U md# @s dZddlZddlmZddlmZmZzddlm Z Wn e k rXddl m Z YnXddl mZeddjZed d jZed d gd d ggd d gd d gggZed ZejdZedZejeedddddfddZejeedddddfddZeedddddfeZedddddfZeee ejddddfZe e eejeedddfe!eedddfe!ddZ"ed Ze"eedddddfZ#e e#eddedde"eeddddddfZ$e e%e$eddddf&dedd&ddddfkee'e(dddddfeZ)ej*+dZ,ee,eddgZ-eej.e/de,feddgZ0e1dgddge,Z2e/dZ3e4ddD]&Z5de3e5de,e5de3e5<qe/dZ6e4ddD]"Z5e,e5de,e5de6e5<q&e de e7e6dde3dde-dde2dde0ddfddZ8e e8e3dde2e e8e3dde0ddej*+dd Z9edddgdd d!ggZ:edddgdd"d"ggZ:edddgdd"d"ggZ:edddgdd"d"ggZ:ej.ed#de;d fZe4ddD]8Z5e&e:dddfe>e5de,e5de>e5<qe/d%Z?de?d<edddgdd"d"ggZ:eej.e/d&e?fe:ddedddgdd'd"ggZ:eej.e/d&e?fe:dded d"d"gd"d d"gd"d"d ggdd"d"gd"dd"gd"d"dgggZ@ed d d"gd"d d"gd"d"d ggdd"d"gd"dd"gd"d"dgggZ@eej.e/d&e?fdddddfe@jddZAeAeAdddddfZBed dd"gd"d d"gd"d"d ggdd(d"gdd"d"gd"d"dgggZ@eej.e/d&e?fdddddfe@ddZAeAeAdddddfZBeeCe?e?e?fe@dddddfd)ZDe/eDd fZ?d e?d<e/eDdd fZ>e4deDdD]e5de?e5de>e5<qe/eDdd d fZFe@deFdddddf<e@d eFdddddf<e4deDdD]@Z5eEe@d eFe5dddddfeFe5ddddf<qed dd"gd"d d"gd"d"d ggdd(d"gdd"d"gd"d"dgggZGd)ZDed d"gd"d ggdd"gd*dgggZHe/eDdddfZIeHdeIdddddf<eHd eIdddddf<e4deDdD]@Z5eEeHd eIe5dddddfeIe5ddddf<qd)ZDe/eDdfZ?d e?d+<ed d"gd"d ggdd"gd!dgggZJe/eDddfZKe4deDdD]>Z5eEeJdddddf eKe5de?e5deKe5< qXej*+d)dZLe/eDddfZMe4deDdD]>Z5eEeJdddddf eMe5deLe5deMe5< qe/eDdddfZNeJdeNdddddf<eJd eNdddddf<e4deDdD]@Z5eEeJd eNe5dddddfeNe5ddddf< q^d,ZOe/eOd eOZPejQRePZSe eSe ejTjUeSd-d.d/d0dS)1atrying out VAR filtering and multidimensional fft Note: second half is copy and paste and does not run as script incomplete definitions of variables, some I created in shell Created on Thu Jan 07 12:23:40 2010 Author: josef-pktd update 2010-10-22 2 arrays were not defined, copied from fft_filter.log.py but I did not check what the results are. Runs now without raising exception N) assert_equal)signalstats) _centered)fftconvolveinv()<)r g?g?)rr r rvalidmodec Csbt|}t|}|jdkr.|dddf}|jdkr@td|jd}|jd}|d}|jdkrtj||dddfddS|jdkrt|jdkrtj||ddSt|jd|d|f}t |D]8}tj|dd|f|dd|fdd|dd|f<q|S|jdkr^t|dddddf|}||| |jddddf}|SdS) a0apply an autoregressive filter to a series x x can be 2d, a can be 1d, 2d, or 3d Parameters ---------- x : array_like data array, 1d or 2d, if 2d then observations in rows a : array_like autoregressive filter coefficients, ar lag polynomial see Notes Returns ------- y : ndarray, 2d filtered array, number of columns determined by x and a Notes ----- In general form this uses the linear filter :: y = a(L)x where x : nobs, nvars a : nlags, nvars, npoly Depending on the shape and dimension of a this uses different Lag polynomial arrays case 1 : a is 1d or (nlags,1) one lag polynomial is applied to all variables (columns of x) case 2 : a is 2d, (nlags, nvars) each series is independently filtered with its own lag polynomial, uses loop over nvar case 3 : a is 3d, (nlags, nvars, npoly) the ith column of the output array is given by the linear filter defined by the 2d array a[:,:,i], i.e. :: y[:,i] = a(.,.,i)(L) * x y[t,i] = sum_p sum_j a(p,j,i)*x(t-p,j) for p = 0,...nlags-1, j = 0,...nvars-1, for all t >= nlags Note: maybe convert to axis=1, Not TODO: initial conditions rNrzx array has to be 1d or 2drr r r ) npZasarrayndim ValueErrorshaperconvolveminzerosrange) xaZnvarnlagsntrimresultiyfyvalidr a/home/sam/Atlas/atlas_env/lib/python3.8/site-packages/statsmodels/sandbox/tsa/try_var_convolve.pyarfilter7s,4         6 "r"igdg?z< compare: errloop - arloop - fft - lfilter - fftp (padded)cCstt||S)N)rmaxabs)ryr r r!maxabssr,r g?g)rr )r%r ) r )r$r gg?r-g)rr gBi?g?gףp= C@)locscale)V__doc__numpyrZ numpy.testingrZscipyrrZscipy.signal._signaltoolsrZ trim_centered ImportErrorZscipy.signal.signaltoolsZ#statsmodels.tsa.filters.filtertoolsrZ fftconvolveZarangeZreshapeTrarrayZa3fZonesrrrrZy0y1rr+rprintZravelr"Zy0arZyresallsumZastypefloatZyffrandomZrandnZrvsZar1fftZr_rZar1fftpZlfilterZar1lfZar1rrZerrar1Z column_stackr,Zrvs3Za3neyeZa3neZar13fftZar13impZa3n3ZtttZgfttZdstackZnobsdotZa3n3invZa3n3syrZa2n3invZa2Zar12uZar12rZa2invZnbinsZbinProbadd accumulateZ binSumProbgammaZppfr r r r!s:    """Z  F" $ $  .   6 ""  6 4*:>  > <<>