DUfddlmZddlZddlZdZejd dZej d dZ d d Z dd Z dS))IterableNc tjd5tjtjtj|tj|tj|}dddn #1swxYwY|S)a  Interpolate a function in the log-log space. Equivalent to np.exp(np.interp(np.log(xs), np.log(xp), np.log(fp))). Parameters ---------- xs : array-like The x-coordinates at which to evaluate the interpolated values. xp : 1-D sequence of floats The x-coordinates of the data points, must be increasing. fp : 1D array The y-coordinates of the data points, same length as xp. Returns ------- ys : 1D array The interpolated values, same shape as x. ignore)divideN)nperrstateexpinterplog)xsxpfpyss a/var/www/html/software/conda/lib/python3.11/site-packages/cooltools/sandbox/expected_smoothing.py _log_interprs& H % % %  V Ir r r                     IsABBB皙?c |dg}|d}d|z}|ddD]"}|||zkr|||}#|d|dkr||dtj|S)a Thin out a sorted array, by selecting a subset of elements that are uniformly spaced in log-space. Parameters ---------- xs : array-like An array of elements to thin out. min_log10_step : float, optional The minimal log10 ratio between consecutive elements in the output, by default 0.1 Returns ------- xs_thinned : array-like A subset of elements from xs, whose logs are approx. uniformly spaced. r N)appendrarray)r min_log10_step xs_thinnedprev min_ratioxs r _log_thinr&s"Q%J a5DN"I V ti     a D"~B"R&!!! 8J  rc|}|rt|||z }|j}|jd}tj|}tj|} tj||f} t |D]} | | } tj|| ||zz } tj|| ||zz}tj| || |z dz dz |z |z }| }|dkr=||z}t |D](}tj ||| |f|z| || f<)|| fS)Nr) rsizeshaperlog10zerosrange searchsortedr sum)r r sigma_log10 window_sigmapoints_per_sigmarNN_FUNCSlog_xslog_thinned_xs ys_smoothedi cur_log_xlohismooth_weightsnormks r_log_smooth_numbar9DslJCr;1A#ABB AhqkG Xb\\FXj))N(GQ<((K 1XX J J"1% _VY|1K%K L L _VY|1K%K L L6"R%=(Q. /! 3k AK O  !!## !88 d "N7^^ J J$&F2aBh<.+H$I$I AqD!! { ""rctjtj|}jdkrtd|jdvrtdjd|jdkrtd|jdkr|tjddfn|}t ||||\}|r!tjfd |D}|jddkr|dn|}|S) a1 Convolve a function or multiple functions with a gaussian kernel in the log space. Parameters ---------- xs : 1D array The x-coordinates (function arguments) of the data points, must be increasing. ys : 1D or 2D array The y-coordinates (function values) of the data points. If 2D, rows correspond to multiple functions, columns correspond to different points. sigma_log10 : float, optional The standard deviation of the smoothing Gaussian kernel, applied over log10(xs), by default 0.1 window_sigma : int, optional Width of the smoothing window, expressed in sigmas, by default 5 points_per_sigma : int, optional If provided, smoothing is done only for `points_per_sigma` points per sigma and the rest of the values are interpolated (this results in a major speed-up). By default 10 Returns ------- xs_thinned : 1D array The subset of arguments, uniformly spaced in log-space. ys_smoothed : 1D or 2D array The gaussian-smoothed function values. rzxs must be a 1D vector)rr"z3ys must be either a 1D vector or a "tall" 2D matrixrrz3xs and ys must have the same number of observationsNc2g|]}t|S)r).0ys_rowr rs r zlog_smooth..s% K K KV[Z 0 0 K K Kr)rasarrayndim ValueErrorr$newaxisr9)r rr*r+r,r1rs` @r log_smoothrDjsB BB BB w!||1222 wfNOOO x{bhrl""NOOO gllBJM  B/ B \+;J  j K K K K K{ K K K  %'HQK1$4$4+a..+K rc||d|dd|ddi}t||djt j||djt j||djt jg|||\}}|||d|z<|||d|z<||d|z||d|zz ||d|z<|S)Ndistn_pixelsr) n_contacts)r*r+r, output_prefix)groupbyagg reset_indexrDvaluesastyperfloat64) cvdr*r+r,colssuffix cvd_smoothedsmoothed_balanced_sumsmoothed_n_valids r_smooth_cvd_grouprWsJ DL!! Z %\"E   /9T&\")00<< l+ , 3 : :2: F F j) * 1 8 8 D D  !) / / /++/?Lj!F*+0ELl#f,-T,'&01 tJ'&0 1 2o&/0 r)r)rr r)NrE) collections.abcrnumpyrnumbarnjitrr9rDrWr<rrr\s$$$$$$ >     : "#"#"# "#P 8888xIK      r