diff --git a/applications/lofar2/model/pfb_os/README.txt b/applications/lofar2/model/pfb_os/README.txt new file mode 100644 index 0000000000000000000000000000000000000000..011e8e527f7a9c931c0aa558bcd8e995450ccd87 --- /dev/null +++ b/applications/lofar2/model/pfb_os/README.txt @@ -0,0 +1,34 @@ +Author: Eric Kooistra, nov 2023 + +* Practise DSP [1]. + +* Try to reproduce LOFAR subband filter FIR coefficients using scipy instead + of MATLAB. + The pfs_coeff_final.m from the Filter Task Force (FTF) in 2005 use fircls1 + with r_pass and r_stop to define the ripple. In addition it post applies a + Kaiser window with beta = 1 to make the filter attenuation a bit more deep + near the transition. The pfir_coeff.m from Apertif also uses fircls1. + Both use fircls1 with N = 1024 FIR coefficients and then Fourier + interpolation to achieve Ncoefs = 1024 * 16 FIR coefficients. Both scripts + can not exactly reproduce the actual LOFAR1 coefficients, therefore these + are loaded from a file Coeffs16384Kaiser-quant.dat + +* Try low pass filter design methods using windowed sync, firls, remez [3] + The windowed sync method, firls leased squares method and remez method all + yield comparable results, but firls and remez perform slightly better near + the transition band. The firls and remez functions from scipy.signal use + transition bandwidth and weights between pass and stop band to influence + the transition region and ripple. For remez the ripple is constant in the + pass band and stop band, for firls the ripple is largest near the band + transition. + +* It is possible to design a good FIR filter using Python scipy. Possibly with + some extra help of a filter design and analysis (FDA) tool like pyfda [2]. + +[1] dsp_study_erko.txt, summary of DSP books +[2] pyfda, dsp, at https://github.com/chipmuenk +[3] Try FIR filter design methods + * dsp.py import for Python jupyter notebooks + * filter_design_firls.ipynb + * filter_design_remez.ipynb + * filter_design_windowed_sync.ipynb diff --git a/applications/lofar2/model/pfb_os/dsp.py b/applications/lofar2/model/pfb_os/dsp.py new file mode 100644 index 0000000000000000000000000000000000000000..19db600633d9292fa2b11dc12dde7dd515fb449d --- /dev/null +++ b/applications/lofar2/model/pfb_os/dsp.py @@ -0,0 +1,331 @@ +#! /usr/bin/env python3 +############################################################################### +# +# Copyright 2022 +# ASTRON (Netherlands Institute for Radio Astronomy) <http://www.astron.nl/> +# P.O.Box 2, 7990 AA Dwingeloo, The Netherlands +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +############################################################################### + +# Author: Eric Kooistra +# Purpose: Utilities and functions for DSP +# Description: + + +import numpy as np +import matplotlib.pyplot as plt + + +c_interpolate = 10 +c_atol = 1e-15 +c_rtol = 1e-8 # 1/2**32 = 2.3e-10 + + +############################################################################### +# Utilities +############################################################################### + +def ceil_div(num, den): + """ Return integer ceil value of num / den """ + return int(np.ceil(num / den)) + + +def ceil_log2(num): + """ Return integer ceil value of log2(num) """ + return int(np.ceil(np.log2(num))) + + +def ceil_pow2(num): + """ Return power of 2 value that is equal or greater than num """ + return 2**ceil_log2(num) + + +def pow_db(volts): + """Voltage to power in dB""" + return 20 * np.log10(np.abs(volts) + c_atol) + + +def is_even(n): + """Return True if n is even, else False when odd.""" + return n % 2 == 0 + + +def is_symmetrical(x, anti=False): + """Return True when x[n] = +-x[N-1 - n], within tolerances, else False.""" + rtol = c_rtol + atol = np.min(np.abs(x[np.nonzero(x)])) * rtol + n = len(x) + h = n // 2 + if is_even(n): + if anti: + return np.allclose(x[0:h], np.flip(-x[h:]), rtol=rtol, atol=atol) + else: + return np.allclose(x[0:h], np.flip(x[h:]), rtol=rtol, atol=atol) + else: + if anti: + return np.allclose(x[0:h], np.flip(-x[h + 1:]), rtol=rtol, atol=atol) and np.abs(x[h]) < atol + else: + return np.allclose(x[0:h], np.flip(x[h + 1:]), rtol=rtol, atol=atol) + + +def read_coefficients_file(filepathname): + coefs = [] + with open(filepathname, 'r') as fp: + for line in fp: + if line.strip(): # skip empty line + s = int(line) # one coef per line + coefs.append(s) + return coefs + + +############################################################################### +# Filter design +############################################################################### + +def ideal_low_pass_filter(Npoints, Npass, bandEdgeGain=1.0): + """Derive FIR coefficients for prototype low pass filter using ifft of + magnitude frequency response. + + Input: + - Npoints: Number of points of the DFT in the filterbank + - Npass: Number of points with gain > 0 in pass band + - bandEdgeGain : Gain at band edge + Return: + - h: FIR coefficients from impulse response + . f: normalized frequency axis for HF, fs = 1 + - HF: frequency transfer function of h + """ + # Magnitude frequency reponse + HF = np.zeros([Npoints]) + HF[0] = bandEdgeGain + HF[1 : Npass - 1] = 1 + HF[Npass - 1] = bandEdgeGain + # Zero center HF to make it even + HF = np.roll(HF, -(Npass // 2)) + f = np.arange(0, 1, 1 / Npoints) + # Filter impulse response + h = np.fft.ifft(HF).real # imag is 0 for even HF + h = np.roll(h, Npoints // 2) + return h, f, HF + + +def fourier_interpolate(HF, Ncoefs): + """Use Fourier interpolation to create final FIR filter coefs. + + HF contains filter transfer function for N points, in order 0 to fs. The + interpolation inserts Ncoefs - N zeros and then performs IFFT to get the + interpolated impulse response. + """ + # . insert Ncoefs - N zeros between positive and negative frequencies + N = len(HF) + K = N // 2 + HFextended = np.zeros(Ncoefs, dtype=np.complex_) + if is_even(N): + # Copy DC and K positive frequencies (including fs/2) in lower part + HFextended[0:K + 1] = HF[0:K + 1] + # Copy K - 1 negative frequencies in upper part + HFextended[-(K - 1):] = HF[K + 1:] + else: + # Copy DC and K positive frequencies in lower part + HFextended[0:K + 1] = HF[0:K + 1] + # Copy K negative frequencies in upper part + HFextended[-K:] = HF[K + 1:] + hinterpolated = np.fft.ifft(HFextended) + if np.allclose(hinterpolated.imag, np.zeros(Ncoefs), rtol=c_rtol, atol=c_atol): + print('hinterpolated.imag ~= 0') + else: + print('WARNING: hinterpolated.imag != 0') + return hinterpolated.real + + +############################################################################### +# DFT +############################################################################### + +def dtft(coefs, Ndtft=None, zeroCenter=True, fftShift=True): + """Calculate DTFT of filter impulse response or window. + + Use DFT with Ndtft points, to have frequency resolution of 2 pi / Ndtft. + Define h by extending coefs with Ndtft - M zeros, where M = len(coefs). + This DFT approaches the DTFT using bandlimited interpolation, similar to + INTERP() which interpolates by factor L = Ndtft / M [JOS1]. + + Input: + . coefs: filter impulse response or window coefficients + . Ndtft: number of points in DFT to calculate DTFT + . zeroCenter: when True zero center h to have even function that aligns + with cos() in DTFT, for zero-phase argument (+-1 --> 0, +-pi). Else + apply h as causal function. + . fftShift: when True fft shift to have -0.5 to +0.5 frequency axis, + else use 0 to 1.0. + Return: + . h: zero padded coefs + . f: normalized frequency axis for HF, fs = 1 + . HF: dtft(h), the frequency transfer function of h + """ + M = len(coefs) + if Ndtft is None: + Ndtft = ceil_pow2(M * c_interpolate) + # Time series, causal with coefs at left in h + h = np.concatenate((coefs, np.zeros([Ndtft - M]))) + if zeroCenter: + # Zero center h to try to make it even + h = np.roll(h, -(M // 2)) + # DFT + HF = np.fft.fft(h) + # Normalized frequency axis, fs = 1, ws = 2 pi + f = np.arange(0, 1, 1 / Ndtft) # f = 0,pos, neg + if fftShift: + # FFT shift to center HF, f = neg, 0,pos + f = f - 0.5 + HF = np.roll(HF, Ndtft // 2) + return h, f, HF + + +############################################################################### +# Plotting +############################################################################### + +def plot_time_response(h, markers=False): + """Plot time response (= impulse response, window, FIR filter coefficients). + + Input: + . h: time response + . markers: when True plot time sample markers in curve + """ + if markers: + plt.plot(h, '-', h, 'o') + else: + plt.plot(h, '-') + plt.title('Time response') + plt.ylabel('Voltage') + plt.xlabel('Sample') + plt.grid(True) + + +def plot_spectra(f, HF, fs=1.0, fLim=None, dbLim=None): + """Plot spectra for power, magnitude, phase, real, imag + + Input: + . f: normalized frequency axis for HF (fs = 1) + . HF: spectrum, e.g. frequency transfer function HF = DTFT(h) + . fs: sample frequency in Hz, scale f by fs, fs >= 1 + """ + Hmag = np.abs(HF) + Hphs = np.angle(HF) + Hpow_dB = pow_db(HF) # power response + fn = f * fs + if fs > 1: + flabel = 'Frequency [fs / %d]' % fs + else: + flabel = 'Frequency [fs]' + + plt.figure(1) + plt.plot(fn, Hpow_dB) + plt.title('Power spectrum') + plt.ylabel('Power [dB]') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + if dbLim: + plt.ylim(dbLim) + plt.grid(True) + + plt.figure(2) + plt.plot(fn, HF.real, 'r') + plt.plot(fn, HF.imag, 'g') + plt.title('Complex voltage spectrum') + plt.ylabel('Voltage') + plt.xlabel(flabel) + plt.legend(['real', 'imag']) + if fLim: + plt.xlim(fLim) + plt.grid(True) + + plt.figure(3) + plt.plot(fn, Hmag) + plt.title('Magnitude spectrum') # = amplitude + plt.ylabel('Voltage') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + plt.grid(True) + + plt.figure(4) + plt.plot(fn, Hphs) + plt.title('Phase spectrum (note -1: pi = -pi)') + plt.ylabel('Phase [rad]') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + plt.grid(True) + + +def plot_power_spectrum(f, HF, fmt='r', fs=1.0, fLim=None, dbLim=None, showRoll=False): + """Plot power spectrum + + Input: + . f: normalized frequency axis for HF (fs = 1) + . HF: spectrum, e.g. frequency transfer function HF = DTFT(h) + . fmt: curve format string + . fs: sample frequency in Hz, scale f by fs, fs >= 1 + """ + if fs > 1: + flabel = 'Frequency [fs / %d]' % fs + else: + flabel = 'Frequency [fs]' + + plt.plot(f * fs, pow_db(HF), fmt) + plt.title('Power spectrum') + plt.ylabel('Power [dB]') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + if dbLim: + plt.ylim(dbLim) + plt.grid(True) + + +def plot_two_power_spectra(f1, HF1, name1, f2, HF2, name2, fs=1.0, fLim=None, dbLim=None, showRoll=False): + """Plot two power spectra in same plot for comparison + + Input: + . f1,f2: normalized frequency axis for HF1, HF2 (fs = 1) + . HF1, HF2: spectrum, e.g. frequency transfer function HF = DTFT(h) + . fs: sample frequency in Hz, scale f by fs, fs >= 1 + """ + if fs > 1: + flabel = 'Frequency [fs / %d]' % fs + else: + flabel = 'Frequency [fs]' + + if showRoll: + plt.plot(f1 * fs, pow_db(HF1), 'r', + f1 * fs, np.roll(pow_db(HF1), len(f1) // 2), 'r--', + f2 * fs, pow_db(HF2), 'b', + f2 * fs, np.roll(pow_db(HF2), len(f2) // 2), 'b--') + plt.legend([name1, '', name2, '']) + else: + plt.plot(f1 * fs, pow_db(HF1), 'r', + f2 * fs, pow_db(HF2), 'b') + plt.legend([name1, name2]) + plt.title('Power spectrum') + plt.ylabel('Power [dB]') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + if dbLim: + plt.ylim(dbLim) + plt.grid(True) diff --git a/applications/lofar2/model/pfb_os/dsp_study_erko.txt b/applications/lofar2/model/pfb_os/dsp_study_erko.txt new file mode 100644 index 0000000000000000000000000000000000000000..382ab3c98ec8be5be4ff0a9fa63b8bc5a689106c --- /dev/null +++ b/applications/lofar2/model/pfb_os/dsp_study_erko.txt @@ -0,0 +1,370 @@ +############################################################################### +# Copyright 2023 +# ASTRON (Netherlands Institute for Radio Astronomy) <http://www.astron.nl/> +# P.O.Box 2, 7990 AA Dwingeloo, The Netherlands +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +############################################################################### +# +# Author: Eric Kooistra +# Purpose: DSP theory summary +# +# References: +# +# * [LYONS] Understanding Digital Signal Processing, 3rd edition +# * [PROAKIS] Digital Signal Processing, 3rd edition +# * [HARRIS] Multirate Signal Processing for Communication Systems +# * [CROCHIERE] Multirate Signal Processing +# * [JOS1] Mathematics of the Discrete Fourier Transform +# * [JOS2] Introduction to Digital Filters +# * [JOS3] Physical Audio Signal Processing +# * [JOS4] Spectral Audio Signal Processing +# + +1) Linear Time Invariant (LTI) system [LYONS 1.6] + +- Time shift in input causes equal time shift in output. +- Order of sequential LTI operations can be rearranged with no change in final + output +- LTI output is linear combination (weighted sum) of delayed copies of the + input signal [JOS1 4.3.11] +- Transforms use discrete or continuous range of complex phasors [JOS1 4.3.12] + * For causal signals x(n) = 0 for n < 0, yields unilateral (one sided) + transforms. Used to solve difference equations with initial conditions + [PROAKIS 3.5]. Only unique for causal signals, because these are 0 for + n < 0. + * DFT: Every signal x(n) can be expressed as a linear combination of complex + sinusoids W_N^kn = exp(j w_k t_n). The coefficients of projecting x(n) on + W_N^kn for n = 0,1,...,N-1 yield the DFT of x is X(k) for k = 0,1,...,N-1. + * DTFT: For N --> inf, linear combination of exp(j w t_n) = exp(j w T)^n + * z-transform: linear combination of z^n. Generalization (analytic + continuation) of the DTFT on the unit circle in the complex plane, to the + entire complex z-plane. + * FT: integral 0 --> inf, linear combination of exp(j w t) + * Laplace transform: integral 0 --> inf, linear combination of exp(s t), + s = o + jw, so analytic continuation of FT (on jw axis) to the s-plane. +- Analogue (Laplace) and digital (z) complex planes [JOS1 4.3.13] + . Transform of growing functions, important for transient behaviour and + stability analysis + . Poles and zeros, frequency reponse z = exp(jw) [PROAKIS 4.4.6] + . Laplace: Every point in s-plane corresponds to a complex sinusoid + A exp(s t), t >= 0. Frequency axis s = j w + . Z: Every point in z-plane corresponds to sampled z = exp(s T), z^n + +- FT, DTFT, DFT [MATLAB sinusoids-and-fft-frequency-bins.m] + . Fourier transform (FT): continuous time <-> continuous frequency + . Discrete-time Fourier transform (DTFT): discrete time <-> continuous + frequency. If there is no aliasing, then the DTFT is the same as the + Fourier transform up to half the sampling frequency. + . Discrete Fourier transform (DFT): discrete time <-> discrete frequency. + For a signal that is nonzero only in the interval 0 <= n < N, an Ndtft + point DFT exactly samples the DTFT when N_dtft >= N. + +- Transforms are used because the time-domain mathematical models of systems + are generally complex differential equations. Transforming these complex + differential equations into simpler algebraic expressions makes them much + easier to solve. Once the solution to the algebraic expression is found, + the inverse transform will give you the time-domain repsponse. + . Fourier is a subset of Laplace. Laplace is a more generalized transform. + Fourier is used primarily for steady state signal analysis, while Laplace + is used for transient signal analysis. Laplace is good at looking for the + response to pulses, step functions, delta functions, while Fourier is + good for continuous signals. + Many of the explanations just mention that the relationship between the + Laplace and Fourier transforms is that s = o + jw, so the Fourier + transform becomes a special case of the laplace transform. Better + explanations deals that Laplace is used for stability studies and Fourier + is used for sinusoidal responses of systems. Systems are stable if the + real part of s is negative, that is to say there is a transient that will + vanish in time, in those cases, it is enough to use Fourier. Of course + you will lose the insight of the transient part. Laplace should be able to + determine the full response of a system, be it stable or unstable, + including transient parts. + +2) Windows [JOS4 3] +- Tabel [PROAKIS 8.2.2] +- Rectangular window with length M [LYONS 3.13] + . Dirichlet kernel or aliased sinc: + HF(m) = c sin(pi * m * M / Ndtft) / sin(pi * m / Ndtft) + . Ndtft = M yields all-ones form that defines the DFT frequency response + to an input sinusoidal and it is also the of a single DFT bin: + HF(m) = sin(pi * m) / sin(pi * m / M) + ~= Ndtft * sinc(pi * m) for Ndtft = M >~ 10 +- Properties of rectangular window with M points from [JOS4 3.1.2]: + . Zero crossings at integer multiples of 2 pi / M = Ndtft / M [LYONS Eq. + 3.45] + . Main lobe width is 4 pi / M + . As M increases, the main lobe narrows (better frequency resolution). + . M has no effect on the height of the side lobes (same as the Gibbs + phenomenon for truncated Fourier series expansions. + . First side lobe only 13 dB down from the main-lobe peak. + . Side lobes roll off at approximately 6dB per octave. + . A phase term arises when we shift the window to make it causal, while + the window transform is real in the zero-phase case (i.e., centered + about time 0). + +3) Low pass filter (LPF) +- Design parameters [JOS4 4.2] + . Pass band edge frequency: w_pass + . Pass band ripple (allowed gain deviation): + r_pass = 10**(r_pass_dB / 20) - 1 + . Stop band edge frequency: w_stop + . Stop band ripple (allowed leakage level): + r_stop = 10**(r_stop_dB / 20) +- Ideal LPF [JOS4 4.1] + . w_cutoff = w_pass = w_stop, r_pass = r_stop = 0 + . sinc(t) = sin(pi t) / (pi t) [JOS4 3.1, numpy) + . h_ideal(n) = 2 f_c sinc(2 f_c n), n in Z + - f_c is normalized cutoff frequency with fs = 1 +- LPF FIR filter design [LYONS 5.3] + . Methods based on desired response characteristics [MNE]: + - Frequency-domain design (construct filter in Fourier domain and use an + IFFT to invert it, MATLAB fir2) + - Windowed FIR design (scipy.signal.firwin(), firwin2(), and MATLAB fir1 + with default Hamming) + - Least squares designs (scipy.signal.firls(), MATLAB firls, fircls1) + . firls = least squares + . fircls, fircls1 = constrained ls with pass, stop ripple + - The Remez or Parks-McClellan algorithm (scipy.signal.remez(), MATLAB + firpm) + . MATLAB filters yield n + 1 coefs + . LS and Remez can do bandpass (= flat), differentiator, hilbert + . Linear phase filter types (filter order is Ntaps - 1, fNyquist = f2/2): + Type Ntaps Symmetry H(0) H(fs/2) + I Odd Even any any --> LPF, HPF + II Even Even any 0 --> LPF + III Odd Odd 0 0 --> differentiator, hilbert + IV Even Odd 0 any --> differentiator, hilbert + +2) Finite Impulse Response (FIR) filters +- FIR filters perform time domain Convolution by summing products of shifted + input samples and a sequence of filter coefficients [LYONS 5.2]. +- Convolution equation [LYONS Eq. 5.6]: + + N-1 + y(n) = sum h(k)(x(n-k) = h(k) * x(n) + k=0 + +- Impulse response h(k) are the FIR filter coefficients: + + x(n) --> x(n-1) --> ... --> x(N-1) --\ + | | | + h(0) h(1) h(N-1) + \----------\-- ... ------------\--> + --> y(n) + +- Convolution in time domain is equivalent to multiplication in frequency + domain + y(n) = h(k) * x(n) ==> DFT ==> Y(m) = H(m) X(m) + +- Number of FIR coefficients (Ntaps) + . Trade window main-lobe width for window side-lobe levels and in turn filter + transition bandwidth and side-lobe levels + . Transition bandwidth: df = fstop - fpass + . Window based design [HARRIS 3.2, LYONS 5.10.5]: + - Ntaps ~= fs / df * (Atten(dB) - 8) / 14 + . Remez = Parks-McClellan [HARRIS 3.3, LYONS 5.6]: + - yield a Chebychev-type filter + - Steeper transition than window based, but constant stopband peak levels + - Ntaps = f(fs, fpass, fstop, passband ripple +-d1, stopband ripple +-d2) + ~= fs / df * Atten(dB) / 22 + +- Linear phase FIR filter + . Even or odd symmetrical h(n) = +-h(M - 1 - n), n = 0,1,...,N-1 + [PROAKIS 8.2.1]. Reason for using FIR [LYONS 5.10.3] + . Group delay (= envelope delay[LYONS 5.8]) of symmetrical FIR filter is: + G = (N_taps - 1) / 2 [Ts] [LYONS 5.10.3] + . Design using windowed sinc, because windows are symmetrical [PROAKIS 8.2.2, + LYONS 5.3.2, DSPGUIDE 16] + +- Half band FIR filter [LYONS 5.7] + . Symmetrical frequency response about fs / 2, so fpass + fstop = fs / 2 + . When Ntaps is odd, then half of the coefs are 0. + + +3) Discrete Fourier Transform (DFT) +- The N roots of unity [JOS1 3.12, 5.1, PROAKIS 5.1.3, LYONS 4.3]. Note JOS + uses +j in W_N because inproduct is with conj(W_N), others use -j because + then W_N can be used directly in equation and matrix: + + W_N = exp(-j 2pi / N) is primitive Nth root of unity + W_N^k = exp(-j 2pi k / N) + W_N^kn = exp(-j 2pi k / N * n) = exp(-j w_k * t_n) + . w_k = k 2pi fs / N + . t_n = n Ts + . fs / N is the frequency sampling interval in Hz + . Ts = 1 / fs is time sampling interval in seconds + . ws = 2pi fs is the frequency sampling interval in rad/s + +- Normalized frequency axis [LYONS 3.5, 3.13.4]: + . fs = 1, ws = 2pi fs = 2pi + . -fs/2, 0, fs/2 [Hz] + -pi, 0, pi [rad] + -0.5, 0, 0.5 [fs] + . N even, e.g. N = 4: + + <---- N = 4 -----> + 0 fs/2 fs + | | | + n = 0 1 2 3 + 0/4 1/4 2/4 3/4 4/4 + DC positive negative + + . N odd, e.g. N = 5: + <------- N = 5 --------> + 0 fs/2 fs + | | | + n = 0 1 2 | 3 4 | + 0/5 1/5 2/5 | 3/5 4/5 5/5 + DC positive | negative + + . With K = N // 2: + . N even : DC, K - 1 positive, fs/2, K - 1 negative frequencies + . N odd : DC, K positive, K negative frequencies + +- The DFT project a length N signal x on a set of N sampled complex sinusoids + that are generated by the Nth roots of unity [JOS4 6.1]. These sinusoids form + an orthogonal basis and are the only frequencies that have a whole number of + periods in N samples [JOS1 6.2]. + +- Discrete Fourier Transform of x(n), n, k = 0,1,...,N-1 [JOS1 5.1, 6.6, 7.1], + [PROAKIS 5.1.2, 5.1.3]: + + N-1 + X(w_k) = X(k) = sum x(n) W_N^kn + n=0 exp(-j w_k t_n) + exp(-j 2pi k n / N) + Inverse DFT: + + N-1 + x(n) = 1/N sum X(k) exp(+j w_k t_n) + k=0 s_k(n) + with: + . s_k(n) = exp(+j w_k t_n) + +- Matrix formulation, DFT as linear transformation [JOS1, PROAKIS 5.1.3]: + + DFT: + XN = WN xN + + |X(0) | |1 1 1 ... 1 | |x(0) | + |X(1) | |1 W_N W_N^2 ... W_N^(N-1) | |x(1) | + |X(2) | = |1 W_N^2 W_N^4 ... W_N^2(N-1) | |x(2) | + |... | |... ... | |... | + |X(N-1)| |1 W_N^(N-1) W_N^2(N-1) ... W_N^(N-1)(N-1)| |x(N-1)| + + IDFT: + xN = WN^-1 XN = 1/N conj(WN) XN, so + + WN conj(WN) = N IN, where IN i N x N identity matrix + +- Real input: X(k) = conj(X(N - k)) + +- Spectral leakage or cross-talk occurs for frequencies other then w_k, because + this cause truncation distortian in the periodic extension of x(n) = + x(n + mN) [JOS1 7.1.2]. + +- DTFT Ndtft >= N [LYONS 3.11, JOS1 7.2.9] + . Zero padding N to Ndtft increases the interpolation density, but does not + increase the frequency resolution in the ability to resolve, to distinguish + between closely space features in the spectrum. The frequency resolution + can only be increased by increasing N +- N point DFT of rectangular function yields aliased sinc (= Dirchlet kernel): + + x(n) = 1 for K samples + X(m) = c sin(pi * m * K / N) / sin(pi * m / N) + + . c = 1 for symmetric rect -(K-1)/2 to + (K-1)/2 + . m = 0: X(0) = K + . m first zero crossing = N / K --> main lobe width is 2N / K + . K = N yields all-ones form that defines the DFT frequency response + to an input sinusoidal and it is also the of a single DFT bin: + X(m) = sin(pi * m) / sin(pi * m / K) + ~= K * sinc(pi * m) for K = N >~ 10 + +4) Multirate processing: +- Linear Time Variant (LTV) process, because it depends on when the + downsampling and upsampling start. +- Polyphase filtering ensures that only the values that remain are calculated, + so there are D or U phases [LYONS 10.7]. The LPF with all phases is called + the protype filter. +- For large D or U use two stage D = D1 * D2 or U = U1 * U2, where D1 > D2 and + U1 < U2 [LYONS 10.8.2] + +LPF + downsampling = decimation: +- Do not calculate samples that will be thrown away. +- Discarding samples folds the spectrum, first the LPF has to remove all + folds. + +Upsampling + LPF = interpolation: +- Do not calculate samples that will be inserted as zeros. +- Inserting zeros replicates the spectrum, the LPF remove all replicas and by + that it interpolates to fill in the zeros. +- Using zero order hold would be a naive approach, because then all samples + need to be calculated and the LPF then needs to compensate for the non-flat + pass band of sin(x)/x [LYONS 10.5.1] + + +5) Signal operators [JOS1 7.2] + +- Operator(x) is element of C^N for all x element of C^N + . assume modulo N indexing for n in x(n), so x(n) = x(n + mN) or periodic + extension +- FLIP_n(x) = x(-n) reversal + . x(0) = x(-0) + . x(-n) = x(N - n) for modulo N +- SHIFT_L,n(x) = x(n - L) + +- ZEROPAD_M,m(x) = x(n) for |m| < N / 2 + = 0 else + . zero centered, zero-phase, periodic + . ZEROPAD_10([1,2,3,4]) = [1,2,0,0,0,0,0,0,3,4] + . ZEROPAD_10([1,2,3,4,5]) = [1,2,3,0,0,0,0,0,4,5] +- CAUSALZEROPAD_M,m(x) = x(n) for m < N + = 0 for N < m < M + . CAUSALZEROPAD_10([1,2,3,4]) = [1,2,3,4,0,0,0,0,0,0] +- INTERP_L,k'(X) = X(w_k'), for X(w_k) with k = 0,1,...,N-1, where: + w_k' = 2pi k' / M, k' = 0,1,...,M-1 + M = L * N + . Interpolates a signal by factor L using bandlimited interpolation + +- STRETCH_L,m(x) = x(n) for n = m / L is an integer + = 0 else + . Upsampling by inserting L-1 zeros after every x sample +- REPEAT_L,m(x) = x(m), where: + m = 0,1,...,M-1 and M = L * N and n = m modulo N + . REPEAT_2([1,2,3,4]) = [1,2,3,4,1,2,3,4] +- DOWNSAMPLE_L,m = x(mL), where N = L * M and m = 0,1,...,M-1 + . DOWNSAMPLE_L(STRETCH_L(x) = x + . DOWNSAMPLE_2([1,2,3,4,5,6]) = [1,3,5] + L-1 +- ALIAS_L,m(x) = sum x(m + lM), with m = 0,1,...,M-1 and N = L*M + l=0 + . ALIAS_3([1,2,3,4,5,6] = [1,2] + [3,4] + [5,6] = [9,12] + +- DFT_N,k(x) = X(k) with N points +- DFT relations: + . STRETCH_L <==> REPEAT_L + . DOWNSAMPLE_L(x) <==> 1/L * ALIAS_L(X) [JOS1 7.4.11] + . ZEROPAD_LN(x) <==> INTERP_L(X) [JOS1 7.4.12] + . conj(x) <==> FLIP(conj(X)) + . FLIP(conj(x)) <==> conj(X) + . FLIP(x) <==> FLIP(X) + . x even <==> X even + . SHIFT_L(x) <==> exp(-j w_k L) X(k) + + + +https://learning.anaconda.cloud/ +https://realpython.com/python-scipy-fft/ + +https://mne.tools/0.24/auto_tutorials/preprocessing/25_background_filtering.html diff --git a/applications/lofar2/model/pfb_os/filter_design_firls.ipynb b/applications/lofar2/model/pfb_os/filter_design_firls.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..2d9d1bc97368846a346265c79a1056988a801efb --- /dev/null +++ b/applications/lofar2/model/pfb_os/filter_design_firls.ipynb @@ -0,0 +1,442 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e0a005d", + "metadata": {}, + "source": [ + "# Try firls FIR filter design method\n", + "\n", + "Author: Eric Kooistra, nov 2023\n", + "Purpose:\n", + "* Practise DSP [1].\n", + "* Try firls least squares FIR filter design method for LPF.\n", + "* Try to reproduce LOFAR subband filter FIR coefficients using scipy instead of MATLAB.\n", + "\n", + "MATLAB:\n", + "* The pfs_coeff_final.m from the Filter Task Force (FTF) in 2005 use fircls1 with r_pass and r_stop to define the ripple. In addition it post applies a Kaiser window with beta = 1 to make the filter attenuation a bit more deep near the transition.\n", + "* The pfir_coeff.m from Apertif also uses fircls1. \n", + "* Both use fircls1 with N = 1024 FIR coefficients and then Fourier interpolation to achieve Ncoefs = 1024 * 16 FIR coefficients. Both scripts can not exactly reproduce the actual LOFAR1 coefficients, therefore these are loaded from a file Coeffs16384Kaiser-quant.dat\n", + "\n", + "Python (scipy.signal):\n", + "* The windowed sync method, firls leased squares method and remez method all yield comparable results, but firls and remez perform slightly better near the transition band. The firls and remez functions from scipy.signal use transition bandwidth and weights between pass and stop band to influence the transition region and ripple. For remez the ripple is constant in the pass band and stop band, for firls the ripple is largest near the band transition.\n", + "\n", + "Conclusion:\n", + "* It is possible to design a good FIR filter using Python scipy. Possibly with some extra help of a filter design and analysis (FDA) tool like pyfda [2].\n", + "\n", + "References:\n", + "\n", + "1. dsp_study_erko, summary of DSP books\n", + "2. pyfda, dsp, at https://github.com/chipmuenk" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3563bc63", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f820b0ac", + "metadata": {}, + "outputs": [], + "source": [ + "import dsp" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a131b5b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<module 'dsp' from '/dop466_0/kooistra/git/hdl/applications/lofar2/model/pfb_os/dsp.py'>" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import importlib\n", + "importlib.reload(dsp)" + ] + }, + { + "cell_type": "markdown", + "id": "2a467746", + "metadata": {}, + "source": [ + "# 1 Least squares method" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "da2a98e9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "r_pass = 0.059254\n", + "r_stop = 0.000035\n", + "r_pass / r_stop = 1669.996877\n" + ] + } + ], + "source": [ + "# passband ripple (in dB);\n", + "r_pass_dB = 0.5;\n", + "r_pass = 10**(r_pass_dB / 20) - 1;\n", + "# stopband ripple (in dB);\n", + "r_stop_dB = -89;\n", + "r_stop = 10**(r_stop_dB / 20);\n", + "print('r_pass = %f' % r_pass)\n", + "print('r_stop = %f' % r_stop)\n", + "print('r_pass / r_stop = %f' % (r_pass / r_stop))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "4b23f0c1", + "metadata": {}, + "outputs": [], + "source": [ + "# LPF specification for LOFAR subband filter\n", + "Npoints = 1024 # = number of bins in fs, = DFT size\n", + "BWbin = 1 / Npoints # bandwidth of one bin\n", + "# . Use half power bandwidth factor to tune half power cutoff frequency of LPF, default 1.0\n", + "hp_factor = 0.9\n", + "BWpass = hp_factor * BWbin\n", + "fpass = BWpass / 2 # bin at DC: -fpass to +fpass\n", + "\n", + "# Actual FIR filter length\n", + "Ntaps = 16\n", + "Ncoefs = Npoints * Ntaps" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a81f3239", + "metadata": {}, + "outputs": [], + "source": [ + "# Initial FIR filter length\n", + "# . Use interpolation of factor Q shorter filter to ensure the FIR filter design converges\n", + "# and to speed up calculation. N >> 1000 is not feasible.\n", + "# . The passband ripple and stopband attenuation depend on the transition bandwidth w_tb\n", + "# and the weight. Choose 0 ~< w_tb ~< 1.0 fpass, to ensure the FIR filter design converges\n", + "# and improve the passband ripple and stopband attenuation. A to large transition band \n", + "# also gives the design too much freedom and causes artifacts in the transition.\n", + "Q = Ntaps\n", + "N = Ncoefs // Q + 1 # + 1, because firls only supports odd number of FIR coefficients\n", + "f_pb = fpass * Q # pass band cut off frequency\n", + "w_tb = 0.4 * fpass * Q # transition bandwidth\n", + "f_sb = f_pb + w_tb # stop band frequency\n", + "weight = [1, 1000000] # weight pass band ripple versus stop band ripple\n", + "hFirls = signal.firls(N, [0, f_pb, f_sb, 0.5], [1, 1, 0, 0], weight, fs=1.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "1d05396d", + "metadata": {}, + "outputs": [], + "source": [ + "# Apply Kaiser window with beta = 1 like in pfs_coeff_final.m, this improves the\n", + "# stopband attenuation near the transition band somewhat\n", + "# . beta: 0 rect, 5 hamming, 6 hanning\n", + "win = signal.windows.kaiser(N, beta=1)\n", + "hFirls *= win" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "dbd8577f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ". f_pb = 0.007031\n", + ". w_tb = 0.002813\n", + ". f_sb = 0.009844\n", + ". Q = 16\n", + ". N = 1025\n", + ". DC sum = 0.995106\n", + ". Symmetrical coefs = True\n" + ] + } + ], + "source": [ + "# Symmetrical FIR coeffients: coefs[0] = 0, coefs[1] = coefs[-1]\n", + "print('. f_pb = %f' % f_pb)\n", + "print('. w_tb = %f' % w_tb)\n", + "print('. f_sb = %f' % f_sb)\n", + "print('. Q = %d' % Q)\n", + "print('. N = %d' % len(hFirls))\n", + "print('. DC sum = %f' % np.sum(hFirls))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hFirls))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "cdf06c69", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "hinterpolated.imag ~= 0\n", + ". Ncoefs = 16384\n", + ". DC sum = 0.995106\n", + ". Symmetrical coefs = False\n" + ] + }, + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x7fe43d6f7430>,\n", + " <matplotlib.lines.Line2D at 0x7fe43d6f7460>]" + ] + }, + "execution_count": 9, + "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": [ + "# Use Fourier interpolation to create final FIR filter coefs\n", + "HFfirls = np.fft.fft(hFirls)\n", + "hInterpolated = dsp.fourier_interpolate(HFfirls, Ncoefs)\n", + "print('. Ncoefs = %d' % len(hInterpolated))\n", + "print('. DC sum = %f' % np.sum(hInterpolated))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hInterpolated))\n", + "\n", + "plt.plot(hInterpolated, 'r', hInterpolated - np.flip(hInterpolated), 'r--')" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "e2ddf023", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ". DC sum = 1.000000\n", + ". Symmetrical coefs = True\n" + ] + } + ], + "source": [ + "# The coefs are almost symmetrical. Therefore use simple way to make impulse\n", + "# response exactly symmetrical\n", + "hInterpolated = hInterpolated + np.flip(hInterpolated)\n", + "hInterpolated /= np.sum(hInterpolated)\n", + "print('. DC sum = %f' % np.sum(hInterpolated))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hInterpolated))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "891341c8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "dsp.plot_time_response(hInterpolated)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "3ed56c18", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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lR9sHAbiwrjTPkiw9nGfuvANF8aJKRSlKjrUPUFcW1cyvPLC8PEY8EnStRUXxokpFKUqOtg+wQa2UvBAICBfWlaqloviiSkUpOowxHG0f5MI6jafkiwtrE2qpKL6oUlGKjq7BMXqHk27AWFl4NtQlaOkZZiSpQ8WUXFSpKEXHiU5rooX1tfE8S7J0WVcbxxg41TU0/cHKkkKVilJ0NHdbDdmaKlUq+WJNtfXsm1SpKONQpaIUHU5DtlqVSt5wFLoqFWU8qlSUoqOpa5jaRJSSiC78mS9qExFi4QBN3cP5FkUpMFSpKEVHc88Qq6tK8i3GkkZEWF0Vd12RiuKgSkUpOpq6hl2fvpI/1lSV0NSlloqSiyoVpahIZwyne4ZZo5ZK3llTHadJLRVlHKpUlKKitXeYVMaopVIArK4qoX8kRe9QMt+iKAWEKhWlqHDcLRpTyT9uBphaK4oHVSpKUaFjVAoHx1rUYL3iRZWKUlS09FiWyspKtVTyjWMtNmtaseJBlYpSVLT1jVCbiBAJadHNNxUlYWLhAGd6R/ItilJAFGzNFJGPi4gRkVr7u4jIl0TkiIjsFpGr8y2jsvC09Y1SXxbLtxgK1liV5eUxzvSpUlGyFKRSEZE1wG3AKc/mNwGb7L+7gK/lQTQlz5zpHWF5hSqVQmFZeYw2VSqKh4JUKsA/Ap8EjGfbncB3jcWzQKWIrMiLdEreONs/wrLyaL7FUGyWV8RoVfeX4iGUbwHGIyJ3Ai3GmJdExLtrFdDk+d5sb2v1ucZdWNYMdXV1NDY2zpu8c8HAwEDBywj5lzOVMXQMjDHcdYbGxq5Jj8u3nDNlMciZ7B3jTE+Sxx9/nHH1dcFZDM9zMZAXpSIijwHLfXbdDfwvLNfXrDHG3APcA7BlyxbT0NBwPpebdxobGyl0GSH/crb0DMMjv+KGKy6i4fq1kx6XbzlnymKQ83j4OA8d38cV172amkR+LcjF8DwXA3lRKsaYW/22i8jlwHrAsVJWAztF5HqgBVjjOXy1vU1ZIji+e3V/FQ7Ly6341pm+kbwrFaUwKKiYijFmjzGm3hizzhizDsvFdbUx5gzwAPABOwvslUCvMWaC60tZvLT1OkpFA/WFgpM0oWnFikPBxVSm4CHgDuAIMAR8KL/iKAtN1lJRpVIouEpFM8AUm4JWKra14nw2wEfyJ42Sb870jRIOCtXxSL5FUWxqSi2XV+fAWJ4lUQqFgnJ/KcpUnO0bob4sRiCQ3ywjJUskFKCiJEzHwGi+RVEKBFUqStFwpm+Eeg3SFxy1iYgqFcVFlYpSNHQMjFKnGUYFR00iSoe6vxQbVSpK0dA1OEZNQuMphUZdIqqWiuKiSkUpCjIZQ/dQ0g0MK4VDbSJCR78qFcVClYpSFPQOJ0lnDNWlaqkUGjWJKH0jKUZT6XyLohQAqlSUoqBz0OoJq/ur8Ki141xdgxpXUVSpKEWCMw5CLZXCo9ZW9B39qlQUVSpKkeD0glWpFB7OnF8arFdAlYpSJHTaSkUD9YVHnSoVxYMqFaUoUEulcKksDQNWMoWiqFJRioKuwTHKYiEiIS2yhUZZNEQwIPQMqVJRVKkoRULn4Bg1aqUUJCJCRUmYnmEN1CuqVJQioWtwVF1fBUxlSVgtFQVQpaIUCT1DSap0yvuCpSIe1piKAkyznoqI/OkMrjFojPn6HMmjKL70jSTZvKws32Iok1BZEtZJJRVgekvlz4AEUDbF38fnU0BFAegdSlIeK+g15ZY0lfGIxlQUYPqVH79njPn8VAeISOkcyqMoE8hkDP2jKSpKwvkWRZmECo2pKDZTWirGmE9Od4GZHKMo58PAWApjoFyVSsFSGQ/TP5Iilc7kWxQlz0wbqBeRm0TkCvvzu0XkyyLyJyIyb0ObReR/iMgBEdkrIn/r2f5pETkiIgdF5I3zdX+lsOi1e8DlMVUqhUqlrfD7RlJ5lkTJN9MF6r8CXAFEReQQVnzll8CNwLeA35xrgUTkZuBO4BXGmFERqbe3XwK8F7gUWAk8JiKbjTE63/Yip2/EVipqqRQslXZmXs/QmKZ+L3Gmi6ncbIy5RERiQAtQb4xJi8jXgd3zJNMfAn9jjBkFMMactbffCfzA3n5cRI4A1wPPzJMcSoHgpKqWl2igvlCpiFsKv0fTipc807m/RgCMMSPASccqMMYYYL5Kz2bgtSLynIhsFZHr7O2rgCbPcc32NmWR0zdsuVQ0UF+4OO6vXg3WL3mm6/rV22NVxPMZ+3vdbG8qIo8By3123W3LVA28ErgOuE9ELjzH698F3AVQV1dHY2PjbEVdEAYGBgpeRsifnNubrYZq364dtB+afryuPs+5ZSZynhm0AvTP7NyNnMmPRbmYnmcxM93b/1essSjjPwN8Y7Y3NcbcOtk+EflD4Ce2NfS8iGSAWiz32xrPoavtbX7Xvwe4B2DLli2moaFhtqIuCI2NjRS6jJA/OY88eQxe3s9tN792RtaKPs+5ZSZydgyMwpOPsWb9RhpetW5B5BrPYnqexcyUSsUY85cLJYiHnwI3A4+LyGYgAnQADwD/ISL/gBWo3wQ8nwf5lAWmbziJiDUbrlKYJOx30z+q2V9Lnemyv7401X5jzB/PrTiAlVX2LRF5GRgDftu2WvaKyH3APiAFfEQzv5YGvcNJyqIhAgHJtyjKJERDAUIBYUBTipc803X9dtj/bwQuAe61v78Lq3Gfc4wxY8D7J9n3BeAL83FfpXDpG0lpOnGBIyIkYiEG1FJZ8kzn/voOuHGO1xhjUvb3fwGenH/xFMVyf2nmV+GTiKpSUWY+9X0VUO75nrC3Kcq80z+Scn32SuGSiIbU/aVM6/5y+BvgRRF5HCud+HXA5+ZLKEXxMjiWYnl5LN9iKNNQpu4vhRkqFWPMt0XkF8AN9qY/N8acmT+xFCXL0FiauFoqBU8iGqJzUKe/X+pMl/213FEe9v+fTXWMoswHg6MpSiPBfIuhTEMiFuZk51C+xVDyzHQxlYdmcI2ZHKMos2ZoLE08opZKoZOIBnWcijKt++sVItI3xX4BptqvKOeFMYbBsRSJqFoqhU4iGmJQlcqSZ7qUYq3JSl4ZSWYwBo2pFAGJaJihsTTpjCGoA1WXLDNNKVaUvDA4ZvV8NaZS+MTtdzSc1IkuljKqVJSCxnGnaEyl8Ik5SmVMlcpSRpWKUtAMjloNVKnGVAqekrD1jkbUUlnSzGSN+qCIHFgIYRRlPENjaqkUC45SUffX0mZapWLPBHxQRNYugDyKksPgmFoqxUJJxGpO1P21tJlp968Ka+r554FBZ6Mx5m3zIpWi2AxpTKVoiKmlojBzpfLZeZVCUSbBtVRUqRQ86v5SYOZzf20VkQuATcaYx0QkDqg/Qpl3nAYqFtackkKnxM7+GlH315JmRjVVRH4P+BHwdXvTKqxlfxVlXhm1lUo0rH2YQsexVIZUqSxpZtr9+wjW6o99AMaYw0D9fAmlKA6jqQxgLVerFDbq/lJg5kpl1F7mFwARCQFmfkRSlCxjqlSKBmfwo45TWdrMtKZuFZH/BZSIyBuAHwL/NR8CiciVIvKsiOwSkRdE5Hp7u4jIl0TkiIjsFpGr5+P+SmExmsoQCQUQ0bmkCh3XUlH315JmpkrlU0A7sAf4fazp7j8zTzL9LfCXxpgrgb+wvwO8Cdhk/90FfG2e7q8UEKOpNNGgWinFQDgYIBwUdX8tcWaap3kz8O/GmH+dT2FsDFBuf64ATtuf7wS+a4wxwLMiUikiK4wxrQsgk5InRlMZopr5VTTEwkFVKkucmSqVDwBfE5Eu4EngCeApY0z3PMj0MeBhEfl7LEvq1fb2VUCT57hme5sqlUXMaDJDNKSZX8VCSTioMZUljlgd/xkeLLISeCfwCWClMWZWI9JE5DFguc+uu4FbgK3GmB+LyLuBu4wxt4rIz4G/McY8ZV/jv4E/N8a84HP9u7BcZNTV1V1z3333zUbMBWNgYIBEIpFvMaYlH3J+bdcIJ/sy/M3r4jM+R5/n3HIucn7yiSE2VAT4/VfE5lmqiSzG55kvbr755h3GmGtndbIxZto/4P1YY1SeBh4APgm8aibnnusf0EtW2QnQZ3/+OvA+z3EHgRXTXW/z5s2m0Hn88cfzLcKMyIecv/ed7eaN/7j1nM7R5zm3nIuct/3DVnPXd7fPnzBTsBifZ74AXjCzbMNnamn8E3AU+BfgcWPMiVlpsJlxGrgJaAReDxy2tz8AfFREfgDcAPQajacsekZTGU0nLiLCIXHTwJWlyUynaakVkUuB1wFfEJFNwEFjzG/Ng0y/B/x/9liYEWw3FlbG2R3AEWAI+NA83FspMEZTaY2pFBGRYIBkWoewLWVmpFREpBxYC1wArMPKypqX7oixYibX+Gw3WCP7lSXEaCpDQtenLxoioYBaKkucmdbWpzx/XzbGNM+fSIqSZSyVIVqq7q9iIRIK0juczLcYSh6ZqfvrCgARKeyUBWXRYcVU1P1VLESCaqksdWY6S/FlIvIisBfYJyI7ROSy+RVNUayYSkQD9UVDJCQk06pUljIzra33AH9qjLnAGLMW+Li9TVHmFWvwoyqVYkEtFWWmtbXUGPO488UY0wiUzotEiuJBU4qLCw3UKzMN1B8Tkc8C37O/vx84Nj8iKUqWsVRGF+gqIiKhAGPq/lrSzLQL+GGgDvgJ8GOg1t6mKPOGMcYep6KWSrEQCQbVUlniTGmpiEgM+ANgI9a09x83xmi+oLIgpDKGjNEFuoqJcEjUUlniTFdbvwNci6VQ3gT83bxLpCg2zlLCmv1VPETtQL05h4lqlcXFdDGVS4wxlwOIyDeB5+dfJEWxSNvTfQQDqlSKBeddZQwEdbHOJcl0tdV1dRljUvMsi6LkkLZ7u6GAtk7FQsjWJOmMWipLlekslVeISJ/9WbDWqO+zPxtjTPnkpyrK+ZHKWO6vgCqVoiEgqlSWOlNaKsaYoDGm3P4rM8aEPJ9VoShzxsEz/Tyy90zONlunqKVSRDjvKj0upvLg7laOtQ/kQyRlgVFntZIXeobGePzgWdIZa2GfN/7TE9z1vR0c7xjkTO8Iu5t7XEslKKpUioWgo1TShp2numnvH+Xlll4+8h87ufPL2wBIpjP86kAb/SOaSLoYUaWi5IXP/PRlPvTt7fxsVwtn+kbc7TtOdvOJH77E2768jRMdQ0C2oVIKH+dd7W3t5de++jSf+ekeXjjRBUD/aIre4SQ/eP4UH/63F/jrXxzIp6jKPKFKRVkQ/uGRg9z+T0/QMzSGMYath9oB+O/9Zzlwpt897lBbP08d6QDg5dO9gCqVYsJ5V7ubrXf38N42Dp3Nur0OtfXz2P6zADx+wPp/tm+EW/5fI19rPLrA0irzgSoVZc4xxvD9506y77SV49E3kuRLvzrCgTP9/PTFFpq6hukfsZIJD7b109pjWSqhgNDcPeRe54jdGKlSKR6cd+W8OxFo6x1xYy2tvSMcaut3P3cOjHLfC00cbR/ki788wEgyDcBLTT3ct71Jx7sUIapUlPNmJJnmbH/WhfXw3jbuvv9l3nPPM6Qzht1Nve6+7Se7Odk1CMBVays52TnI6Z5hAgKXrizPsVo6BkYBVSrFhPOunHdnDBzvHOTy1RUAnOwYpLV3hKvXVgJwqmuIF052u+cfONPPWCrDO766jU/+eDfbjnS6+9r6RnQKmCJAlYpy3nzo29t5zRcf56CtEB7d1wZA/0iKA2f6OHDGsliuXFPJsXZLiQBctaaKZNpw+Gw/NYkoyytiHGsfdK/bPWQFclWpFA9OUoXz7gCOtQ9yYW2CknDQdWletbYKgNM9IxxtH+AqW8kcaO1jV1MPTkbyo/usjMBdTT3c+De/4o++v3OBfokyW/KiVETkXSKyV0QyInLtuH2fFpEjInJQRN7o2X67ve2IiHxq4aVWwFIY1/7Vo67iON4xyDPHOhlLZfjxTmuV6b2ne1lfa62MsLelj+buYcqiIa5cU0lT1xCne0YQgctXW1npR84OUFESpioeyblX9+AYoNlfxYQz+NF5dw6V8TAVJWHXLXaFbbmcssvDKy+sIRgQmruHebnFUjzra0vZa7tQ73uhiVTG8Nj+Ns7aiR0/29XCtX/1GE8d7liQ36bMjHxZKi8DvwY84d0oIpcA7wUuBW4HvioiQREJAl/Bmn/sEuB99rHKPNLSM8w7vrqN/3z+lLvtS/99mI6BMb78+BHAytYCqCgJs/NkN+mM4Vj7ILdeXE8oIJzoHKS5e4hVVSWsqixhYDTFqa4hKkrCrKgoAeBo+yDlsRDxSHYsbjwSpHvIVio630fREHAtlTHikeySBaXREBUlYY7aluiGugShgHCorZ90xrCmKs7y8hjN3UOc6BykLBbi1Rtq3PjLi6d6qCgJA7DzVA/glMVRvvz4Yfc+33rqOO/6l6dp7x9diJ+r+JAXpWKM2W+MOeiz607gB8aYUWPMceAIcL39d8QYc8wYMwb8wD5WmSMGR1N88NvP86X/zlbQbzx5jBdP9fC5B/YykkwzmDS8fLoXEdjd3MPgaIoDrX1EQwHuuHwFh88O0N4/ylg6w7raUpZXxGjpGaatb5Rl5TGqSy1L5FjHIJUlYcpjYfdeFSVhSqPZRmhZecwN5qulUjw4Afn+kRTLymPu9tJIkPKSbKehoiRMZTzsDoisSURYURGjrW+Ulu5hVlWWsLY6Tt+IlYZ89OwA77hqFQGBA2f66BgY5Wj7ICKw82QPI8k0Q0nD53++j+0nuvneMyfce33xlwf4ve++4CYBKPNLocVUVgFNnu/N9rbJtiszwBlg6DCSTPP+bzzHx+97yd3+ox3NNB5s5x8ePeRmYDluhdFUhpdbemnuz2AMvO/6tRhjZW6d6hrigpo462ri9A4n3Z7liooYqypLON0zTPfQGDWlkaxSaR+gMh6hLJZtZMpLwjmWinMs6Ij6YsI7pY73HcZtS8UhEQ1RGY+4MbTq0ghVpRG6h8Y43TvCysoSlldYSumlph7G0hk2LUuwvDzGqa4h9rdabrH3Xb+WsXSGY+2DHOnJKo0n7LJ7uK2frzUe5dF9bTy4uxWATMbwke/v5Hf+bTtJzzT9mYzR6WXmgJmu/HjOiMhjwHKfXXcbY342X/e1730XcBdAXV0djY2N83m782ZgYGDOZOwdNWSMoSpm9RdGU4bPPztMKCB89pUxQgHh6dMpnjpiuQcuCnewqSrIT3Zks7e+9eA2blge4sjZIRpWh2hsTnH/1h2QHAWEZSkrnvLLp3ZwsDlJRUToaz0OwI+3vghA06GXyQwnae7P0D1iGOxq4/hBK5OnfyRFZrifXS88596zr/MsLaNZ33hyqM/9vHv3S4w1z3z1x7l8nvPJYpRz/9nsvLPed3jq6CEGe7ON/o7ntiFjI/SPWo36kZd3MdqX5Ey3dUxtYIgzx6zznTLVdeowpZJk34lWEiPWOKf6pFUWH3zieU52jwDCTatDPN3Sw3//6nEeO5WV54dPvUxN/xH2tKd4cI9V/v/5R7/i6mUhRlOGv3x2mGhAuNuuJwCdwxkiQaEsMncdm2J577Nl3pSKMebWWZzWAqzxfF9tb2OK7X73vge4B2DLli2moaFhFqIsHI2NjcxGxm1HOggFhBsurAGs4GjD3zcSEPjVxxuoKo3wk53NtAy8BBiSdRdx6+UreOC+XUSCrYylMwyWraGhYTN//vRjvP3KZTy6r41M+UouuGwN5rEn+fXXXs72H+8mXLWSzjMtBAMpPvzWm/jHHY9QsWIdA0ePc+OG5dx05Sq+susZUvFaoJU33nQjB9OHOfDSaUbSKS7fciG3vGIln3+mEYALVi3jttdfAb/6JQAbLljDRSvK+ff9LwGwbuUydrefBuDaq6/i2nXV8/48F5pFKefBs7BzOwDrV2Xf4TWvuJyBQ2d55nQTkWCAW19/M/9xajuHe6wBkG9ouJETTx7j2dYTIHDxhrXccu1q/vr5J0jGa4Az3HLj9RxOHWVXUw+l9SsIHzzGh992E/+08xHKVqynp/0Iy8qD3H79Zrb+ZA9brrqBhzoOU1/WzhWrKznWMUBDQwPbHtxHQI4TEKEntpyGhsv44QtNnB7YDRjSyy7m1kuX09Y3wi3/byslkSCNn2igNGo1l08d7iAczNa7eX2eRUihub8eAN4rIlERWQ9swlrDZTuwSUTWi0gEK5j/QB7lnFeGx9KMprK9ulQ6w6d+vJu/ezg7rcWhtn5+8xvP8Z57nuVkp+VC+Pnu0/QOJ+keSvKLl61UzGeOdlIWC1ESDvLsMctSeLmll9dsqmVDXSn7W/sYHE3R1jfK5uVlbKhPcLR9gFOdlgtsbXWctTWlNHUN0TNqqE1EKItZ/vAWP9dWhyVLZTxMZUnYjYtUxCOUeAK38XCQaCjoLsAVDQco9e73fNZZiosHb/q3170Zj1jvGyBhby8JewL5kRCVJRHG0hnGUhkqSsJUlDjuUqtM1SSsctY9OEZrzzDLymOUx8KURoKc7RulfSjDBdWlrK2OA1Zm2bGOATbUJdi8LMHJziFS6Qz7W/u5bFUFV19QxR470+yZY51UxsPEwgG3njyw6zQDoyna+0d5xE5tPnCmj/d/06p3TV1WHTHG8H9+vo///bOXyWRy3cxLMY6Tr5Tid4hIM/Aq4EEReRjAGLMXuA/YB/wS+IgxJm2v5fJR4GFgP3CffWxRY4zhvu1NnPC4BVp7h7nxi7/i17/2NCnb3/vovjZ+sL2Jrzx+lN3NPQCufxjgYXt23+eOd7GiIkZtIsoLJ635lva19nHV2iouW1XO/tZ+MhnDiY4hNi1LsKEuwdH2QZrsGMqaqjhrq+M0dQ3R2mu5w1ZVlbCsPMrZ/lF6Rw11ZVEAahNRTnQMkjFQFc+Nl0RCAWLhYE6KcGkkmBMziYWtohdzlIpHwQCEg9nPGlMpHrxKxenZg7UktLMstJOQEbOViohVHryJGlXxiBuDOe7pqFSXRui3O0G1Cass1pVFOds/Qs+oob48yqpKK6vwdM8ITV3DrK2Os6Y6TjpjaO21xsVsrEuwqT7BCfva+1v7uXJNJZetrGBvi+V2236iiwtq4lSUhHnumFWfHtqTnUn7l07H7Vgn33zqON955iTbjjpxyDRv+eeneN3fPk7nQDYTbeepbp4+nVrUMwXkK/vrfmPMamNM1BizzBjzRs++LxhjNhhjthhjfuHZ/pAxZrO97wv5kHumZDLW3FYDo1l/blPXEHd+ZRvffOq4u+3BPa188se7+b/PjTA8ZimWe7c30TU4xsstfTx33CrIjx88657TeNDyJe893cfmZQkuqImzq6kHgBOdg2xeVsbltgIBON0zzJqqEtbXlnKsY5C2/hHG0hlXgbR0D9PSbQ1GXF1VQn1ZjLP9o3QOjBIQq3LXJqJ0DIzSO2aosytyZUnYrexVpZZVImIF9SvtxsCb7ROPBHN6prFIbowkGgrkWCRepRLQ7K+iwZupF/W8w2BAXKXiWCwlEet7STiIiOSUj7JYiEgoQDwSZDSVIRENEQ0FqYpbZetE5yCV9uf6shjt/aP0jRlqE1Fq7Y5PW98InYOjLKuIsabKsl5OdlodpjW2oukeStI7nOREhzVA88K6Uo7blv/+M31ctqqCi1eUcdBOQNnV1MMlK8pZW52td1vtOgnw+AHrc+PBdo6cHeBs/yj3v2h56nuHk/zaV5/mnt2jNB7KnvOVx4/wa1/dRptnYtXe4SRPHm4vSuVTaO6vgmY0lWb7ia4cE3fnqW7e8/Vn3PEaAN986ji//a3n+dgPdrnb/mXrUV5q6uGvHtxHnz3l93+9ZPmbxzK4JvezxzrZWJ8gIPCcvW13cy8NW+rYVJ9wLZXjHQNcWJvgouVl7tQmTV3DrKku4YKaUk51DjI0lqJ7KMnKSmtbx8AoR89aFcayQGIMJ9Oucqgvj1FfHmVoLM3JriGqSyMEA0JtIkrnwBgDY8a1PirjYdeaqYxHCASEUtsSKbeVSizsdWeFCAaEsD3mxGlAnEcZCwdzGqRwKPs5pONUigbvu8rpGASEqP3OnYYy5igXe7vXsnG2OWnnCXtflW0Rt/aOuJ2XiniY9v5RhlOW1VIaCRINBTjU1o8xUF8WdS1sJ2tseUWM1VWWRbOnuZfhZJq1dt1p7x+ldzjJ6Z4RLqwtZWN9wh20eaC1j4tWlHHxijL3Wi8193DlmkquW1fFS3b9fPZYJyXhIBfUxHn6qFWPt3oUiVP3z/aP8HcPH2TnqR6+5elw/sH3dvBb33ye/3w+m/T69NEO3vP1Z9h7OjvtUTpjeP54V04WW75RpQKc6hxyR/E6/Ofzp/jAt57PGUT1p/e9xLv+5Rm+/fQJd9sXHtzPc8e7+Px/Zb1x971gFYTH9rfRZY8sfuJwO9WlEYyBZ+1CtuNkD3dcvpyg4LqrjncM8orVlWyqL2Pv6T6MMTR1DbGuxircx9oHSaUznOoaYn1dKetqSmnuHqZ32OpxramKc0FNnMGxtDsaeUVFbEKlqktEqS+3tjkTP9aURlxL5EBrPzWlUXf7WDpD14hx/eSVHtdWueMjj+Q2ErlKxXF15CoVJ4UzGgrkuE4i3l6uWipFQyCnY5D7Dh1LxelIuOVl3H/v5/i4/wmP4nHKYFksxAnbuqiKRxCxOkLOtEF1ZVHXPeuU/2XlUdd9lt0WY4WdxryrqccalFkdZ3VVnP6RFJ0Do5ztH2V9TSnraq16l8kYjrYPsqk+wcb6Mnfczd7TfVy8oowr11RywL7+zpPdxCNBrqwLstPuhDpp+zWlEVfpNHUN8YzdoXTaEoDP/vRlnjvexRd/mR3i95XHj/Durz/DZ3/6srutpWeY3/zGs9z/YnPOu9nV1EOLPUXSfLLolcqYJ06WTGf4yPd38qf37nIbs6GxFO/46jbe8s9P8ZJtzvYOJ/nMT1/miUPtfOPJY9a2oSS/2GPFMe7dbo0w7xkaY8fJbmLhAC8199IxMErP0BiHzw5w85Y6wBpxPpJM09w9zLuuXU1ArED5wGiKjoFRLl9VSX1cONw2wNCY5SteXxtnfW0pJzoH6RtJMTiWZnVVCetqSznVNURT9zDJtGF9bSmrqkoYS2VcU3xNddwddOb8nhUVJdSPUyq1iWzv7WBbP/FIkFg46Pqxm7qHqLDdC05g1QBlds/RO3CxJGztL51CqTiNhNPkOPucFQKj4VylEh7nOlGKg1DAPy7mdX85dc8pA877jXvdo/Znx7qJRx3lkju2Cayy6Cgqp9NTURLmpJ1sYk0BZB176KylaKpLo9QmchVNfXm2TjjWwHKPonFG8q+qKmF1VZyxdIaTXUO094+yrraUC2tL6R5K0jM0xsnOQS6sS7B5WRmne0cYGkvR1DXE2uo4F5QHONk1xEgyzcstfcTCAd593RoOnx1gJJl2vR43b6ljT0svw2NpmrqGONo+SCwc4OkjHYwk0xhjuHe7pXTuf7HFTQr4yuNH2Hakk8/c/7K77Zmjnbz9K9t459eedq2asVSGP/r+Dv703l053henLZkti16ptA5m3HjFw3vP8OCeVn7yYgtP2L2Cxw+002lbE47v89ljnaQzhlg44MYwdjVbk9y9dlMth9oG6B1Oupkjv/faCwGrd+K4kt5+lTU281BbPyc6BzEGLl1ZwdrqOEc7spMqrqoqYUVpgOMdg+6iVOtqS1lTXUJz97A7EHFlZQkrKmKkMsZVFmur4+5UJ9vt+MvqqhJq7F6ZY32trPRYKmecShVxFcPJziHXreVU1KGxNGV2r9DrlnAqbdwnU6vErvDRcNZXnj3G2heY1FIJqlJZBHh0ChGPKyzocX8579wpA85Rvokc9v94ePJy580ycyyZRCzEsN2glsVChIIBK2PRjh+WRoKuJe64j+sSXove2laTiLidtF1NVmO/oqKElRXjt8VYaScInOgcoq1vlDVVcdfFdrpnmObuYVZXxVleGsAYq9452WmXrCgnnTEc7xjkWIc1U8CdV64inTEcbR9wra4Pvno9qYxhX2sfrb0jtPQMc9PmOkZTGbdd2HqwnVg4wOBYVkH9aIdltbT2jrDNXq/o4b1neGjPGX7yYgtbD1vtXO9Qknd+7WnOh0WvVAyw9ZAV6N56sN0O+AVotIPf2090EY8EefWGGjcw/nJLLwGB33nNeg629TM0luK4bda+w1YW+1v73J7Qm69YAVijd5vsQrtleRnLyqMcax90UyIvrC1lTXWc5q4h1wxdVRmjOiac6R1xTfh1NaWsqixxR7KDpVTqy6yCvM+1NrJZV47Pt64sG6g84DH/HVdBc9cQiagVBHWskoHRlFsxvRXUUSYJT1aOY6lM5aqIuZZKtng5+1wlEs7ttUZDgVzXiadBqhw30aRSuDjuU5jcUnGWiXbKScpRMt4yFc61ekvGlS3IZg76l1mPReOJyzizJ3ut8lNdWYvGqU+H2xxFE3U7aU48ssZT7xzls8yORwLsseMqKyuziqa5e5im7iHWVJdQV2KV7dM9w671ssZOg262E2eWlcW4eIU14erR9gG3bbjt0mW2LAOu2/q9162xZemja3CMlp5h7rI7uo7VseNkF6/bXEcwILxwwlI0Tx5ud+NPTrLBo/vb3PcxWxa9UhGykx7uaenlunVVXLG6wrUyDrX1s2V5GZevquDo2QFS6QxNXUOsqCjh0pXWTKrH2gc53jFIIhri2gusQXgnOwdp7bVGqm+qL6MsGrIKTlduem5Lz5BrvayvLWV1VYlbcABWVcapign9oyn3uJWVJdTYlXOPx9pwCq1jrleXZn3FbtplScStBCc6BwkFrKwap+L1j6bcCud1YTmVsbxk4rZE1LvNdkt4/OXjlYqf+8uJkWRsd5e3wbGul2upOOnFm+oTOdN7KIVNfXnMLWvjM/icrC8npuwE9Z0EJ2+Zio0rQ+NjK5Atd97ymfCxrp1yXuqxhEoiQQIBIRENuVmaiVgox3oHKzHAcQO72Y7xiGvluK6zsqjrYt5nK5rasijLbSvnUFs/Q2Np1lTFqYxZv7utz7I0VleVsMa2aJq6hmjpsSdgrcqmRp/sHKIsFuLyVRUEA8LJziFO2m3NDRfWUBYNcaJzyPVsXLaqguXlMbdNa+4e5rKV5WyqT7gyHzk7wOWrK7h8VYXbed1xsjtHSc+GRa9UwgE41DaAMYZjHYNsWlbGluVl7mypp3usyes21CcYS2do6RmmqdvKonKmbz/ROcjxziHW15aystKawsFJTVxWHiMYEFZWltDSY7mrakojlEZDVnpu3yhtfSP2hIkh6hJRuobGaOoeIhwU6sui7pQq+1v7CIjVY6qx/b0Hz/QjArWlUTfb5XjHIAGx0nq9KZaRYIBYOOBWrJFkhrJYCBEhEQnhGAKOYkj49PByXQnBnOPBmw6aO5ARvMpkovtr/ADG8R6taDiQMx7FaZC8jYNSHDjlzxuoDwXEtU6djsX4VHFvGZnMUvEqFUfheMc3JXysa6ece8txNuMsmwDgWFPhoDCcTBMLBwgHsxa9Yy1UxsNUJ3I7cxXxsNsRdKyc2tKom622xx77sqqqhIqouOeOJDNuIkEoILQPjHK6Z4RVlSUkoiHKoiHa+iwvxvraUsLBAMvLrYlam7qGKIuGqIqHWVVVQnP3EM3dWbf6+lorPfp0zwipjGFdjZXYc7xzEGOsBIMNdQm2LC9z5+w72j7AlmVlnA9LQKlY06/3DCUZS2VYXm7lrDvZUqd7rRe42jNg6pRtkjoBura+UU52DrKutpRQMGAPthqltWfEnfRuRWWMM70jtt/Uula9PWiwc3DMVRI1iag1GeOZfurLYlZvye5oHe8YpDJupfE6PaHjHYOURUMEAuJaEc3dw1SUhK1tsTABe3xIeUkYESFkKxfIuqucXhlAwt4W9G5zAqEeReD0AL2uBKc36aSDAoSCjv87t3cZDee6P7yMb1Amur9sX/q48SxK4eMogAkxlXGB+nHGak6W3/gyFAtP7Mz4KZW4R0lAblaht4PinJsY15kSEbfOOOU/GgoSCwcYTWUoi4YIB63ZH8JBcRtxZ2R/QLLKpzoRoTQSJBIMuFlh1aURwgGhoiTsuqdrSqOICNWlETr6R2ntHXatlOUVVrvS0j3sjrWpL7fGjZ3ptdofEWFVZa4HZHVVnBWVMdo8bvULauJcUGsNbm4fsNKmN9YncmaDbu0ddl12s2XRK5VQAFq6h90xFcvKY67/8qWmHsZSGSsIbj/IYx3W9O1rqqyRtJFQgLa+Edr7R1lmm7c1iYj1UvtGXMVTHbdmWO0aHMsZdT4wmqKle9h1SXndVU4PKG6PyTjRMehaHs7Aro6BMd+MK6eCBALiBjgrSrxWxkTLI+tb9lZMp/G2jgt5arrTi/O6MZyGocSnsXcqr9MLjAazxzgNhuOtHa9UYuFc91d1qSXr4NjSm+ai2Bkatd6Zd0aFQCDr/nIyjSZaKtnPTkzNzRCzj/WmmruKx6NUHAXjlGfv8Y77K+JRNH71xPnsrSdOXXXqnYi4n6P2DBKOQuoYsBJ/Ku1OXlVp2B2571ynoiSco3zAahuOtA+QTBvXbVZtz9zs7ZjWJqK094/SOTjqbqsri9I5OEZzt+Ums9YrsgYyO9bUutpSlpXFSKYNu+xMtvV2nBcs19sZe4bo82HRK5VgwAoEOkvaLq/Ipg068YoVFTHXH/qybaauqCxBRFhWHuVU5xBDY2n35TuDAVt7h12lUhm35iTqGUq6FoXXbK4ep1ROdg65I87jYauAD46l3XNzfML2tkgo4DbYXush62/2yYLxOS7X8pi4zcFRJl6l4lRabxDewWkknGO8jURg3OHjv1s9yuz3K1ZXArCuJj7hPkphs2lZAsBdlx5yx6k4aeQyTql4LRWn0XcsYue795wSH0vFUSLZMjhx2hivWzbhZjP6Z5A5OPtzFh4bN9jX+uwoneyxFSVht3PktAnlJSE3blMdd7wYEVf5OJ3KipIwXYNj9I0k3YSVujJLqXQMjLljbZw50Vps1xlYMw1YbV8/Ackdm+aMYVtWHmOZJ1abTBtWVmbXwZkNi95h7VjgjgKpL4u5edrezKq4baY6L9XpKVfFIxzrsE1X5+WXRtnT3MtIMuO+6OpSq+AkM6NUluSm5/YMJSeMDAZPADGcLfjOfq8bqnxcL2o4mfZP6fVO0OdUIM9x43txkFUOUR8l4QRSvZlYWaUy0VJx6rvTAHjHLDgNhnOlie6vYM5aFrWJKD/9yI1srE9MuI9S2Hz5fVfT1D2UU84CgWxZc91f45WKRwE4ysPpaPhN1eOWXZ954pz/Xq+rX6wv7rFeHNx4S049meh+cyz5id6AYUojIfc3eJ+Dq1Q8XgdHeZXHwm52mrO/Mh7mVNcQxkC1R9H0jSQZS2dylEoqYw2UdqwXRzGdsN3qgYC4GaROsL4mEaFk1PodbntYcX6WyuJXKnapch5YfXmUkaS9hsPZ7KpzIkJlPDuflfflH7CzOZygW1ks5I5tcRp8R7mMpTLuyyz3CYT7WSBxT3KTU6CtaU+CDI6lcwqtU6hzprQYNz7Euz/iY2VEctxZtotrvOlA1kIJ+RwfDU1UKg5uhfZc0nkPk7m/oqEAY6lcGa5cUznpPZTCpSIepiJekbMtFAhk3V9uoD73PL/ZqIN2IRoffwFyZrjOHu90hGxLZZo4nVMX/FxouTGYiec6yiLH8nHr+UTlYyXSWJ9zlIrTkcwZ2JltV0ZTGfczWO1PMm1IprNDAbxudSfByOspcdokx73uzCZeHY9QErasKNdzc56WyuJ3f9ll6mi79WCjoSDlsZCbwQXZYHZ1aYQz9qRuFa61EWLMtmycgpCTIeX6X729Fb/03ImZVM45IclWMG9Bdn22Pqm5pePWcwf/FF4/10DIx/Lwm18rPIWl4jcg0UkNDfhYKhNcHePOj4YDE1xiyuLB6/5yxkFM5f5ytzmWik95czovEU/szrmmU2a9l3SO99YTp9xP1/ly5ynzcZN561gs7NPpswduel3G45cFsK7n9U5M7Ji68Z+ozzb7+LF0JkchgTXgsdpVSE7KtBXTDQWtbNFIMOAqmqrzHBe26KuxUxa7BsdyMjxKo5ayCEh2ehHveIiKcXERyE0/dCiLThwM6PQ4yn19shNNahGZkI9v3S8bCHRwemXxqPd+E5WKU6kiPj0wv2nlx48bsfbZxwcmXmOq+bicfVMNhB9/eiQY0JHzi5hAIGvdOp2P8e/b7/1ny9LEfeNjeF4c69qruJxt3roanqLzFc5RFk5nbmK9y6mfjpUT8XYOJ9bPaM7AYLttiE7srJb4dB7LfFxnXrmcNqvSpz1zFE4ybdx2TERIxEL02K43HacyDd6i6DdIqiwW9vg+sy+mzOPndHBefqnPy/ee6xQYr4vINYu9x/n0cOI+PlvvdZwC7zdZY4mnoIZ9zPqoq1QmBkT91ixxXQiefdEpLJXx1xzfE/UyvpEIBQM6ceQiJugZp+Iwwf3lpzh8YiMOTqcn6qNUnLKbM/P1uBmyvdv8O1+epACfSS+zKc3euj+xHjvtRo5S8czQPD4TzSuj17opcZXKREvFq5AcpeNtp5z9k93PaWtEchXibFj0SiXgcS0lfHr3ZT7WBPinzvoF5hKel+XgptT6TFMS8jGzIVuAvTL4+XuzMRCZsC3XUplowvtZKq5S8bFUwj4usancXw4zWf/Et1eqlsqixTtOxWF8OZnKUhH8FI71389S8Xd/TbRK/Dpfbj3xWOgxn1ii4zrz67h5XdalPhZNNm4zsU3y3ienXfGJp/p1VscPGLW2ZS03d/4+b9wnknXjn+9Kq4s+UA/Wg+obSfnGK7za2s3wsHPOIbcQuZbKNMonmz8/8VywKk86Y3IKmVNpcvy9Tk8sPLEwBgMTFcO07i+fwHs2sJktSAGxpif3c4k51/ALnBo7DD+T9U+ccvvP77uKXx04myOLsvgIiiAivPHSZbzrGmuuqulmWYCsUjBMnI/KKS9TWSqBHPfXRKvcT9G4Fr1nTR9HSXjLfXiKc7338Ju3bPyCZeDfruR4JMITYzilPpaKm6HpHRQ6LhbUM5TMafv8pm6aLUtKqfg9xGjOg59ocvrt9zOVvS+txOc63kbbyX7xXtsvfTdbaSYWxlwlYCuVnOtNLLSuD9rX/RXIOS5jjK9ycO4/lTUyE0vFUdpvfcVK3vqKldZ5qlQWLU45+/pvXetuG/+6p3KXTnXNuI+7xmnUvZfMJp546mVoYrDfqTPeOuHU5ZyxNL6WinPuxDoW8+kceld29NY3py74WSp+3gevpZJNvrGmnEmmjW+n16vE/Nz4s2XRu7/A++An+hBzrYmJJqefS8lvMGDOnEShiS/fe45TjvzMcG9v3emd+ZnNuTn92Ns8FohPENOptF5Lxc3r9ynQfpaKe40pUrVmYnH4ZvpoTGXR4qcwzneZaKe8+A3E9atPTpnNWZ3Sx9pws79CE+tJIOd6PkolPLGNCPl03Jy2IZ2jVCb+Dj8Xek574JN8EMm5t70/p01zXG9+mabnrxKWlFKJ5lggE60O58VEfczU3OtlC5YbOA95exRZ/6WDf68/e45T+L2VwJ4h3FephHyUlLdMOgopV6lY//1iKl7LJxaaWDHGM1X670yUg1+Dou6vpcV5K5UpEkLCPvXSz1LxHeDruIkDEzta3rKdTRSY2F54RQr4dNyya8t4ZPYp/34dXL/OqJ/14sUvXpPTHvpcZ7bkRamIyLtEZK+IZETkWs/2N4jIDhHZY/9/vWffNfb2IyLyJTkHW9k3ldbHdPUz/fxGjvtZKkFvgfEZGOjXs5/OUnHWnfAqOadnFfKxaLy9KGdwureQBFylMtE091ZwR7n6ZYSNP8+PmbwZv2NUqSwtZvK6p8wgnOICTv2Oeer0+DEskO2Qea8U8XHxOsokx/LxiVuOT5sG/7R9pxHPTGOpeNsf595+CT7e5+Td77QNue4vuz30/Ba/1OrZki9L5WXg14Anxm3vAN5qjLkc+G3ge559XwN+D9hk/90+05u5fs5pzF7nOMk5d3LT2nu+twfjd85U8QnIWhnehjzts85EwMeice+RY+XkLoZlXSeYs8+6zkRZnd7RVJbKVNbITPT9VJk+ytLgvLOMpjg/464umS3DKdss8HbwRlLWaPKoT+PtXaxqxu6vcTMxW9ebqKTGL1I32e/x9ZRM4lZ39/skAPkN5Az5drKLNKZijNlvjDnos/1FY8xp++teoEREoiKyAig3xjxrrMjWd4G3z/R+ER/Tzs9Scd5pxMdH6iVHqbiDrLL7p2vw3XN9Xr63kc9kJsZUnFv7pft6C62zlKrfzMbemX8dubyF2+kdJb22+Th8rYpzWDBuqjEJytLgXF638SlbU7nPnPLvdR8l0xMXiBt0FujyyQJ11neHbNn0u2POtEd2e+GnkLziuovWZfwD9Q5+9cwv/uNluhisI2NOJ3sOLZVCzv76dWCnMWZURFYBzZ59zcCqyU4UkbuAuwDq6uro7+2xTjp1ksbGVgDOnhkFoLP9LI2NjQAcOWWNKB0cHHS3HerOFixn29mhbGO7detWILcQPfP00yQiuYXhpRd30nsstxewb89u0i1BBgYGGOi39h06eIDG/iMA9PZZayMcObifxp7DALSetuQ+fuwYjZkmANrs33L86FEa06es33rGmm7m2KF9NHYfsuQ+bc1XtvfQMRrFepztZ61z9+7bT3Wfdd9Q0jr3+RdeoOOwJdelNQFKg2n3GQyMZX+vs+1Mm3Wtgwf2u79h/DFOtssLL2ynNTF5AXaOnw0DAwPndf5CsZTk9Dv/aI9Vt0ZGRibsd74fO2aV2VOnTtHYeCbnmKeefMJtsK+uD5JOp9zzdp+1lMVYf7e77aB9rdbTzTQ2WmnsR09aZb3p+GEax05Yn5usduDYqWYaG61ldk+dnCjHCWfbyeM0NrYAcLzFOre9o8O971G7Xem0tw0MDHDk7F5LvlRW5v2dE9uadk9b42xLetqa5559hvJxbc3e3S8x1mTHbFLWvQ8eOECjXb97Oq16erq5icbGNgDO2G1Db1fHeb/reVMqIvIYsNxn193GmJ9Nc+6lwBeB22Zzb2PMPcA9AFu2bDHVNdXQ2c6mjRfS0LARgG2D++DkcdatWUVDw2UAtD5/CvbtIZFI0NDwWgCqm3vguW0ANDQ0ANZqkTzxq5xt6YyBRx4C4LWvfU12epdfPgjAK2+4jouWl+dsu+G6a7hyTSWNjY2Ul4egr5fLLr2EBjvFtuTFJ6C/n6uvvIKGLfUAbO3fC6dOsGHDBhrsdagfOLsLTrewZcsmGl61DoCvHnwGOrq4/uqreNWGGgCOh4/zk8P7qF2+0v3Nv+jYDS1NbNq8hYbr1wJw2bWj3Lu9iQ81bHBdWQ0NVqF2fm/fSBJ+9UjOM3igzZLjoosupuGa1Tm/1TlGHnkIjOGVN1zPhrqJMxD/0cgBXn9RPdeuq/Z9tzPBK2chsxTk/P7qDl440U1Dw6YJ+6qaeuDZbcRisez1x5WXveYIHD7I2rVraWi4KOeY1zc0uBbE+PL52oxBqg/zoRvXu3Vxd/owHDrEheuy1/r+qRegtY1rX3EZDZetAKDnxRbYu4uq2noaGq6aVI5tg/vg+HE2bdxAw+s2AND/0mnY8yKVVdU0NFwPZNuVurpaGhqupbGxkWu3XAY7nwMJuDInTnTB9mdyfn+LT1uT8bQ1Da97TdYb4bQ1113rLjsQfuIRSCa51NOu/LJzN0+fbmLj+vXue3l+5ACcOMrqFctpaLhyqlc6LfOmVIwxt87mPBFZDdwPfMAYc9Te3AKs9hy22t42I1y3Vo77a6K55+fT9x+tO3Gb10r1d39N7Rt1bOOcuIjPeBZHRm+Az3E75bi/bBeXN0B348ZaAF5/UX32esGJ/uPaRJSP3Lxxgrxe/J7VOXi/JnVdfPL2i87hKkqhc+PGWrfcjedcsr/8ytZU7tJgQPjYrZtztvnFVN76ipU8uq+Ny+31eyDr/hryWSDOK4fjHc6JlfjGVBzX2cRg+nSBer965v3dftlafm2W9zp+2Wh+wyVmS0G5v0SkEngQ+JQxZpuz3RjTKiJ9IvJK4DngA8A/z/i69v+cNdB9Min8yvhUo8rHye5+9isIvkE4T7zG2etVSGlXqUwMIvqFO7z3WF1Vwp6WXneqa4DNy8o4/td35KY6+8RUZsL5Zmpp+ERZ6FmpHbeRNx75tles5K1XrMipE85CVs7qi5PhKITceIWTKjx1TMVP+fi1EdM9o+kC9e51PJfOZqN5lcrERITZkhelIiLvwFIKdcCDIrLLGPNG4KPARuAvROQv7MNvM8acBf4I+DegBPiF/TcjnJ5EOEeB2Nu8ueh+lorfnFihqR+8n3LyC8J5r+2c45vB5ZP9lfGJXHoLxBffeQXvvGY1F9SUjpMtV44/uGkDB1r7ufPKlZP9HF/ON6X4fMcoKMXPzGZemLv7fejV69hxspv32m7e7D1yb3L12ir+5f3XcNPmuimv5y425mM5eAc1Bn2UStZSyW7zm0Zmumc0XSDfIafT6zOMIDutzZS3mxF5USrGmPuxXFzjt/8V8FeTnPMCcNls7pdVIJ70QnsMiN9AQC9TTQk/GTO9znSWiuOS8o4Ydqwgbw/HjNsHVtbXLRcvm1JOsFa9vO8PXjXtcePxdX/5pehMgmZ6Kefk/jo3Q9qX+vIY9/3+zMr67Zf5hYNzSbuLjXksf1sxeLO6nP1e95fvsAMn9dg7xcsstKpfRzh3ZoGJHdOQTxbrbMnXOJUFxZ3kzWMtpNLO5IfTub/8FMQ0vYeZur98FhcK+loqnvm7pnBXLWTnfyqlMJUcZpJV/5Slxxy47/NKxsdScRRIyqfT581HnmpmZb/4x7kwnfvLuWaOjHa99M6BNluK/LXODCdY7SgSwF3N0W9iRi/haUxJP3xXqZt2kJKFX0zFL5ngXGMghYYOdFTOdQLJQsN1f/m4lrxWgNNge3/tVAuLeduA2cQu/awgv0GbaU976CQleKfiny0FFaifL5wZPIfGUu62lM9AKF//5CTdqQ+86gJu3lLvu8+PaQc/2ru9is3PZ+uIk/YptMVEsTcoyvlTjHE1b1Vz3V9+DbavJ8Hr/vKbymmit2IynfLV37yal5p6fPf5tVk5U84EJsZ9Bu22sWQOZileEkrFWZJzyDNC1omp5MzOO8PsL4DP33lu4Z3pRsv6LUJ0+2XL+fdnT+XMruwUiEye3V8z5aLlZTlmtoO6vxQ/a7WuLMr62lKfo/OLX91y6qC3w1hfZmWOeTucfvOL+VoTPsMKJlO8d1y+gjsuX+G7z89TkjPkwcfb4QxBiPvMdXiuLAml4gx+8jbEYynbUgl4rQUnoJblfFNn45EgQ2PpnPv4Yt/G2xP63Fsv5X/esjmn9/C+69fw7LFOftce+Fjo/PJjr/PdrpNHKn7t5fa7ZzW8LS984o1b6B1O8oZLsgkx9eUxnr/7FmpKo+42Z1JHv2lavDjHlXvWlj/feuLGanMsFeu/X2evTBfpmhkfunEd3UNjfOjG9e42P0tlPvz8P/vIjWw91D5twM3Z7V3hLhQMUFcWzTmuMh7hOx++fs7lnAvOxQmn7i/lXPBb+TEfeOVYXRXn2x+aWBfry3LHtzgdxcA0Afi6RJRP3r6Ft1yeTe+fqzZJ/NxfHqXyp2+wOq9vO8ehBX4sCaUSCwf5X3dcnLPtlouX8bNdp7l8VYW7bT4GY21aVsamZWU52779oet48VRPzjbH/XU+4RE/F9pCkl1qePoHqYaKMpP20ilT01r688z51C0/9xfA7990IQ2bs24yEeGPGnJnspir1HuvxXP9emsKJO9MB5XxCJ9+08UTzpsNS0Kp+PG2V6zktkuW5axXsFCBw5u31E8I8ouP+2umFEYfDu5+88VUlUZ40wxy/NX9pcyE97/yAs70jvCHDRvyLYrFLCpbZhKtMleN+EzwVrdrLqjiwP+53XetqLlgySoVmLgAVzFmo8DcDAybDX/3zityrLDKeGSCRTgZxfqslYUlFg7ymbdckrPtvt9/FWf6RvIkUXEy3t08XwoFlrhSGc9UDd0FNfF5vfetFy/j6aOdrKkumfU1Frqdfte1a2Z9rioVZbY47puF5HyK68UrrNnJX7vJf2LNuaIsFqJ/JOW7byE9A6pUPEzmtt352Tf4pgDOJR+6cR3vuGoVVaWReb1PoaDeL2WpcNmqCl787BvmvW4/8+lb3JmYx7OQ9W1JjKifKZP1nqtLI+6qifOFiCwJhfL6i6z0S7VUlLKolb76mkmmxl9MLETdTkRDVMb977OQ9U0tFQ/a0M0/X/6Nq2jvH9UJJRUq4mG2/lkDKypm7/JVZoYqlTxRrBPcFUr210yIhYOsqZ7f+JRSPIxfmqHQKaa65mUhM7KLtBmdH9wR9UXWiXZnYc5zLr+iLFbc8TLTzFBeaLgT1aqlkh+Kdebcz7z5YmoTUd546fTrpyiKcu78xg1raesbmTA4sVhYyBksVKl4KNaYSmU8wqfepGu7K8p8EQsH+fQMx2AVIguZUqz+Eg9FqlMURVGmRFOKFUVRlDljIb0weVEqIvIuEdkrIhkRudZn/1oRGRCRT3i23S4iB0XkiIh8aj7kKsK1rhRFUaZlIVP482WpvAz8GvDEJPv/AfiF80VEgsBXgDcBlwDvE5FLJjlXURRF8bCQ7q+8BOqNMfvBPyNBRN4OHAcGPZuvB44YY47Zx/wAuBPYN9+yKoqiFDtLNqVYRBLAnwNvAD7h2bUKaPJ8bwZumOI6dwF3AdTV1dHY2Dij+5/otZbUHBgYmPE5fpzrued7v4VC5ZxbVM65ZbHLOZtzkskxAJ5+5mkqowvjmJo3pSIijwF+C2vcbYz52SSnfQ74R2PMwPnkVRtj7gHuAdiyZYtpaGiY0Xl7mnvhmacoK0vQ0PDac77v1ssHSWcMF9Ylzum8xsZGZipjPlE55xaVc25ZrHI+enE/JZEgq6vOfSaKyFOPwtgYN776xgmryM4X86ZUjDGzWWz6BuCdIvK3QCWQEZERYAfgnWd9NdBy3kLOMcU25YSiKIXP+JVjC52Ccn8ZY1zzQEQ+BwwYY74sIiFgk4isx1Im7wV+Iz9SKoqiKJORr5Tid4hIM/Aq4EEReXiq440xKeCjwMPAfuA+Y8ze+ZdUURRFORfylf11P3D/NMd8btz3h4CH5lEsNtSXUhkP84nbtsznbRRFURaEv3zbZXzuv/ZSGQ8v2D0Lyv2Vb+KRELv+4rZ8i6EoijInvPmKFbz5ihULek+dpkVRFEWZM1SpKIqiKHOGKhVFURRlzlCloiiKoswZqlQURVGUOUOViqIoijJnqFJRFEVR5gwxi3xlKhHpBw7mW45pqAU68i3EDFA55xaVc25ROeeOLcaYWU06thQGPx40xkxYXbKQEJEXCl1GUDnnGpVzblE55w4ReWG256r7S1EURZkzVKkoiqIoc8ZSUCr35FuAGVAMMoLKOdeonHOLyjl3zFrGRR+oVxRFURaOpWCpKIqiKAuEKhVFURRlzlh0SkVE/k5EDojIbhG5X0QqJznudhE5KCJHRORTCyzju0Rkr4hkRGTS1EIROSEie0Rk1/mk+M2Wc5Azb8/Svn+1iDwqIoft/1WTHJe2n+UuEXlgAeWb8vmISFRE7rX3Pyci6xZKtnFyTCfnB0Wk3fMMfzcPMn5LRM6KyMuT7BcR+ZL9G3aLyNULLaMtx3RyNohIr+dZ/kUeZFwjIo+LyD67nv9Pn2PO/XkaYxbVH3AbELI/fxH4os8xQeAocCEQAV4CLllAGS8GtgCNwLVTHHcCqM3js5xWznw/S1uGvwU+ZX/+lN87t/cN5OEZTvt8gD8C/sX+/F7g3gKV84PAlxdatnEyvA64Gnh5kv13AL8ABHgl8FyBytkA/DzPz3IFcLX9uQw45PPOz/l5LjpLxRjziLHWtAd4Fljtc9j1wBFjzDFjzBjwA+DOBZRxvzGm0Ef5z1TOvD5LmzuB79ifvwO8fYHvPxUzeT5e+X8E3CIisoAyQmG8x2kxxjwBdE1xyJ3Ad43Fs0CliCzs0ofMSM68Y4xpNcbstD/3A/uBVeMOO+fnueiUyjg+jKVlx7MKaPJ8b2biwywEDPCIiOwQkbvyLcwkFMKzXGaMabU/nwGWTXJcTEReEJFnReTtCyPajJ6Pe4zdIeoFahZEOh8ZbCZ7j79uu0F+JCJrFka0c6IQyuNMeZWIvCQivxCRS/MpiO1yvQp4btyuc36eRTlNi4g8Biz32XW3MeZn9jF3Ayng+wspm8NMZJwBrzHGtIhIPfCoiBywe0BzxhzJOe9MJaf3izHGiMhkefIX2M/zQuBXIrLHGHN0rmVdxPwX8J/GmFER+X0s6+r1eZapWNmJVR4HROQO4KfApnwIIiIJ4MfAx4wxfed7vaJUKsaYW6faLyIfBN4C3GJsx+A4WgBvL2u1vW3OmE7GGV6jxf5/VkTux3JRzKlSmQM55/1ZwtRyikibiKwwxrTapvnZSa7hPM9jItKI1TObb6Uyk+fjHNMsIiGgAuicZ7nGM62cxhivTN/AimUVGgtSHs8Xb+NtjHlIRL4qIrXGmAWdaFJEwlgK5fvGmJ/4HHLOz3PRub9E5Hbgk8DbjDFDkxy2HdgkIutFJIIVHF2wbKCZICKlIlLmfMZKQPDNJMkzhfAsHwB+2/7828AEC0tEqkQkan+uBW4E9i2AbDN5Pl753wn8apLO0HwyrZzjfOlvw/LBFxoPAB+ws5ZeCfR6XKMFg4gsd+JmInI9Vlu8oB0J+/7fBPYbY/5hksPO/XnmM/tgPv6AI1g+wF32n5NVsxJ4yHPcHVjZDkexXD0LKeM7sHyTo0Ab8PB4GbGycF6y//YutIwzlTPfz9K+fw3w38Bh4DGg2t5+LfAN+/OrgT3289wD/M4Cyjfh+QCfx+r4AMSAH9pl93ngwoV+hjOU86/tsvgS8DhwUR5k/E+gFUjaZfN3gD8A/sDeL8BX7N+whymyK/Ms50c9z/JZ4NV5kPE1WHHb3Z728o7zfZ46TYuiKIoyZyw695eiKIqSP1SpKIqiKHOGKhVFURRlzlCloiiKoswZqlQURVGUOUOVilI0SO4sw7vyNZvvXOOZ/fcbnm3/aU+H8ifncJ0dzlgcz7aP2jPMGnt8jrPdd/ZZEblSRJ6xZ63dLSLv8bnPl0RkwPP9T0TklIh8+Vx/u7L4KMoR9cqSZdgYc6XfDnsglxhjMgsr0pxxrzHmo2ANjAOuM8ZsnOnJIrIeaDHGjI7btQ34OdZM017ehDUtyCbgBuBr9v8h4APGmMMishLYISIPG2N67PtcC+QsLWCM+UcR6cYaF6QscdRSUYoWEVkn1vof38WabWCNiPyZiGy3e9l/6Tn2bhE5JCJP2VbAJ+ztjXZDiYjUisgJ+3NQrLV5nGv9vr29wT7nR2Kt2/N9z8jo60TkabEmCXxeRMpE5AkRudIjx1Mi8oppftojwCrbGnutiPyxWGte7BaRH0xyzu3AL8dvNMa8aIw54XO87+yzxphDxpjD9rmnsaa8qXOeCfB3WDNWKIovaqkoxUSJiOyyPx8H/gSrp/3bxphnReQ2+/v1WCOBHxCR1wGDWNOOXIlV5ncCO6a51+9gTUlxne1S2iYij9j7rgIuBU5jWQI3isjzwL3Ae4wx20WkHBjGmgbjg8DHRGQzEDPGvDTNvd+GtdbGlQAici+w3lgTOVZOcs7t9vOYKZPNPutOwWFPHxIhOz/aR4EHjDXH2jncSllKqFJRiokc95cdUzlp97TBmh/tNuBF+3sCS8mUAfcbey44mdmqj7cBV4jIO+3vFfa1xoDnjTHN9rV2AeuwpqtvNcZsh+yEgSLyQ+CzIvJnWEsx/Ns5/mawptH4voj8FGs22xzsubpWG2OOzeLavtjzfH0PS2FnbFfYu7AWl1KUSVGlohQ7g57PAvy1Mebr3gNE5GNTnJ8i6waOjbvW/zDGPDzuWg1Yc6E5pJmiHhljhkTkUSx307uBa6aQZTLejLWS4FuBu0XkcpNdiA7gtcBT53jNSWefta2sB7Hm/3IU9lXARuCIbaXEReTIucR9lKWBxlSUxcTDwIfFWh8CEVkl1lo0TwBvF5ESsWZ+fqvnnBNkG/p3jrvWH4o1NTgislms2aIn4yCwQkSus48vE2sae7Cmif8SsN0Y030uP0hEAsAaY8zjwJ9jWUyJcYfdjv9idFPhO/usbfXcjxVv+ZFzsDHmQWPMcmPMOmPMOmBIFYrih1oqyqLBGPOIiFwMPGP3pgeA9xtjdtpxiZewAs/bPaf9PXCfWCtrPujZ/g0st9ZOOxDfzhTLFBtjxuz0238WkRKseMqtwIAxZoeI9AHfnsXPCgL/LiIVWNbTl5xMLA8NwF/4nSwif4wVWF8O7BaRh4wxvws8hDUj7RGsjK8P2ae8G8sqqhFrXSKADxpjds1CdmUJorMUK0sOEfkcVmP/9wt0v5VYKb0X+aU82433tU5K8TleezXwr8aYN52vnOfD+fwGZXGh7i9FmUdE5ANY637fPcUYmmHgTeIZ/DhTjDHNBaBQ/gT4NHDeS9EqxY9aKoqiKMqcoZaKoiiKMmeoUlEURVHmDFUqiqIoypyhSkVRFEWZM1SpKIqiKHPG/w/U7eyeyPQUFQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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MAo111Uyoqx5oeYkUQ0EhsfRSRy9TE+p2ymVqok5dT1ISCgqJpZ3JXqY2aSA7lylN9ezSYLaUgIJCYiloUSgocpnWVKeuJykJBYXE0q5kz8CArQxtaqJu4DBikWIoKCR2uvv66ejtV4tiBFOa6nmpozfnpVdF8qGgkNjJ9LtrjCK3aYk6+vqdtu7hrwcukg8FhcTOS2G/+xQFRU6Z/bMrqe4nKY6CQmJnT1cQFJMVFDlNnhDsnz1dfWWuROJOQSGxszf84JvYcOD1oGWfiY3B/tmroJAiKSgkdtq6gj73lkYFRS6Z/dOmoJAiKSgkdgZaFJrnKacWtSikRBQUEjtt3X3UVhuN4/DqdaU0EBSdCgopjoJCYmdvVx8TG2o1IeAI6mqqaKytVotCiqagkNhp6+rT+ESeWhprFRRSNAWFxM7erj6aFRR5UVBIKSgoJHbaulNqUeRJQSGloKCQ2FHXU/4mKiikBBQUEjttXX1MbNChsfloaazVeRRSNAWFxIq7s1ctiryp60lKQUEhsdLV108q7QPTU0huLY21dPT209efLncpEmMKComVzLdjtSjy0xKeva7uJymGgkJiJTPPkyYEzE/LBE3jIcVTUEisqEVRmOb6YD8le3TxIhm9SIPCzM4ws/VmtsHMLh9i+WFmdp+ZPWJmq83srCjrkfhr04SABUmER4cldZU7KUJkQWFm1cC1wJnAMcAFZnbMoNX+L3CLu58InA98M6p6ZHxQi6IwzWFQtKtFIUWIskVxCrDB3Te6ey9wE3DuoHUcmBjebgG2RliPjAO6aFFhMl1P7WpRSBHM3aN5YbPzgDPc/cPh/b8DTnX3S7PWmQncDUwGmoDT3X3lEK91MXAxwPTp00+65ZZbIqm5lJLJJIlEotxljChudf5qQy+/2tDH9982gaoKmz22Evdle6/z8Xs7ee/Rdbzl8HC8ogLrHIrqLK0lS5asdPdFo3luuTt6LwB+6O7/ZWavAX5iZse6+34Hfbv7dcB1AAsXLvTFixePfaUFam1tRXWWTqbOPySfoOm55zhtyZJyl3SAStyXvak03HsHM+fOY/HiBUBl1jkU1Vk5oux62gLMzbo/J3ws20XALQDu/iDQAEyLsCaJuWR3amCAVkZWV1NFfU2Vup6kKFEGxQpggZnNN7M6gsHqpYPWeQ54M4CZHU0QFDsirEliLtmboqleQVGI5oYaDWZLUSILCndPAZcCdwHrCI5uWmtmV5vZOeFqnwH+3sweA24ELvSoBk1kXEh2p2hWUBSkuaFWh8dKUSL9i3P3ZcCyQY9dmXX7CeB1UdYg40tHj1oUhUrU19DerTOzZfR0ZrbESrInRUJBUZBEfY3OzJaiKCgkVhQUhWtuqNFgthRFQSGxoq6nwiUUFFIkBYXESrJHh8cWqlldT1IkBYXERk+qn75+V9dTgZobakn2pNABhTJaCgqJjcwhngqKwiQaauhPO119/eUuRWJKQSGx0dETfNBpjKIwmWDVuRQyWgoKiY32nuBcALUoCqOpxqVYCgqJjUyLQkFRmIGgUItCRklBIbGRzLQodNRTQRKZy6EqKGSUFBQSG8mBFkV1mSuJl0yLIhO0IoVSUEhsZL4RazC7MJmuuja1KGSUFBQSGx09Ojx2NDRGIcVSUEhsZM4ubqpTUBQiE6wdOupJRklBIbGR7EnRVFdNVVVlXSu70tVUV9FQW6WgkFFTUEhsaELA0UvU1+o8Chk1BYXERrsmBBy1RH21Do+VUVNQSGx06FoUo5ZoqFHXk4yagkJiI9mtoBitRH2Nup5k1BQUEhtJjVGMWqK+Rl1PMmoKCokNXQZ19BL1NXT0KihkdBQUEhsaoxi9JrUopAgKCokNdT2NXqJBYxQyegoKiYW+tNPX7wPTUUhhmutr6E2l6U2ly12KxJCCQmKhK/wy3FSnmWNHo0nTeEgRFBQSC90pByDRUFvmSuJp4HKoCgoZBQWFxEJXJih0LYpR2XdNCgWFFE5BIbGQOWAnc7U2KUyTWhRSBAWFxEJ3f9CiaFKLYlTU9STFiDQozOwMM1tvZhvM7PJh1nm3mT1hZmvN7GdR1iPx1TXQotBRT6Mx0PWkcylkFCL7qzOzauBa4C3AZmCFmS119yey1lkAfA54nbvvNrNDoqpH4m3fYLaCYjSyu56ay1yLxE+ULYpTgA3uvtHde4GbgHMHrfP3wLXuvhvA3bdHWI/E2MDhsWpRjIqucifFGPGvzsyOAr4FzHD3Y83seOAcd//CCE+dDTyfdX8zcOqgdY4Kt/FHoBq4yt3vHKKGi4GLAaZPn05ra+tIZZddMplUnSXU1tkDGA8/+ABVVplXuKvkfZn2oEW25i8bOHRmb8XWma2S92e2uNRZjHy+nl0PXAZ8B8DdV4djCSMFRb7bXwAsBuYA95vZce6+J3sld78OuA5g4cKFvnjx4hJsOlqtra2oztK5cd1dTKhzTluypNylDKvS92XTfXcybeYcEontFV1nRqXvz4y41FmMfLqeJrj7nwc9lk/7dQswN+v+nPCxbJuBpe7e5+7PAE8SBIfIfrr6NZBdLF28SEYrn6DYaWYvAxzAzM4DtuXxvBXAAjObb2Z1wPnA0kHr/IqgNYGZTSPoitqYV+VyUOlOuYKiSE26eJGMUj5/eR8j6PZ5uZltAZ4B3jfSk9w9ZWaXAncRjD98393XmtnVwMPuvjRc9lYzewLoBy5z912jfC8yjnWndMRTsZo11biM0oh/ee6+ETjdzJqAKndvz/fF3X0ZsGzQY1dm3Xbg0+E/kWF1pZxpdQqKYqjrSUYrn6OePj3oPsBeYKW7PxpNWSL76+7XobHFaqqrYVeys9xlSAzlM0axCLiE4HDX2cBHgDOA683ssxHWJjKgO6VrURQr0VCjKTxkVPL5y5sDvMrdkwBm9i/Ab4E3AiuBL0dXnkigK+Wa56lIzfWZoKgrdykSM/m0KA4BerLu9xGcfNc16HGRyHSnNHNssTLXzfbw5DuRfOXTorgBeMjMfh3ePxv4WTi4/cTwTxMpjZ5UPynXtSiKlWioIZV2+nQ1VClQPkc9/ZuZ3Qm8NnzoEnd/OLz93sgqEwl19PQDGswuVnO4/3SErBQqr788d19hZpuABgAzO8zdn4u0MpFQ5pBOnXBXnEzQZq4WKJKvEccozOwcM3uK4ES7/w3/vyPqwkQy2rsVFKWQ2X+Zi0CJ5Cufwex/A14NPOnu84HTgeWRViWSpaM3CAp1PRUnMdCiKHMhEjv5BEVfOK1GlZlVuft9BOdWiIyJzLH/msKjOJn9p64nKVQ+f3l7zCwB3A/cYGbbgY5oyxLZJ6mup5JIaDBbRimfFsW5QCfwKeBO4Gng7VEWJZJNg9mlkdBgtoxSPkFxpbun3T3l7j9y92uAf4q6MJGMTNeTxiiKk+l66lZQSIHyCYq3DPHYmaUuRGQ4A0FRpxPuitFYW02VBReBEinEsF/RzOwfgI8CR5jZ6qxFzcAfoy5MJKOjJ0VdNdRU5/O9RoZjZjTV16hFIQXL1Zb/GcH5Ev8BXJ71eLu7vxRpVSJZkj39NFRbucsYF5rra+hOaTRbCpMrKKqBNoIr3O3HzKYoLGSsJHtSNGp4oiQSDTV0pfrKXYbETK4/v5WE18kGBn+dc+CISCoSGaSjJ0VDjVoUpdBUX0NXh7qepDDDBkV4FrZI2SW7UzRoHLskEvU1bN1b7iokbvJq0JvZOQQXKgJodffboytJZH9B15NaFKWQqK+hS3M9SYHymRTwP4FPEFx74gngE2b271EXJpLR0ZtCs3eURqK+RmdmS8Hy+fM7CzjB3dMAZvYj4BHgn6MsTCQj2Z2iYYJaFKUQDGarRSGFyffA9ElZt1siqENkWOp6Kp1Mi0KXQ5VC5Drh7lrgRuDfgVVm1kpw9NMb2f+8CpHI9PWn6UmlaajWaHYpJOprcKCzt19Tokjecv2mPAl8BZgJ/B54FngU+Cd3fyHyykTYNyGgWhSlkZnvqaMnpaCQvA3b9eTuX3f31wBvIgiNdxIEx8VmtmCM6pODXGaeJw1ml0ZmBtn2Ho1oS/5GHKNw903u/iV3PxG4APhr4C+RVyYCdPQEM9jphLvSyARFUoc+SQHyOTy2xszONrMbCOZ+Wk/QuhCJXLInmG6iUUMUJZEJig61KKQAuQaz30LQgjgL+DNwE3Cxu+vqdjJmkmpRlFSTup5kFHK1KD4H/Ak42t3PcfefFRoSZnaGma03sw1mNuyRUmb2N2bmZqZrcct+OgbGKBQUpdDcoBaFFC7XXE+nFfPCZlYNXEtw4aPNwAozW+ruTwxar5ngzO+HitmejE+ZvnTNHlsamRZFUkEhBYjySjCnABvcfaO79xJ0XZ07xHr/BnwJ6I6wFompgaOedD2Kkhg46kmD2VKAKL+nzQaez7q/GTg1ewUzexUw191/a2aXDfdCZnYxcDHA9OnTaW1tLX21JZZMJlVnCazZ0AtAf3dHRdcJlb8vITgju9qcdU9tpNU2l7ucnOKwPyE+dRajbA16M6sCvgZcONK67n4dcB3AwoULffHixZHWVgqtra2ozuI92LmO+mefpWViY0XXCZW/LzMa7v0tU2bMYvHiY8tdSk5x2Z9xqbMYUXY9bQHmZt2fEz6W0QwcC7Sa2bPAq4GlGtCWbMme1EB3iZRGY43pPAopSJRBsQJYYGbzzawOOB9Ymlno7nvdfZq7z3P3ecBy4Bx3fzjCmiRmkj2pgWknpDQaa0yD2VKQyILC3VPApcBdwDrgFndfa2ZXhxdCEhlRR0+KpjoFRSk1VOuoJylMpH+B7r4MWDbosSuHWXdxlLVIPO1rUfSXu5RxQy0KKVSUXU8iRdMYRek11KhFIYVRUEhFa+tKMVFjFCXVoMFsKZCCQipae3cfExtry13GuNJYoyk8pDAKCqlY7k5bd2pgfiIpjcYao6O3n/60Locq+VFQSMXqDD/MJjaoRVFKmelQOnrVqpD8KCikYmXmI2pWUJRUZoJFdT9JvhQUUrHauoOLFk3U1LEllZmyXQPaki8FhVSs9jAo1KIorUzu6uJFki8FhVSstq7gg0yHx5ZWY9iiUNeT5EtBIRWrTS2KSKjrSQqloJCK1RZ+kGmMorQaqoP/1fUk+VJQSMXKjFHo8NjSUteTFEpBIRWrrStFXXUVDbXV5S5lXMkM+ajrSfKloJCK1dbdp26nCNRUGfU1VZoYUPKmoJCK1d6d0kB2RJobahQUkjcFhVSstq4+HRobkaZ6BYXkT0EhFau9u08tiogk6ms0RiF5U1BIxWrrTmmMIiItjbXs7eordxkSEwoKqVjt3X0016tFEYVJE2rZo6CQPCkopGK1dalFEZWWxjr2dCooJD8KCqlIff1puvr6NUYRkUkTatnb1Yu7Ll4kI1NQSEXady0KtSiiMHlCLX39Tkdvf7lLkRhQUEhF2tPZC8DkCXVlrmR8mtQY7NfMfhbJRUEhFWl32H/eMkFdT1HI7FeNU0g+FBRSkdSiiNakxiAodIis5ENBIRUp8013sloUkZg0IdP1pKCQkSkopCLtDlsUmb50Ka1JYQDv1hiF5EFBIRVpT2cfVaajnqLSoq4nKYCCQirS7s5eJk2oo6rKyl3KuNRQW01jbbWOepK8RBoUZnaGma03sw1mdvkQyz9tZk+Y2Woz+72ZHR5lPRIfe7r6BrpHJBqTJtRqjELyEllQmFk1cC1wJnAMcIGZHTNotUeARe5+PHAr8OWo6pF42dPZO3BkjkSjpVHzPUl+omxRnAJscPeN7t4L3AScm72Cu9/n7p3h3eXAnAjrkRjZ3dGnQ2MjFrQo1PUkI4typHA28HzW/c3AqTnWvwi4Y6gFZnYxcDHA9OnTaW1tLVGJ0Ukmk6qzCC/s7mSydQ7UVql1ZotDjbCvzr6ObrZ1pCu25rjtz/GsIg4pMbP3AYuANw213N2vA64DWLhwoS9evHjsihul1tZWVOfodd97Jy8/Yi6LFwe9lZVaZ7Y41Aj76rzrpdU8t257xdYct/05nkUZFFuAuVn354SP7cfMTgeuAN7k7j0R1iMx0ZPqp7O3XyfbRaylsY69nX24O2Y6ukyGF+UYxQpggZnNN7M64HxgafYKZnYi8B3gHHffHmEtEiMvdYTTdzRpjCJKkyfU0tuf1rWzZUSRBYW7p4BLgbuAdcAt7r7WzK42s3PC1b4CJICfm9mjZrZ0mJeTg8jO9iAopiXqy1zJ+JbZvzuTGtCW3CIdo3D3ZcCyQY9dmXX79Ci3L/G0Mxn0QCooojW9ORMUPcyf1lTmaqSS6cxsqTg7wqA4pFlBEaWBFkW7hgYlNwWFVBy1KMbGtOZgDCgTzCLDUVBIxdnZ3ktTXTWNddXlLmVcmzKhDjO1KGRkCgqpODuSPUxTt1PkaqqrmNpUxw4NZssIFBRScXa296jbaYxMS9QPdPWJDEdBIRVnZ7KHaQmdQzEWpiXq2aGuJxmBgkIqThAUalGMhWmJOrUoZEQKCqkoff1pdnf2DRzjL9Ga3hx0Pbl7uUuRCqagkIqyPewGmTGxocyVHBxmTGyguy9NW5em8ZDhKSikomzZ3QXA7EmNZa7k4JDZz1v2dJW5EqlkCgqpKFvDD6xZCooxMUtBIXlQUEhF2TIQFOp6GguZoNiqoJAcFBRSUbbs6WLyhFom1FXENbXGvalNddTVVCkoJCcFhVSUrXu6mD1Z3U5jparKmD2pUV1PkpOCQirK1j1dzGpRUIylWZMa1KKQnBQUUjHcnS27uzSQPcZmtahFIbkpKKRi7O7so6O3nznqehpTc6dMYHt7D129/eUuRSqUgkIqxsYdSQBeNj1R5koOLi+bnsAdNu5MlrsUqVAKCqkYTysoymLBjGB/b9iuoJChKSikYmzc0UFdTZWOehpj86Y2UV1lPPWigkKGpqCQivHU9iTzww8tGTt1NVUcPnWCWhQyLAWFVIy1W/dyzKyJ5S7joLTgkARPbW8vdxlSoRQUUhG2t3fzYlsPx85uKXcpB6WFM5p5dlcnnb2aRVYOpKCQirB2SxsAx6pFURYnHDaJ/rSzevPecpciFUhBIRXhoWdeoqbKOG6OWhTlcOLcyQCs3LS7zJVIJVJQSEV48OmdnHjYJE0GWCaTm+pYcEiCB5/eVe5SpAIpKKTsdrT3sGbLXl77smnlLuWgdtrLD+GhZ3aR7NE4hexPQSFld8fj20g7nHXczHKXclB789Ez6Ot37l77QrlLkQqjoJCySqedny7fxNEzJ7Lw0OZyl3NQW3T4ZOZPa+Inyzfh7uUuRypIpEFhZmeY2Xoz22Bmlw+xvN7Mbg6XP2Rm86KsRyrPrSs38+SLSS550xHlLuWgV1VlfOj183nkuT0sW6NWhewTWVCYWTVwLXAmcAxwgZkdM2i1i4Dd7n4k8N/Al6KqRypLbyrNbas28/lfP86p86fw9uNnlbskAS44eS7HzW7hs7c+xm8e20qqP13ukqQCRHmIySnABnffCGBmNwHnAk9krXMucFV4+1bgG2ZmnqPduyWZ5s3/1Tpw/4AVPefdIZvUB64zeLnnXD7UY93d3TQsv3fY7Q71Bgvdbj6vMXitwct7e3up/cPvhq1zqO0cUEce723wgz2pNL39aU6YO4lvvvdVmrajQtRUV/HdDyzigz9YwcdvfIS6mipmTKynpqoKAzAwwCz6n1dnRycTVv1v5NspVlzqLEaUQTEbeD7r/mbg1OHWcfeUme0FpgI7s1cys4uBiwGaZhzO1OrunBse/Cucz+/0AavY4LuWa/EBUnVpamv7CnoOjFzrAe8tj5VyPaevz6mtO/Bb40i1FruPa6qqOWpyLcdP72XNww+O+NxkMklra+vIGymjONQI+dX56eOc1YfW8+Tufvb29JL2fVk/VqMXzY1paqr2v6CSe36/a2NpqDrHm1gctO7u1wHXASxcuNBv+eQZZa5oZK2trSxevLjcZYxIdZZOHGqE/Os8PfpSchpv+7Pc7FOjf26Ug9lbgLlZ9+eEjw25jpnVAC2AzvgREakgUQbFCmCBmc03szrgfGDpoHWWAh8Ib58H3JtrfEJERMZeZF1P4ZjDpcBdQDXwfXdfa2ZXAw+7+1Lge8BPzGwD8BJBmIiISAWJdIzC3ZcBywY9dmXW7W7gXVHWICIixdGZ2SIikpOCQkREclJQiIhITgoKERHJyeJ2NKqZtQPry11HHqYx6AzzCqU6SycONYLqLLW41LnQ3Uc1RXMszsweZL27Lyp3ESMxs4dVZ+nEoc441Aiqs9TiVOdon6uuJxERyUlBISIiOcUxKK4rdwF5Up2lFYc641AjqM5SG/d1xm4wW0RExlYcWxQiIjKGFBQiIpJTxQeFmX3FzP5iZqvN7JdmNmmY9c4ws/VmtsHMLh/jMjGzd5nZWjNLm9mwh8qZ2bNmtsbMHi3mcLXRKqDOcu/PKWb2OzN7Kvx/8jDr9Yf78lEzGzyNfVS15dw3ZlZvZjeHyx8ys3ljUdcQdYxU54VmtiNr/324DDV+38y2m9njwyw3M7smfA+rzexVY11jWMdIdS42s71Z+/LKodaLmpnNNbP7zOyJ8O/8E0OsU/g+dfeK/ge8FagJb38J+NIQ61QDTwNHAHXAY8AxY1zn0cBCoBVYlGO9Z4FpZdyfI9ZZIfvzy8Dl4e3Lh/q5h8uSY1zXiPsG+Cjw7fD2+cDNZfg551PnhcA3xrq2QTW8EXgV8Pgwy88C7iC4ku6rgYcqtM7FwO3l3JdhHTOBV4W3m4Enh/i5F7xPK75F4e53u3sqvLuc4Ep5g50CbHD3je7eC9wEnDtWNQK4+zp3r/gzxvOss+z7M9zej8LbPwLeMcbbH04++ya79luBN5uN+ZWeK+FnOCJ3v5/gWjTDORf4sQeWA5PMbObYVLdPHnVWBHff5u6rwtvtwDpg9qDVCt6nFR8Ug3yIIAkHmw08n3V/MwfunErhwN1mttLMLi53McOohP05w923hbdfAGYMs16DmT1sZsvN7B1jUFc++2ZgnfBLzl5g6hjUNmQNoeF+hn8Tdj/camZzh1hebpXwu5iv15jZY2Z2h5m9otzFhF2eJwIPDVpU8D6tiCk8zOwe4NAhFl3h7r8O17kCSAE3jGVt2fKpMw+vd/ctZnYI8Dsz+0v4baVkSlRn5HLVmX3H3d3MhjuO+/Bwfx4B3Gtma9z96VLXOk79BrjR3XvM7CMEraDTylxTXK0i+F1MmtlZwK+ABeUqxswSwC+AT7p7W7GvVxFB4e6n51puZhcCbwfe7GEn2yBbgOxvQ3PCx0pqpDrzfI0t4f/bzeyXBF0EJQ2KEtRZ9v1pZi+a2Ux33xY2i7cP8xqZ/bnRzFoJvkFFGRT57JvMOpvNrAZoAXZFWNNQRqzT3bNr+i7BuFClGZPfxWJlfxi7+zIz+6aZTXP3MZ8s0MxqCULiBne/bYhVCt6nFd/1ZGZnAJ8FznH3zmFWWwEsMLP5ZlZHMIA4JkfAFMLMmsysOXObYKB+yKMoyqwS9udS4APh7Q8AB7SEzGyymdWHt6cBrwOeiLiufPZNdu3nAfcO8wUnSiPWOahf+hyC/uxKsxR4f3ikzquBvVldkhXDzA7NjEOZ2SkEn61j/eWAsIbvAevc/WvDrFb4Pi33KH0eo/gbCPrTHg3/ZY4mmQUsGzSS/yTBt8krylDnXxP09fUALwJ3Da6T4AiUx8J/ayu1zgrZn1OB3wNPAfcAU8LHFwHfDW+/FlgT7s81wEVjVNsB+wa4muDLDEAD8PPwd/fPwBFjvf/yrPM/wt/Dx4D7gJeXocYbgW1AX/h7eRFwCXBJuNyAa8P3sIYcRxSWuc5Ls/blcuC1Zarz9QTjoKuzPjPPKnafagoPERHJqeK7nkREpLwUFCIikpOCQkREclJQiIhITgoKERHJSUEhZWP7z/z6aLlmWS21rFlZv5v12I3hVBmfKuB1VmbOE8l67NJw1k8Pzx3JPD7kjKBmdoKZPRjOJLrazN4zxHauMbNk1v1PmdlzZvaNQt+7jE8VcWa2HLS63P2EoRaEJw6Zu6fHtqSSudndL4XgZCzgZHc/Mt8nm9l8YIu79wxa9EfgdoLZf7OdSTBlxALgVOBb4f+dwPvd/SkzmwWsNLO73H1PuJ1FwH5TuLv7f5vZboJzVkTUopDKYWbzLLh+wo8Jzlifa2aXmdmK8Nvwv2ate4WZPWlmD4Tf1v9P+Hhr+OGHmU0zs2fD29UWXNsk81ofCR9fHD7nVguue3JD1hm2J5vZnyyY6O3PZtZsZveb2QlZdTxgZq8c4a3dDcwOW01vMLN/tOB6AavN7KZhnnMGcOfgB939EXd/doj1h5wR1N2fdPenwuduJZgKZXpmnwBfIZj5QGRYalFIOTWa2aPh7WeATxF8I/6Auy83s7eG908hOJt0qZm9EeggmJLiBILf4VXAyhG2dRHBVAUnh905fzSzu8NlJwKvALYSfGN/nZn9GbgZeI+7rzCziUAXwfQIFwKfNLOjgAZ3f2yEbZ9DcK2CEwDM7GZgvgeT8U0a5jlnhPsjX8PNCDowNUM4tUQd++bCuhRY6sF8WgVsSg42Cgopp/26nsIxik3hN2II5sJ6K/BIeD9BEBzNwC89nPvL8ruy3VuB483svPB+S/havcCf3X1z+FqPAvMIpgbf5u4rYN+kb2b2c+DzZnYZwbT3PyzwPUMwvcINZvYrgllG9xPOzTTH3TeO4rWHFM7r9BOCEE6H3VDvIrjgjkhOCgqpNB1Ztw34D3f/TvYKZvbJHM9Psa9LtWHQa33c3e8a9FqLCea9yugnx9+Fu3ea2e8IunreDZyUo5bh/BXBFdPOBq4ws+N838W5AN4APFDgaw47I2jYGvotwXxPmRA+ETgS2BC2JiaY2YZCxlHk4KExCqlkdwEfsmBufcxstgXX8bgfeIeZNVowG+/ZWc95ln0f3ucNeq1/sGAKZszsKAtm8B3OemCmmZ0crt9swZThEEzJfQ2wwt13F/KGzKwKmOvu9wH/RNCySQxa7QyGvkBXLkPOCBq2Tn5JMH5xa2Zld/+tux/q7vPcfR7QqZCQ4ahFIRXL3e82s6OBB8NvvUngfe6+Kuznf4xgcHZF1tO+CtxiwdUDf5v1+HcJupRWhYPVO8hxeVV37w0PJf1/ZtZIMD5xOsE1uleaWRvwg1G8rWrgp2bWQtDKuSZzBFKWxcCVQz3ZzP6RYPD5UGC1mS1z9w8DywhmCd1AcKTTB8OnvJug9TLVguu6AFzo7o+OonY5SGn2WIk9M7uK4AP8q2O0vVkEh6e+fKjDd8MP5EWZw2MLfO05wPXufmaxdRajmPcg44+6nkQKYGbvJ7gG8RU5zvHoAs60rBPu8uXumysgJD4FfA4o+hKaMj6oRSEiIjmpRSEiIjkpKEREJCcFhYiI5KSgEBGRnBQUIiKS0/8H7KjoBVPELQ0AAAAASUVORK5CYII=\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "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": [ + "fLim = (-2, 2)\n", + "#fLim = None\n", + "dbLim = (-150, 5)\n", + "#dbLim = None\n", + "h, f, HF = dsp.dtft(hInterpolated)\n", + "dsp.plot_spectra(f, HF, Npoints, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "e8acbe8f", + "metadata": {}, + "source": [ + "# 2 Compare firls filter and LOFAR subband filter" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "732899c1", + "metadata": {}, + "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": [ + "fLim = (-2, 2)\n", + "dbLim = (-140, 5)\n", + "\n", + "#plt.figure(0)\n", + "fs = Npoints / Q\n", + "h, f, HF = dsp.dtft(hFirls)\n", + "dsp.plot_power_spectrum(f, HF, 'b', fs, fLim, dbLim)\n", + "\n", + "#plt.figure(1)\n", + "fs = Npoints\n", + "h, f, HF = dsp.dtft(hInterpolated)\n", + "dsp.plot_power_spectrum(f, HF, 'r', fs, fLim, dbLim)\n", + "\n", + "#plt.figure(2)\n", + "lofarCoefs = dsp.read_coefficients_file('../data/Coeffs16384Kaiser-quant.dat')\n", + "lofarCoefs /= np.sum(lofarCoefs)\n", + "fs = Npoints\n", + "h, f, HF = dsp.dtft(lofarCoefs)\n", + "dsp.plot_power_spectrum(f, HF, 'g', fs, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5f307eee", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/applications/lofar2/model/pfb_os/filter_design_remez.ipynb b/applications/lofar2/model/pfb_os/filter_design_remez.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..93a8c6892de495047c58f370474b85522de2d44b --- /dev/null +++ b/applications/lofar2/model/pfb_os/filter_design_remez.ipynb @@ -0,0 +1,413 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e0a005d", + "metadata": {}, + "source": [ + "# Try remez FIR filter design method\n", + "\n", + "Author: Eric Kooistra, nov 2023\n", + "Purpose:\n", + "* Practise DSP [1].\n", + "* Try remez FIR filter design method for LPF.\n", + "* Try to reproduce LOFAR subband filter FIR coefficients using scipy instead of MATLAB.\n", + "\n", + "MATLAB:\n", + "* The pfs_coeff_final.m from the Filter Task Force (FTF) in 2005 use fircls1 with r_pass and r_stop to define the ripple. In addition it post applies a Kaiser window with beta = 1 to make the filter attenuation a bit more deep near the transition.\n", + "* The pfir_coeff.m from Apertif also uses fircls1. \n", + "* Both use fircls1 with N = 1024 FIR coefficients and then Fourier interpolation to achieve Ncoefs = 1024 * 16 FIR coefficients. Both scripts can not exactly reproduce the actual LOFAR1 coefficients, therefore these are loaded from a file Coeffs16384Kaiser-quant.dat\n", + "\n", + "Python (scipy.signal):\n", + "* The windowed sync method, firls leased squares method and remez method all yield comparable results, but firls and remez perform slightly better near the transition band. The firls and remez functions from scipy.signal use transition bandwidth and weights between pass and stop band to influence the transition region and ripple. For remez the ripple is constant in the pass band and stop band, for firls the ripple is largest near the band transition.\n", + "\n", + "Conclusion:\n", + "* It is possible to design a good FIR filter using Python scipy. Possibly with some extra help of a filter design and analysis (FDA) tool like pyfda [2].\n", + "\n", + "References:\n", + "\n", + "1. dsp_study_erko, summary of DSP books\n", + "2. pyfda, dsp, at https://github.com/chipmuenk" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3563bc63", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f820b0ac", + "metadata": {}, + "outputs": [], + "source": [ + "import dsp" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a131b5b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<module 'dsp' from '/dop466_0/kooistra/git/hdl/applications/lofar2/model/pfb_os/dsp.py'>" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import importlib\n", + "importlib.reload(dsp)" + ] + }, + { + "cell_type": "markdown", + "id": "6ca908a5", + "metadata": {}, + "source": [ + "# 1 Remez method" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "efe5479c", + "metadata": {}, + "outputs": [], + "source": [ + "# LPF specification for subband prototype filter\n", + "Npoints = 1024 # = number of bins in fs, = DFT size\n", + "BWbin = 1 / Npoints # bandwidth of one bin\n", + "# . Use half power bandwidth factor to tune half power cutoff frequency of LPF, default 1.0\n", + "hp_factor = 0.85\n", + "BWpass = hp_factor * BWbin\n", + "fpass = BWpass / 2 # bin at DC -fpass to +fpass\n", + "\n", + "# Actual FIR filter length\n", + "Ntaps = 16\n", + "Ncoefs = Npoints * Ntaps" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "dfc5651a", + "metadata": {}, + "outputs": [], + "source": [ + "# Initial FIR filter length\n", + "# . Use interpolation of factor Q shorter filter\n", + "# . The passband ripple and stopband attenuation depend on the transition bandwidth w_tb\n", + "# and the weight. Choose 0.4 ~< w_tb ~< 1.0 fpass, to ensure the FIR filter design converges\n", + "# and improve the passband ripple and stopband attenuation. A large transition band does not\n", + "# cause artefacts.\n", + "Q = Ntaps\n", + "N = Ncoefs // Q\n", + "f_pb = fpass * Q # pass band cut off frequency\n", + "w_tb = 0.5 * fpass * Q # transition bandwidth\n", + "f_sb = f_pb + w_tb # stop band frequency\n", + "weight = [1, 1000] # weight pass band ripple versus stop band ripple\n", + "hRemez = signal.remez(N, [0, f_pb, f_sb, 0.5], [1, 0], weight, fs=1.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "0d4569d1", + "metadata": {}, + "outputs": [], + "source": [ + "# Apply Kaiser window with beta = 1 like in pfs_coeff_final.m, this improves the\n", + "# stopband attenuation near the transition band somewhat\n", + "# . beta: 0 rect, 5 hamming, 6 hanning\n", + "win = signal.windows.kaiser(N, beta=1)\n", + "hRemez *= win" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4b8d732e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ". f_pb = 0.006641\n", + ". w_tb = 0.003320\n", + ". f_sb = 0.009961\n", + ". Q = 16\n", + ". N = 1024\n", + ". DC sum = 0.978544\n", + ". Symmetrical coefs = True\n" + ] + } + ], + "source": [ + "# Symmetrical FIR coeffients: coefs[0] = 0, coefs[1] = coefs[-1]\n", + "print('. f_pb = %f' % f_pb)\n", + "print('. w_tb = %f' % w_tb)\n", + "print('. f_sb = %f' % f_sb)\n", + "print('. Q = %d' % Q)\n", + "print('. N = %d' % len(hRemez))\n", + "print('. DC sum = %f' % np.sum(hRemez))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hRemez))" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9314f402", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "hinterpolated.imag ~= 0\n", + ". Ncoefs = 16384\n", + ". DC sum = 0.978544\n", + ". Symmetrical coefs = False\n" + ] + }, + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x7f62755cb160>,\n", + " <matplotlib.lines.Line2D at 0x7f62755cb190>]" + ] + }, + "execution_count": 8, + "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": [ + "# Use Fourier interpolation to create final FIR filter coefs\n", + "HFremez = np.fft.fft(hRemez)\n", + "hInterpolated = dsp.fourier_interpolate(HFremez, Ncoefs)\n", + "print('. Ncoefs = %d' % len(hInterpolated))\n", + "print('. DC sum = %f' % np.sum(hInterpolated))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hInterpolated))\n", + "\n", + "plt.plot(hInterpolated, 'r', hInterpolated - np.flip(hInterpolated), 'r--')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "6600a7bd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ". DC sum = 1.000000\n", + ". Symmetrical coefs = True\n" + ] + } + ], + "source": [ + "# The coefs are almost symmetrical. Therefore use simple way to make impulse\n", + "# response exactly symmetrical\n", + "hInterpolated = hInterpolated + np.flip(hInterpolated)\n", + "hInterpolated /= np.sum(hInterpolated)\n", + "print('. DC sum = %f' % np.sum(hInterpolated))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hInterpolated))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "0971f31e", + "metadata": {}, + "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": [ + "dsp.plot_time_response(hInterpolated)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "580e0fd5", + "metadata": {}, + "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" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "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": [ + "fLim = (-2, 2)\n", + "#fLim = None\n", + "dbLim = (-150, 5)\n", + "#dbLim = None\n", + "h, f, HF = dsp.dtft(hInterpolated)\n", + "dsp.plot_spectra(f, HF, Npoints, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "00759606", + "metadata": {}, + "source": [ + "# 2 Compare remez filter and LOFAR subband filter" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "73baa95f", + "metadata": {}, + "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": [ + "fLim = (-2, 2)\n", + "dbLim = (-140, 5)\n", + "\n", + "#plt.figure(0)\n", + "fs = Npoints / Q\n", + "h, f, HF = dsp.dtft(hRemez)\n", + "dsp.plot_power_spectrum(f, HF, 'b', fs, fLim, dbLim)\n", + "\n", + "#plt.figure(1)\n", + "fs = Npoints\n", + "h, f, HF = dsp.dtft(hInterpolated)\n", + "dsp.plot_power_spectrum(f, HF, 'r', fs, fLim, dbLim)\n", + "\n", + "#plt.figure(2)\n", + "lofarCoefs = dsp.read_coefficients_file('../data/Coeffs16384Kaiser-quant.dat')\n", + "lofarCoefs /= np.sum(lofarCoefs)\n", + "fs = Npoints\n", + "h, f, HF = dsp.dtft(lofarCoefs)\n", + "dsp.plot_power_spectrum(f, HF, 'g', fs, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5f840ab", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/applications/lofar2/model/pfb_os/filter_design_windowed_sync.ipynb b/applications/lofar2/model/pfb_os/filter_design_windowed_sync.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..fc6969db46c3383c704a57828ba870b8c35c9863 --- /dev/null +++ b/applications/lofar2/model/pfb_os/filter_design_windowed_sync.ipynb @@ -0,0 +1,356 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e0a005d", + "metadata": {}, + "source": [ + "# Try windowed sync FIR filter design method\n", + "\n", + "Author: Eric Kooistra, nov 2023\n", + "Purpose:\n", + "\n", + "Practise DSP [1]:\n", + "- Use windowed sync method for FIR filter design in time domain\n", + "- Compare LOFAR subband filter with windowed sync LPF for Kaiser window with beta\n", + "\n", + "References:\n", + "\n", + "[1] dsp_study_erko, summary of DSP books" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3563bc63", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f820b0ac", + "metadata": {}, + "outputs": [], + "source": [ + "import dsp" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a131b5b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<module 'dsp' from '/dop466_0/kooistra/git/hdl/applications/lofar2/model/pfb_os/dsp.py'>" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import importlib\n", + "importlib.reload(dsp)" + ] + }, + { + "cell_type": "markdown", + "id": "672a425f", + "metadata": {}, + "source": [ + "# 1 Windowed sinc method" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "4e185794", + "metadata": {}, + "outputs": [], + "source": [ + "# LPF specifications\n", + "Npoints = 1024\n", + "Ntaps = 16\n", + "Ncoefs = Npoints * Ntaps\n", + "hp_factor = 0.97\n", + "fpass = hp_factor / Npoints" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ccbe2065", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Window method: firwin, kaiser with beta = 8.000000\n", + ". Ncoefs = 16384\n", + ". Coefs sum = 1.000000\n", + ". Symmetrical coefs = True\n" + ] + } + ], + "source": [ + "# Select windowed sinc method\n", + "# . method\n", + "method = 'manual'\n", + "method = 'firwin'\n", + "# Window type\n", + "window = 'hann'\n", + "window = 'kaiser'\n", + "if window == 'kaiser':\n", + " beta = 8 # beta: 0 rect, 5 hamming, 6 hanning\n", + " print('Window method: %s, %s with beta = %f' % (method, window, beta))\n", + "else:\n", + " print('Window method: %s, %s' % (method, window))\n", + "\n", + "# FIR coefficients\n", + "if method == 'manual':\n", + " # sinc, sinc(t) = sin(pi t)/(pi t)\n", + " nlo = -Ncoefs//2\n", + " n = np.arange(nlo, nlo + Ncoefs)\n", + " sinc = np.sinc(fpass * (n + 0.5))\n", + " print('. Symmetrical sinc = %s' % dsp.is_symmetrical(sinc))\n", + " # window\n", + " if window == 'hann':\n", + " win = signal.windows.hann(Ncoefs)\n", + " elif window == 'kaiser':\n", + " win = signal.windows.kaiser(Ncoefs, beta) \n", + " print('. Symmetrical win = %s' % dsp.is_symmetrical(win))\n", + " # FIR coefs\n", + " coefs = win * sinc\n", + " # Normalize DC gain\n", + " coefs /= np.sum(coefs)\n", + "elif method == 'firwin':\n", + " if window == 'hann':\n", + " coefs = signal.firwin(Ncoefs, fpass, window='hann')\n", + " elif window == 'kaiser':\n", + " coefs = signal.firwin(Ncoefs, fpass, window=('kaiser', beta))\n", + "# Plot\n", + "h, f, HF = dsp.dtft(coefs)\n", + "# Symmetrical FIR coeffients: coefs[0] = 0, coefs[1] = coefs[-1]\n", + "print('. Ncoefs = %d' % len(coefs))\n", + "print('. Coefs sum = %f' % np.sum(coefs))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(coefs))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "0eddef92", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "dsp.plot_time_response(coefs)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "cecb34c7", + "metadata": {}, + "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" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "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": [ + "fLim = (-2, 2)\n", + "dbLim = (-120, 5)\n", + "dsp.plot_spectra(f, HF, Npoints, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "a49c1d87", + "metadata": {}, + "outputs": [], + "source": [ + "# Compare coefs using different methods\n", + "# . first run manual window, then run using scipy.signal window to compare the coefs,\n", + "# the difference is zero after ensuring that sinc and win are symmetrical and with correct fc.\n", + "try:\n", + " plt.plot(coefs - prefCoefs)\n", + " prefCoefs = coefs\n", + "except:\n", + " prefCoefs = coefs" + ] + }, + { + "cell_type": "markdown", + "id": "b03374df", + "metadata": {}, + "source": [ + "# 2 Compare LOFAR subband filter with Kaiser window LPF" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a1c86a38", + "metadata": {}, + "outputs": [], + "source": [ + "# LOFAR coefs\n", + "Npoints = 1024\n", + "Ntaps = 16\n", + "lofarCoefs = dsp.read_coefficients_file('../data/Coeffs16384Kaiser-quant.dat')\n", + "lofarCoefs /= np.sum(lofarCoefs)\n", + "hLofar, fLofar, HFlofar = dsp.dtft(lofarCoefs)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "29baa88c", + "metadata": {}, + "outputs": [], + "source": [ + "# Windowed sync type LPF\n", + "fpass = 1 / Npoints\n", + "window = 'hann'\n", + "window = 'kaiser'\n", + "\n", + "windowLegend = window\n", + "if window == 'hann':\n", + " coefs = signal.firwin(Ncoefs, fpass, window='hann')\n", + "elif window == 'kaiser':\n", + " beta = 8 # beta: 0 rect, 5 hamming, 6 hanning\n", + " coefs = signal.firwin(Ncoefs, fpass, window=('kaiser', beta))\n", + " windowLegend = window + ', beta = %.1f' % beta\n", + "hWin, fWin, HFwin = dsp.dtft(coefs)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "697c358d", + "metadata": {}, + "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": [ + "# Compare frequency response\n", + "fs = Npoints\n", + "fLim = (-2, 2)\n", + "#fLim = None\n", + "dbLim = (-120, 5)\n", + "dsp.plot_two_power_spectra(fWin, HFwin, windowLegend,\n", + " fLofar, HFlofar, 'LOFAR',\n", + " fs, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "73baa95f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/applications/lofar2/model/pfb_os/rectangular_window_and_ideal_lpf.ipynb b/applications/lofar2/model/pfb_os/rectangular_window_and_ideal_lpf.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..6d8919d29c34a13c8ba7ede9a383896ad793536b --- /dev/null +++ b/applications/lofar2/model/pfb_os/rectangular_window_and_ideal_lpf.ipynb @@ -0,0 +1,585 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e0a005d", + "metadata": {}, + "source": [ + "# Try rectangular time window and frequency response\n", + "\n", + "Author: Eric Kooistra, nov 2023\n", + "Purpose:\n", + "\n", + "Practise DSP [1]:\n", + "- DTFT of rectangular time window\n", + "- Impulse response of rectangular frequency reponse (= ideal LPF)\n", + "- Half band ideal LPF\n", + "- Compare LOFAR subband filter with ideal LPF\n", + "- Compare LOFAR subband filter with rectangular time window (= FFT bin response)\n", + "\n", + "References:\n", + "\n", + "[1] dsp_study_erko, summary of DSP books" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3563bc63", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f820b0ac", + "metadata": {}, + "outputs": [], + "source": [ + "import dsp" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a131b5b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<module 'dsp' from '/dop466_0/kooistra/git/hdl/applications/lofar2/model/pfb_os/dsp.py'>" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import importlib\n", + "importlib.reload(dsp)" + ] + }, + { + "cell_type": "markdown", + "id": "76144f4f", + "metadata": {}, + "source": [ + "# 1 DTFT of rectangular time window" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "861313c3", + "metadata": {}, + "outputs": [], + "source": [ + "# Select rectangular time window with Nrect time samples:\n", + "# . Nrect = 16 : [LYONS Fig 5.24]\n", + "# . Nrect = 31 : [LYONS Fig 5.25] use 31 odd, instead of 32, for zero phase.\n", + "# . Nrect = 99 : [HARRIS Fig 3.4] use 99 odd, instead of 100, for zero phase, first sidelobe\n", + "# level is -22 relative to main lobe of +100, and 20log10(100/22) = -13.2 dB.\n", + "# . Nrect = 1024 : implicit rectangular window of FFT in LOFAR PFB without prefilter.\n", + "Nrect = 16\n", + "Nrect = 31\n", + "Nrect = 99\n", + "Nrect = 1024\n", + "rect = np.ones([Nrect]) / Nrect" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "29ed15d4", + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate frequency response using DTFT\n", + "Ninterpolate = 20\n", + "Ndtft = Nrect * Ninterpolate\n", + "hRect, fRect, HFrect = dsp.dtft(rect, Ndtft)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "0c79a5b9", + "metadata": {}, + "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": [ + "# Plot time window\n", + "dsp.plot_time_response(hRect)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c2a7daba", + "metadata": {}, + "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" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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SVyIIhjEZiRwstURgQssSgTFeWtuU/LK6gC1W353R6QkcKK0LyrWM6YwlAmO8HKqop7lVGZOREJTr5aQnUlnfTEWdTT5nQscSgTFe8txP58EqEeS4r2OlAhNKlgiM8bLfXV+fE6xE4C55HDhq7QQmdCwRGOMl72gtcdERDA3w8pSdyUpNQMTVQG1MqFgiMMbLgdI6Rqc533XUIy46khGD449VSRkTCpYIjPGSV1rL6PTgNBR7uHoOWYnAhI4lAmPc2tqUvLI6coI0hsBjdHqilQhMSFkiMMatuKqBppa2oJcIctITKKttorK+OajXNcbDEoExbgeC3GPIw9NV9aCVCkyIWCIwxu34GIIglwg8XUitncCEiCUCY9wOlNYSExnB8MHOzjra3qg0VyLIs0RgQsQSgTFueUfryE6LJzJIXUc9EmKiyBwUa6OLTchYIjDGLZizjrbn6jlkJQITGpYIjAFUlbzS4M062t6Y9EQrEZiQsURgDHCkupH65lZygtxQ7DE6I4Ej1Y3UNraE5PpmYLNEYAzHZ/8MVYnA02XVBpaZULBEYAyhG0Pg4emyau0EJhQsERiD6ws4KkIYkRIXkuuPtnUJTAhZIjAG1xdwdloCUZGh+ZNIio0iIynWSgQmJCwRGENoZh1tL8dmITUhYonADHiqSt7RupC1D3iMTk/kwFGrGjLBZ4nADHjldc1UN7aQnRbaEsHo9ASKqxpoaG4NaRxm4LFEYAa8gnLXU3h2anDnGGovO811/cKK+pDGYQYeSwRmwMsvc33xhrpEkJXqun5+mVUPmeCyRGAGPE+JICvUJQJPIii3EoEJLkcTgYgsEpFdIrJHRO7o5JgviMh2EdkmIv9wMh5jOpJfXkdKQjTJcdEhjWNociwxUREUWInABFmUUycWkUjgfuB8oABYKyLLVHW71zG5wA+B01S1XESGOhWPMZ0pKK8PeWkAICJCyEqJJ7/cEoEJLidLBPOAPaq6T1WbgKeBxe2OuQG4X1XLAVS1xMF4jOlQflndsWqZUMtKS6DAqoZMkDlWIgBGAvlerwuA+e2OmQAgIu8CkcBPVfWV9icSkRuBGwEyMzNZvXq1E/H6paamJiziCAd9+V6oKgdL68hNbOz17xCI+xBZ38i+wy199n569OXPRKD1hXvhZCLw9fq5wEIgC3hLRKapaoX3Qaq6FFgKMGfOHF24cGFwo+zA6tWrCYc4wkFfvhcl1Q00r3ydU2dMZOGCnF6dKxD3YQd7WZW/kzkLTicpNtR/nj3Xlz8TgdYX7oWTVUOFQLbX6yz3Nm8FwDJVbVbV/cBuXInBmKDwVMOEQxsBHB9LYF1ITTA5mQjWArkiMkZEYoArgGXtjnkRV2kAEcnAVVW0z8GYjDmB5ws3XNoIsm0sgQkBxxKBqrYAtwArgR3As6q6TUTuEpFL3YetBEpFZDuwCvieqpY6FZMx7XlKBCPDpkRgYwlM8HVbCSkiE4A/A5mqOlVEpgOXqurPu3uvqq4AVrTb9hOvnxX4jvufMUFXUF5HemIMCTHhUR+fmhBNYkyklQhMUPlSIvgbrr7+zQCquhlXNY8xfV5BeT1ZIZ5awpuIkG1dSE2Q+ZIIElT1w3bbbIVt0y/kl9WFTUOxR1Zq/LFpL4wJBl8SwVERGQcogIgsAYocjcqYIGhrUwor6sOmodgjKzWB/LI6XDWnxjjPl4rRb+Dqwz9JRAqB/cCXHI3KmCAoqW6kuVXDrkSQnZZAbVMr5XXNpCXGhDocMwB0mwhUdR9wnogkAhGqWu18WMY4zzOnT6inn27Psy5CflmdJQITFL70GvpOu9cAlcB6Vd3oTFjGOC9cpp9u73gX0jpmZKeENhgzIPjSRjAHuAnX3EEjga8Bi4C/icj3HYzNGEd5FqQZmRJeiSDrWInAeg6Z4PCljSALOFlVawBE5H+A5cCZwHrgHufCM8Y5BeV1DE2OJS46MtShnCA5LpqUhGjrOWSCxpcSwVCg0et1M67BZfXtthvTp+SX1Ydd+4BHdmqCjS42QeNLieBJ4AMR+bf79SXAP9yNx9s7f5sx4a2goo6TR6WGOowOZafFs7PI+mWY4Oi2RKCqd+NqF6hw/7tJVe9S1VpVvcrZ8IxxRktrG4cqGsJuDIFHdqprdHFbm40lMM7zaYIVVV0rInlAHICIjFLVg45GZoyDiqsaaG0LvzEEHllpCTS1tlFS3ciwwXGhDsf0c92WCETkUhH5GNdAsjfd/33Z6cCMcZKnR05W2JYI3D2HrMHYBIEvjcV3A6cAu1V1DHAesMbRqIxxWMGxwWThWSI4NpbAZiE1QeBLImh2rxEQISIRqroK19gCY/qs/PJ6RGD44PBMBJ6xDYXWc8gEgS9tBBUikgS8BTwpIiVArbNhGeOsgvI6hg+KIybKyUX6ei4uOpIhybE2HbUJCl/+ChYDdcC3gVeAvcCnnQzKGKcVlNWHbfuAR1ZqPAUVVjVknOdLIviJqrapaouqPqqqfwR+4HRgxjipoLyOrDBtH/DISrUFakxw+JIIzu9g24WBDsSYYGlqaaOoqqFPlAgOVdTTamMJjMM6bSMQkZuBrwNjRWSz165k4F2nAzPGKUWV9age76IZrrJS42luVUqqG8K2Udv0D101Fv8D13iBXwF3eG2vVtUyR6MyxkHhPobAwxNfQXm9JQLjqK6qhiKBKlwrlFV7/UNE0pwPzRhnhPsYAg/PqGebhdQ4rasSwXrc6xQD0m6fAmMdicgYh+WX1xEZIQwbFN5TN3jGEhTYugTGYZ0mAvcoYmP6nYLyekakxBEVGZ5jCDxsLIEJFp8mnRORS3EtRAOwWlVfci4kY5yVX1ZHVkp4tw942FgCEwy+TDr3a+A2XGsPbAduE5FfOh2YMU4pKK8P21lH27OxBCYYfCkRXATMVNU2ABF5FNgA/MjJwIxxQkNzKyXVjWHfY8gjKzWeV7YW0dqmREa0b6ozJjB8rSRN8fp5sANxGBMUhypcT9fh3mPIw3ssgTFO6WpA2f3AU8AvgY9EZDWu3kNncuK4AmP6DM86wH2nRGBjCYzzuqoa2g3cCwwHXgcOABuBH6hqseORGeOAvjKGwMN7LMHcHBu+Y5zRadWQqv5BVRcAZ+FKCp/DlRhuFJHcIMVnTEAVlNcTHSkMTQ7vMQQeNpbABIMvi9fnqer/quos4Ergs8BOX04uIotEZJeI7BGRTquTROQyEVERsQVvjKNcYwji+0zDq40lMMHgS/fRKBG5RESexDX30C5cpYPu3hcJ3I9rptIpwJUiMqWD45JxdU/9wM/YjfFbQXldn+k66mFjCYzTOk0EInK+iDwEFAA3AMuBcap6har+24dzzwP2qOo+VW0Cnsa1yE17dwP/C1i3COO4gvL6PjOYzMPGEhinddVY/ENcM5B+V1XLe3DukUC+1+sCYL73ASJyMpCtqstF5HudnUhEbgRuBMjMzGT16tU9CCewampqwiKOcNBX7kVTq3KkupHmymJWrw78BLpO3Ye2qiYKypp5Y9UqIqRvVGn1lc9EMPSFe9HVXEPnOHlhEYkA/g+4prtjVXUpsBRgzpw5unDhQidD88nq1asJhzjCQV+5F3uP1MB/3+SMk6ewcFZWwM/v1H0ojM9j+f6tTJp1CiNS+ka1Vl/5TARDX7gXTs66VQhke73Ocm/zSAamAqtF5ABwCrDMGoyNUwr62BgCD++xBMY4wclEsBbIFZExIhIDXAEs8+xU1UpVzVDVHFXNAdYAl6rqOgdjMgPYsTEEfS4R2LoExlmOJQJVbQFuAVYCO4BnVXWbiNzlns3UmKDKL/OMIYgNdSh+OTaWwEoExiE+TUPdU6q6AljRbttPOjl2oZOxGFNQXsfIlHgi+sgYAo+46EiGJsdaicA4JrxX5jAmgFzTT/etaiGPrNR4KxEYx1giMANGX1qHoD0bS2CcZInADAgNza0crWnsw4kgnkMV9bS2afcHG+MnSwRmQOirXUc9slITaGlTDlfZAHwTeJYIzIDgaWjtyyUCsJ5DxhmWCMyA4PkCzU7rqyUCG0tgnGOJwAwIBeX1xERGMCSpb40h8BhhYwmMgywRmAEhv7yOkal9bwyBh40lME6yRGAGhL7cddTDxhIYp1giMANCYR9ckKY9G0tgnGKJwPR79U2tHK1p6rNdRz1sLIFxiiUC0+8VVvTtrqMeNpbAOMUSgen38o8NJuvricB6DhlnWCIw/d6xMQT9oGoIbCyBCTxLBKbfKyivIyYqgow+OobAw8YSGKdYIjD9XkF5PVl9cB2C9mwsgXGKJQLT7xWUuQaT9Qc2lsA4wRKB6ff68oI07dlYAuMESwSmX6traqG0tqnP9xjysLEExgmWCEy/VthPuo562FgC4wRLBKZf6+vTT7dnYwmMEywRmH6try9I056NJTBOsERg+rWC8npio/ruOgTt2VgC4wRLBKZfKyivZ2RqPCJ9ewyBh2csQX6ZlQhM4FgiMP1aQXldv+k66mFjCUygWSIw/Vp+P1iQpr2s1AQKKqxEYALHEoHpt2obWyjrR2MIPLJS4ymqaKCltS3UoZh+whKB6bcOuuvRR/WTrqMeo9JcYwmKKm0sgQkMSwSm3/IkgtFpiSGOJLBGpbsS20FrMDYBEhXqAIwprWlk6dv7KCyvJyMpli8vGM24IUm9Pu/BUneJIL1/lQhGp7sSW15pHaeN7/35dhZX8Y8PDlJa28SY9ERuOGMsgxOie39i02c4mghEZBHwByASeFBVf91u/3eA64EW4AhwrarmORmTCS8rthTx/ec3U9/cyqi0BIoq63lmbT53f2YqS2Zn9erceWW1DI6PZnB8//pSGzYojuhIIa+sttfnenxNHne/tJ2oCCFzUBwrthTx+Jo8fn/5TM6eNDQA0Zq+wLGqIRGJBO4HLgSmAFeKyJR2h20A5qjqdOB54B6n4jHh552Pj3Lb0xvIzUxi5bfOYNXtC1l9+9nMyB7M7c9t4s3dR3p1/rzSOkb3s9IAQGSEkJ2acKzE01MrthRx54tbWTA2nbe+fzarbl/I8lvPYGRKPDc/uZ71eeUBitiEOyfbCOYBe1R1n6o2AU8Di70PUNVVqur5NK8BevcIaPqMvNJavvb4OsYNSeKRr85j/NBkAIYNjuORr85jQmYStz+3ibLaph5f42BZXb9rKPYYlZ7QqzaC4soGfvivLczITuHBr8w5tnrblBGDeOy6eQwbFMe1j6ylqNLGKwwEourMdLYisgRYpKrXu19/GZivqrd0cvx9QLGq/ryDfTcCNwJkZmbOfvrppx2J2R81NTUkJfW+Hrs/8PdeqCq/WdfA3oo2fnF6POnxn3weya9u42fv1TN3WCRfmxHnd0ytbcqN/63jwjHRLJkQ4/f7eyKYn4nHtzfy3qEWHjg3oUejpv/wUQPbS1v52anxDEv85P0vrm3jznfrmTEkkltm+X//7e/juHC5F2efffZ6VZ3T0b6waCwWkS8Bc4CzOtqvqkuBpQBz5szRhQsXBi+4TqxevZpwiCMc+Hsv/r2xkG2lG7lr8UlctiCn0+MKonbwt7f28aur5pKT4V/Pn/yyOlpfXcWZsyazcG62X+/tqWB+JvZG7ef1g9uZMe800hL9S3TbD1Wx4ZW3uf2CCVxxTm6nx5Um7OHelbtoGzaZcyZl+nUN+/s4ri/cCyerhgoB77/ALPe2E4jIecCPgUtVtdHBeEwYaGhu5VcrdjIjazBXzR/d5bHXnTaGqMgI/vrWPr+vk+euP+8v00+356nyyiv1v8H4z2/uJSk2ii93kYQBbjhjLLlDk7jrP9tt8Fo/52QiWAvkisgYEYkBrgCWeR8gIrOAv+JKAiUOxmLCxHPrCyiuauAHiyYR2c1i8kMHxbFkdhb/XF9AiZ8LsXh61PTHxmI4/nv5206QV1rL8s2HuGr+qG57U8VERXD7pyZyoLSOlzYX9ThWE/4cSwSq2gLcAqwEdgDPquo2EblLRC51H3YvkAQ8JyIbRWRZJ6cz/UBTSxt/Wb2X2aNTWTAu3af3fO3MsTS1tvHM2ny/rnWwtI6YqAiGDfK/frsv8JQI/O059I8PDxIhwnWnj/Hp+PMnZzJpWDJ/euNjWx6zH3N0ZLGqrlDVCao6TlV/4d72E1Vd5v75PFXNVNWZ7n+Xdn1G05e9uKGQwop6bj1nvM8NnKPTE5mXk8a/Nx3Cn44NeaV1ZKfGE9FNqaOviouOJHNQLHl+lAja2pT/bDzEmROGMNTHBBkRIdxyznj2Hqnl5a1WKuivbIoJExSqykPv7mfy8EGcNWGIX++9ZOYI9pTUsKOo2uf39Oeuox6j0vwbS7Aur5xDlQ1cOmOEX9e5cOpwRqcn8Oh7B/yM0PQVlghMUKzPK2dncTVXLxjtd3fHi6cNJypCWLbpkE/HqyoHy+qOTcXQX41KS/RrdPGyTYXERUdw/hT/egBFRghfmj+atQfK2VFU5W+Ypg+wRGCC4vE1eSTHRrF4pn9PowBpiTGckZvBso2FtPlQT11W20RNY0u/LxGMTk/gcFUjDc2t3R7b3NrG8s1FnD9lGImx/vcaXzI7i9ioCJ5YYzPA9EeWCIzjjtY0smJLEZfNziIhpmdDVy6aNpxDlQ1s9+GJ1FNv3l97DHl4fj9flq1cn1dOeV0zF08b1qNrpSbGcMmMEbywoZDqhuYencOEL0sExnEvbiikuVX54vxRPT6Hp13hrY+7n3/IU2/e3xPB8bEE3SeCt3YfISpCOHV8Ro+v98X5o6hramXFFms07m8sERjH/fOjQqZnDWZCZnKPzzF0UBxThg/izV0+JAL3E3J/W6u4vWOJwIcSwZu7j3Dy6FQGxfV8JtZZ2SmMzUjkn+s/MS7U9HGWCIyjth+qYkdRFZed3Pv5BM+cMIT1eeXdVk3kldYxbFAccdGRvb5mOEtLjCEpNqrbqqEj1Y1sO1Tld2+t9kSEy2Zn8eGBsl7PfGrCiyWCAaytTSmpauDjw9WOTSHwz48KiI4ULvGzy2JHzpowhJY25f29pV0ed7Cstt8tRtMREWFUWkK300y87a5O620iAPjsrJGIuP6/OqG5tY3dh6s5Ut3o17gR0zthMemcCa6qhmYee+8AD797gFL3NM/JsVGcPyWTOy6axNDkwIzGbW1Tlm06xMKJQ/2eGK0js0enkhgTyZu7j3DBSZ03euaV1gXkS68vGJ2ewK7DXY+veHP3ETKSYpgyfFCvrzciJZ5Tx6Xz4sZCvnVebo9mPu3IoYp6frliB6t2llDb5OoFNTQ5luvPGMNV80f3qKeT8Z3d3QFmZ3EVNzy2jvyyehZOHMK5k4aSEBPF2gNl/GtDIa/tOMxvvzDT777mHflwfxlHqht71GW0IzFREcwfm86afZ2XCOqbWimpbuz3DcUeo9ITeH1HCa1t2uHcTarKmn2lnDouI2CjrC+ZPoI7/rWFbYeqmDpycK/Pt2zTIX74z820KXzu5JHMHp1KVX0zr+0o4ZcrdvLM2nz+dvUcxgZg+VLTMasaGkDe31vK5x54j8bmNp6/aQGPfHUeX16Qw2Wzs/j1ZdN5+bYzyMlI5OtPruf1HYd7fb0VW4qIi47gnAAueTg3J429R2oprel4otr88v4962h7o9ISaGpto7iTSfkKyus5XNXI3DFpAbvmp04aRmSEsDwAvYf+s+kQ33p6A5OHD+LVb5/JLz47jc+dnMU1p43hievn88R18ymva2bx/e/y0UFbMc0plggGiO2HqrjxsXWMTInnP7eezpycT34xjBuSxBPXz2fy8EHc/MRHbMqv6PH1WtuUl7cWcY67xBEoc3JSATpdRjHvWNfR/j2q2GN0muv37Kzxdu2BMgDmjE4N2DVTE2M4bXwGyzcX9aoef82+Ur71zEZmj07lsevmdZi8T8/NYNktp5GaEMN1j6xl75Ga3oRuOmGJYAA4WtPINQ9/SFJcFI9eO4/MLiYcGxQXzaNfnceQ5Fhue3oDtY0tPbrmB/tLOVrTxMXTAlMt5DFt5GBiIiO6SATu6acHSInAUwV2oJMG43V55STHRfWq625HPj1tOAfL6tha2LMpJyrrmvn2MxsZlZbAQ9fM7fJhISs1gceunUdkhHDNwx9SWW8D2gLNEkE/19amfPfZTVTUN/P3r8xlREp8t+9JTYzh/74wg7yyOu5+aXuPrrt8cxHx0ZGcPSmwjbZx0ZFMzxp87Em3vX1Ha0lNiCY1AI3TfcGIlHhioiI4cLSTRHCgjNmjU7td+8FfF5yUSVSE8NIW3+Z/au/HL27hSHUjf7hiJsk+jG3IyUhk6dVzKKpo4Ef/2mI9igLMEkE/98h7B3hz9xHuvHgyU0b43mtk/th0bjxzLE+vzWejn1VELa1tvLK1mHMmB7ZayGNOThpbCis7nGNn/5Faxvi5rGVfFhkh5KQnsK+DRFBR18TuwzXM7aAasLdSEnpePfTunqO8tLmI287NZXpWis/vO3lUKt+5YALLtxTx3Dpnuq8OVNZrKIhaWtv47/bDvL6zhG2HqmhqaSVzUBzzx6SzZE4WI314WvdHflkd967cxbmThvKlU7peFrIj3zwnl399VMjdL23n+ZsW+NxV8IP9ZZTWNvHpacP9vqYv5uak8pc3lU35Fcwfe+ICN/uP1nJaL6ZR6IvGZCSy98gnE4Gn+iyQ7QPeLp4+nO8/v5nNBZXMyE7x6T2tbcrdL20nOy2eG84c6/c1bzpzHG/tPsLdy7ezcNKQgHV19sgrreWf6wv4YH8ZR2saiY1ylUDPnZzJuZOG9tv1LaxEECSrdpbwqd+/xc1PfsR/tx9m2KBYJg5LpqKumd+/vpuz713NXf/ZTn1T9zNJ+kJV+cm/tyICd39mao/6eyfGRnH7BRNYn1fuVw+R5VuKSIiJZOHEwPUW8nbyKNcX20cHK07YXtvYQnFVA2OHDJwSAcCYjCTySms/MShww8EKIiPE5y9pf31qyjCiI8WvuYeeW5fPzuJq7lg0uUcjvyMihF9+dhqNzW3c/dIOv9/fmZrGFn78whbO/e2b3LdqD/XNrUwclsyQ5FiWby7ihsfWcdEf3+bdPUcDds1wYiUChzW1tPHrl3fy0Lv7GTckkT9fdTIXuLvfeRRW1POn1z/m4ff28/6+Uv76pdm9Hhm7clsxq3Yd4c5PT/GpXaAzS2Zn89A7B/jDax9z0dTh3T4RHasWmjSU+BhnpnhITYwhOy2erYWVJ2z3NJgOpKohgLEZiTS3KoUV9Sf0ltpcWMmEzGTHptoYnBDN6eMzeGlzEXdcOKnbh43m1jb+9MYeZmancFEPZ0EFGDskiW+cPZ7fvbaby+dkc3pu70qAe0qq+drj69l/tJYvnTKab5w9/oQOFc2tbazYUsT//Xc3Vz34Ad84exzfPm8CUZH95zm6//wmYai+qZXrH1vHQ+/u55pTc1hx2xlcOG34JxruRqbE8+vLpvPQV+ZSWF7HZX95j/2dNP75orGllV+u2MmEzCS+ssD/KiFvkRHC188ex8clNfzXh7EFH+wvo6y2iYsdqhbymD4yhc2FFSds89yzgZYIxrhLQN7tBKrKloIKpgdgwFdXLpo2nMKKejYVVHZ77H82HfJ7qdLO3LRwLFmp8fzq5R0+rVHRmV3F1Sz5y/tU1DXzxPXzuWvx1E/0qouOjGDxzJG8ctuZXD4nm/tX7eUb//iIxpbAlN7DwYAoEbS0trF61xHe+vgI2w9VUdvUSkxUBFOGD2LBuHQ+dVImsVGBfWqqa2rhqw+v5cMDZfzvZdO4fG73UzCfPWko/7z5VC5fuoar/raG524+tUftBo+9l8fBsjoeu3ZeQJ5aLp42nN++upsHVu/lgimZXf4Rr9ji6i3kVLWQx7SswSzfUkRFXRMpCa4eQvvd9eQ5A2QMgYcn8e0/UsvZE13bCivqKa9rZmqWs4ngginD+GHEFl7eWsTMLqqg2tqUB1bvZdKw5IAMMIyNiuT2CybyrWc2smzTIT4za6Tf59h/tJarHvyA2KgInv3agm7HnsTHRPK/S6YzaXgyP/vPdm58bD1Lr54d8O+OhuZWXt5axJq9ZewsrqKpVUmOjWLKiEEsnDiEM3KHBLwXWL8uEbS0tvH4mjxO/fUbXP/YOv71USERImSlxpMYE8nyzYf45lMbOO3Xb/Dg2/sCNvFaS2sbt/5jA2sPlPH7y2f6lAQ8cjOTefy6eVQ3tvC1x9f5tPqUt8q6Zv74xsecPXEIZwZovp2oyAhuOmscm/IrWLOv426b4GoIXLntMGdPGuJYtZDHNPeT7hav6qH9R2sZmRLv+LXDTXpiDIPiok4oRW5xP6E7XSIYnBDNgnHpvLK1uMveQ2/sLGFPSQ03LxwXsPmJLp0xgpNGDOLelbv8fjqvaWzh+kfX0qbKk9ef4tcAxK+eNoZffW4ab+4+wu3Pbe5VicRbU0sb96/aw4Jfvc63n9nEyu3FJMdFk5UaT6sqz67L55qH13LmPat4dl1+wK4L/bhEsPtwNbc9vZEdRVXMG5PGzz8zlbMnDSXa6wm5rU15Z89R/vb2Pn6+fAcvbCjkT1fO6vWcJne9tJ3Xd5Zw1+KTWDzT/yeVk0YM5veXz+S6R9dx54tbuffzM3x+74Pv7KO6oYUfXDjJ7+t25XMnj+SelTt5Yk0eC8ald3jM+rxyjtY0smiqs9VCAFNHuL7gNhdUckauK+HtPTqwuo56iAhjhiSdkAg2F1YSFSFMHBbYgWQduXDqcH70wha2F1Vx0oiOE89ja/IYNiguoFWGERHCDy+czJf+/gGPv5/H9Wf41gtJVfn+85vYf7SWJ66fz/ih/v+9XzlvFOV1Tdzzyi5GpsRzRy//3nYWV/HNpzaw+3AN504aynVnjGHB2PQTkmZTSxuv7TjM0rf28f3nN/Pkmjx+f8WsgHzm+2WJ4J/rC7j0vnc4Ut3An686mWduPIULThp2QhIA1wfpzAlDeOzaeTxw1ckUVTaw+P53eXN394ufdObFDYU89n4eN5wxhqsX5PT4POdOzuTWc8bz3PoCXtrs26Cd8tomHnpnPxdPH86kYb2fadJbXHQkX5iTzcptxRzuZF6bFVuKiIkK7NxCnRmcEE1OesKxBmNVZf+RmgGZCMDVYLzPa/qFrYWVTBzmXEOxtwtOyiRC4JWtxR3uP3C0lrd2H+GL80cFvIH19NwMzsjN4L5Ve3wecfzM2nxWbCnmB4smceq4njc033zWOK6aP4q/vLnX57/RjqzcVsznHniPirpm/v6VOfz9mrmcOi7jEyWnmKgILpo2nBe+fip/uGImB0rr+PQf3w7IinH9KhGoKr/7726++9wmZmWnHmuc7a4oKiJcNG04//7GaYxMiefaR9bycg9u7p6SGn70whbm5aTxg0W9fyK/7dxcZmQN5s4Xt3KkuuNJ1rwtfXsfdc2tfOvc3F5fuyNXzR9FS5vy1IcHP7GvrU1Zua2YM3OHkBSkKYOnjhzMZncVSGltE1UNLeQM0EQwJiORQ5UN1DW1oKpsLqg8Vn3mtIykWOaNSePlThLBE2vyiIoQrpib7cj177hwEpX1zfx59d5ujy0or+Pny3ewYGw6N/hYguiMiPA/l5zEyaNS+P7zm/m4m+nAO/LP9QXc9MR6cjOT+c+tp3Pu5O5n/RURFs8cycu3ncHEYcl8/cmPWPrW3l6Ntu43iUBV+cXyHfzh9Y+57OQsHr12nt+DTbLTEnj+5lOZmZ3CLU9t6PQJpyP1Ta1848mPiIuO5I9XzgrIk09UZAS/+fwMapta+cm/t3Z5bGlNI4++d4BLZ4wgN8DzyniMTk/krAlDeOrDg59oT9lUUEFRZQMXTu15t0B/TRs5mMKKespqm9hT4noa7kkxvz8Y567O3HekloLyeirrmwMyRbSvLpw6nD0lNZ/4MmxobuW59QV8auowhnYxx1VvnDRiMJdMH8Gj7x3odFZacH1H/NA9PcU9S6YHZHBYTFQED1w1m/joSG59aoNfbRUvbCjg9uc3ceq4dJ6+4ZQu5wDryIiUeP5xwylcPH04v1yxk9+/9rG/4R/TbxLBb1/dzYPv7OcrC0bzm89PJyaqZ79aUqxrYrYZWYP55tMbWJ/XeeOot5/8eyu7S6r53eUzGTY4cB/43Mxkbjs3l5e3FndZZbX0rX00NLfyTYdKAx5XzsvmcFUj77QbWPPK1mKiI4XzfHiiCRTPlBk7i6uOJYLcAZoIcjNdv/eekhp2FLkmgvNnSpHeWuR+AGhfKnhtx2Eq65u50o8OEz3xzXNzaWhpZenb+zo9ZsWWYt7++CjfXzQpoNOUDxscxz1LprOzuJrfvrrbp/e88/FRvvfcZk4Zk86DV8/tcQeHuOhI/nTFLD4/O4s/vP4xf3mz+1JRR/pFIrjvjY+5b9Uerpibzf9cclKveyUkxUbx4FfmMjIlnusfXdft+qwvbT7Ec+sL+MbC8Y6sjHX9GWMYk5HIT5dt6/CJ40h1I4++f4DPzBx57MnQKedMyiQ1IZrn1x+f60VVeXlrMaeOy2BwQs8XR/eXpyF0V3E1e0pqSIyJZHgAk3BfkpOeSGSEsKekhl3FrqfyiQ6VDDuSOSiO2aNTP5EInl9fwIjBcZ12MAiU8UOTuHTGCB57L6/DUkFtYws/X76dKcMH9Wi6le6cOzmTq+aP4m9v7+O9bkYf7z5czc1PrGf80CT+evXsXvdyi4gQfn3ZdC6ZMYJfv7yTR97d7/85ehVBGHj43f385tXdfHbWSH7x2WkBmwskLTGGh6+ZS2ubdjl4pKS6gTtf3MqMrMF86zxnnsZjoyL56aUnsf9oLQ+/e+AT+//y5l6aW5VbHS4NgKsovHjmSF7dfpjKOlfj3MHqNg6W1QW1WghgSFIs6Ykx7CxyJYLxQ5MC1jWxr4mJimB0egIfl1Szs7iaUWkJQV/e8cKpw9hRVHVsKvDiygbe2n2Ez52cFfB+7x259ZxcGltaWfrWJ0sFf3lzL0WVDdz9mZMci+X/XTyFMRmJfOfZTVTUNXV4TFVDMzc9vp7Y6EgeumYug3yYedUXkRHC/31hBp86KZOf/mc7z67N9+v9fToRvLqtmLte2s6nTsrk3iXTA/4/OCcjkd98fgZbCiv55fJPzmuiqvzoX1upbWrlt1+Y4eiQ87MmDOHsiUN4YNWeY1/AACVVDTyxJo/PzRoZtB4zS2Zn0dTSxrJNhQCsK24lMkK6XEfYCSLCpOHJ7Cyu4uOSasYN0Gohj/FDklxVQ8VVTApCt9H22lcPvbChkDZ1fV6C4Vip4P08jnqVCkqqG3jw7f18evpwZo8O/EysHvExkfzh8lkcrWnkxy9+sk1PVfnec5vIK6vj/i/O6tXULx2Jjozgj1fO4ozcDH70whbe+dj3eZH6bCLYWljJbU9vZPrIwfz+8sA0znbkgpOGcd3pY3j0/bxPdNP610euNX6/d8FExg91/g/v+4smUd3Ywl/eOl4P+MDqvbS2Kbee43xpwOOkEYOYmJnMixtdXebWHW5h/pi0gCxQ769Jwwaxo6iaw1WNA7ah2GP80CTySus4cLSWSQFYqN5fWakJTM8afKzH3YsbCpk9OjWoPbluPddVKvibV6ngT6/vobm1jdsvmOj49ae5awaWby76RJfSJz44yMpth/nhhZM+MWtuoMRGRfLAVSczbkgSNz+5nj0lvvVk6pOJoKiynuseXUtaYgx/+8ocx0eS/mDRJGZmp/CD5zcfK/aWNbTx0/9sY87oVK49fYyj1/eYPHwQi2eM4OF393O4qoGiynr+8eFBlszO6vUkdf4QES6dOYL1eeWs2lVCUa0GvVrIY+KwZJrcPZhyg5CMw1luZhItbUqbwuQQlAjAVSrYVFDJpiMt7DpczeKZgV2hrjvjhiSxeObIY6WCvNJanvrwIFfMyw5aQrrprHFMb9fte09JDb9Yvp0zJwzhOoe/L5Ljovn7NXOIjYrkq4+sPaF01BlHE4GILBKRXSKyR0Tu6GB/rIg8497/gYjkdHfONlWue2QdtY2t/P2aOQGfj7wjMVER3PfFWURECN98agPNrW08tLWJllblN5+fEZT6T4/vnD+R1jblD69/zAOrXH2Hv3H2+KBd3+PSGa4/8Dv+uRnBtaB5KEz2Gjg34EsEQ45/+YeiRACubqQAD29tIjLCNT4n2G45Z/yxtoLfvrqb6MgIvhnEEnNUZAS//fwMahtbufPFrbS0Kd96ZgPx0ZH8Zsn0oLRjZaUm8OBX5lBS1ciNj3U/VY1jiUBEIoH7gQuBKcCVIjKl3WHXAeWqOh74HfC/3Z33YFkdO4uruO+LswI+erYrWakJ/PKz09hUUMmVS9ew9WgrP7xoUtAHMI1KT+CL80bxzNp8nl57kC/MyQ5oVzhfZaclcPKoFA5XNZKbGuFYH/Hu5GYmESGuZJ2dGtg6175m3FDXZzE+OpJRIVqzeUxGIpOGJVPRqJw6Lp2MpNigx+ApFTzy3gGWbTrEtafnBP3zmZuZzHcumMAr24q5Z20DWwur+PVl04Max8zsFH53+Uw+OljBd57d2OWxTpYI5gF7VHWfqjYBTwOL2x2zGHjU/fPzwLnSTbqsbmjhZ5ee5Pjslh25ePpwFs8cwbq8cianRfCl+YHvhuaLW87JJTYqAkFCUhrw8JQKZmeGbsqquOhIcjISGZuR2K/mh++JhJgoRqbEMyEzKail1PY8pQLP5yMUbj1nPC2tbQyOj+bGM8eFJIYbzhjLrFEp7C5v44q52SEpNV80bTjfXzSRFVu6HhwrTi0CLSJLgEWqer379ZeB+ap6i9cxW93HFLhf73Ufc7TduW4EbgRIycye/cLTjzkSsy9qm5Xl+5o5NaOJrPTQVUV8UNRCU6tyRlbw+u23V9esvLinifOGNzM0JXT3Ym1xCwLMGRbaORRrampISgpt9dT7h1qIi4JZQ0N3LyoblRd31XLFlERio0KXkN442ExKrHByCB9UjtS18eq+Oi6blEhciO6FqvLKgRbuufaC9ao6p6Nj+sTso6q6FFgKMGfOHF24cGFI47kYWL16NaGMI3RXPtFF59u98Aj1fYDwuReDY+1eeAwJg8/F2cA913a+38mydCHgPctUlntbh8eISBQwGCh1MCZjjDHtOJkI1gK5IjJGRGKAK4Bl7Y5ZBnzF/fMS4A11qq7KGGNMhxyrGlLVFhG5BVgJRAIPqeo2EbkLWKeqy4C/A4+LyB6gDFeyMMYYE0SOthGo6gpgRbttP/H6uQH4vJMxGGOM6drA7m9njDHGEoExxgx0lgiMMWaAs0RgjDEDnGMji50iIkeAvFDHAWQAvk/43b/ZvXCx+3Cc3YvjwuVejFbVDpdQ7HOJIFyIyLrOhmsPNHYvXOw+HGf34ri+cC+sasgYYwY4SwTGGDPAWSLouaWhDiCM2L1wsftwnN2L48L+XlgbgTHGDHBWIjDGmAHOEoExxgxwlgh6SUS+KyIqIhmhjiVUROReEdkpIptF5AURSQl1TMEmIotEZJeI7BGRO0IdT6iISLaIrBKR7SKyTURuC3VMoSYikSKyQUReCnUsnbFE0Asikg1cABwMdSwh9l9gqqpOB3YDPwxxPEElIpHA/cCFwBTgShGZEtqoQqYF+K6qTgFOAb4xgO+Fx23AjlAH0RVLBL3zO+D7wIBucVfVV1W1xf1yDa7V6AaSecAeVd2nqk3A08DiEMcUEqpapKofuX+uxvUFODK0UYWOiGThWt32wVDH0hVLBD0kIouBQlXdFOpYwsy1wMuhDiLIRgL5Xq8LGMBffh4ikgPMAj4IcSih9HtcD4ttIY6jS31i8fpQEZHXgGEd7Pox8CNc1UIDQlf3QlX/7T7mx7iqBp4MZmwm/IhIEvBP4FuqWhXqeEJBRD4NlKjqehFZGOJwumSJoAuqel5H20VkGjAG2CQi4KoK+UhE5qlqcRBDDJrO7oWHiFwDfBo4dwCuO10IZHu9znJvG5BEJBpXEnhSVf8V6nhC6DTgUhG5CIgDBonIE6r6pRDH9Qk2oCwAROQAMEdVw2GGwaATkUXA/wFnqeqRUMcTbCIShauR/FxcCWAt8EVV3RbSwEJAXE9GjwJlqvqtEIcTNtwlgttV9dMhDqVD1kZgAuE+IBn4r4hsFJG/hDqgYHI3lN8CrMTVOPrsQEwCbqcBXwbOcX8WNrqfiE0YsxKBMcYMcFYiMMaYAc4SgTHGDHCWCIwxZoCzRGCMMQOcJQJjjBngLBGYkBGRVq8uhhvdUxL0eSJyjYgcEZEHvbY95Z6d9dt+nGe9iMS223aLe4bTE2a8FZc/uvdtFpGT3dtnisj77plAN4vI5R1c548iUuP1+tsiclBE7vP3dzd9k40sNqFUr6ozO9rhHpgkqhrWc7R04RlVvQVARIYBc1V1vK9vFpExuOayamy3613gJWB1u+0XArnuf/OBP7v/Wwdcraofi8gIYL2IrFTVCvd15gCp3idS1d+JSDkwx9d4Td9mJQITNkQkxz2n/2PAViBbRL4nImvdT7M/8zr2xyKyW0TecT9t3+7evtr95YaIZLhHfXvmhL/X61xfc29f6H7P8+41FZ50JyFEZK6IvCcim0TkQxFJFpG3RGSmVxzviMiMbn61V4GR7lLPGSLyTfd8/ZtF5OlO3rMIeKX9RlXdoKoHOjh+MfCYuqwBUkRkuKruVtWP3e89BJQAQzz3BLgX16RoZgCzEoEJpXgR2ej+eT/wbVxPtF9R1TUicoH79TxAgGUiciZQC1wBzMT1Gf4IWN/Nta4DKlV1rru65V0RedW9bxZwEnAI1xP3aSLyIfAMcLmqrhWRQUA98HfgGuBbIjIBiPNhBtpLgZc8pR8ReQYYo6qN0vkiPovc98NXnc2AWuTZICLzgBhgr3vTLcAyVS1y5z4zQFkiMKF0QtWQu40gz/1EC67ZXS8ANrhfJ+FKDMnAC6pa537fMh+udQEwXUSWuF8Pdp+rCfhQVQvc59oI5ACVQJGqrgXwzKApIs8Bd4rI93BNuf2In78zwGbgSRF5EXix/U4RiQGyVHVfD87dIREZDjyOK8m2uauJPg8sDNQ1TN9licCEm1qvnwX4lar+1fsAEflWF+9v4XiVZ1y7c92qqivbnWsh4F0P30oXfxeqWici/8VVFfMFYHYXsXTmYuBM4BLgxyIyzWthH4AzgHf8PGenM6C6SzPLcU0Z7kmys4DxwB53aSBBRPb4045h+g9rIzDhbCVwrbjmtkdERorIUOAt4DMiEi8iybi+UD0OcPzLeUm7c90srimSEZEJIpLYxbV3AcNFZK77+GRxzTIKrtWm/gisVdVyf34hEYkAslV1FfADXCWTpHaHLcL/xX2WAVe7ew+dgqsarMhdungBV/vB856DVXW5qg5T1RxVzQHqLAkMXFYiMGFLVV8VkcnA++6n1hrgS6r6kbuefROuxs+1Xm/7DfCsiNyI6ynY40FcVT4fuRuDjwCf6eLaTe6uln8SkXhc7QPnATXuhUaqgId78GtFAk+IyGBcpZQ/enrweFkI/KSjN4vIN3E17g4DNovIClW9HlgBXATswdVT6Kvut3wBV+kjXVxrRgBco6obexC76ads9lHT54nIT3F9Qf8mSNcbgav75qSOure6v3DneLqP+nnuLOBvqnphb+Psjd78DqbvsaohY/wgIlfjWoP3x12McagHLhSvAWW+UtWCMEgC3wZ+CAzIJSYHIisRGGPMAGclAmOMGeAsERhjzABnicAYYwY4SwTGGDPAWSIwxpgB7v8D1BCZyr8UCjcAAAAASUVORK5CYII=\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "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": [ + "# Plot frequency response\n", + "fs = 1\n", + "fLim = (-0.5, 0.5); dbLim = (-70, 5)\n", + "if Nrect == 1024:\n", + " fs = Nrect # to have frequency in units of fsub = fs / Nrect\n", + " fLim = (-5, 5); dbLim = (-70, 5)\n", + "dsp.plot_spectra(fRect, HFrect, fs, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "98200c25", + "metadata": {}, + "source": [ + "# 2 Impulse response of rectangular frequency reponse (ideal LPF)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "5c1de1c5", + "metadata": {}, + "outputs": [], + "source": [ + "# Try ideal subband prototype filter [HARRIS Fig 3.6]\n", + "# . Npass = Npoints / 5\n", + "Npoints = 100\n", + "Npass = Npoints // 5 + 1 # Ideal LPF number of points in pass band\n", + "bandEdgeGain = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "90d0823a", + "metadata": {}, + "outputs": [], + "source": [ + "# Try half band FIR filter\n", + "# . fpass = fs / 4 --> Npass = Npoints / 2 for half band\n", + "Npoints = 64\n", + "Npass = Npoints // 2\n", + "bandEdgeGain = 0.5 # Band edge gain 0.5 for half band\n", + "#bandEdgeGain = 1.0\n", + "if bandEdgeGain == 0.5:\n", + " Npass += 1 # make odd for fc = 0.5" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "d47b1dd4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DC response: sum(hIdeal) = 1.000000\n" + ] + }, + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x7fa3ad57e5e0>,\n", + " <matplotlib.lines.Line2D at 0x7fa3ad57e730>]" + ] + }, + "execution_count": 10, + "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": [ + "# Use ifft of sampled frequency response to obtain impulse response = FIR filter coefs\n", + "hIdeal, fIdeal, HFideal = dsp.ideal_low_pass_filter(Npoints, Npass, bandEdgeGain)\n", + "print('DC response: sum(hIdeal) = %f' % np.sum(hIdeal))\n", + "\n", + "# Plot coefs, for half band all even coef except [0] are zero\n", + "plt.plot(hIdeal, '-', hIdeal, 'o')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "82875d5f", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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RplVVkQ8pKVEd2LNEb824X7WwsN1sjBXxUC9owXOIyw5pYD4wQkSGikga8A3gxZBt6nQMPH4wX+Idnnumutk34uf+VcMJfMDwE3Jia5yR2IwezWX8lS/2ZJCXF/mQzEz4bFcmPyv4LvTsGVPzEoG4FAdVrQauA14HVgHPqOqKcK3qhIwdy4XMYv3GFFatapq9ZQt8siSZC3gexo6NuXlGAtO1K2cOW09aUhWvvdb8YUlJ0CWzHXv4jTriUhwAVPUVVT1cVYer6j1h29MpGTOGM3iTI/sVsDNCs+5777nv03nbxMGIOVnjRjAlfT5vvNE0r7YWjhlfyxNDfgbPPBN74xKAuBUHIwb06cPwAeWs+vrPOOWUptnvvw9ZKRWMyd4MgwfH3j4jsRk7llPLXmX5cmXv3oZZK1bAJ4uTSP7sU6cURrtj4pDorF4NDz4Ysc/hgw/guKxlpBw9un0H5xtGWxg7lsnMQ1WYP79h1vvvu+8T+MC82ihh4pDoZGfz9NPQty8UFNQnFxfDkiXKCWXWpGSExNixTOJjRJR58xpmffAB5GTuY1jaVjj88HDs6+SYOCQ6y5fT+6G7KCiATz6pT16xws0bOKbyQxMHIxyGDqV7Vg3Duu1i2bKGWUuWwITMlchRoyElXgM9dGxMHBIdVcbPuR9oKA4rvUAlo1lh4mCEQ1ISjBnDqJS1dfXR54QT4JzRn8FXvhKObQmASW6ic8QR9E7dR7/UfaxZk12XvHIlpKdUM7R6Ixx1VIgGGgnN2LGM+mQ+r605gepqqXMSHn4Y4Ovex4gG5jkkOmlpMHIkh6dvbhDHa+VKOCJrKynDcyE7u9nTDSOqHH00oyoWUVUlbNjgkioqQKuqDyyWidFmTBwMGDuW6bVPc8YZ9UkrV8Ko2uXWpGSEy9ixjPKCMftNS7/9LXTPrqG07xAXS96ICiYOBkyaxPUjXuMnN5cBUFoKmzbBqOKPTByMcBkzhiNxoat9cVi5EronF5OZWgXduoVoXOfGxMGA66+H+fMpowvl5bBxo0seoWtNHIxw6d6drkP60L/LbvwgpRs2wIikT61uRhkTBwOANWvc4h+zZjmvAWAIm+0GNMJn7FiGsLmuXm7apAwpXWV1M8qYOBgADLnpIlTd4lGbN7u03C47YNiwcA0zjLFjyS1fzeZNSmUlbN8OQ2rNc4g2NpTVACCjbDd9UwrZsqUXxcWQJpXkjOnnxpobRpiMHcsQ/ZTnPlPKy4Xbr93Ll3blwPHHh21Zp8bEwXCMHcug2ZvJ39KTvXthsOSTdPSYsK0yDK9ZaTZV1Uns2wd3/a4HcHXYVnV67LXQcIwdyyDdzJZPK9m8rsrcdiN+OOwwhqRuB2DZMiiY/ylaWhayUZ0fEwfDMXYsl/JXrjl5BZs31ZLLJhMHIz5ISSF3RCoAjz0G/SYNoeqK/wnZqM5P3ImDiNwhIltFZLH3OSdsmxKC0aP52nnV/PdX9/L57gw3UmmMNSsZ8cGQY3oDsHF9NQPYRtr40SFb1PmJO3Hw+K2qjvM+r4RtTEKQkUHVsy/wYcZpAAzsWWbr8hpxQ9aEI+nBbnZtrWQgW82rjQHxKg5GCHz4IXzpS267/2FZ4RpjGEHGjuUQPmfvPqE/200cYkC8jla6TkQuAxYAN6nq7sYHiMhMYCZATk4OeXl5sbUwAsXFxXFhx4FS++c84A633bvqoP6Wjl4W7YmVRT0HWhapRUUcgrC+8jD6pRaSt3YtrFvX/gbGkLivF6oa8w/wFrA8wud8IAdIxnk19wCPt3a9CRMmaDwwe/bssE04KMr//bK6UJeq2x6adVDX6uhl0Z5YWdRzMGXxjYxZ2jdtt87+6TvtZ1CIxEO9ABZoM8/VUDwHVZ3aluNE5DHgpSibY3ikTziKdMqpIJ2+J9rSi0Z8cUhOLWVbUjn1ztPCNiUhiLs+BxHpH9i9EOdRGLFg0CAyqCCdClJGmTgY8UWPfmkU12axc01B6wcbB03ciQNwr4gsE5GlwGnA98M2KGEQ4bDkDQyUbbYurxF37K3uCsCcR1aHbEliEHdPAFW9NGwbEpnktBQOYytgAfeMOEPEfVu8r5hgpWw0IL+mP0npcffOYBhU1brHVWWNhGxJYmBPAaMOVfi8shfbKydTUwPJyWFbZBj1lFW7EBqF+9JDtiQxMM/BqGPvXqglGSWJwsKwrTGMhhRVZADKF3szwjYlITBxMOooCAwC2bEjPDsMIxI3TN9GV/ZRUNMjbFMSAhMHo46gt2DiYMQbJ0yqpj+fU1hizUqxwMTBqMM8ByOeeefdZDIpocCaPGOCiYNRh+853J92CyedFK4thtGY8343lb10p3C3jVaKBSYORh2+5/BfuR8ycGC4thhGkIoKKKlKpzt7KdiXFrY5CYGJg1GH7zks6XIcixeHaophNMCvm73YTWGxiUMsMHEw6igogO7J+7hy1c3cf3/Y1hhGPb449GEnRaWpVFWFa08iYOJg1FFYCL11Fz2qd7K7yQoahhEevjjk8AWA1c8YYOJg1FFYCL1kNz3ZYzefEVccdRS8dtu7jGUpgE3SjAEmDkYdBQXQW3bTU/awZ0/Y1hhGPT17wrRTyhnCZ0DDYddGdLDYSkYdhYUwXHaTQZl5DkZcsWwZrH8hiYG4immeQ/Qxz8Goo6AAeiXt5pa0/+PZZ8O2xjDq+cc/4OJHTqM3zmUwzyH6hCIOIvJ1EVkhIrUiMrFR3m0isl5E1ojItDDsS0RqamDPHuidVcHII2qZPDlsiwyjnoIC6JVRSh8Th5gRluewHPgqMCeYKCKjgG8Ao4GzgIdExAJHx4B9+1zI7h6ZlWzsPo4nn4SSkrCtMgzHnj3QI72MbhQhouzdG7ZFnZ9QxEFVV6nqmghZ5wNPqWqFqm4E1gOTYmtdYlJU5L671xTy4fZcZsyA/PxQTTKMOoqKoHt6OQJ061JVV1+N6BFvHdIDgXmB/XwvrQkiMhOYCZCTk0NeXl7UjWuN4uLiuLDjQNi4MQs4lszdm8jaVQzA228vYvv2A7sLO3JZtDdWFvUcaFnk54+nZ61zF7qklLFmTQF5eZHeLzsO8V4voiYOIvIWcEiErNtV9YWDvb6qPgo8CjBx4kQ99dRTD/aSB01eXh7xYMeBkOZFJOiVXEo2RVAFQ4cew4H+OR25LNobK4t6DrQsnn0Wat8phGuhd69ksrL6c+qp/dvfwBgS7/UiauKgqlMP4LStwKDA/qFemhFlfDe9m+yjh+wBbBaqET8ceSTwhYvG2i2zxpqVYkC8DWV9EfiGiKSLyFBgBPBxyDYlBEFx6OmJg02EM+KFxx6DBW/tAaBbRoWJQwwIayjrhSKSDxwPvCwirwOo6grgGWAl8BpwrarWhGFjohEUh966i0WL4BvfCNcmwwA3iu5//gdefNOtHd0t3cQhFoTSIa2qs4BZzeTdA9wTW4uMOnHonUpKzmjGjw/XHsPwKSlxAtEttRyAbl2qKfosZKMSgHhrVjJCwheHrpm10L8/jz8Ob78drk2GAYEXlzRfHGwoaywwcTAAdwNmZ0NSeSkUFPCTn7iQBYYRNk3EIbOaffugtjZEoxKAeJvnYIREURF06wbs2gXbt5M9yM2aNoywqROH9Ar33cWt9FNc7NVZIyqY52AAAXEAUCU728TBiA+OPhrWroWTv30EAN16uCGt1rQUXUwcDKCROICJgxE3pKfDiBHQtXc64OY5ABZfKcq02KwkIje24RolqvpIO9ljhMTevZ44qAJOHDZvDtcmwwBYtAjeeQf+J2MN2UC31DLAPIdo05rncAvQFchu4XNTNA00YkNjz+GRR+CNN8KzxzB85s6FW26BymUulpKJQ2xorUP6r6r685YOEJGsdrTHCImiIujeHejRA4YP55BIUbEMIwQaj1bqnlnVIN2IDi16Dqr6g9Yu0JZjjPinznNIS4NDDmHOHLj77rCtMgxXN7t0gdQk19fQLaOyLt2IHq12SIvIKSIy1tueLiIPisj3RSQ9+uYZsUDVdT5nZwPl5bBtG3l58JOfQHV12NYZiY4/B8enW6arlNYhHV1a65D+PTAWSBeRtbj+h9eAE4HHgW9G3UIj6pSVOYHo2hV3x330Ednnu7ziYtfSZBhhUVLi1U2PrPTqunQjerTW53Caqo4SkQxc6Ox+qlojIo8AS6NvnhEL/JssK9B75N+M+/aZOBjh8oc/QGkpsOmb8MADpHRJJS3NxCHatNasVA6gquXAZj9CqqoqUBVl24wYUVrqvjMzvQRvEhw4z8EwwqRrV+jXj/oVqXAvMiYO0aU1z6GfN9dBAtt4+32japkRMxqIQ2CeA9hEOCN8HnrIicHlFd7SLlVVJg4xoDVxeAw3l6HxNsAfo2KREXOaeA7A1KlusZ9gR6BhhMGf/gQDBsDlQ5e7hNpaE4cY0KI4qOqd0fhREfk6cAcwEpikqgu89FxgFeCvHD5PVb8TDRuMenxxyMrCqcExx5Ce7sIWGEbYlJQ09GpRNXGIAa2NVnqgpXxV/e4B/u5y4KtApLAbG1R13AFe1zgA/JssMxNISYG+fdm9G375S7joIpg0KVTzjASntLShV4uIiUMMaK1DeqH3yQCOAdZ5n3FAWvOntYyqrlLVNa0facSCBs1KFRWwcSPl5XDffS6ujWGESZ04+J4D1iEdC1prVnoSQESuBk5S1Wpv/w/A3CjZNFREPgGKgB+rasTfEZGZwEyAnJwc8vLyomRO2ykuLo4LO/aXhQtzgJEsW/YRo4qKSHr/fRYufA84iWXL1pOXl7/f1+yoZRENrCzqOZCyKC6eQkHBVvIrtnIosGLFCkpKdrJjRyZ5efOjYmcsiPt6oaqtfnB9AL0C+z2BNa2c8xau+ajx5/zAMXnAxMB+OtDb254AbAG6tWbfhAkTNB6YPXt22CYcEI88ogqqW7eqalaWamqqVlS4tLvvPrBrdtSyiAZWFvUcSFlUVqqWl6vqihWuUv7zn3rppapDhrS3dbElHuoFsECbea62dSW4XwGfiMhs3DDWk3Edyi2JztQ2Xjt4TgVQ4W0vFJENwOHAgv29ltF2Ik2CS02F5GQ3e9owwiQ11dsQqUvLyqpvDjWiQ5sW+1HVPwOTgVnAv4Hj1Wtyak9EpK+IJHvbw4ARwKft/TtGQyLNcxBxwc5MHIwwKSqCa6+F998H/CYYG8oaE1obrXSIqn4O4H2/0NIxbUVELgR+h5tI97KILFbVaTiP5OciUgXUAt9R1cL9ubax/5SWukFKdW9oHrt3u3TDCIvdu90kuAkT4MTly+vSfc+hthaSbD3LqNDarf8KbpTSwR7TAFWdhfNCGqc/Bzy3P9cyDp4GQwW7dIFzzgFMGIzwiTRB05/nAM6zzbIVZaJCa7f/0SLSUtR0wY0qMjowpaWBGywpCfr0Adx6Dj17OrfeMMIgUn9YUBxKSkwcokVrQ1mTY2WIER51M1ABKith5UoAXnjBBTwzcTDCIlJ/GKp19dX6HaKHtdYZDZuVKiq83j/rkDbCp7LSBWPNzKQ+KqsqXbq4zfLy0Ezr9Jg4GE3DE3hkZtpwQSNcpk517yvHHQd814vWo0pGhts0cYgeJg5GQ3Fw04wA5zmYOBjxgAj18xzMc4gJbVlDOllEVsfCGCMcmuvU69Gj6fBWw4glb70FM2Z460X/5z8uMeA5WLNn9GhVHNSt/rZGRAbHwB4jBJprVvrzn2HhwtjbYxg+y5bBk/50W2+ghHkOsaGtI9l7AitE5GOgbnyAqp4XFauMmNJAHNLS4JJLQrXHMHyam+dgnkP0aas4/CSqVhih0sRz6NEDgGeegVmz4J//DMUsw4g8e988h5jQ1thK7wKbgFRvez5gkf47CQ0mwVVXw3wXBnn1anjqKaipCc82I7FpMljCwzyH6NMmcRCRbwPPUr9y20Dg+SjZZMQQVXcD+m9iVFc3mOcAdgMa4ZGa6taPBuoXNDfPISa0dSjrtcCJeKEyVHUd0C9aRhmxo7LSfftvYkH8tIqK2NljGEHuvRdWrfJ2vv999219DjGhreJQoaqV/o6IpADawvFGB8F/8KenewmBEAV+momDERcE5jnYJLjo01ZxeFdEfgR0EZEzgH8B/4meWUasaCIOPqr06AEDB1qfgxEed98NN97o7fzjH+5blZQU11Ft4hA92ioOPwR2AsuA/8GF6f5xtIwyYod/czURB2D6dMjPh0GDYmuTYfi8/z7M9VeRX7PGfQdm8FuzUvRo61DW04C/qepj7fGjInIfcC5QCWwA/ltV93h5twFXAjXAd1X19fb4TSMyvudQ1+eQlATXXddgSUbDCIuKigj9YZ44ZGSY5xBN2uo5XAYsEZF5InKfiJwrIj0P4nffBI5S1bHAWuA2ABEZBXwDGA2cBTzkLxtqRIeIzUpZWSDCokVw9tn1E1MNI9ZUVETuDwPzHKJNW+c5XK6qhwNfBbYAv8c1Mx0QqvqGqlZ7u/OAQ73t84GnVLVCVTcC64FJB/o7Rus0EYeaGpgzB2pq2LMHXnsNdh7wf9owDo6WxME8h+jSpmYlEfkWMAUYA+wCHgTmtnhS27kCeNrbHogTC598Ly2STTOBmQA5OTnk+YuPh0hxcXFc2LE/LF/eDTiG1auX0K3bbk6urSXpww959513WLG6N3AMH3+8BNXd+3XdjlgW0cLKop79LYvU1DEkJ1eQl7eWYWVlDAbWrV3L1rw8amomsmVLOXl5y1u9TjwS9/VCVVv94AThI+C/gdw2nvMWsDzC5/zAMbfj1pIWb/9B4FuB/D8BF7X2WxMmTNB4YPbs2WGbsN+8846L0V1nuohLKC/X+fPd5osv7v91O2JZRAsri3oOqix27XIV8v/+T1VVJ09WnTatfewKg3ioF8ACbea52ibPQVX7iMho4GTgHhEZAaxR1UtbOGdqS9cUkRnAV4DTPSMBtgLBsTGHemlGlGjSIe1j8xyMeCMwzwGszyHatDV8RjdgMDAEyAW6A7UH+qMichbwA+A8VQ0uJ/Mi8A0RSReRocAI4OMD/R2jdVqaBNe1KxxxROTZ04YRCy68EH73O2/n4Yfdt1dH09PtxSWatHUo63uBz4Oqmn+Qv/sgkA68Ke5tYJ6qfkdVV4jIM8BKoBq4Vt16EkaUaHaegypDh7rge4YRFu+8A0OGeDvr17tvTxzS0urDvxjtT1ublcYCiEjX9vhRVT2shbx7gHva43eM1ok4lPVHPwpE4jOM8GgwWsnHxCEmtLVZ6SgR+QRYAawUkYUiclR0TTNiQYM+B79JKTUVRCgpgZNPtvUcjHBQbXkoq4lDdGnrJLhHgRtVdYiqDgZu8tKMDk6DZiX/5nv1VSgvJynJhS7YvDk084wExn/wm+cQDm0VhyxVne3vqGoeEGFJeqOj0aBZyReHjz+GykobrWSESk0NjB/vgj8CMNhbxt7EISa0VRw+FZGfiEiu9/kx8Gk0DTNiQ0tRWZOSXAuTzUI1wiAzExYtghkzvIQf/KBBvolDdGmrOFwB9AX+DTwH9PHSjA5ORYUbPp6aSoNlGIMhCsxzMOKCRvMcTByiS4viICIZInIDcBeuM3qyqk5Q1Rt0f+MpGHFJebnzGkSIKA6TJwfcesOIIVu2wMSJrgsMgF/+0n2bOMSE1oayPglU4eIonQ2MBG6Isk1GDIk4GiQpqW77zTfDscsw9u2DhQvdN1A/MsLEISa0Jg6jVHUMgIj8CZut3OmIKA533QW9eoVmk2FAyxM0wYmDquu4TrbA/u1Oa30OVf6G1ofYNjoREcUhsNDPRRfVr+tuGLGkyWCJWi9iT0AcwLyHaNGaOBwtIkXeZx8w1t8WkaJYGGhEl4ji8Nxzdb78hg31UQsMI5a0NJIOTByiTYvNSqpqzlonp6qq/iarE4eFC51Pn51NaipUm89ohEB2tpuhX9fCeeSR7tvEISa0dSir0UmpqoIU/xUhwmil1FR3jGHEmgkT4N134eijvYTbbnPfJg4xwcQhwamq8uY4QLPiYJ6DERdEmOcAJg7RwsQhwamubtlzmDjRhTAwjFjz+uuuJWnNGi/hllvct4lDTGjreg5GJyWi5xAI1/3rX8feJsMA2LPHCUONv6LL9u3u28QhJoTiOYjIfSKyWkSWisgsEenhpeeKSJmILPY+fwjDvkSiujqCONx9NxxySGg2GQbU93U1qZ8mDjEhrGalN4GjvEWE1gK3BfI2qOo47/OdcMxLHCJ2SAfmOVxzDUybFnu7DMPEIVxCEQdVfSMwqW4ecGgYdhjNNCs9+SQUFACwaxd89lk4thmJjT8QosnLS2CwBJg4RIt46HO4Ang6sD/UW3WuCPixqs6NdJKIzARmAuTk5JCXlxdtO1uluLg4LuzYH/bsmUh6ejl5ectJKSriJIAlS/jw7bep6NePwsKRFBV1Iy/vo/26bkcsi2hhZVHP/pRFYWEvJk8eyCefrGL9+moG9ezJMOCzTZvYmJfH8uXdgGOYP38JHTEOaNzXC1WNygd4C1ge4XN+4JjbgVmAePvpQG9vewKwBejW2m9NmDBB44HZs2eHbcJ+M2qU6te+5u3s2qXq3stUN29WVdXLL1cdPHj/r9sRyyJaWFnUc9BlkZys+qMfqarqxx+7qvrSSwdvVxjEQ70AFmgzz9WoeQ6qOrWlfBGZAXwFON0zElWtACq87YUisgE4HFgQLTsTnQYd0kFsnoMRjwT6w6zPIbqENVrpLOAHwHmqWhpI7ysiyd72MGAEtuJcVGlthvQxx1iHtBEODz4Ihx4aWInwqqvcuFbrkI4JYfU5PIhrQnpT3JvAPHUjk04Gfi4iVUAt8B1VLQzJxoQgYod0z551MZCvvtp9DCPW7NkDW7cGXl4KC/1GT8DEIdqEIg6qelgz6c/hliE1YkTEeQ533QWDBoVmU2tUVVWRn59PeQdZ3Lp79+6sWrUqbDPaREZGBoceeiipEdsaY4s/lLVurYbaWtesZOIQE+JhtJIRIq3Nc7j7bnj4YfcGFy/k5+eTnZ1Nbm4uErA1Xtm3bx/Z2dlhm9EqqkpBQQH5+fkMHTo0bHPq6mbdv9jmOcQUi62U4ERsVvr972HbNsC1937+eTi2NUd5eTm9e/fuEMLQkRARevfuHTceWZPBEjbPIaaYOCQ4EQPvrVwJpW6cQEqK8+b9RbjiBROG6BBP5Tp2LEyfHkg4+WTXxuTVU7/e2mi66GDikOC0JWQ32A1oxJ5vfQueeCKQcPPN9QtHY+IQbUwcEpyIHdKBbT/PFvxpyAknnBAxfcaMGTz77LMHdM077riDX1sY3JYJdEibOEQXE4cExh8yHnGeg9eONGYMXH45JFlNacAHH3wQtgmdnmuugZEjAwlf+xqUlZk4xAgbrZTANBv1sn//uqEgZ5/tPnHLDTfA4sXte81x4+D++1s8pGvXrhQXF6OqXH/99bz55psMGjSItLoFuWHhwoXceOONFBUV0a9fP5544gn69+/PY489xqOPPkplZSWHHXYYf/3rX8nMzGzfv6ETUFwcmAAHThigrp4mJbmPiUN0sPfBBKbZqJd33QXDhoViU0dj1qxZrFmzhpUrV/KXv/ylzqOoqqri+uuv59lnn2XOnDlcccUV3H777QB89atfZf78+SxZsoSRI0fypz/9Kcw/IW5pbbQSuLpr4hAdzHNIYJr1HAIjVp58EmbOhPXr43ReXCtv+NFmzpw5XHLJJSQnJzNgwAC+9KUvAbBmzRqWL1/OGWecQW1tLapK//79AVi+fDk//vGP2bNnD8XFxUyz+CQRaTAHB1z9DPQ5gIlDNDFxSGD8m6qJOPzyl3DqqXXeQ2WldUjvL6rK6NGj+fDDD5tMgpsxYwbPP/88Rx99NE888UR8h20OkQYj6cA8hxhjzUoJjP/Ab9KstH593TwHG8raMieffDJPP/00NTU1bN++ndmzZwNwxBFHsHPnTj788EPANTOtWLECcDOm+/fvT1VVFX//+99Dsz3eOeMMuOiiQMI55zQYygomDtHEPIcEptlmpcC2LxzmOUTmwgsv5J133mHUqFEMHjyY448/HoC0tDSeffZZvvvd77J7925qa2u54YYbGD16NHfddReTJ0+mb9++TJ48mX379oX8V8Qn117bKOF734Of/9zEIUaYOCQwzTYrBbZtnkNkiouLATej+MEHH4x4zLhx45gzZ06TZqWrr76aqyOEur3jjjuiYmtHxe9iaJAQ/MbEIZpYs1IC02yzUmB7+HD3BterV2xtM4xTTgGvf98xdSoUFZk4xAjzHBKYJs1KPsOHQ5cugItv08yLsWFElaoqyMgIJARfXjxMHKJHaJ6DiNwlIktFZLGIvCEiA7x0EZEHRGS9l39MWDZ2dpqd53DHHXD44XVJVVXxF3jP6Pw0CAoJNpQ1xoTZrHSfqo5V1XHAS8BPvfSzccuDjgBmAg+HY17n5aab4MUX2zbPYe5cN0AkLw/efNM1MUV4gTOMduGtt9zKg/5LSVuHspaUwCWXuIDCRvsQmjioalFgNwvw/+PnA39Rxzygh4j0j7mBnZQVK+A3v4Hzz2+hQ/q22+rusuBopbPPhocego8+iq3NRuJwxhnwhz+4iCgRPYfgN/Xi8OKL8NRT8O1vx9TcTk2ofQ4icg9wGbAXOM1LHghsCRyW76Vtb3TuTJxnQU5OTlxMJCouLo4LO1rizTf7AaMA+PjjT4DxLF++mLS0PWR+9hmTALZsYcHcuRTv2MHq1dnABBYtWsq0aX155ZX+PPPMGsrLtzf/I0S3LLp3796hhn/W1NR0KHvLy8uj9r9rrV5MmTKauXP78q9/reLEE9Po2bOSvLwvABgwfjxDFyxg59atrPWuUVY2gc8/r+Tll4uBIezYsY+8vIVRsb29ifvnhapG7QO8BSyP8Dm/0XG3AXd62y8BJwXy3gYmtvQ7EyZM0Hhg9uzZYZvQKnfe6a/QrvrMM+57zhwvc+XK+sz581VVddEitztrlmp1tWpamuott7T+O9Esi5UrV0bt2tGgqKgobBP2i2iWb2v1orjY1bdf/rKZA/r3V73qqrrdSZNUp01TnTHDnde9u2ptbbuZG1Xi4XkBLNBmnqtR9RxUdWobD/078ArwM2ArEIzic6iXZrQDwbWgP/vMfUec5+D1QPt5ZWUuQubUqdCtW/TtNBKP6mpIT3cLvvXsCfv2uf6u9HTvgNJS/9Wl7hy/Wclb1Za9e915VkcPntCalURkhKqu83bPB1Z72y8C14nIU8BkYK+qttyGYbSZwsL6bf+GammeQ79+cOutThy6doWXXoIvfzk2traZU09tmjZ9ulsQoLTUhV1ozIwZ7rNrV6MYDbjedyPmvPMOTJsG770HJ57oIsefey48+qh3wJlnwu7dEcUhWK937jRxaA/CHK30KxFZLiJLgTOB73nprwCfAuuBx4BrQrKvU1JYWP8mtmeP+05O9jL9m27MmLq7q18/+NWvIDfXZWVlxcpSI9HYvdt99+jhvmtqAnUTInZIJye744qK6s/buTPaliYGoXkOqvq1ZtIVaBxVxWgnCgthyBBYu7YFcfjpT+uW4Kqpca76rl0u66GH4Ec/grhaCK2lN/3MzJbz+/QxTyFO8N/+b7kFund3LZttEYeKCteUNHw4LFwIX3wRO5s7MxY+I8HwxQHcQx8CS4BGmOeQnw+9e8Mjj7j96mp3AxpGe+OLQ3U1rFnjXkwaLE8bYRJcUpI7bt+++nrteyDGwWHikGAExaFZz+Gaa+oUwL85fSEZMMCt71BZGRNzjQRi927n6PXp4x72bfUcKitdn9iAAS6tA40ajmsstlICUVnp1uX1V3Rr1nPYsaNu8V7/5jz6aNdZ2L2729+3z3kUhtFenHKKG/SwfburXz/8IYwfHzjgqqvcBM1GnkORN53WxKF9Mc8hgfDd7T593E3YrOcQ2PaFY+JEuOce6NvX7dsNaLQ3557rwnplZ7v6ddttcNZZgQOuusplNvIc/JecPn3c0Gurm+2DiUMC4bfp9uzpol16i7019RwC275wFBY6h2LoUOdBJFnNMdqZnTtd89CYMW7U6rZtjR70O3e6tqZGnkNJidvOyKgXFuPgsVs8gfA9h8bi0JLnkJUFd98NL78MRxzhphS89hoMHhwzs40E4Utfgm9+Ey6/HGbNcn1jv/pV4IBzznEC0chzKCtz2yYO7YuJQwLhv2F17RqYdUoEcTjuuLoOhcxMuP129zYXPMcw2puSElc3fSKOVgp+0zA/Pd3EoT0xcUgg/DeszMyGD/omTUS33w6jRwPOi9+82TUppafDunXOa3jxxdjYbCQOZWWubv75z3DIIU4DIo5WChDMN3FoX2y0UgLhNyM1FoeIzUoeZWX1s6NHjHAdflu21E+KM4z2orTU1c3KyvqJbG2Z5+Dji4M/0MI4OMxzSCB8cejSpRnPwb/pvvlNF+CGyDcf2NuZ0f744hDxxQWanefgY55D+2LikEC02XMoKqqb5ebnHXusW0HOxOHgyc3NZZfnep1wwgkHdI3777+fUv8fCpxzzjns6cCvzKrwi1+4kXB+3bzqKjj99MBBN97oJtpYn0NMMHFIIILiEFy4PeJQVi9kt5937rkuiGlamvvYDehQVWoPYoHtDw4wSFVjcXjllVfo4Uee64CIuJhKU6bUi8N117mxEXVceqkLCNmM52CjldoX63NIIJprVmppKKuf9+mnbtz5gAFurV6vvzp0brjBLSnZnowbB/ff33z+pk2bmDZtGpMnT2bhwoVMnz6dl156iYqKCi688ELuvPNOAC644AK2bNlCaWkp3//+95k5c2aTa3Xt2pXi4mK2b9/OxRdfTFFREdXV1Tz88MNMmTKFq6++mvnz51NWVsZFF13EnXfeyQMPPMC2bds47bTT6NOnD7NnzyY3N5cFCxbQp08ffvOb3/D4448DcNVVV3HDDTewadMmzj77bE466SQ++OADBg4cyAsvvECXLl3at/AOkKoqN/DhkEPcENaLL3b1bfBgN/QagI0bXeClNngOfveEceCY55BAlJa6t6ukpFb6HALbIu5B+cQTzs0Ht33ZZTEwOI5Zt24d11xzDb/97W/ZunUrH3/8MYsXL2bhwoXMmTMHgMcff5yFCxfy7rvv8sADD1BQUNDs9f7xj38wbdo0Fi9ezJIlSxg3bhwA99xzDwsWLGDp0qW8++67LF26lO9+97sMGDCA2bNnM3v27AbXWbhwIX/+85/56KOPmDdvHo899hiffPJJnc3XXnstK1asoEePHjz33HPRKZwD4LPP3ICHf/8bJkxwgR7POcfVtTrOPdf1VLfQ55CZ6ZzeqqqYmd5pMc8hgfA7/KAVz+H0091KKx7f+x786U/xOc+hpTf8aDJkyBCOO+44br75Zt544w3Ge0GAiouLWbduHSeffDIPPPAAs2bNora2li1btrBu3Tp6NxOQ6thjj+WKK66gqqqKCy64oE4cnnnmGR599FGqq6vZvn07K1euZOzYsc3a9d5773HhhReS5S288dWvfpW5c+dy3nnnMXTo0LrrTpgwgU2bNrVbeRwswSZPcHMcIMIw61ZGK/nNpRUVrvnTOHBC8RxE5C4RWSoii0XkDREZ4KWfKiJ7vfTFIvLTMOzrrDQnDk08h1tvdbPePFascG92/s120kmuaSmR8R++qsptt93G4sWLWbx4MevXr+fKK68kLy+Pt956iw8//JAPPviA8ePHU+4FM4zEySefzJw5cxg4cCAzZszgL3/5Cxs3buTXv/41b7/9NkuXLuXLX/5yi9dojfTAPz05OZnq6uoDvlZ7ExSHhQvrgzruz2il4JKiB1FMhkdYzUr3qepYVR0HvAQERWCuqo7zPj8Px7zOiT/JCBreVE08h0aNtRMnuuBm/nKiFRX1wc4SnWnTpvH4449TXFwMwNatW9mxYwd79+6lZ8+eZGZmsnbtWubNm9fidTZv3kxOTg7f/va3ueqqq1i0aBFFRUVkZWXRvXt3vvjiC1599dW647Ozs9kXoed1ypQpPP/885SWllJSUsKsWbOYMmVK+/7RUaCx5+CzPzOkU1LqxaGiov1tTDRCaVZS1aLAbhbQdPaV0e4EPYeUwH++iedwzjnwn/+4cYWBfP+cjAy7+XzOPPNMVq1axfHHHw+4Dua//e1vnHXWWfzhD39g5MiRDB8+nOMaDLtpSl5eHvfddx+pqal07dqVv/zlLwwdOpTx48dz5JFHMmjQIE488cS642fOnMlZZ51V1/fgc8wxxzBjxgwmTZoEuA7p8ePHx1UTUiSC4hCsm008h0bNSsH8lJT6ZiXzHNoBVQ3lA9wDbAGWA329tFOBAmAJ8Cowui3XmjBhgsYDs2fPDtuEFpk6VfWEE9z29dergqpI4IC8PJcIqi+/XJecna2ak6P6zjtu//TTVU88seXfimZZrFy5MmrXjgZFRUVhm7BfRLN8m6sXGzeq/v73qjt2qC5b5qrg1KmqK1YEDnr6adVhw1TPO68u6aab6qtsVZU7BFSXL4/an9BuxMPzAligzTxXo+Y5iMhbwCERsm5X1RdU9XbgdhG5DbgO+BmwCBiiqsUicg7wPDCimevPBGYC5OTkkBcH6wAXFxfHhR3NsX37eNLTa8nLW8L27cOBQSQl1ZKX50bX9Fi8mHHesUuXLKHQczNqa0/ixBM/R2Q9eXlQUjKGwsI08vKaXy80mmXRvXv3iE0q8UpNTU2Hsre8vDxq/7uW6sWoUa5/a/PmTGASxx+/kh07drBjh3dAv35MSEqiYtculnvX2Lp1GOBCBM+dm8e6db2BMbz33gJ27iyOyt/QXsT78yI0z8H/4P6zy5vJ2wT0ae0a5jm0jXHjVM89123ffLN7w0pLCxzwzjv1r2H/+U9dcq9eqiedpPrZZ27/d79TvfPOln/LPId6zHOop7l68fnnqosXu7f/zz9Xvewy50ns2hU4aNky1VGjVL/ylbqkH/7QVdekJLf/2mtu//33o/YntBvx8LygBc8hrNFKQW/gfGC1l36IiOsNFZFJuA7z5geHG/tFpD6HZqNeBrZ/9zsXaunee93+ddfBT20cmdGO/O1vbvJhaSnk5MBPfgLXXguvvBI46MIL3RqiEfoc/G/rc2g/whqt9CsRWS4iS4Ezge956RcBy0VkCfAA8A1P3Yx2oKzMzY6G+psp4miQCy5w01Q9/uu/XNSCoJAcRMQIw2iCH07er5/+PIcGLy/QbIe0/7Jjo5Xaj7BGK32tmfQHgQdjbE7CUFlZP1fBv5kiisONN0JgotXChS4Wn38jXncdPPMM9W3BhnGQeHEeSUlxYTOOPNLtt3Uoq/9tnkP7YeEzEoiqKrceA0R4I4P6m66mpoFrcMEF7tsXlJQUezMz2he/boo0MwcHWpwE50/NMc+h/TBxSCCCnoN/U0VstDvtNHjhhbrdSO269mZmtCdVVU29WmhmnkMA32Pwk4PhM4yDw8QhgQh6Dv4N2EAcmumQTkpy502f7vYzMpzQWG+Q0V5ccgn88Y9uO7iGyLHHBg66/37o16/ZSXBg4TPaEwu8l0AE384ieg7NiENyMnz96240CTR03YPrQoTFqac2TZs+Ha65xo1+OeecpvkzZrjPrl1w0UUN8+J56HlnZcIE94H6F5fp02HQoMBB553nVgSK0OdgzUrtj3kOCYLfjdDYc2hAM+IgAm+/7YLvgVuA5aabomerkXisXg0ff+y209JcePh9+6CwMHDQhx86l6CFPgfrkG4/zHNIEPz49o07pNviOdx3n+uU/sc/4Ic/dF0Sp50WVXP3i5be9DMzW87v08c8hXjgF7+AuXPdej5paXDFFXDCCXD88XDWWd5B06c7l6Bv37rzzHOIHuY5JAi+ODTu9IsoDpdeCkccUZfsr+Prn1NT497q/LHohnGwBJs8oT7qb5OhrM3Mc/DFISXFpZnncPCYOCQI/jjyxp5Dg8ls/k133XUN5jnMndvwnKeecpPiNmyInr1GYlFZWV83Ac4+231HXOqzUZMnNF0RzjyHg8fEIUFoznNosN6Lf9MVFTW4u/zlQYMhu8FuQKP9CI6ka5YInoNPUBxsqHX7YOLQyfE9hv3yHM44A2bNqkv2BcQ/x4YLGu1NcA5Os7RRHIKeg6qtJ32gmDh0Yh5+GLKyYNOmph3S+zNaqXt3d54/JLSx57B7N6xc2a6mGwlASQn4i9vdcYcb+BDk8MPrh08D8OSTMGBARHEI1ufgYlTf/CaMHGlzcg4EE4dOzG9/6976X3mlabNSi+EzGm1nZMBXvgK5uQ2v4d+AX/4yXHllu5puJADf/jbcdpvbPu44OPnk+rxu3dzLSGBgkvNos7Nb9RzS0lzdrK2Ff/7T9Y0tXx6dv6EzY+LQifEjXa5b17RZaX88h5ISePFFyM93+7m58LOfue9PPnHNS2vWtLf1LWPBeqNDrMp15Ur49FNYv95VtblzYf78+vzvfMfV2Z07Aye98YarjK14Dqmp7mVo27b6tNWr2/9v6OyYOHRSqqvrb46NGw/Oc/jpT92wVX8+wODBrhlg+HD4zW+cQOze7Ya3xoKMjAwKCgpMINoZVaWgoICMGEx7v/9++Ogj96zfuRNuuAHuvLM+/7zz4KGHYPHiwEnf+par1K14Dqmprv4Hl832J3AabccmwXVStm+v72wuLNxPz+Haa+Hoo+uSJ09ueE51tQvX3aMHFASWYtqyxS31GG0OPfRQ8vPz2dngtTJ+KS8vj8kDtz3IyMjg0EMPjfrvbNlSv+3Xz2CH9BdfRDiphQ7pYH1OSXEvQ8G6aeKw/5g4dFL856aIu/mamyHdAP+mmzkTxoypS379dfftT0haswaOOsqt6VBY6NJra12coliQmprK0KFDY/Nj7UBeXh7jx48P24y4YufO+nrj18/gUNavRVzxxSOCOAQny/nNSn7oDZHY1c3OROjNSiJyk4ioiPTx9kVEHhCR9SKyVESOCdvGjoj/1jRiRENx8N/OWpxctH07FNcvzn7jjQ3PCXoQhYUu8N3f/95gUrVhtEhBAUyd6iZUjhjRdIZ0RFrwHBqLQ3V103vA2D9CFQcRGYRbJjTo9J0NjPA+M4GHQzCtwxO8MQoKmjYrRcS/6c46C559ttnD/Gv4b2dHHumWEs3JOXi7jcSgsNANMb34YjciqfEM6Yi0IA5B/GalwkLnIefmNmxiMtpG2M1KvwV+ALwQSDsf+Iu3dvQ8EekhIv1VdXsoFnZQ/DelYcPcjVdS4vZbvQF9Ajdgbq673imnuH3fc6iqgn//24XYf/dd6N/fjU03jNZ4/nkX9PCtt9zAhmeecX1YPt26Qe/e9WG8ATdk7tZbG03rdwT1IjXVTfIvKnLX6dPHjYoy9g8Ja8SHiJwPfElVvycim4CJqrpLRF4CfqWq73nHvQ3cqqoLGp0/E+dZABwBxHgwZUT6ANa66bCyqMfKoh4ri3rioSyGqGrfSBlR9RxE5C3gkAhZtwM/wjUpHRCq+ijw6IGeHw1EZIGqTgzbjnjAyqIeK4t6rCzqifeyiKo4qOrUSOkiMgYYCiwR18t5KLBIRCYBW4Hg+k+HemmGYRhGjAilQ1pVl6lqP1XNVdVcIB84RlU/B14ELvNGLR0H7LX+BsMwjNgSdod0JF4BzgHWA6XAf4drzn4RV81cIWNlUY+VRT1WFvXEdVmE1iFtGIZhxC+hT4IzDMMw4g8TB8MwDKMJJg4HgYj0EpE3RWSd992zhWO7iUi+iDwYSxtjRVvKQkTGiciHIrLCC41ycRi2RgMROUtE1nhhX34YIT9dRJ728j8SkdwQzIwJbSiLG0VkpVcH3haRIWHYGQtaK4vAcV/zwgjFzdBWE4eD44fA26o6Anjb22+Ou4A5MbEqHNpSFqXAZao6GjgLuF9EesTOxOggIsnA73GhX0YBl4hI4/i0VwK7VfUwXGSA/42tlbGhjWXxCW7S61jgWeDe2FoZG9pYFohINvA94KPYWtgyJg4Hx/nAk972k8AFkQ4SkQlADvBGbMwKhVbLQlXXquo6b3sbsAOIODuzgzEJWK+qn6pqJfAUrjyCBMvnWeB0kYjhDzs6rZaFqs5W1VJvdx5uLlNnpC31AtyL4/8CcbUqu4nDwZETmIPxOU4AGiAiScD/A26OpWEh0GpZBPEmPKYBG6JtWAwYCARWKCDfS4t4jKpWA3uB3jGxLra0pSyCXAm8GlWLwqPVsvCiTg9S1ZdjaVhbiMd5DnFFKyFA6lBVFZFI44KvAV5R1fyO/qLYDmXhX6c/8FfgclWtbV8rjY6CiHwLmAicErYtYeC9OP4GmBGyKRExcWiF5kKAAIjIF37EWO+BtyPCYccDU0TkGqArkCYixaraUv9EXNIOZYGIdANeBm5X1XlRMjXWtCXki39MvoikAN2BzhhIuk3hb0RkKu6l4hRVrYiRbbGmtbLIBo4C8rwXx0OAF0XkvMaBRsPAmpUOjheBy73ty2kYehwAVf2mqg72woTcjAtH3uGEoQ20WhYikgbMwpVB8wtGdDzmAyNEZKj3N34DVx5BguVzEfCOds4ZqK2WhYiMBx4BzlPViC8RnYQWy0JV96pqn0AYoXm4MgldGMDE4WD5FXCGiKwDpnr7iMhEEfljqJbFnraUxXTgZGCGiCz2PuNCsbYd8foQrgNeB1YBz6jqChH5uYic5x32J6C3iKwHbqTlkW0dljaWxX04L/pfXh1oLKSdgjaWRdxi4TMMwzCMJpjnYBiGYTTBxMEwDMNogomDYRiG0QQTB8MwDKMJJg6GYRhGE0wcjE6JiNQEhssu7ixRUEVkhojsDA6VFpF/ehFOv9/MORd7UUFfip2lRkfHZkgbnZUyVR0XKcMLeCcdOHTH06p6HYCIHAIc60V7jYiqPi0iX9D543sZ7Yh5DkZCICK5Xlz9vwDLgUEicouIzPfeuu8MHHu7iKwVkfe8t/KbvfQ8P96+iPQRkU3edrKI3Be41v946ad65zwrIqtF5O9+JFYROVZEPhCRJSLysYhki8ic4KRA7/ePbuVPewMY6HlHU0Tku1K/VsJT7VeCRqJhnoPRWekiIou97Y3A94ERuGB/80TkTG9/EiC4mDYnAyW4MAfjcPfHImBhK791JbBXVY8VkXTgfRHxw7OPB0YD24D3gRNF5GPgaeBiVZ3vxZsqw82ingHcICKHAxmquqSV3z4PeMn3kkTkaWCoqlZIJ1grwwgPEwejs9KgWcnrc9gcCPZ3pvf5xNvvihOLbGCWv95AG0M7nAmMFZGLvP3u3rUqgY9VNd+71mIgFxeue7uqzgdQ1SIv/1/AT0TkFuAK4In9/JsBlgJ/F5HngecP4HzDAEwcjMSiJLAtwC9V9ZHgASJyQwvnV1PfFJvR6FrXq+rrja51KhCMOFpDC/ecqpaKyJu4BWGmAxNasKU5voyLX3UucLuIjPFi/BjGfmF9Dkai8jpwhYh0BRCRgSLSD7eU6wUi0kXc8o3nBs7ZRP0D+6JG17paRFK9ax0uIlkt/PYaoL+IHOsdn+2F8Qb4I/AAMF9Vd+/PHyRufYBBqjobuBXnwXTdn2sYho95DkZCoqpviMhI4EOvj7gY+JaqLvLa7Zfg1qSYHzjt18AzIjITtyaFzx9xzUWLvA7nnTSzZKz325UicjHwOxHpgutvmAoUq+pCESkC/nwAf1Yy8DcR6Y7zZh5Q1T0HcB3DsKishtESInIH7qH96xj93gAgDzgy0lBbEZkBTPSHsu7HdU8FblbVrxy8lUYiYM1KhhEniMhlwEe4VfKam4NRBpy9P+uFeF7KQ8B+NVMZiY15DoZhGEYTzHMwDMMwmmDiYBiGYTTBxMEwDMNogomDYRiG0QQTB8MwDKMJ/x/VBpG6gQvPugAAAABJRU5ErkJggg==\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Compare frequency response between ideal and Npoints realisation\n", + "fs = 1\n", + "fLim = (-0.5, 0.5)\n", + "dbLim = (-40, 5)\n", + "\n", + "# Calculate frequency response using DTFT\n", + "_, f, HF = dsp.dtft(hIdeal)\n", + "dsp.plot_two_power_spectra(fIdeal - 0.5, np.roll(HFideal, Npoints // 2), 'ideal',\n", + " f, HF, 'realisation',\n", + " fs, fLim, dbLim, showRoll=True)" + ] + }, + { + "cell_type": "markdown", + "id": "ee728eb1", + "metadata": {}, + "source": [ + "# 3 LOFAR filter impulse response (= coefs) and spectrum" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "2b398ab5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ncoefs = 16384\n", + "Symmetrical = True\n" + ] + } + ], + "source": [ + "# LOFAR filter\n", + "Npoints = 1024\n", + "Ntaps = 16\n", + "Ncoefs = Npoints * Ntaps # = len(lofarCoefs)\n", + "lofarCoefs = dsp.read_coefficients_file('../data/Coeffs16384Kaiser-quant.dat')\n", + "lofarCoefs /= np.sum(lofarCoefs)\n", + "if Ncoefs == len(lofarCoefs):\n", + " print('Ncoefs = %d' % Ncoefs)\n", + " print('Symmetrical = %s' % dsp.is_symmetrical(lofarCoefs))\n", + "hLofar, fLofar, HFlofar = dsp.dtft(lofarCoefs)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "66ba1f2b", + "metadata": {}, + "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" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "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": [ + "fs = Npoints\n", + "fLim = (-2, 2)\n", + "dbLim = (-120, 5)\n", + "dsp.plot_spectra(fLofar, HFlofar, fs, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "f5328ae3", + "metadata": {}, + "source": [ + "# 4 Compare LOFAR subband filter with ideal LPF" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "741d2424", + "metadata": {}, + "outputs": [], + "source": [ + "# Ideal LPF\n", + "Nideal = Npoints * Ntaps\n", + "hIdeal, fIdeal, HFideal = dsp.ideal_low_pass_filter(Nideal, Ntaps)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "d2595f67", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DC response: sum(h) = 1.000000\n" + ] + }, + { + "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": [ + "# Compare coefs\n", + "plt.plot(hIdeal,'-r', lofarCoefs, '-g')\n", + "plt.title('Impulse response comparison')\n", + "plt.ylabel('Amplitude')\n", + "plt.xlabel('Sample index')\n", + "plt.legend(['Ideal (aliased sinc)', 'LOFAR'])\n", + "plt.grid(True)\n", + "print('DC response: sum(h) = %f' % np.sum(hIdeal))" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "abdfe51a", + "metadata": {}, + "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": [ + "# Compare frequency response LOFAR filter and ideal LPF\n", + "fs = Npoints\n", + "fLim = (-2, 2)\n", + "dbLim = (-120, 5)\n", + "dsp.plot_two_power_spectra(fIdeal - 0.5, np.roll(HFideal, Nideal // 2), 'ideal',\n", + " fLofar, HFlofar, 'LOFAR',\n", + " fs, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "8bf65780", + "metadata": {}, + "source": [ + "# 5 Compare LOFAR filter and rectangular time window" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "209ae412", + "metadata": {}, + "outputs": [], + "source": [ + "# Rectangular time window yields response of FFT bin, so PFB = FFT without pre filter.\n", + "Nrect = 1024\n", + "rect = np.ones([Nrect]) / Nrect\n", + "\n", + "# Calculate frequency response using DTFT\n", + "Ninterpolate = 40\n", + "Ndtft = Nrect * Ninterpolate\n", + "hRect, fRect, HFrect = dsp.dtft(rect, Ndtft)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "5fa3a246", + "metadata": {}, + "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": [ + "fs = Npoints\n", + "fLim = (-2, 2)\n", + "dbLim = (-120, 5)\n", + "dsp.plot_two_power_spectra(fRect, HFrect, 'rect',\n", + " fLofar, HFlofar, 'LOFAR',\n", + " fs, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1c33fc6b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}