMRYHDhzAhx9+iFmzZiEgIABt2rSBu7s7zM3N8fjxY1y5cgXHjh2DiYkJpk2bhrFjx4odMhEREREZEV8nK7WuUAAgk0jg42QpXlBl4BgLADExMVi7di0OHTqEu3fvIisrC05OTmjVqhVCQ0PRq1cvyGQVW3JdTJGRkYiMjIRCocB///3HMRZEREREtcCqY3cw/a9/AVTvMRZMLGohDt4mIiIiqj2KTze7739dDDorFAdvExERERHVQq525mKHUCYmFkREREREpDMmFkREREREpDMmFkREREREpDMmFkREREREpDOjXsfi4sWLFa7bsmXLKoyEiIiIiKhmM+rEIjAwEBKJBGXNuFu0TSKRQKFQGDg6IiIiIqKaw6gTi+joaLFD0KviC+QRERERERmSUScW9erVEzsEvRo/fjzGjx+vWsiEiIiIiMhQjDqxKOn69etYtGgRrl69CgBo1qwZJk6ciCZNmogcGRERERFR9cZZoQqtX78e/v7+OHPmDAICAhAQEICzZ8/C398f69evFzs8IiIiIqJqjS0WhaZMmYJp06bhk08+USufOXMmpkyZggEDBogUGRERERFR9ScRypoSychYWlri4sWLaNiwoVr5jRs3EBAQgMzMTJEi017RGIuUlBTY2tqKHQ4RERER1VDa3FeyK1Shrl274tChQxrlhw8fRqdOnUSIiIiIiIio5mBXqELh4eH44IMPcObMGbRr1w4AcPz4caxduxazZ8/G5s2b1eoSEREREdFT7ApVSCqtWONNTVgsj12hiIiIiEgftLmvZItFIaVSKXYIREREREQ1FhOLcjx58gT29vZih6G1okao1NRUkSMhIiIiopqs6H6yIp2cmFgU+vLLL+Hj44PBgwcDAAYOHIj169fDzc0N27ZtQ0BAgMgRVlxaWhoAwMvLS+RIiIiIiKg2SEtLg52dXbl1OMaikK+vL1avXo0OHTpg9+7dGDRoEKKiovDnn38iJiYGu3btEjvEClMqlXjw4AFsbGwgkUieWb9t27Y4deqUzvVSU1Ph5eWF2NhYoxrbUdHXzxAMEYu+z6HL8Sq7rzb76bOuMV4j1en6AGreNaLrsSqzv7b78H+IbqrTNVLTrg9dj8f/IRUjCALS0tLg7u7+zDHJbLEoFB8fr/qEf8uWLRg0aBB69uwJHx8fBAcHixyddqRSKTw9PStcXyaTVegNWtF6tra2RvVPoaKviyEYIhZ9n0OX41V2X232q4q6xnSNVKfrA6h514iux6rM/truw/8huqlO10hNuz50PR7/h1Tcs1oqinAdi0IODg6IjY0FAOzYsQMhISEACrK06j4LlK7Gjx+v13rGpjq9LoaIRd/n0OV4ld1Xm/2qqq6xqG6vSU27RnQ9VmX213Yf/g/RTXV6XWra9aHr8fg/RP/YFarQhAkTsGXLFjRq1Ajnzp3DnTt3YG1tjT/++APz5s3D2bNnxQ6x2uM0t0Tl4zVCVDZeH0TlqwnXCLtCFfr222/h4+OD2NhYzJs3D9bW1gCAuLg4vPXWWyJHVzPI5XLMnDkTcrlc7FCIqiVeI0Rl4/VBVL6acI2wxYKIiIiIiHRm1C0WmzdvRq9evWBqaorNmzeXWzc8PNxAURERERER1TxG3WIhlUoRHx+PunXrljt9lkQiqfUDuImIiIiIdGHUiQUREREREekHp5slIiIiIiKdMbFAwUrVy5YtQ9++feHv748WLVogPDwcK1euBBt09GfLli1o0qQJGjVqhJ9//lnscIiqlf79+8PBwQGvvPKK2KEQVTuxsbHo2rUr/Pz80LJlS6xdu1bskIiqjSdPnqBNmzYIDAyEv78/fvrpJ9FiMfquUIIgICwsDNu2bUNAQACaNm0KQRBw9epVXLp0CeHh4di0aZPYYdZ4+fn58PPzw/79+2FnZ4fWrVvj6NGjqFOnjtihEVULBw4cQFpaGlasWIF169aJHQ5RtRIXF4eEhAQEBgYiPj4erVu3xn///QcrKyuxQyMSnUKhQE5ODiwtLZGRkQF/f3+cPn1alHsso2+xWL58OQ4ePIi9e/fi3Llz+P333/HHH3/gwoUL2LNnD/bt24eVK1eKHWaNd/LkSTRv3hweHh6wtrZGr169sGvXLrHDIqo2unbtChsbG7HDIKqW3NzcEBgYCABwdXWFk5MTkpOTxQ2KqJqQyWSwtLQEAOTk5EAQBNF63Bh9YvH777/jww8/RLdu3TS2de/eHVOnTsXq1atFiKx6OXjwIMLCwuDu7g6JRFJqK05kZCR8fHxgbm6O4OBgnDx5UrXtwYMH8PDwUD338PDA/fv3DRE6UZXT9fogqu30eY2cOXMGCoUCXl5eVRw1kWHo4/p48uQJAgIC4Onpiffffx9OTk4Gil6d0ScWFy9exIsvvljm9l69euHChQsGjKh6ysjIQEBAACIjI0vdHhUVhcmTJ2PmzJk4e/YsAgICEBoaisTERANHSmR4vD6IyqevayQ5ORnDhw/H0qVLDRE2kUHo4/qwt7fHhQsXEB0djTVr1iAhIcFQ4asTjJypqanw4MGDMrffv39fMDMzM2BE1R8AYePGjWplQUFBwvjx41XPFQqF4O7uLsyZM0cQBEE4cuSI0K9fP9X2t99+W1i9erVB4iUypMpcH0X2798vDBgwwBBhEommstdIdna20KlTJ2HlypWGCpXI4HT5H1Jk3Lhxwtq1a6syzDIZfYuFQqGAiUnZC5DLZDLk5+cbMKKaJzc3F2fOnEFISIiqTCqVIiQkBMeOHQMABAUF4fLly7h//z7S09Oxfft2hIaGihUykcFU5PogMmYVuUYEQcCIESPQvXt3DBs2TKxQiQyuItdHQkIC0tLSAAApKSk4ePAgmjRpIkq8Zd9RG4miP1ZyubzU7Tk5OQaOqOZJSkqCQqGAi4uLWrmLiwuuXbsGADAxMcE333yDbt26QalUYsqUKZwRioxCRa4PAAgJCcGFCxeQkZEBT09PrF27Fu3btzd0uEQGV5Fr5MiRI4iKikLLli1V/c9XrVqFFi1aGDpcIoOqyPVx9+5djBkzRjVoe+LEiaJdG0afWERERDyzzvDhww0QSe0XHh6O8PBwscMgqpb27NkjdghE1VbHjh2hVCrFDoOoWgoKCsL58+fFDgMAEwv8+uuvYodQ4zk5OUEmk2kMFEpISICrq6tIURFVD7w+iMrHa4SobDXt+jD6MRakOzMzM7Ru3Rp79+5VlSmVSuzdu5ddOcjo8fogKh+vEaKy1bTrw+hbLKhi0tPTcfPmTdXz6OhonD9/Ho6OjvD29sbkyZMRERGBNm3aICgoCAsWLEBGRgZGjhwpYtREhsHrg6h8vEaIylarrg9R5qKiGmf//v0CAI1HRESEqs6iRYsEb29vwczMTAgKChKOHz8uXsBEBsTrg6h8vEaIylabrg+JIIi05jcREREREdUaHGNBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6Y2JBREREREQ6MxE7ANI/pVKJBw8ewMbGBhKJROxwiIiIiKiGEgQBaWlpcHd3h1RafpsEE4ta6MGDB/Dy8hI7DCIiIiKqJWJjY+Hp6VluHSYWtZCNjQ2AgjeAra2tyNEQERERUU2VmpoKLy8v1f1leZhY1EJF3Z9sbW2ZWBARERGRzirSvZ6Dt4mIiIiISGdMLIiIiIiISGdMLIiIiIiISGdMLIiIiIiISGdMLIiIiEhUmbn58Jm6FT5TtyIzN1/scIiokphYEBERERGRzphYEBERERGRzphYVGORkZHw8fGBubk5goODcfLkSbFDIiIiIiIqFROLaioqKgqTJ0/GzJkzcfbsWQQEBCA0NBSJiYlih0ZElRSXkoWjt5IQl5IldihERER6x5W3q6n58+dj9OjRGDlyJABgyZIl2Lp1K5YtW4apU6eKHF3p4lKyEJ2UAV8nK7jZWYgdDlG1kZmbjxVH72DezusQBEAiAd4JaYTwAA+YyiQwk0lhKpPCzKTgq6lMUqEVTqs7/k0gIjIuTCyqodzcXJw5cwbTpk1TlUmlUoSEhODYsWMiRla2qFMxmLbhEpSFN03/e6Ex+rXygNxEBjMTKeQmUpjJpJBKa/7NEhk3QRCQmp2P5IxcJGfk4FF6bsH3mblILvz+UUZhWUYuHmXkIDtPWeIYwLe7b+Db3TfKPI+pTFKYZBQmHTIJTE1KPFdLRqQwMyllH5lUtZ+ZTKJeXyaFabF9zGRPExtTE2mJhOdpAmRa+NxUWvY1verYHUz/618AgFQCzHm5BQa39dbfL6KWy8zNh9+MnQCAK5+EwtKM/66JqPrjX6pqKCkpCQqFAi4uLmrlLi4uuHbtmkb9nJwc5OTkqJ6npqZWeYzFxaVkqZIKoOCm6etd/+HrXf9p1DWRFtzYmBXetMhNC76aFSUghTcxmtufPjTryMqtU5TcFNVnokPFKZQCnmSqJwSPMoqShBwkZ+apJRCPM3ORpxD0cm4LUykEALn5StX1UyRPISBPoQCg0Mu5qoqJVKJKRoqSFqkEuP8kW1VHKQAfrL+ELRfjYGdhCnNTGeQmUpibymBuWnCNlvq1WL2yvprK2KO3tolPyUZ9Z2uxwyCiSmBiUQvMmTMHs2fPFu380UkZGjdFQMENR36JDflKAfm5CmTmVo+bJROppCDJMJGWSD6eJjoayU0pSYxGclOyjiqZkZVyLiY6+pSbr8TjzFxVIvAoI6dY60HxVoUcPM7Mw+PMXAiVyBOszGRwsDJDHSszOFqZwdFKjjrWRd8/La9jJUdOvgKhCw6qXScyiQT73uuq6iKkUArIUyiRq1AiL19ZmFgUPlcokZtf9LWgvOiRqxAK6xc8cort+/R4JZ4rBOTmK56eQ7W/+jnz8gVVPLmF5SVfq3ylgHylAll5z37NDt1I0v6FfgZZ4TVcMukonpSYFz4v+CqFuYlM9dXcVKZWJjeRlVKn+P4FX00MmNDUlhttQRCgUAqF7xkBCoWAPKUSCqWAP0/FqOqFzP+nUi1c7HpHJD4mFhWUk5MDuVxukHM5OTlBJpMhISFBrTwhIQGurq4a9adNm4bJkyernqempsLLy6vK4yzi62QFqQQaN02HPugGV1vzgpuYwpuX3HwlcvIVhV+VauW5hc+LtpdVJ6dYXfU6ilK3q/YrfF5cUaKTUU0SnaLuJqUlOnIT9SREMzmRqSUyJeuUTJBKJjrykuc0QKJTkRuBzNz8p92N1LoYFbYoFO96lJ6LtJzKLa5lZ2FaLElQfxQkDHK17eamMq2OP+flFvhww2UoBAEyiQRfvOyv9jPLpBLIpDKtj2topSVARddbUfISn5KFsb+dVUtCJBLg/dAmMDeRITtfgZw8peprTr4C2eV8zc5TICf/6dfi17FCKSBThA8rZFIJzEskNGZltKpUplVmz5Wnf/97zP8H74Q0Qkgzl6c35goB+YU35QXfC1AoC34fT+soC8sLfmfF91Uolaob/KJjlbzZLzpGaecseZ5nnrOwrCKKWrgW7b0Bd3tLONvK4WJjjrq2ctS1kaNuse/tLEwhkUjUuuPqq+udrokKEx0yRhJBqMxndbXf9u3b8ccff+DQoUOIjY2FUqmElZUVWrVqhZ49e2LkyJFwd3evsvMHBwcjKCgIixYtAgAolUp4e3tjwoQJzxy8nZqaCjs7O6SkpMDW1rbKYiwu6lSMxk1TdexPLQjqSY56wlOY2OSVSEoU6olOWYnL00RHUXqd4olQsbLqrGSio0peNBKU0pITzUSneHJz+u5j/H4iBgIACYCODZ3gbCN/5viEipBKoJ4YWMk1kwUrMzgWtjA4WJoZpEtNXEoW7iRlwsfJstbfaFTl3wSlsuA6zs4rPyEpKzHJKfG84DiaZQVfC6/pvOp/vdZUJT+Y0oaZiRSOlmaIT81WK5cAGNHBBw5WZqouegV/l5522TMrHC8kL/xafEzR1osP8O2eG6r4PnnJH0OCvCGr4IctpY0x6tzYWSPRYPJBNYE295VMLErYuHEjPvjgA6SlpaF3794ICgqCu7s7LCwskJycjMuXL+PQoUM4duwYRowYgU8//RTOzs56jyMqKgoRERH48ccfERQUhAULFuDPP//EtWvXNMZelCRGYgEY102TvpSW6BRPbEpLUFQtOmXUKd7iU1odzcSp+ic6ZjJpidaD4t2N5KpyB8uCMjsLU3YrqwZq298EhbKgdabsJKTsBCVHrU75yVBKZh6SMnI1zm9nYQorMxlkMglMpFKYSCWQFY5xkUklMJFKYFK4raBcUlguhUnh96ZSaeH+JcslkBU+LzpuwfGkal+fHleqOl/xc2get/j5CmMr9lwmlSA+NRvPz92nllxIJcDiIa2gEIDEtBwkpmXjYWoOEtKykZiag8S0HKRUpP+dnkklUEtKiiZZeDqxgQSCAPz7oOyxjhIJMCW0CcxNZZj99xXVcYsnH1ZmMmTkKphwULXAxEIH7du3x8cff4xevXpBKi37E8z79+9j0aJFcHFxwbvvvlslsSxevBhfffUV4uPjERgYiIULFyI4OPiZ+4mVWFDNV/RJcNmtMaUnLpp1Sm/xKUpsEtOycem+5j/eIUFeaOXtoDY+wdHaDFZmslox/SpRRcSlZGncaMskEhye2q3W3mRWZhax7DwFHqbl4GpcKsauOoPiNzMSAAOe84CpiazY+KSn44yKd9/LLdGlLzMnX5TusRIAJW/IJABGd/LFyI6+tfZ3T9UfEwsjx8SCqjtjvHEi0oaxTddbfHrdff/rovVgdX12vSvt75NUAmx/uxMcrMwKJjnIV58MIa/YJAcJqTmYuv6iRpKgD5V5bYh0pc19JQdva0GhUODSpUuoV68eHBwcxA6HqMZys7N45mBmImM2oLWnKrHYM9m4biZd7cy13mdwW290buysl653Zf19auKqzQd1gmp/KQpaIoonGlIAggRaz0jX45t/2IJB1RoTi3K88847aNGiBd544w0oFAp06dIFR48ehaWlJbZs2YKuXbuKHSJRjaXPGwGi2qwyN9rGyM3OQm9/R3T9+1Ry/4P/PdRIVACUm3yURgCw9FA0fj4cXetbsahmYleocnh6emLTpk1o06YNNm3ahPHjx2P//v1YtWoV9u3bhyNHjogdYqnYFYqIiGoSY1hpvLTJDIqXFU8+KoLdR8lQ2BVKT5KSklTrRmzbtg0DBw5E48aNMWrUKHz33XciR0dEREQ1RWktKsXLirdyWJpJsfViPH46dLvMVgyFIOBOUiYTC6pWDLd0aA3k4uKCK1euQKFQYMeOHXjhhRcAAJmZmZDJqvciVkRERFSzuNlZoH2DOgjwcsCHfZrh6LTuGNOpPkqbE08CwMfJ0tAhEpWLiUU5Ro4ciUGDBsHf3x8SiQQhISEAgBMnTqBp06YiR0dERES1mZudhVqCUXx5HgFA+zn74DN1K24/TBctRqLiOMbiGdatW4fY2FgMHDgQnp6eAIAVK1bA3t4eL730ksjRlY5jLIiIiGqfojEZWy4+wOoTMapyY5iSmMTDdSyMHBMLIiKi2uve40x0/HK/WhkHc1NV4eBtPdq7dy/27t2LxMREKJVKtW3Lli0TKSoiIiIyVjHJmRplHMxN1QETi3LMnj0bn3zyCdq0aQM3NzdIJKUNnyIiIiIyHF8nK0hKLLAnk0g4mJtEx8SiHEuWLMHy5csxbNgwsUMhIiIiAlAwqPuT8Oaq1dmlEuCLl/3ZWkGi46xQ5cjNzUWHDh3EDoOIiIhIzbD2PrC3MAUALB8RxIHbVC0wsSjHm2++iTVr1ogdBhEREZEG7zoFXZ+y8xUiR0JUgF2hypGdnY2lS5diz549aNmyJUxNTdW2z58/X6TIiIiIyNh5Oljg4r0U3H+SJXYoRACYWJTr4sWLCAwMBABcvnxZbRsHchMREZGYPOwLxlTce8zEgqoHJhbl2L9//7MrEREREYnA06GgK9S9x5rTzxKJgWMsiIiIiGogT4eCFgt2haLqgi0Wz3D69Gn8+eefiImJQW5urtq2DRs2iBQVERERGTsPB3aFouqFLRbl+OOPP9ChQwdcvXoVGzduRF5eHv7991/s27cPdnZ2YodHRERERqxojMWTzDykZeeJHA0RE4tyffHFF/j222/x999/w8zMDN999x2uXbuGQYMGwdub80UTERGReGzMTWFvWTBjJbtDUXXAxKIct27dQp8+fQAAZmZmyMjIgEQiwbvvvoulS5eKHB0REREZO9U4C3aHomqAiUU5HBwckJaWBgDw8PBQTTn75MkTZGZyBgYiIiISF6ecpeqEg7fL0blzZ+zevRstWrTAwIED8fbbb2Pfvn3YvXs3evToIXZ4REREZOQ45SxVJ0wsyrF48WJkZ2cDAD766COYmpri6NGjGDBgAD7++GORoyMiIiJjxylnqTphYlEOR0dH1fdSqRRTp04VMRoiIiIidewKRdUJE4sSUlNTYWtrq/q+PEX1iIiIiMTwtCsUEwsSHxOLEhwcHBAXF4e6devC3t4eEolEo44gCJBIJFAoFCJESERERFSgaJG85IxcZObmw9KMt3YkHr77Sti3b5+qC9T+/ftFjoaIiIiobHYWprAxN0Fadj7uP85CIxcbsUMiI8bEooQuXbqU+j0RERFRdeTpYImrcam4x8SCRMbEooSLFy9WuG7Lli2rMBIiIiKiZ/N0sChMLDjlLImLiUUJgYGBkEgkqnEU5eEYCyIiIhJb0ZSz9zjlLImMK2+XEB0djdu3byM6Ohrr16+Hr68vvv/+e5w7dw7nzp3D999/jwYNGmD9+vVih0pERETEKWep2mCLRQn16tVTfT9w4EAsXLgQvXv3VpW1bNkSXl5emD59Ovr16ydChERERERPccpZqi7YYlGOS5cuwdfXV6Pc19cXV65cESEiIiIiInWq1beZWJDImFiUo1mzZpgzZw5yc3NVZbm5uZgzZw6aNWsmYmREREREBYoSi6T0HGTncfwniYddocqxZMkShIWFwdPTUzUD1MWLFyGRSPD333+LHB0RERFRwVoW1nITpOfk497jLDSsay12SGSkmFiUIygoCLdv38bq1atx7do1AMDgwYPx2muvwcrKSuToiIiIiACJRAJPBwtci0/D/SdMLEg8TCyewcrKCmPGjBE7DCIiIqIyedgXJBZcy4LExMSiAq5cuYKYmBi1sRYAEB4eLlJERERERE+p1rLgAG4SEROLcty+fRv9+/fHpUuXVIvmAVAtnMcF8oiIiKg64JSzVB1wVqhyvP322/D19UViYiIsLS3x77//4uDBg2jTpg0OHDggdnhEREREAIpPOcuuUCQetliU49ixY9i3bx+cnJwglUohlUrRsWNHzJkzB5MmTcK5c+fEDpGIiIgIHuwKRdUAWyzKoVAoYGNjAwBwcnLCgwcPABSszn39+nUxQyMiIiJSKeoKlZjGtSxIPGyxKIe/vz8uXLgAX19fBAcHY968eTAzM8PSpUtRv359scMjIiIiAgA4WJrC0kyGzFwF4lKy4evEafHJ8NhiUY6PP/4YSqUSAPDJJ58gOjoanTp1wrZt27Bw4UKRoyMiIiIqIJFI4GFf1B2K4yxIHGyxKEdoaKjq+4YNG+LatWtITk6Gg4ODamYoIiIiourA08ECNxLTOc6CRMMWizLk5eXBxMQEly9fVit3dHRkUkFERETVTtE4i/tMLEgkTCzKYGpqCm9vb65VQURERDXC05mh2BWKxMHEohwfffQRPvzwQyQnJ4sdChEREVG5uPo2iY1jLMqxePFi3Lx5E+7u7qhXrx6srNRnWDh79qxIkRERERGp4+rbJDYmFuXo16+f2CEQERERVUhRi0VCWjZy85UwM2HHFDIsJhblmDlzptghEBEREVVIHSszmJtKkZ2nRFxKFurV4VoWZFhMZUsQBEHsEIiIiIi0pr6WBbtDkeExsSihefPm+OOPP5Cbm1tuvRs3bmDcuHGYO3eugSIjIiIiKh+nnCUxsStUCYsWLcIHH3yAt956Cy+88ALatGkDd3d3mJub4/Hjx7hy5QoOHz6Mf//9FxMmTMC4cePEDpmIiIgIAKecJXExsSihR48eOH36NA4fPoyoqCisXr0ad+/eRVZWFpycnNCqVSsMHz4cQ4cOhYODg97Pf+fOHXz66afYt28f4uPj4e7ujtdffx0fffQRzMzM9H4+IiIiqj045SyJiYlFGTp27IiOHTsa/LzXrl2DUqnEjz/+iIYNG+Ly5csYPXo0MjIy8PXXXxs8HiIiIqo5VFPOPmFiQYbHxKKaefHFF/Hiiy+qntevXx/Xr1/HDz/8wMSCiIiIylXUYsExFiQGJhY1QEpKChwdHcvcnpOTg5ycHNXz1NRUQ4RFRERE1Yxn4axQcSlZyFMoYSrjPD1kOHy3VXM3b97EokWLMHbs2DLrzJkzB3Z2dqqHl5eXASMkIiKi6sLJWg4zEymUAhCfki12OGRkmFgYyNSpUyGRSMp9XLt2TW2f+/fv48UXX8TAgQMxevToMo89bdo0pKSkqB6xsbFV/eMQERFRNSSVSlStFhzATYbGrlAG8r///Q8jRowot079+vVV3z948ADdunVDhw4dsHTp0nL3k8vlkMvl+giTiIiIajgPBwvcTsoonHK2jtjhkBFhYvEMt27dwq+//opbt27hu+++Q926dbF9+3Z4e3ujefPmFT6Os7MznJ2dK1T3/v376NatG1q3bo1ff/0VUikbloiIiKhiOOUsiYV3rOX4559/0KJFC5w4cQIbNmxAeno6AODChQuYOXNmlZzz/v376Nq1K7y9vfH111/j4cOHiI+PR3x8fJWcj4iIiGoX1erbnHKWDIwtFuWYOnUqPvvsM0yePBk2Njaq8u7du2Px4sVVcs7du3fj5s2buHnzJjw9PdW2CYJQJeckIiKi2sPDnqtvkzjYYlGOS5cuoX///hrldevWRVJSUpWcc8SIERAEodQHERER0bOwKxSJhYlFOezt7REXF6dRfu7cOXh4eIgQEREREVH5irpCxadkI1+hFDkaMiZMLMrx6quv4oMPPkB8fDwkEgmUSiWOHDmC9957D8OHDxc7PCIiIiINdW3kMJVJkK8UkJCW8+wdiPSEiUU5vvjiCzRt2hReXl5IT0+Hn58fOnfujA4dOuDjjz8WOzwiIiIiDVKpBO5F4yySOc6CDIeDt8thZmaGn376CTNmzMClS5eQnp6OVq1aoVGjRmKHRkRERFQmTwcL3H2UiXuPsxAsdjBkNJhYVICXlxe8vLygUChw6dIlPH78GA4ODmKHRURERFQqT3tLAI845SwZFLtCleOdd97BL7/8AgBQKBTo0qULnnvuOXh5eeHAgQPiBkdERERUBg8HTjlLhsfEohzr1q1DQEAAAODvv//G7du3ce3aNbz77rv46KOPRI6OiIiIqHSccpbEwMSiHElJSXB1dQUAbNu2DYMGDULjxo0xatQoXLp0SeToiIiIiErH1bdJDEwsyuHi4oIrV65AoVBgx44deOGFFwAAmZmZkMlkIkdHREREVLriXaHYHYoMhYlFOUaOHIlBgwbB398fEokEISEhAIATJ06gadOmIkdHREREVLrd/8YDABRKoPO8/Yg6FSNyRGQMOCtUOWbNmgV/f3/ExsZi4MCBkMvlAACZTIapU6eKHB0RERGRpriULHyy5YrquVIAPtxwGZ0bO8PNzkLEyKi2Y2LxDK+88opGWUREhAiREBERET1bdFIGlIJ6mUIQcCcpk4kFVSkmFs+QkZGBf/75BzExMcjNzVXbNmnSJJGiIiIiIiqdr5MVpBKoJRdSCeDjZCleUGQUmFiU49y5c+jduzcyMzORkZEBR0dHJCUlwdLSEnXr1mViQURERNWOm50FZoc3x/S//lWVRXTwYWsFVTkO3i7Hu+++i7CwMDx+/BgWFhY4fvw47t69i9atW+Prr78WOzwiIiKiUg1r74Nj07qjl3/BtPkPOO0sGQATi3KcP38e//vf/yCVSiGTyZCTkwMvLy/MmzcPH374odjhEREREZXJzc4C777QGACw92oiEtOyRY6IajsmFuUwNTWFVFrwEtWtWxcxMQVTtdnZ2SE2NlbM0IiIiIieqbGLDZ7ztke+UsC6M/fEDodqOSYW5WjVqhVOnToFAOjSpQtmzJiB1atX45133oG/v7/I0RERERE926tB3gCAqFOxUJacLopIj5hYlOOLL76Am5sbAODzzz+Hg4MDxo0bh4cPH2Lp0qUiR0dERET0bH1busFGboK7jzJx/PYjscOhWoyzQpWjTZs2qu/r1q2LHTt2iBgNERERkfYszUwQHuiO1Sdi8PupWHRo6CR2SFRLscWCiIiIqJYbUtgdaselOOz8Nx5xKZwlivSPiUU5EhISMGzYMLi7u8PExAQymUztQURERFQT+HvYwc3OHHlKAWNXncHzc/ch6lSM2GFRLcOuUOUYMWIEYmJiMH36dLi5uUEikYgdEhEREZHW4lKyEJ/ydLpZpQB8uOEyOjd25sJ5pDdMLMpx+PBhHDp0CIGBgWKHQkRERFRp0UkZKDkflEIQ0H7OPuz7XxfUd7YWJS6qXZhYlMPLywuCwGnZiIiIqGbzdbKCVFLQUlFSyPx/VOVMMqqnzNx8+M3YCQC48kkoLM2q5y08x1iUY8GCBZg6dSru3LkjdihEREREleZmZ4HZ4c1L3VY82QiZ/w/HXlClVc90R0QODg5qYykyMjLQoEEDWFpawtTUVK1ucnKyocMjIiIiqpRh7X0Q4ueCrRfj8NnWq6XWUQrAtA2X8Jy3Axq52ABQ/7ScLRpUHiYWJSxYsEDsEIiIiIiqhJudBfq0dMMX266W2i0KKEguQhccRAtPe7Sr74jMnHzVtpD5/2DOyy0wuK23VuetKV15SDf8rZYQEREhdghEREREVaaoW9T0v/4ts45SAC7EPsGF2Cca5VPXX8KtxHQ0qGsNZxs56tqYw9lGjjpWZjCRPbuXfXxKts6tHkxUqif+FkqhVCrx1VdfYfPmzcjNzUWPHj0wc+ZMWFhwOjYiIiKq+Yq6Rd1JysSZu8n4etd/AACpBJjzcgt0auSM47cf4a/z9/HPf0lq+woAlh6K1jimRALUsTKDc2GiUddGrvp6NS5VVa+yrR5U/TGxKMXnn3+OWbNmISQkBBYWFvjuu++QmJiIZcuWiR0aERERkV642VnAzc4C7RvUwYDWnriTlAkfJ0vVuhYvP+eJ9g3q4Pm5+9S6TUkA9G3phvScfDxMz0Fiag6S0nOgFICk9FwkpefialzZ51UKwAfrL2H9mXto7GqDeo5WqFfHEvXqWMHb0RIWZlyEuKZiYlGKlStX4vvvv8fYsWMBAHv27EGfPn3w888/QyrlRFpERERUuxQlGaWVF+82VdSiUbK1QaEUkJyRi4dpOUhMy8bDtBxV0nE1PhUnbmtOeHPyzmOcvPNYo7yujRz16ljCW5VwFCQd9RwtYW9pqrFgsT66VpF+SAQu1KBBLpfj5s2b8PLyUpWZm5vj5s2b8PT0FDGyiklNTYWdnR1SUlJga2srdjhERERUg+k6K1RcSpZGq4dUAkx9sSlSsvNw91EmYpIzcScpA6nZ+WUfCICNuQnq1bGEIAD/PijoXiUB0MvfFc/Vc4CJVAITmVTtq0wqgalMApm0qLygzEQqhYlMUqyOtLC82DEK68lkEtVzmVSikdxUNTFn5tLmvpKJRSlkMhni4+Ph7OysKrOxscHFixfh6+srYmQVw8SCiIiIqpNVx+48s9UDAJ5k5uLuo0zcTc5EzKOMgu8fZeJucgYSUnMMHXaZihIMzQSmeHJSkMyYyorVLUxmVImNVAKZTAJTqXriYyJV3/dKXCoOXH8IoPzXryowsdCRVCpFr169IJfLVWV///03unfvDisrK1XZhg0bxAjvmZhYEBERUXWij0/cs3IViH2ciZ3/xuObwsHmxT3foA7srcyQr1BCoRSQrxSQrxCQryx4nqcQipUr1b7PVwqFdQrrFj5XlDUnr8hkEgkOT+1Wavc1fdPmvpJjLEpR2pSzr7/+ugiREBEREdV8lmYmuDO3j07HsDCTobGLDWzMTfDt7v/UulbJJBJ8PShA7zfagiCoko6ykpCyExgl8hWa+xYvz1MKUKjKC+sWHqvoecyjDOz4N0EtLoUg4E5SpkESC20wsSjFr7/+KnYIRERERFSK0gaUf/Gyf5XcZEskBeMzTEWcqCouJQu7riRoJFI+TpbiBVUGTnFERERERDXKgNZPJ9PZM7lLrV4ToyiRKlKViZSumFgQERERUY3lamcudghVrqYkUuwKRUREREQ1ij7GbNRU1TmRYosFERERERHpjIkFERERERHpjIkFERERERHpjIkFERERERHpjIkFERERERHpjLNCERERERFVYzVlFiy2WBARERERkc6YWBARERERkc6YWBARERERkc6YWBARERERkc44eLsWEgQBAJCamipyJERERERUkxXdTxbdX5aHiUUtlJaWBgDw8vISORIiIiIiqg3S0tJgZ2dXbh2JUJH0g2oUpVKJBw8ewMbGBhKJ5Jn127Zti1OnTulcLzU1FV5eXoiNjYWtra1WMddkFX39DMEQsej7HLocr7L7arOfPusa4zVSna4PoOZdI7oeqzL7a7sP/4fopjpdIzXt+tD1ePwfUjGCICAtLQ3u7u6QSssfRcEWi1pIKpXC09OzwvVlMlmF3qAVrWdra2tU/xQq+roYgiFi0fc5dDleZffVZr+qqGtM10h1uj6AmneN6Hqsyuyv7T78H6Kb6nSN1LTrQ9fj8X9IxT2rpaIIB28Txo8fr9d6xqY6vS6GiEXf59DleJXdV5v9qqqusahur0lNu0Z0PVZl9td2H/4P0U11el1q2vWh6/H4P0T/2BWK9CY1NRV2dnZISUmpNp++EFUnvEaIysbrg6h8NeEaYYsF6Y1cLsfMmTMhl8vFDoWoWuI1QlQ2Xh9E5asJ1whbLIiIiIiISGdssSAiIiIiIp0xsSAiIiIiIp0xsSAiIiIiIp0xsSAiIiIiIp0xsSCD2bJlC5o0aYJGjRrh559/Fjscomqlf//+cHBwwCuvvCJ2KETVTmxsLLp27Qo/Pz+0bNkSa9euFTskomrjyZMnaNOmDQIDA+Hv74+ffvpJtFg4KxQZRH5+Pvz8/LB//37Y2dmhdevWOHr0KOrUqSN2aETVwoEDB5CWloYVK1Zg3bp1YodDVK3ExcUhISEBgYGBiI+PR+vWrfHff//ByspK7NCIRKdQKJCTkwNLS0tkZGTA398fp0+fFuUeiy0WZBAnT55E8+bN4eHhAWtra/Tq1Qu7du0SOyyiaqNr166wsbEROwyiasnNzQ2BgYEAAFdXVzg5OSE5OVncoIiqCZlMBktLSwBATk4OBEGAWO0GTCyoQg4ePIiwsDC4u7tDIpFg06ZNGnUiIyPh4+MDc3NzBAcH4+TJk6ptDx48gIeHh+q5h4cH7t+/b4jQiaqcrtcHUW2nz2vkzJkzUCgU8PLyquKoiQxDH9fHkydPEBAQAE9PT7z//vtwcnIyUPTqmFhQhWRkZCAgIACRkZGlbo+KisLkyZMxc+ZMnD17FgEBAQgNDUViYqKBIyUyPF4fROXT1zWSnJyM4cOHY+nSpYYIm8gg9HF92Nvb48KFC4iOjsaaNWuQkJBgqPDVCURaAiBs3LhRrSwoKEgYP3686rlCoRDc3d2FOXPmCIIgCEeOHBH69eun2v72228Lq1evNki8RIZUmeujyP79+4UBAwYYIkwi0VT2GsnOzhY6deokrFy50lChEhmcLv9DiowbN05Yu3ZtVYZZJrZYkM5yc3Nx5swZhISEqMqkUilCQkJw7NgxAEBQUBAuX76M+/fvIz09Hdu3b0doaKhYIRMZTEWuDyJjVpFrRBAEjBgxAt27d8ewYcPECpXI4CpyfSQkJCAtLQ0AkJKSgoMHD6JJkyaixGsiylmpVklKSoJCoYCLi4tauYuLC65duwYAMDExwTfffINu3bpBqVRiypQpnBGKjEJFrg8ACAkJwYULF5CRkQFPT0+sXbsW7du3N3S4RAZXkWvkyJEjiIqKQsuWLVX9z1etWoUWLVoYOlwig6rI9XH37l2MGTNGNWh74sSJol0bTCzIYMLDwxEeHi52GETV0p49e8QOgaja6tixI5RKpdhhEFVLQUFBOH/+vNhhAODgbdIDJycnyGQyjYFCCQkJcHV1FSkqouqB1wdR+XiNEJWtpl0fTCxIZ2ZmZmjdujX27t2rKlMqldi7dy+7cpDR4/VBVD5eI0Rlq2nXB7tCUYWkp6fj5s2bqufR0dE4f/48HB0d4e3tjcmTJyMiIgJt2rRBUFAQFixYgIyMDIwcOVLEqIkMg9cHUfl4jRCVrVZdH6LMRUU1zv79+wUAGo+IiAhVnUWLFgne3t6CmZmZEBQUJBw/fly8gIkMiNcHUfl4jRCVrTZdHxJBEGnNbyIiIiIiqjU4xoKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHTGxIKIiIiIiHRmou0OXbp0wRtvvIGBAwfCwsKiKmIiHSmVSjx48AA2NjaQSCRih0NERERENZQgCEhLS4O7uzuk0vLbJCSCIAjaHPydd97BmjVrkJOTg0GDBuGNN95Au3btdAqY9OvevXvw8vISOwwiIiIiqiViY2Ph6elZbh2tEwsAyM/Px+bNm7FixQps374dDRs2xKhRozBs2DC4uLhUOmDSj5SUFNjb2yM2Nha2trZih0NERERENVRqaiq8vLzw5MkT2NnZlVu3UolFcYmJiVi6dCk+//xzKBQK9O7dG5MmTUL37t11OazR27JlC/73v/9BqVTigw8+wJtvvlnhfVNTU2FnZ4eUlBQmFkRERERUadrcV+o0ePvkyZOYOXMmvvnmG9StWxfTpk2Dk5MT+vbti/fee0+XQxu1/Px8TJ48Gfv27cO5c+fw1Vdf4dGjR2KHRURERERUJq0Ti8TERHzzzTfw9/dHp06d8PDhQ/z++++4c+cOZs+ejZ9//hm7du3CkiVLqiJeo3Dy5Ek0b94cHh4esLa2Rq9evbBr1y6xwyIiIqIaJC4lC0dvJSEuJUvsUMhIaJ1YeHp64ueff0ZERATu3buHdevW4cUXX1Sbfahly5Zo27atXgOtSQ4ePIiwsDC4u7tDIpFg06ZNGnUiIyPh4+MDc3NzBAcH4+TJk6ptDx48gIeHh+q5h4cH7t+/b4jQiYiIqBaIOhWD5+fuw2s/ncDzc/ch6lSM2CGREdA6sdi7dy+uXr2K999/H87OzqXWsbW1xf79+3UOrqbKyMhAQEAAIiMjS90eFRWFyZMnY+bMmTh79iwCAgIQGhqKxMREA0dKREREtU1cShambbgEZeEoWqUAfLjhMlsuqMppnVh06tSpKuKoVXr16oXPPvsM/fv3L3X7/PnzMXr0aIwcORJ+fn5YsmQJLC0tsWzZMgCAu7u7WgvF/fv34e7uXub5cnJykJqaqvYgIiIi4xSdlKFKKoooBAF3kjLFCYiMhtYL5AHAunXr8OeffyImJga5ublq286ePauXwGqr3NxcnDlzBtOmTVOVSaVShISE4NixYwCAoKAgXL58Gffv34ednR22b9+O6dOnl3nMOXPmYPbs2VUeOxEREVV/vk5WkEqgllzIJBL4OFmKFxQZBa1bLBYuXIiRI0fCxcUF586dQ1BQEOrUqYPbt2+jV69eVRFjrZKUlASFQqGx3oeLiwvi4+MBACYmJvjmm2/QrVs3BAYG4n//+x/q1KlT5jGnTZuGlJQU1SM2NrZKfwYiIiKqvtzsLPBezyaq5xIAX7zsDzc7C/GCIqOgdYvF999/j6VLl2LIkCFYvnw5pkyZgvr162PGjBlITk6uihiNUnh4OMLDwytUVy6XQy6XV3FEREREVFO09LRXff96u3oY3NZbvGDIaGjdYhETE4MOHToAACwsLJCWlgYAGDZsGH7//Xf9RlcLOTk5QSaTISEhQa08ISEBrq6uIkVFREREtcm9xxxPQYandWLh6uqqapnw9vbG8ePHAQDR0dHQcRFvo2BmZobWrVtj7969qjKlUom9e/eiffv2IkZGREREtUVsscQiPSdfxEjImGjdFap79+7YvHkzWrVqhZEjR+Ldd9/FunXrcPr0abz88stVEWONk56ejps3b6qeR0dH4/z583B0dIS3tzcmT56MiIgItGnTBkFBQViwYAEyMjIwcuRIEaMmIiKi2iI2+enUsmnZTCzIMLROLJYuXQqlUgkAGD9+POrUqYOjR48iPDwcY8eO1XuANdHp06fRrVs31fPJkycDACIiIrB8+XIMHjwYDx8+xIwZMxAfH4/AwEDs2LFDY0A3ERERUWXcU2uxyBMxEjImEoH9l2qd1NRU2NnZISUlBba2tmKHQ0RERAbW9vM9eJiWAwDw97DFlolch4wqR5v7ygq1WFy8eLHCJ2/ZsmWF6xIRERGRfmXnKVRJBQCksysUGUiFEovAwEBIJJJnDs6WSCRQKBR6CYyIiIiItHfvcZbacw7eJkOpUGIRHR1d1XEQERERkR4Uja+wkZsgLSefg7fJYCqUWNSrV6+q4yAiIiIiPYgtbLFo6maDU3ceIydfidx8JcxMtF5lgEgrWs8KBQDXr1/HokWLcPXqVQBAs2bNMHHiRDRp0uQZexIRERFRVSpqsWjqaotTdx4DADJy8mFmYiZmWGQEtE5d169fD39/f5w5cwYBAQEICAjA2bNn4e/vj/Xr11dFjERERERUQfcK17CoV8cSFqYyABxnQYahdYvFlClTMG3aNHzyySdq5TNnzsSUKVMwYMAAvQVHRERERNoparHwcrSEtbkJsvIUHGdBBqF1i0VcXByGDx+uUf76668jLi5OL0ERERERUeUUjbHwdLCAjbzgM2S2WJAhaJ1YdO3aFYcOHdIoP3z4MDp14uIrRERERGLJyMlHckYuAMDToaDFAuDq22QYWneFCg8PxwcffIAzZ86gXbt2AIDjx49j7dq1mD17NjZv3qxWl3TXv39/HDhwAD169MC6devEDoeIiIiqqaI1LGzNTWBnYQrrwhYLdoUiQ9A6sXjrrbcAAN9//z2+//77UrcBXCxPn95++22MGjUKK1asEDsUIiIiqsZik5+OrwCgSiwycnhPRlVP665QSqWyQg8mFfrTtWtX2NjYiB0GERERVXNFA7c9HSwAgF2hyKD0slLKkydPKr1vWloa3nnnHdSrVw8WFhbo0KEDTp06pfM+s2bNgkQiUXs0bdq00nGW5uDBgwgLC4O7uzskEgk2bdpUar3IyEj4+PjA3NwcwcHBOHnypF7jICIiIgKeDtz2cihosVAN3mZXKDIArROLL7/8ElFRUarnAwcOhKOjIzw8PHDhwgWtA3jzzTexe/durFq1CpcuXULPnj0REhKC+/fv67xP8+bNERcXp3ocPny4zGMeOXIEeXma2fyVK1eQkJBQ6j4ZGRkICAhAZGRkmceNiorC5MmTMXPmTJw9exYBAQEIDQ1FYmKiqk5gYCD8/f01Hg8ePCjzuEREREQlFZ9qFgCsisZYcFYoMgCtE4slS5bAy8sLALB7927s2bMHO3bsQK9evfD+++9rdaysrCysX78e8+bNQ+fOndGwYUPMmjULDRs2xA8//KDzPiYmJnB1dVU9nJycSj2mUqnE+PHj8dprr6l14bp+/Tq6d+9e5tiGXr164bPPPkP//v3L/Bnnz5+P0aNHY+TIkfDz88OSJUtgaWmJZcuWqeqcP38ely9f1ni4u7uXeVwiIiKikmKTn041CxTrCsUWCzIArROL+Ph4VWKxZcsWDBo0CD179sSUKVOe2YWppPz8fCgUCpibm6uVW1hYlNm6oM0+N27cgLu7O+rXr4+hQ4ciJiam1GNKpVJs27YN586dw/Dhw6FUKnHr1i10794d/fr1w5QpU7T6uYrk5ubizJkzCAkJUTtXSEgIjh07VqljlicyMhJ+fn5o27at3o9NRERE1V/JFguuY0GGpHVi4eDggNjYWADAjh07VDfNgiBoPWDbxsYG7du3x6effooHDx5AoVDgt99+w7Fjx8pcbK+i+wQHB2P58uXYsWMHfvjhB0RHR6NTp05IS0sr9bju7u7Yt28fDh8+jNdeew3du3dHSEhImS0nFZGUlASFQgEXFxe1chcXF8THx1f4OCEhIRg4cCC2bdsGT0/PMpOS8ePH48qVK1oneERERFTzpWTlIbWwZcLDvuTgbSYWVPW0nm725ZdfxmuvvYZGjRrh0aNH6NWrFwDg3LlzaNiwodYBrFq1CqNGjYKHhwdkMhmee+45DBkyBGfOnNFpn6K4AKBly5YIDg5GvXr18Oeff+KNN94o9bje3t5YtWoVunTpgvr16+OXX36BRCLR+mfStz179ogdAhEREVVzRVPN1rEyU42tsJabAuA6FmQYWrdYfPvtt5gwYQL8/Pywe/duWFtbAwDi4uLU1rGoqAYNGuCff/5Beno6YmNjcfLkSeTl5aF+/fp63cfe3h6NGzfGzZs3y6yTkJCAMWPGICwsDJmZmXj33Xe1/nmKc3Jygkwm0xj8nZCQAFdXV52OTURERFRc0eJ4ReMrgKfrWLDFggxB6xYLU1NTvPfeexrlut6EW1lZwcrKCo8fP8bOnTsxb948ve6Tnp6OW7duYdiwYaVuT0pKQo8ePdCsWTOsXbsW//33H7p27Qq5XI6vv/66Uj+TmZkZWrdujb1796Jfv34ACgaK7927FxMmTKjUMYmIiIhKo1rDonB8BQDYcPA2GVCFEovNmzejV69eMDU1xebNm8utGx4erlUAO3fuhCAIaNKkCW7evIn3338fTZs2xciRIwEAixcvxsaNG7F3794K7wMA7733HsLCwlCvXj08ePAAM2fOhEwmw5AhQzRiUCqV6NWrF+rVq4eoqCiYmJioWmS6d+8ODw+PUhOn9PR0tRaQ6OhonD9/Ho6OjvD29gYATJ48GREREWjTpg2CgoKwYMECZGRkqMVKREREpKt7JdawANhiQYZVocSiX79+iI+PR926dVWfvJdGIpFoPYA7JSUF06ZNw7179+Do6IgBAwbg888/h6lpQZ/ApKQk3Lp1S6t9AODevXsYMmQIHj16BGdnZ3Ts2BHHjx+Hs7OzRgxSqRRffPEFOnXqBDMzM1V5QEAA9uzZU+o+AHD69Gl069ZN9Xzy5MkAgIiICCxfvhwAMHjwYDx8+BAzZsxAfHw8AgMDsWPHDo0B3URERES6KBpjodYVqtjgbaVSgFQq/thRqr0kgiAIYgdB+pWamgo7OzukpKTA1tZW7HCIiIjIAEK/PYjrCWlYMSoIXRoXfCianadA0+k7AACXZvWEjblpeYcg0qDNfaXWg7eJiIiIqHoRBAGxjzVbLOQmUpjKClop2B2KqlqFukItXLiwwgecNGlSpYMhIiIiIu09zsxDZm5Bd/SiNSyAgm7q1nITPM7MKxjAbSdWhGQMKpRYfPvtt2rPHz58iMzMTNjb2wMAnjx5AktLS9StW5eJBREREZGBFY2vqGsjh7mpTG2btXlBYpHGFguqYhXqChUdHa16fP755wgMDMTVq1eRnJyM5ORkXL16Fc899xw+/fTTqo6XiIiIiEoo6gblVWyq2SJFi+RxylmqalqPsZg+fToWLVqEJk2aqMqaNGmCb7/9Fh9//LFegyMiIiKiZ3s61ayFxjYbTjlLBqJ1YhEXF4f8fM03pkKh0FhhmoiIiIiq3tOpZktpseAieWQgWicWPXr0wNixY3H27FlV2ZkzZzBu3DiEhIToNTgiIiIiejZVi4WjZotF0SJ5HGNBVU3rxGLZsmVwdXVFmzZtIJfLIZfLERQUBBcXF/z8889VESMRERERlePpVLNssSDxVGhWqOKcnZ2xbds23LhxA1evXgUANG3aFI0bN9Z7cERERERUPkEQcF81xkIzsXg6xiLPoHGR8an0AnmNGjVCeHg4wsPDS00qbG1tcfv2bZ2Co6f69+8PBwcHvPLKK2KHQkRERNXIw7Qc5OQrIZUAbvbmGtutOXibDKTKVt4WBKGqDm2U3n77baxcuVLsMIiIiKiaiS1srXCzs4CpTPPWrqgrVBq7QlEVq7LEgvSra9eusLGxETsMIiIiqmbuFY6v8ChlqlmALRZkODUisUhLS8M777yDevXqwcLCAh06dMCpU6f0vk9lHDx4EGFhYXB3d4dEIsGmTZs06kRGRsLHxwfm5uYIDg7GyZMn9R4HERERGaeiqWZLG18BADYcvE0GUiMSizfffBO7d+/GqlWrcOnSJfTs2RMhISG4f/++3vY5cuQI8vI0BzVduXKl3PU5MjIyEBAQgMjIyFK3R0VFYfLkyZg5cybOnj2LgIAAhIaGIjExUVUnMDAQ/v7+Go8HDx6UeV4iIiIioPypZoFiK2+zxYKqWJUlFhKJRC/HycrKwvr16zFv3jx07twZDRs2xKxZs9CwYUP88MMPetlHqVRi/PjxeO2116BQKFTl169fR/fu3bFixYoy4+vVqxc+++wz9O/fv9Tt8+fPx+jRozFy5Ej4+flhyZIlsLS0xLJly1R1zp8/j8uXL2s83N3dK/oyERERkZEqb6pZgGMsyHCq/eDt/Px8KBQKmJurz3JgYWGBw4cP62UfqVSKbdu24dy5cxg+fDiUSiVu3bqF7t27o1+/fpgyZUqlYs/NzcWZM2fUFg6USqUICQnBsWPHKnVMIiIiouJULRYcY0Ei0ymxEAShzARi+/bt8PDw0OXwAAAbGxu0b98en376KR48eACFQoHffvsNx44dQ1xcnN72cXd3x759+3D48GG89tpr6N69O0JCQspsFamIpKQkKBQKuLi4qJW7uLggPj5eq2OFhIRg4MCB2LZtGzw9PUtNTCIjI+Hn54e2bdtWOmYiIiKqORRKAQ+eFCQWno7PGGORk89ZO6lKVSqx+OWXX+Dv7w9zc3OYm5vD399fY9Xtjh07Qi6X6yXIVatWQRAEeHh4QC6XY+HChRgyZAik0rLDr8w+3t7eWLVqFaKiomBiYoJffvlFb126dLVnzx48fPgQmZmZuHfvHtq3b69RZ/z48bhy5UqVDFInIiKi6ichNRt5CgEmUglcbTXXsACetlgolAKy85SGDI+MjNaJxYwZM/D2228jLCwMa9euxdq1axEWFoZ3330XM2bMqIoY0aBBA/zzzz9IT09HbGwsTp48iby8PNSvX1+v+yQkJGDMmDEICwtDZmYm3n33XZ3idnJygkwm0xj8nZCQAFdXV52OTURERFQ0I5S7vQVk0tI/DLU0k6Hoc9I0rr5NVUjrxOKHH37ATz/9hDlz5qhW3p4zZw6WLl2K77//vipiVLGysoKbmxseP36MnTt34qWXXtLbPklJSejRoweaNWuGDRs2YO/evYiKisJ7771X6XjNzMzQunVr7N27V1WmVCqxd+/eUlsciIiIiLTxrBmhgIIJdVTjLDiAm6qQibY75OXloU2bNhrlrVu3Rn5+1bxZd+7cCUEQ0KRJE9y8eRPvv/8+mjZtipEjRwIAFi9ejI0bN6rdwD9rn+KUSiV69eqFevXqqbpB+fn5Yffu3ejevTs8PDzKbL1IT0/HzZs3Vc+jo6Nx/vx5ODo6wtvbG5MnT0ZERATatGmDoKAgLFiwABkZGaXGQURERKSNohmhylrDooiN3ARp2fkcwE1VSuvEYtiwYfjhhx8wf/58tfKlS5di6NChegusuJSUFEybNg337t2Do6MjBgwYgM8//xympgXzMiclJeHWrVta7VOcVCrFF198gU6dOsHMzExVHhAQgD179sDZ2bnM2E6fPo1u3bqpnk+ePBkAEBERgeXLl2Pw4MF4+PAhZsyYgfj4eAQGBmLHjh0aA7qJiIiItBWbXDhwu4wZoYpYscWCDEAiaDk9wMSJE7Fy5Up4eXmhXbt2AIATJ04gJiYGw4cPV7txL5l8kGGkpqbCzs4OKSkpsLW1FTscIiIiqiKDfzyGE9HJ+O7VQLwUWPZsnP2/P4JzMU/w47DWCG3OcZ5UcdrcV2rdYnH58mU899xzAKBqJXBycoKTkxMuX76sqlddZlMiIiIiqq2Kxlg8q8WCYyzIELROLPbv318VcRARERGRFvIUSsSlFC2O94wxFuZcJI+qnk4L5MXGxiI2NlZfsRARERFRBcU9yYZSAMxMpHCyLn/tMK6+TYagdWKRn5+P6dOnw87ODj4+PvDx8YGdnR0+/vhj5OVxbmQiIiIiQ7hXOCOUp4MFpGWsYVHEWl4wBpaJBVUlrbtCTZw4ERs2bMC8efNUazEcO3YMs2bNwqNHj/DDDz/oPUgiIiIiUherSizK7wYFANbmHGNBVU/rxGLNmjX4448/0KtXL1VZy5Yt4eXlhSFDhjCxICIiIjIA1eJ4zxi4DRSsYwGwxYKqltZdoeRyOXx8fDTKfX191daAICIiIqKqE5tcuDieY8VbLNLYYkFVSOvEYsKECfj000+Rk5OjKsvJycHnn3+OCRMm6DU4IiIiIipdRaeaBYoP3uZ4WKo6WneFOnfuHPbu3QtPT08EBAQAAC5cuIDc3Fz06NEDL7/8sqruhg0b9BcpEREREakUjbF41lSzQLExFuwKRVVI68TC3t4eAwYMUCvz8vLSW0BEREREVL7sPAUSUgt6j1SkxcKGC+SRAWidWPz6669VEQeVo3///jhw4P/bu/e4KMu8f+CfYTgPA4ggMAh4QEFQQUFIC0WklBTPh7QnQbT2+WWlsWm6u5ZtapnVWsrqbo+KYRmioltbmpJ4QC0hMUlFIVRQDuKBw4AgM/fvD2RknAFmhqP6eb9e84K557qv+zuHm7m/XKcUjBo1Cjt37uzocIiIiKiDXb9T1w3KzNgI1bWKZsuzxYLag85jLAICArBx40aUlZW1ZTykxYIFC/Dll192dBhERETUSWz7+SoAoLpWiWdWH0LCqatNlq8fY8HB29SWdE4sfH19sXjxYjg7O+Oll15CSkpKG4ZFDYWEhEAqlXZ0GERERNQJFJRWYcuxXNV9pQD8ZXcmCkqrGt1Hen+BvOpaJWpqlW0eIz2ZdE4sNm3ahMLCQsTGxiIvLw+jRo2Ch4cHVq1ahWvXrhkcQHl5ORYuXAh3d3dYWFhg2LBhOHXqVKPlFQoFli1bhp49e8LCwgK9e/fG+++/D0EQVGWWL18OkUikdvPy8jI4xsYcOXIEERERkMlkEIlE2LNnj9ZysbGx6NGjB8zNzREUFIRffvml1WMhIiKiJ0NuiRzCQ9sUgoDLJZWN7iMxE6t+l7M7FLURvaabtbS0RFRUFFJSUnDx4kW88MIL+Ne//oUePXpg7NixBs0CNW/ePBw4cADx8fE4e/YsnnvuOYSFhTWarKxevRobNmzA+vXrcf78eaxevRofffQR1q1bp1bOx8cHBQUFqtuxY8eajCM1NRX37mlOwXbu3DkUFRVp3Ucul8PX1xexsbGN1puQkICYmBi8++67+PXXX+Hr64vRo0ejuLhYVcbPzw/9+/fXuF2/fr3JmImIiOjJU9+tqSGxSIQe9o3PDmUsNoKFSV1ywXEW1Fb0XseiXu/evbFixQpcvnwZ27dvx8mTJzFt2jS96qiqqsKuXbvw0UcfYfjw4fDw8MDy5cvh4eHR6Arex48fx4QJEzB27Fj06NEDU6dOxXPPPafRCmBsbAwnJyfVzd7evtE4lEol5s+fj1mzZkGheDAAKisrC6Ghodi6davW/cLDw7FixQpMmjSp0bo//fRTvPzyy5gzZw68vb2xceNGWFpaYvPmzaoyGRkZyMzM1LjJZLJG6yUiIqInU0beHbX7YpEIqyb3h7NN07NDcZE8amsGJxYAkJKSgqioKERFRUGhUODll1/Wa//a2looFAqYm5urbbewsGi0hWHYsGFITk7GxYsXAdStoXHs2DGEh4erlbt06RJkMhl69eqFF198EVevNj6oycjICN9//z1Onz6N2bNnQ6lUIicnB6GhoZg4cSIWL16s1/OqV1NTg/T0dISFhakdKywsDCdOnDCozqbExsbC29sbQ4YMafW6iYiIqHP44WwhAOD1kR7Y/vJTOLZkJGYMcWt2P9WUs2yxoDai93Sz+fn5iIuLQ1xcHP744w8EBwfjn//8J6ZNmwYLi+bnUW5IKpVi6NCheP/999GvXz84Ojpi+/btOHHiBDw8PLTus2TJEpSVlcHLywtisRgKhQIrV67Eiy++qCoTFBSEuLg4eHp6oqCgAO+99x6Cg4ORmZnZ6CBomUyGn376CcHBwZg1axZOnDiBsLCwRltOdFFSUgKFQgFHR0e17Y6Ojrhw4YLO9YSFheHMmTOQy+Xo3r07EhMTMXToUI1y8+fPx/z581FWVgYbGxuD4yYiIqLO6WZFNX7OvQkAmD7EFa52zS+OV+/BlLNcfZvahs6JxY4dO7B582YkJyejW7duiIyMRHR0dKMJgK7i4+MRHR0NFxcXiMViDB48GDNnzkR6enqjcXz11Vf4+uuv4ePjg4yMDCxcuBAymQyRkZEAoNZ6MXDgQAQFBcHd3R07duzA3LlzG43Fzc0N8fHxGDFiBHr16oVNmzZBJBK16Pm1hoMHD3Z0CERERNQJ/HiuCEoB6O9irVdSAXDKWWp7OneF+p//+R9YWFggKSkJeXl5WLVqVYuTCqBurMbhw4dRUVGBvLw8/PLLL7h37x569eqltfyiRYuwZMkSvPDCCxgwYABeeuklvPnmm/jggw8aPYatrS369u2L7OzsJmMpKirCK6+8goiICFRWVuLNN99s0XOzt7eHWCzWGPxdVFQEJyenFtVNRERET54fMuu6QYX3d9Z7Xyt2haI2pnNiMW/ePPz1r3/FuHHjYGTUoqEZWkkkEjg7O+P27dvYv38/JkyYoLVcZWWlxvHFYjGUysbnZK6oqEBOTg6cnRs/CUtKSjBq1Cj069cPu3fvRnJyMhISEvDWW28Z9oQAmJqawt/fH8nJyaptSqUSycnJWrsyERERETWmtPIejmeXAADG9Nf/H5SqrlBssaA2onNXqLt37+L555+HqakpIiIiMH78eIwaNQqmpqYtCmD//v0QBAGenp7Izs7GokWL4OXlhTlz5gAA1q9fj6SkJNXFeUREBFauXAk3Nzf4+Pjg9OnT+PTTTxEdHa2q86233kJERATc3d1x/fp1vPvuuxCLxZg5c6bWGJRKJcLDw+Hu7o6EhAQYGxvD29sbBw4cQGhoKFxcXLS2XlRUVKi1guTm5iIjIwN2dnZwc6sbRBUTE4PIyEgEBAQgMDAQa9euhVwuVz0/IiIiIl0kpuehVimgp70lejtY6b0/B29TW9M5sdi8eTOUSiVSU1Px7bffYuHChSgoKMCzzz6LCRMmYNy4cbCzs9M7gNLSUixduhT5+fmws7PDlClTsHLlSpiY1K0QWVJSgpycHFX5devWYdmyZXj11VdRXFwMmUyGP/3pT3jnnXdUZfLz8zFz5kzcvHkTDg4OeOaZZ3Dy5Ek4ODhojcHIyAirVq1CcHCwWqLk6+uLgwcPNrpfWloaRo4cqbofExMDAIiMjERcXBwAYMaMGbhx4wbeeecdFBYWws/PD/v27dMY0E1ERETUmIRTV7Hiv+cBAJdLKpFw6qpOM0E1xOlmqa2JhIZLVuvp/Pnz+Pbbb7F3716kp6cjMDAQ48ePx8yZM+Hi4tKacZIe6meFKi0thbW1dUeHQ0RERC1QUFqFpz/8CcoGV2xikQjHloxsdu2Khjak5GD1vguY6t8dH0/zbYNI6XGkz3VliwZL9OvXD4sXL0Zqairy8vIQFRWFo0ePYvv27S2ploiIiIjuyy2RqyUVAKAQBFwuqdSrHo6xoLam9zoW0dHR+OyzzzTWg7C0tMSxY8ewd+/eVguOiIiI6EnX014CkQgQHmqx6GGv33SzHGNBbU3vFoutW7eiqqpKY3tVVRW+/PLLVgmKiIiIiOo421hgRoCr6r5YJMKqyf316gYFNFjHgokFtRGdWyzKysogCAIEQUB5eTnMzc1VjykUCnz//ffo1q1bmwRJRERE9CSrnwVqWO+u+GS6r95JBdCwKxRX3qa2oXNiYWtrC5FIBJFIhL59+2o8LhKJ8N5777VqcEREREQEFJffBQB4O1sblFQAXCCP2p7OicWhQ4cgCAJCQ0Oxa9cutallTU1N4e7uDplM1iZBEhERET3JbpRXAwAcpGYG16FKLDh4m9qIzonFiBEjANQtAufm5gaRSNRmQRERERHRAzcq6hKLbtYtSCzud4WS1yiQf7sSYiMRckvk6GkvMbgVhKghvWeFunLlCq5cudLo48OHD29RQERERESkrrjsfouFlXkzJRu3L7NQ9fszqw+pfjcSAR9MHqD3gntED9M7sQgJCdHY1rD1QqFQtCggIiIiIlLX0haLgtIqvLM3U+tjSgFYuussJGbG8HfvwtYLMpje083evn1b7VZcXIx9+/ZhyJAh+PHHH9sixifepEmT0KVLF0ydOrWjQyEiIqJ2Vl2rwJ3KupmcHKwMSyy0LbLXkBLAa1+fxtMf/oSEU1cNOgaR3omFjY2N2s3e3h7PPvssVq9ejcWLF7dFjE+8BQsWcI0QIiKiJ1RJRQ0AwEQsgq2liUF19LSXwEiH4bFKAfjL7kwUlGquWUbUHL0Ti8Y4OjoiKyurtaqjBkJCQjRWOiciIqLHS0FpFY7nlKgu6uvvny8oA1DXWmHo5DnONhb4YPIAiO/vLwLQWFUKQcDlkkqDjkNPNr3HWPz2229q9wVBQEFBAT788EP4+fm1VlxqysvLsWzZMiQlJaG4uBiDBg3CZ599hiFDhmgtr1AosHz5cmzbtg2FhYWQyWSIiorC3/72t1adzerIkSNYs2YN0tPTUVBQgKSkJEycOFGjXGxsLNasWYPCwkL4+vpi3bp1CAwMbLU4iIiI6NGWcOoqlu4+C6VQN5h60iAXJJ2+BqVQlwQAgIO14QO3AWDGEDcM7+uAyyWV6GFvCQBIv3wbb3xzWq2blJEIqseJ9KF3YuHn5weRSARBUO+o99RTT2Hz5s2tFlhD8+bNQ2ZmJuLj4yGTybBt2zaEhYXh3LlzcHFx0Si/evVqbNiwAVu3boWPjw/S0tIwZ84c2NjY4I033tB6jNTUVAQGBsLERL2J8dy5c+jatSscHR019pHL5fD19UV0dDQmT56std6EhATExMRg48aNCAoKwtq1azF69GhkZWWpVir38/NDba3mnNI//vgj1wYhIiJ6zBWUVqmSCqCuO9KuX6+pHq+/4pKa6X3ZpsHZxkJtcPY4XwvIa2rxl91nobh/IDuJKazNDetyRU82kfBwhtCMh6eaNTIygoODA8zNW5ZFN6aqqgpSqRR79+7F2LFjVdv9/f0RHh6OFStWaOwzbtw4ODo6YtOmTaptU6ZMgYWFBbZt26ZRXqlUYvDgwejTpw+++eYbiMViAEBWVhZGjBiBmJiYZsePiEQirS0WQUFBGDJkCNavX686lqurK15//XUsWbJE59chJSUF69evx86dO5stW1ZWBhsbG5SWlsLa2lrnYxAREVGdgtKqNl/jof4YKReK8e+juc2WD/Xqhs1R2ntrtEYsmddK8dekTBSXV2Oaf3esmebbJsdqLe3xHpF+15V6p77u7u4GB2aI2tpaKBQKjcTFwsICx44d07rPsGHD8O9//xsXL15E3759cebMGRw7dgyffvqp1vJGRkb4/vvvMXz4cMyePRvx8fHIzc1FaGgoJk6caPCg9JqaGqSnp2Pp0qVqxwoLC8OJEycMqrMpsbGxiI2N5ZS/RERELfBwt6S2WOOh4TF01aNr23VPqm/JkJqbYNYXJ5GYno/gvg4Y79s5e060x3tE+jOoTe3w4cP4+OOPcf78eQCAt7c3Fi1ahODg4FYNDgCkUimGDh2K999/H/369YOjoyO2b9+OEydOwMPDQ+s+S5YsQVlZGby8vCAWi6FQKLBy5Uq8+OKLjR5HJpPhp59+QnBwMGbNmoUTJ04gLCwMGzZsMDj2kpISKBQKjW5Ujo6OuHDhgs71hIWF4cyZM5DL5ejevTsSExMxdOhQjXLz58/H/PnzVZklERERNa2mVomrtyqRWyJHbkkFfr9eir0ZBarHlQKwdPdZDO/r0Gr/FS8orcKS3WfxcJ8RkQiqbdbmxii7q95NupeDVascvylP9eqK10Z64POfsvHX3WcxyNUWrnYdO96iqkaByzfl998jOTKvleKHBov9KQXg7V1nsSs9H10kppCYGsPSTFz309QYEjMxJGbGsDQVqz32YLsxJKZiGItbbU6jJ5beicW2bdswZ84cTJ48WTVeITU1FaNGjUJcXBxmzZrV6kHGx8cjOjoaLi4uEIvFGDx4MGbOnIn09HSt5Xfs2IGvvvoKX3/9NXx8fJCRkYGFCxdCJpMhMjKy0eO4ubkhPj4eI0aMQK9evbBp06ZWHextqIMHD3Z0CERERG2qpd1amtpfoRRw/U6V6sK04S3/dmWzrQZ1C8j9hldG9MZTPbvCSJd5WxuJz8bCBCv+e14jqQCAtTP8sGxPJsru1qLsbi3EIsDcVAx5dV1PBBMDjmuIN0b1QWrOTaRfuY0F35zGjj8NbZWL7qbeo3sKJfJUCZ76raD0rk71/3L5doviMzU2gsRUDEtTY1iZNUxOGiQmZsaqpMSy4U9TMSzNjGGlul+3v0krJiuPQtcvvcdY9OvXD6+88grefPNNte2ffvopvvjiC1UrRluQy+UoKyuDs7MzZsyYgYqKCvz3v//VKOfq6oolS5Zg/vz5qm0rVqzAtm3bmmwpKCoqwogRI9C3b1+cOnUKU6dOxbp163SKTdsYi5qaGlhaWmLnzp1q2yMjI3Hnzh3s3btXp7r1xTEWRET0KHm4W8vyCB9M8e+u8/670vOx/Nvf62ZQEgGTB7nAXmqG3BtyXL4px+WblaipVTa6v8RUjB72EvS0l8DBygxxxy+jsYsjZxtzTPBzwaRBLvB00m0qeF26PYlFIhxbMhJ/TsjA8T9uqbb3spfgjxI5gLrn9mE7dfnJu1WJ5z8/ivK7tXg91AN/fs6zRfU1fA1EImCCrwx2EjPkllQgt0SOvNtVUDTxAtlYmKCnvQS97CWwtzLFF0dz1d4jIxGwbFw/mIjFqKyphbxagcqaWlTc/1l/X16jQGV1LeTVdb/Lq2tRq09/ND2Zio3UWki0JyOarSmqJMasrlzyhWJ8tO9Ch3T9atMxFn/88QciIiI0to8fPx5/+ctf9K1OLxKJBBKJBLdv38b+/fvx0UcfaS1XWVkJIyP1DFEsFkOpbPyPSklJCUaNGoV+/fohMTERFy9eREhICMzMzPDxxx8bFK+pqSn8/f2RnJysSiyUSiWSk5Px2muvGVQnERHR4+RiUTmW7DqrukhUCsA7//kd7/znd4PqEx6aUameqdgIbl0tVRenPe0l6HH/dwep+voQXs5S/GV3JhSCALEImBfcC2V37+G73wpQUHoXGw/nYOPhHPRztsbkQS4Y7yeDYyNTwT4841O9OU/3wJfHr9w/hgirJvcHAJzIvaVWrj6pqH9uf9md2ardshrjameJVZMG4PXtp7H+UDae9rDHU7266rSvIAgoLq9GVmE5LhaV4/TV2/jv2cIGjwN7Mq5r7GdhIla9J/XvT/371UViqla2dzerBu9R3etn6IV2Ta1SLemoqK5F5f2ko7JGAXlNLSqrFfe3N0hOah4kLQ+XrVHUXXPWKJSoqVSqVk5vDcp2/BzoS+/EwtXVFcnJyRrjGw4ePAhXV9dWC6yh/fv3QxAEeHp6Ijs7G4sWLYKXlxfmzJkDAFi/fj2SkpKQnJwMAIiIiMDKlSvh5uYGHx8fnD59Gp9++imio6O11q9UKhEeHg53d3ckJCTA2NgY3t7eOHDgAEJDQ+Hi4qLRQgMAFRUVyM7OVt3Pzc1FRkYG7Ozs4OZW9+GOiYlBZGQkAgICEBgYiLVr10Iul6tiJyIietIolQJO5t5EYlo+vvvteqOtAy0x2scRw3rbqy5UZbYWEOvYlejh9R7qL97ejfDBoQvFSDp9DYeyinG+oAwrC8rwwQ/n8bSHPSb6uWBMfydIzIxRUFqFrIJyfP3LVa0tFc95O+GV4b3UjnE8p0RrF6mG6heva48LyghfGY5cvIHE9Hy8sf00Vk7sj/7dbdSOfVteg6yiugTiYlE5LhZWIKuoHKVVzV9IP9/fCU/3sb+fPFjB0Vr3BQAbe48MYWpsBFNjU9i24lCSmlolqu4nGvWtI9qSEXnNQ0nM/Z+qJKZagdKqGlRUq0/M056fA33onVj8+c9/xhtvvIGMjAwMGzYMQN0Yi7i4OHz22WetHiAAlJaWYunSpcjPz4ednR2mTJmClStXqtacKCkpQU5Ojqr8unXrsGzZMrz66qsoLi6GTCbDn/70J7zzzjta6zcyMsKqVasQHBwMU9MHGbGvry8OHjwIBwcHrfulpaVh5MiRqvsxMTEA6ro6xcXFAQBmzJiBGzdu4J133kFhYSH8/Pywb98+retiEBERPc7yb1diV/o1JKbnIf92VaPljETAT38OgZNN81PZF5beRegnKWoX72KRCMvH+7Toouvh9R4AwNxEjPABzggf4Izb8hr892wBkk5fQ/qV2zh6qQRHL5Xgb3sy4elkhTN5pY0mTGKRSHUx3PAYPe0lMBKh2S5T7bl43fLxPjiUVYzi8mq8HJ8OEYCnPewBAFlF5bhRXq11PyNR3fPp6yiFs405tqSqdy8Ti0RYFuHd6u9RZ1GXrBjBxrLl64EUlFbh6Q9/0viMd8ZFDPUeYwEASUlJ+OSTT1TjKfr164dFixZhwoQJrR4g6Y9jLIiIqLO4e0+B/b8XIjEtH6kN/iMvNTPGOF8Zpgd0R1ZhOf6aZHi3loRTV1utW4whrt6sxJ6Ma0g6fQ25Dbou1ROhblyBUkCz8T38XCYOkmHP6esd9twKSqsw7MOfmmxJcbWzgKejFH0cpfB0lKKvoxS9HCQwNxGrynT0e/So68jXT5/rSoMSC11s374d48ePh0QiaYvqqQlMLIiIqCMJgoDf8kuxIy0P/zlzHeUNpk0d1rsrpge4YrSPEyxMH1x4FpRWtahbS0v3bw2CIGDbyStYtldzfMj6mYPQ1cpMp/gefi4d+dyO55Rg1hc/a2z/0/BeCB/gjD7drCDRcUXwzvAePco66vXrFImFtbU1MjIy0KtXr7aonprAxIKIiDpCSUU19py+hh1pebhYVKHa7mJrgan+3THVv3uHr4nQ1hrrtnJsychH8mL6cXs+pL82nRVKV22UrxAREVEnck+hRErWDSSm5eGnC8WqqTvNjI0Q3t8J0wJcMbSXYWs/PIqcbSzwweQBGt1WHtWL8Mft+VDbarPEgoiInmyPwmJOZLhLReVITM/H7l+voaTiwQBeX1dbTA/ojnEDZbCxaPnA1UdRa85Y1Bk8bs+H2g4TCyIialWCIGDj4Rx8tC8LAuoGrb4b4Y2oYT07OjRqobK79/DdmQLsSMtDRt4d1XZ7K1NMGuSCaQGu6Ouo26Jxj7vOPGORIR6350Ntg4kFEREZ7J5CiZwbFfj9WhnOFZTh9+ulyLxWqjbnuiAAy/9zDhtT/kB/F2t4OVnDy1kKLydr9LSX6Ly2AHUMpVLAyT9uIjE9Hz9kFuDuvbqFv8RGIoR6dcM0/+4Y6dUNJmKjZmoioscdEwsiItJJZU0tzheU49z1Uvx+vS6RuFBYjppapU77F5bdRWHZXRw8X6zaZmZsBE8nKbycpKqEo5+TtcYqu9T+8m9XYmd6Pnam56utOdGnmxWmB7hi4iAXOEjNOjBCIups2iyxcHd3Vy1gR0REj5Zb8hr8fj+B+P16Gc5dL8UfJXKtc9lbmRnD29ka3jJr+Mis0U1qhjlxp9RmkTES1U23eaOiBhcKy3CuoBwXC8tRdU+B3/JL8Vt+qVqdjtZmqkTD27mulaOXg4T/FW9j9WtO7EjLw/Gcm2prTkT4yTA9wBW+3W10Xh2ZiJ4sBk83m5aWprZAXkBAQKsGRobjdLNEpCtBEJB/u0qVPNQnEoVld7WWd5Cawed+AuEjs4GPzBquXSw1ZvzRZTEnhVLA1VuVuFBQhvOF5bhwvwXk6q1Krcc2EYvg0U2Kfk7SupaN+wkH/2veMoIg4Ex+KRK1rDnxtMeDNScaLnZGRE+ONl3HIj8/HzNnzkRqaipsbW0BAHfu3MGwYcPwzTffoHv37gYHTq2DiQURaVOrUCLnhrxBS0Qpzl0vQ1mDC8mGetpL1FoivGXW6CY11/l4hi7mVFFdi6zCMpwvKMeFwjJcKCjHhcJyVFRrj9PeyrSudcNJCi/nup99HK1gZswL4abcKK9bcyIxXXPNiWkB3TFl8OO/5gQRNa9NE4sxY8bgzp072Lp1Kzw9PQEAWVlZmDNnDqytrbFv3z7DIyetJk2ahJSUFIwaNQo7d+5stjwTCyJSjYcoeNAS0dh4CBOxCH0d67oc+cis4eNig37O1rDScTXd9lDfsnL+fqtGfcKRe1N79yyxkQi9HSRq4za8nKVwsjZ/orvx1K85sSMtD4e0rDkxPcAVTz1Ba04QUfPaNLGwsLDA8ePHMWjQILXt6enpCA4ORmWl9iZsMlxKSgrKy8uxdetWJhZEpKF+PMS5+92Yfr9eitwSudoYh3oNx0PUt0T06SaFqfGjOXahqkaBi0V1icb5gnJV4lFadU9reVtLE9VA8X73Z6bq6yiFhenj3brR2JoTfq62mBbQHRG+Mlibc1wkEWlq05W3XV1dce+e5h9shUIBmUymb3Wkg5CQEKSkpHR0GETUwR4eD1E3vWsZCkp1Gw/h7WwNNzvN8RCPMgtTMXxdbeHraqvaJggCCsvu4kJBOc6rulKVIeeGHHcq7+HkH7dw8o9bqvIiEdCzq+T+mI0H3am6d7F4pFs3yu7ew7dnriMxLf+hNSfMMHmwC6b5d0cfrjlBRK1I78RizZo1eP311xEbG6sasJ2WloYFCxbg448/NiiI8vJyLFu2DElJSSguLsagQYPw2WefYciQIVrL9+jRA1euXNHY/uqrryI2NhbLly/He++9p/aYp6cnLly4YFB8jTly5AjWrFmD9PR0FBQUICkpCRMnTtQoFxsbizVr1qCwsBC+vr5Yt24dAgMDWzUWInq8PDwe4tz96V0b+098j66WdcmDgeMhHicikUi1mNdIr26q7XfvKZBdXFHXlep+y8b5gjLclNfgjxI5/iiR479nC1TlpWbGdVPhOte3cFjD00naqbqIPax+zYkdaXn4IbMQ1fe7vhnXrzkR4IoQTwfOrkVEbULvv45RUVGorKxEUFAQjI3rdq+trYWxsTGio6MRHR2tKnvr1q3GqlEzb948ZGZmIj4+HjKZDNu2bUNYWBjOnTsHFxcXjfKnTp2CQvFg8aXMzEw8++yzmDZtmmqbj48PDh48+OCJGjf9VFNTUxEYGKgxRe65c+fQtWtXODo6auwjl8vh6+uL6OhoTJ48WWu9CQkJiImJwcaNGxEUFIS1a9di9OjRyMrKQrdudV94fn5+qK3VHJT4448/shWI6DFSUFqF3BI5etpL1AYzV9bU4kJhudrMTE2Nh+jTTfqgJcLFBl5OUkjZjaVZ5iZi9HexQX8XG7XtxeV3Va0ada0c5cguLkd5dS3SrtxG2pXbauXd7CxVLRv9nOpmp+rolqC8W5XY9avmmhN9HR+sOWFvxdmziKht6T3GYuvWrTqXjYyMbLZMVVUVpFIp9u7di7Fjx6q2+/v7Izw8HCtWrGi2joULF+K7777DpUuXIBKJsHz5cuzZswcZGRk6xalUKjF48GD06dMH33zzDcTiur62WVlZGDFiBGJiYrB48eIm6xCJRFpbLIKCgjBkyBCsX79edSxXV1e8/vrrWLJkiU7xAXXjLNavX88xFkSPqIRTV7F091kohbquN+E+TjAWGzU7HqKfs1StJeJRHg/xKLmnUOKPG/L7a2486E5VVFattbyFiRieTlLVuI36cRw2lm2X8N29p8C+zEIkpuchNfumarvU3BjjfevWnBjINSeIqIXadIyFLsmCPmpra6FQKGBurt5kb2FhgWPHjjW7f01NDbZt24aYmBi1P56XLl2CTCaDubk5hg4dig8++ABubm5a6zAyMsL333+P4cOHY/bs2YiPj0dubi5CQ0MxceLEZpOKpmJLT0/H0qVL1Y4VFhaGEydOGFRnU2JjYxEbG6vWmkNE7aOiuhY3yqtRXHYXNyqqUVxWjRsV1bhRXo28W5X4OfdBC64gAN9nFqrtXz8eom5mprr1ITr6v+BPMhNx3Yrgnk5STPB70HJ+S17zoGXjfneqi0V1C/1l5N1RG8sA1E3d6qXWnUqKHl0lMDawK1L9mhM70vLwbYM1J0Qi4One9pgW0J1rThBRhzFogTyFQoGkpCTVAnne3t6YMGFCs92NGjNs2DCYmpri66+/hqOjI7Zv347IyEh4eHggKyuryX137NiBWbNm4erVq6puQz/88AMqKirg6emJgoICvPfee7h27RoyMzMhlTY+UO3q1asIDg7G0KFDceLECYSEhCAuLk6n//Zoa7G4fv06XFxccPz4cQwdOlS1ffHixTh8+DB+/vnnZusFgLCwMJw5cwZyuRx2dnZITExUq+9hbLEgah0KpYCbFdUoLr+fJNxPFrQlD5U1+if0M4a4Ykx/p/urVT+Z4yEeB7UKJS7frGyw5kbdDFXX7lRpLW9mbIS+jlK17lReztawk5iqlWvYdc7YyAh7Tl/DjrQ8XCp+sOZE9y4WmObviin+LujehWtOEFHra9MWi99//x3jx49HYWGhah2L1atXw8HBAd9++y369++vd8Dx8fGIjo6Gi4sLxGIxBg8ejJkzZyI9Pb3ZfTdt2oTw8HC1sQjh4eGq3wcOHIigoCC4u7tjx44dmDt3bqN1ubm5IT4+HiNGjECvXr2wadOmTtGE3HCsCBG1nLy+daG8+v7Pu7ih+v3Bz1vyaq1dlBpjZWYMB6nZg5uVGbpZm8HESIRVP1xQW29BLBJhYVgfvRaOo87JWGwEj25W8OhmhXEDH2wvrbqHrMIHicaFwjJkFZajskaBs9dKcfZaqVo93aRmdYmGsxSllfeQkJan+swYiaD6LJqbGCG8vzOmBXTHUz255gQRdR56Jxbz5s2Dj48P0tLS0KVLFwDA7du3ERUVhVdeeQXHjx/XO4jevXvj8OHDkMvlKCsrg7OzM2bMmIFevXo1ud+VK1dw8OBB7N69u8lytra26Nu3L7Kzs5ssV1RUhFdeeQURERE4deoU3nzzTaxbt07v51PP3t4eYrEYRUVFGsdxcnIyuF4i0qRQCrgpr9ZIEG5oSR7kerQuGImArlZm6HY/WXjw01yVQNRvszRt/E+qtYUJ/rI7EwpBgFgkwqrJ/ZlUPOZsLEwQ2NMOgT3tVNuUSgF5tytxvqDByuKF5bhysxLF5dUoLr+BIxdvaNSlFAAfmTVeDHLHOF9nrjlBRJ2S3olFRkaGWlIBAF26dMHKlSsbnR5WVxKJBBKJBLdv38b+/fvx0UcfNVl+y5Yt6Natm9qgb20qKiqQk5ODl156qdEyJSUlGDVqFPr164fExERcvHgRISEhMDMzM3gaXVNTU/j7+yM5OVnVRUqpVCI5ORmvvfaaQXV2Zo3NeEPUGF0+M5U1D7Uu3O+G9HDrws0K/VoXJKbiBomBuVpLQ8PkwU5iCnEr/Ed4xhA3DO/rgMsllehhb8lz5AllZCSCe1cJ3LtKMKa/s2p7RXUtLhbVjdtIuXADB84Xaez7t7HeGNq7a3uGS0SkF70Ti759+6KoqAg+Pj5q24uLi+Hh4WFQEPv374cgCPD09ER2djYWLVoELy8vzJkzBwCwfv16JCUlITk5WbWPUqnEli1bEBkZqTG246233kJERATc3d1x/fp1vPvuuxCLxZg5c6bW4yuVSoSHh8Pd3R0JCQkwNjaGt7c3Dhw4gNDQULi4uODNN9/U2K+iokKtFSQ3NxcZGRmws7NTDRSPiYlBZGQkAgICEBgYiLVr10Iul6ue2+Pi4RlvFoT2wej+bJWhxu3PLMRnP12CIAAiAKP7O8LJ2kJtLMON8mpUVGtOxdwYkQjoKtFsXWiYPNRvk3TAWgT1aysQPczKzBiD3bpgsFsXhHp1Q/KFIrVEWSwSoYc9x1AQUeem9zfrBx98gDfeeAPLly/HU089BQA4efIk/v73v2P16tUoKytTldV14HBpaSmWLl2K/Px82NnZYcqUKVi5cqVqTYmSkhLk5OSo7XPw4EFcvXpVbd2Mevn5+Zg5cyZu3rwJBwcHPPPMMzh58iQcHBy0Ht/IyAirVq1CcHAwTE0fDJ7z9fXFwYMHG90vLS0NI0eOVN2PiYkBUDdzVlxcHABgxowZuHHjBt555x0UFhbCz88P+/bt07ouxqOqoLRKlVQAdTPerE2+hLXJlzo2MHpkCAD2ZWr+h7aehYkY3awfjFmo+2kOByv1VgY7ianBs+0QdRbONhb4YPIAdp0jokeO3rNCGRk9+NKuH9hcX0XD+yKRiNOedpD2nhXqeE4JZn2hOcOVjYUJ59snrWpqlVpXkB7vK4Ofq6168iA1g8RU3CkmUiBqTwWlVew6R0Qdrk1mhcrMzET//v1x6NChFgdIj5ee9hK1GUuAumb7fQuD+WVIWhWUVuHpD3/S+Mwsfd6Lnxmi+9h1jogeNTonFgMHDsSQIUMwb948vPDCC02uB0FPFjbbk774mSEiInr86NwV6ujRo9iyZQt27twJpVKJqVOnYu7cuQgODm7rGElPHbVAHpvtSV/8zBAREXVu+lxX6j3GQi6XY8eOHYiLi8PRo0fh4eGBuXPnIjIykmszdBJceZuIiIiIWkObJhYNZWdnY8uWLYiPj0dhYSHGjBmD//znP4ZWR62ktLQUtra2yMvLY2JBRERERAYrKyuDq6sr7ty5AxsbmybLtiixAOpaML766issXboUd+7c4UxQnUB+fj5cXV07OgwiIiIiekzk5eWhe/fuTZYxeIWoI0eOYPPmzdi1axeMjIwwffp0zJ0719DqqBXJZDLk5eVBKpXqNEXnkCFDcOrUqRaXq89on7SWEl1fv/bQHrG09jFaUp+h++qzX2uWfRLPkc50fgCP3jnS0roM2V/fffgd0jKd6Rx51M6PltbH7xDdCIKA8vJyyGSyZsvqlVhcv34dcXFxiIuLQ3Z2NoYNG4bPP/8c06dPh0QiMThgal1GRkbNZpQNicVinT6gupaztrZ+or4UdH1d2kN7xNLax2hJfYbuq89+bVH2STpHOtP5ATx650hL6zJkf3334XdIy3Smc+RROz9aWh+/Q3TXXBeoejonFuHh4Th48CDs7e0xe/ZsREdHw9PT0+AAqfOYP39+q5Z70nSm16U9YmntY7SkPkP31We/tir7pOhsr8mjdo60tC5D9td3H36HtExnel0etfOjpfXxO6T16TzGYvz48Zg7dy7GjRsHsVjc1nHRI4izURE1jecIUeN4fhA17VE4R3RuseBsT9QcMzMzvPvuuzAzM+voUIg6JZ4jRI3j+UHUtEfhHGnxrFBERERERERGHR0AERERERE9+phYEBERERFRizGxICIiIiKiFmNiQURERERELcbEgtrNd999B09PT/Tp0wf/93//19HhEHUqkyZNQpcuXTB16tSODoWo08nLy0NISAi8vb0xcOBAJCYmdnRIRJ3GnTt3EBAQAD8/P/Tv3x9ffPFFh8XCWaGoXdTW1sLb2xuHDh2CjY0N/P39cfz4cXTt2rWjQyPqFFJSUlBeXo6tW7di586dHR0OUadSUFCAoqIi+Pn5obCwEP7+/rh48SIkEklHh0bU4RQKBaqrq2FpaQm5XI7+/fsjLS2tQ66x2GJB7eKXX36Bj48PXFxcYGVlhfDwcPz4448dHRZRpxESEgKpVNrRYRB1Ss7OzvDz8wMAODk5wd7eHrdu3erYoIg6CbFYDEtLSwBAdXU1BEFAR7UbMLEgnRw5cgQRERGQyWQQiUTYs2ePRpnY2Fj06NED5ubmCAoKwi+//KJ67Pr163BxcVHdd3FxwbVr19ojdKI219Lzg+hx15rnSHp6OhQKBVxdXds4aqL20Rrnx507d+Dr64vu3btj0aJFsLe3b6fo1TGxIJ3I5XL4+voiNjZW6+MJCQmIiYnBu+++i19//RW+vr4YPXo0iouL2zlSovbH84Ooaa11jty6dQuzZ8/Gv//97/YIm6hdtMb5YWtrizNnziA3Nxdff/01ioqK2it8dQKRngAISUlJatsCAwOF+fPnq+4rFApBJpMJH3zwgSAIgpCamipMnDhR9fiCBQuEr776ql3iJWpPhpwf9Q4dOiRMmTKlPcIk6jCGniN3794VgoODhS+//LK9QiVqdy35Dqn3//7f/xMSExPbMsxGscWCWqympgbp6ekICwtTbTMyMkJYWBhOnDgBAAgMDERmZiauXbuGiooK/PDDDxg9enRHhUzUbnQ5P4ieZLqcI4IgICoqCqGhoXjppZc6KlSidqfL+VFUVITy8nIAQGlpKY4cOQJPT88Oide4Q45Kj5WSkhIoFAo4OjqqbXd0dMSFCxcAAMbGxvjkk08wcuRIKJVKLF68mDNC0RNBl/MDAMLCwnDmzBnI5XJ0794diYmJGDp0aHuHS9TudDlHUlNTkZCQgIEDB6r6n8fHx2PAgAHtHS5Ru9Ll/Lhy5QpeeeUV1aDt119/vcPODSYW1G7Gjx+P8ePHd3QYRJ3SwYMHOzoEok7rmWeegVKp7OgwiDqlwMBAZGRkdHQYADh4m1qBvb09xGKxxkChoqIiODk5dVBURJ0Dzw+ipvEcIWrco3Z+MLGgFjM1NYW/vz+Sk5NV25RKJZKTk9mVg554PD+ImsZzhKhxj9r5wa5QpJOKigpkZ2er7ufm5iIjIwN2dnZwc3NDTEwMIiMjERAQgMDAQKxduxZyuRxz5szpwKiJ2gfPD6Km8RwhatxjdX50yFxU9Mg5dOiQAEDjFhkZqSqzbt06wc3NTTA1NRUCAwOFkydPdlzARO2I5wdR03iOEDXucTo/RILQQWt+ExERERHRY4NjLIiIiIiIqMWYWBARERERUYsxsSAiIiIiohZjYkFERERERC3GxIKIiIiIiFqMiQUREREREbUYEwsiIiIiImoxJhZERERERNRiTCyIiIiIiKjFmFgQERG1sZqaGnh4eOD48eOtWu++ffvg5+cHpVLZqvUSERmCiQUREeklKioKIpFI45adnd3RoXVaGzduRM+ePTFs2DDVNpFIhD179miUjYqKwsSJE3Wqd8yYMTAxMcFXX33VSpESERmOiQUREeltzJgxKCgoULv17NlTo1xNTU0HRNe5CIKA9evXY+7cuW1Sf1RUFD7//PM2qZuISB9MLIiISG9mZmZwcnJSu4nFYoSEhOC1117DwoULYW9vj9GjRwMAMjMzER4eDisrKzg6OuKll15CSUmJqj65XI7Zs2fDysoKzs7O+OSTTxASEoKFCxeqymj7D7+trS3i4uJU9/Py8jB9+nTY2trCzs4OEyZMwOXLl1WP17cGfPzxx3B2dkbXrl0xf/583Lt3T1Wmuroab7/9NlxdXWFmZgYPDw9s2rQJgiDAw8MDH3/8sVoMGRkZTbbYpKenIycnB2PHjtXzVQYuX76stXUoJCREVSYiIgJpaWnIycnRu34iotbExIKIiFrV1q1bYWpqitTUVGzcuBF37txBaGgoBg0ahLS0NOzbtw9FRUWYPn26ap9Fixbh8OHD2Lt3L3788UekpKTg119/1eu49+7dw+jRoyGVSnH06FGkpqbCysoKY8aMUWs5OXToEHJycnDo0CFs3boVcXFxasnJ7NmzsX37dnz++ec4f/48/vWvf8HKygoikQjR0dHYsmWL2nG3bNmC4cOHw8PDQ2tcR48eRd++fSGVSvV6PgDg6uqq1ip0+vRpdO3aFcOHD1eVcXNzg6OjI44ePap3/URErUogIiLSQ2RkpCAWiwWJRKK6TZ06VRAEQRgxYoQwaNAgtfLvv/++8Nxzz6lty8vLEwAIWVlZQnl5uWBqairs2LFD9fjNmzcFCwsLYcGCBaptAISkpCS1emxsbIQtW7YIgiAI8fHxgqenp6BUKlWPV1dXCxYWFsL+/ftVsbu7uwu1tbWqMtOmTRNmzJghCIIgZGVlCQCEAwcOaH3u165dE8RisfDzzz8LgiAINTU1gr29vRAXF9fo67VgwQIhNDRUYzsAwdzcXO11lEgkgrGxsTBhwgSN8lVVVUJQUJAwbtw4QaFQqD02aNAgYfny5Y3GQETUHow7Nq0hIqJH0ciRI7FhwwbVfYlEovrd399freyZM2dw6NAhWFlZadSTk5ODqqoq1NTUICgoSLXdzs4Onp6eesV05swZZGdna7QM3L17V62bkI+PD8Riseq+s7Mzzp49C6CuW5NYLMaIESO0HkMmk2Hs2LHYvHkzAgMD8e2336K6uhrTpk1rNK6qqiqYm5trfewf//gHwsLC1La9/fbbUCgUGmWjo6NRXl6OAwcOwMhIvcOBhYUFKisrG42BiKg9MLEgIiK9SSSSRrv+NEwyAKCiogIRERFYvXq1RllnZ2edZ5MSiUQQBEFtW8OxERUVFfD399c6Q5KDg4PqdxMTE41666drtbCwaDaOefPm4aWXXsI//vEPbNmyBTNmzIClpWWj5e3t7VWJy8OcnJw0XkepVIo7d+6obVuxYgX279+PX375RWuXqlu3bqk9RyKijsDEgoiI2tTgwYOxa9cu9OjRA8bGml87vXv3homJCX7++We4ubkBAG7fvo2LFy+qtRw4ODigoKBAdf/SpUtq/6UfPHgwEhIS0K1bN1hbWxsU64ABA6BUKnH48GGNloR6zz/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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "vampl = vpp/2\n", + "\n", + "fig, ax = plt.subplots(3)\n", + "fig.set_size_inches(8, 6)\n", + "\n", + "ax[0].errorbar(freq, a, yerr=a_sigma, marker='.')\n", + "ax[0].set_title(\"Plot of Displacement/Vampl vs. Frequency\")\n", + "# ax[0].legend()\n", + "ax[0].loglog()\n", + "ax[0].set_ylabel(\"Displ (microns)/Vampl (V)\")\n", + "\n", + "ax[1].errorbar(freq, phases, marker='.', yerr=phases_sigma, label=\"0.2 Vpp Data\")\n", + "ax[1].set_xscale('log')\n", + "ax[1].set_ylabel(\"Phase (radians)\")\n", + "\n", + "ax[2].plot(freq, vpp/0.2, marker='.')\n", + "ax[2].loglog()\n", + "ax[2].set_ylabel(\"Vpp_out/Vpp_display\")\n", + "ax[2].set_xlabel(\"Frequency (Hz)\")\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "id": "c8d2b26f", + "metadata": {}, + "source": [ + "Expected transfer function for displ/V_ampl assuming speaker is a damped harmonic oscillator:\n", + "\n", + "$$\n", + "A = \\frac{k f_0^2}{\\sqrt{(f_0^2 - f^2)^2 + \\frac{f_0^2}{Q^2}f^2}}\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "10324403", + "metadata": {}, + "outputs": [], + "source": [ + "def A(f, f0, Q, k):\n", + " return (k * f0**2) / np.sqrt((f0**2 - f**2)**2 + f0**2*f**2/Q**2)" + ] + }, + { + "cell_type": "markdown", + "id": "88247f41", + "metadata": {}, + "source": [ + "Add constant $c$ to add flexibility for potential phase offset from data between 20-1kHz: \n", + "\n", + "\n", + "$$\n", + "\\phi = \\arctan \\left( \\frac{\\frac{f_0}{Q} f}{f^2 - f_0^2} \\right) + c\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "dcf9688f", + "metadata": {}, + "outputs": [], + "source": [ + "def phase(f_trunc, f0, Q, c):\n", + " return np.arctan2(f0/Q*f_trunc, f_trunc**2 - f0**2) + c" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "246a00de", + "metadata": {}, + "outputs": [], + "source": [ + "# for curve-fitting, start from 20Hz where Vpp_out/Vpp_display relatively 1:1\n", + "pfreq = freq\n", + "f_tot = np.append(pfreq, freq) \n", + "y_tot = np.append(phases, a)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "38797d52", + "metadata": {}, + "outputs": [], + "source": [ + "def combined_func(ftot, f0, Q, k, c):\n", + " f_phase = ftot[:len(pfreq)]\n", + " f_ampl = ftot[len(pfreq):]\n", + " \n", + " phase_val = phase(f_phase, f0, Q, c)\n", + " A_val = A(f_ampl, f0, Q, k)\n", + " \n", + " return np.append(phase_val, A_val)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "9fbafb14", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "parameter names: ['f0', 'Q', 'k', 'c']\n", + "independent variables: ['ftot']\n" + ] + } + ], + "source": [ + "model = lmfit.Model(combined_func, weights=np.append(1/phases_sigma[3:], 1/a_sigma[3:]), scale_covar=True)\n", + "params = model.make_params(f0=255, Q=30, k=1, c=-3)\n", + "params['Q'].set(min=0)\n", + "print(f'parameter names: {model.param_names}')\n", + "print(f'independent variables: {model.independent_vars}')" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "f397b873", + "metadata": {}, + "outputs": [], + "source": [ + "result = model.fit(y_tot, params, ftot=f_tot, weights=np.append(1/phases_sigma, 1/a_sigma), scale_covar=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "8dc727ec", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "result.plot(yerr=np.append(phases_sigma, a_sigma))" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "ad9c67fc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

Fit Result

Model: Model(combined_func)

Fit Statistics
fitting methodleastsq
# function evals46
# data points50
# variables4
chi-square 70.4148723
reduced chi-square 1.53075809
Akaike info crit. 25.1190744
Bayesian info crit. 32.7671665
R-squared 0.99960185
Parameters
namevaluestandard errorrelative errorinitial valueminmaxvary
f0 257.208573 0.11358603(0.04%)255.0 -inf infTrue
Q 15.8041109 0.35690497(2.26%)30.0 0.00000000 infTrue
k 33.4249342 0.16401428(0.49%)1.0 -inf infTrue
c-3.20823307 0.00984959(0.31%)-3.0 -inf infTrue
Correlations (unreported values are < 0.100)
Parameter1Parameter 2Correlation
Qk-0.7192
f0Q-0.7071
f0k+0.3911
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "18db6fa7", + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f0_uvar = result.uvars['f0']\n", + "Q_uvar = result.uvars['Q']\n", + "c_uvar = result.uvars['c']\n", + "k_uvar = result.uvars['k']\n", + "red_chi = result.redchi\n", + "\n", + "fig, ax = plt.subplots(nrows=3, sharex='col')\n", + "fig.set_size_inches(8, 6)\n", + "ax[0].errorbar(freq, displ/vampl, marker='.', linestyle='', yerr=a_sigma)\n", + "freq_range = np.linspace(1, 1000, 1000)\n", + "ax[0].plot(\n", + " freq_range,\n", + " A(freq_range, result.params['f0'], result.params['Q'], result.params['k']),\n", + " label=f'Fit: $f_0$ = {f0_uvar:SL}, $Q$ = {Q_uvar:SL},\\n$k$ = {k_uvar:SL}, Red. $\\chi^2$ = {red_chi:3.2f}',\n", + " color=\"orange\"\n", + ")\n", + "# ax[0].set_title(\"Plot of Displacement/Vampl vs. Frequency\")\n", + "ax[0].legend()\n", + "ax[0].loglog()\n", + "ax[0].set_ylabel(\"Displ (microns)/Vampl_out (V)\")\n", + "# ax[0].errorbar(freqs2, displ2/vampl2, yerr=displ2_sigma, fmt='none')\n", + "ax[1].errorbar(freq, phases, marker='.', linestyle=\"\", yerr=phases_sigma)\n", + "pfreq_range = np.linspace(1, 1000, 1000)\n", + "ax[1].plot(\n", + " pfreq_range,\n", + " phase(pfreq_range, result.params['f0'], result.params['Q'], result.params['c']),\n", + " label=f'Fit: $f_0$ = {f0_uvar:SL}, $Q$ = {Q_uvar:SL},\\n$c$ = {c_uvar:SL}, Red. $\\chi^2$ = {red_chi:3.2f}',\n", + " color=\"orange\")\n", + "ax[1].set_xscale('log')\n", + "# ax[1].set_xlabel(\"Frequency (Hz)\")\n", + "ax[1].set_ylabel(\"Phase (radians)\")\n", + "ax[1].legend()\n", + "\n", + "# ax[1].set_title(\"Plot of Phase vs. Frequency\")\n", + "# ax[1].errorbar(freqs_phase, phases, yerr=phase_sigma, fmt='none')\n", + "ax[2].plot(freq, vpp/0.2, marker='.')\n", + "ax[2].loglog()\n", + "ax[2].set_ylabel(\"Vpp_out/Vpp_display\")\n", + "ax[2].set_xlabel(\"Frequency (Hz)\")\n", + "ax[2].set_title(\"Plot of RP Output Vpp/Display Vpp\")\n", + "\n", + "plt.suptitle(\"Frequency Response of Speaker Driven at 0.2Vpp\")\n", + "plt.tight_layout()\n", + "# , $Q$ = {result.uvars['Q']:SL},\\n$c$ = {result.uvars['c']:SL}, Red. $\\chi^2$ = {result.redchi}" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "7bf5e953", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result.params['c']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ba187cb7", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.10.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/util.py b/util.py new file mode 100644 index 0000000..4e82f3e --- /dev/null +++ b/util.py @@ -0,0 +1,146 @@ +import numpy as np +from scipy.fftpack import fft, ifft, fftfreq +import h5py + +def bounded_frequency_waveform(start_frequency, end_frequency, length, sample_rate): + """Generates a random waveform within the given frequency range of a given length. + + Args: + start_frequency (float): the lower bound of the valid frequency range + end_frequency (float): the upper bound of the valid frequency range + length (int): the number of values to generate + sample_rate (float): the rate at which to sample values + + Returns: + [1darr, 1darr]: the array of time points and amplitude points in time domain + """ + # Create an evenly spaced time array + t = np.linspace(0, 1.0, length, False) # 1 second + # Generate a random frequency spectrum between the start and end frequencies + freq = np.linspace(0, sample_rate/2, length//2, False) + spectrum = np.random.uniform(0, 1, len(freq)) + spectrum = np.where((freq >= start_frequency) & (freq <= end_frequency), spectrum, 0) + c = np.random.rayleigh(np.sqrt(spectrum*(freq[1]-freq[0]))) + # See Phys. Rev. A 107, 042611 (2023) ref 28 for why we use the Rayleigh distribution here + # Unless we use this distribution, the random noise will not be Gaussian distributed + phase = np.random.uniform(-np.pi, np.pi, len(freq)) + # Use the inverse Fourier transform to convert the frequency domain signal back to the time domain + # Also include a zero phase component + spectrum = np.hstack([c*spectrum*np.exp(1j*phase), np.zeros_like(spectrum)]) + y = np.real(ifft(spectrum)) + y = np.fft.fftshift(y) + return t, y + +def linear_convert(data, new_min=-1, new_max=1): + """Linearly scales data to a new range. Default is [-1, 1]. + + Args: + data (1darr): data to scale + new_min (float, optional): new minimum value for data. Defaults to -1. + new_max (float, optional): new maximum value for data. Defaults to 1. + + Returns: + 1darr: the newly scaled data + """ + old_min = np.min(data) + old_max = np.max(data) + old_range = old_max - old_min + new_range = new_max - new_min + return new_min + new_range * (data - old_min) / old_range + +def write_data(file_path, entries): + """Add data to a given dataset in 'file'. Creates dataset if it doesn't exist; + otherwise, appends. + Args: + file_path (string): the name of the output HDF5 file to which to append data + entries (dict): dictionary of column name & corresponding data + """ + with h5py.File(file_path, 'a') as f: + for col_name, col_data in entries.items(): + if col_name in f.keys(): + f[col_name].resize((f[col_name].shape[0] + 1), axis=0) + new_data = np.expand_dims(col_data, axis=0) + f[col_name][-1:] = new_data + else: + f.create_dataset(col_name, + data=np.expand_dims(col_data, axis=0), + maxshape=(None, col_data.shape[0]), + chunks=True) + +# Constants from calibration_rp using RPRPData.csv +f0 = 257.20857316296724 +Q = 15.804110908084784 +k = 33.42493417407945 +c = -3.208233068626455 + +def A(f): + """Calculates the expected displacement of the speaker at an inputted drive amplitude 'ampl' for a given frequency 'f', + based on the calibration fit at 0.2Vpp. + + Args: + f (1darr): frequencies at which to calculate expected displacement + + Returns: + 1darr: expected displacement/V_ampl in microns/V + """ + return (k * f0**2) / np.sqrt((f0**2 - f**2)**2 + f0**2*f**2/Q**2) + +def phase(f): + """Calculates the phase delay between the speaker voltage waveform and the photodiode response + at a given frequency 'f'. + + Args: + f (1darr): frequencies at which to calculate expected displacement + + Returns: + 1darr: phase in radians + """ + return np.arctan2(f0/Q*f, f**2 - f0**2) + c + +def displacement_waveform(speaker_data, sample_rate): + """Calculates the corresponding displacement waveform based on the given voltage waveform + using calibration. + + Args: + speaker_data (1darr): voltage waveform for speaker + sample_rate (float): sample rate used to generate voltage waveform + + Returns: + [1darr, 1darr, 1darr]: converted displacement waveform (microns) in time domain, + converted displacement waveform in frequency domain, + frequency array (Hz) + """ + speaker_spectrum = fft(speaker_data) + n = speaker_data.size + sample_spacing = 1/sample_rate + freq = fftfreq(n, d=sample_spacing) # units: cycles/s = Hz + + # Multiply signal by transfer func in freq domain, then return to time domain + converted_signal = speaker_spectrum * A(freq) * np.where(freq < 0, np.exp(-1j*phase(-freq)), np.exp(1j*phase(freq))) + y = np.real(ifft(converted_signal)) + + return y, converted_signal, freq + +def velocity_waveform(speaker_data, sample_rate): + """Calculates the corresponding velocity waveform based on the given voltage waveform + using calibration. + + Args: + speaker_data (1darr): voltage waveform for speaker + sample_rate (float): sample rate used to generate voltage waveform + + Returns: + [1darr, 1darr, 1darr]: converted velocity waveform (microns/s) in time domain, + converted velocity waveform in frequency domain, + frequency array (Hz) + """ + speaker_spectrum = fft(speaker_data) + n = speaker_data.size + sample_spacing = 1/sample_rate + freq = fftfreq(n, d=sample_spacing) # units: cycles/s = Hz + + # Multiply signal by transfer func in freq domain, then return to time domain + converted_signal = 1j*freq * speaker_spectrum * A(freq) * np.where(freq < 0, np.exp(-1j*phase(-freq)), np.exp(1j*phase(freq))) + v = np.real(ifft(converted_signal)) + + return v, converted_signal, freq \ No newline at end of file