ó  ‰\c@ s]ddlmZddlmZddlZdd„Zdd„Zdde id„Z dS(iÿÿÿÿ(tdivision(tproductNicC st|ƒ}tj|ƒr7|f||d|}nP|rft|ƒ|dkrft|ƒd}n!t|ƒ|kr‡tdƒ‚ntj|ƒr²|f||d |}nP|rát|ƒ|dkrát|ƒd }n!t|ƒ|krtdƒ‚ntjtj|ƒdkƒr/tdƒ‚n|rT|ddkrTtdƒ‚ntgt ||ƒD]"\}}t d|d|ƒ^qgŒS( sReturns all combinations of shifts in n dimensions over the specified max_shifts and step sizes. Examples -------- >>> s = list(_generate_shifts(2, False, max_shifts=(1, 2), shift_steps=1)) >>> print(s) [(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2)] iis"max_shifts should have length ndimsshift_steps must all be >= 1iÿÿÿÿsGMultichannel cycle spinning should not have shifts along the last axis.(i(i(i(i( tinttnptisscalartlenttuplet ValueErrortanytasarrayRtziptrange(tndimt multichannelt max_shiftst shift_stepstmctstt((s>lib/python2.7/site-packages/skimage/restoration/_cycle_spin.pyt_generate_shiftss(  cC s]|dkr$tjt|ƒƒ}nx2t||ƒD]!\}}tj|||ƒ}q4W|S(s|Apply np.roll along a set of axes. Parameters ---------- x : array-like Array to roll. rolls : int or sequence The amount to roll along each axis in ``axes``. axes : int or sequence, optional The axes to roll. Default is the first ``len(rolls)`` axes of ``x``. Returns ------- x : array Data with axes rolled. N(tNoneRtarangeRR troll(txtrollstaxestrta((s>lib/python2.7/site-packages/skimage/restoration/_cycle_spin.pyt _roll_axes-s  c sBtjˆƒ‰tˆj|||ƒ}t|ƒ}‡‡‡fd†}|dkršyddl} Wqštk r–ddl} | jdƒd}qšXn|dkrî||dƒ} x"|dD]} | || ƒ7} qÁW| t |ƒ} nPg|D]} | j |ƒ| ƒ^qõ}t |ƒt |ƒ} | j d|ƒ} | S(s Cycle spinning (repeatedly apply func to shifted versions of x). Parameters ---------- x : array-like Data for input to ``func``. func : function A function to apply to circularly shifted versions of ``x``. Should take ``x`` as its first argument. Any additional arguments can be supplied via ``func_kw``. max_shifts : int or tuple If an integer, shifts in ``range(0, max_shifts+1)`` will be used along each axis of ``x``. If a tuple, ``range(0, max_shifts[i]+1)`` will be along axis i. shift_steps : int or tuple, optional The step size for the shifts applied along axis, i, are:: ``range((0, max_shifts[i]+1, shift_steps[i]))``. If an integer is provided, the same step size is used for all axes. num_workers : int or None, optional The number of parallel threads to use during cycle spinning. If set to ``None``, the full set of available cores are used. multichannel : bool, optional Whether to treat the final axis as channels (no cycle shifts are performed over the channels axis). func_kw : dict, optional Additional keyword arguments to supply to ``func``. Returns ------- avg_y : np.ndarray The output of ``func(x, **func_kw)`` averaged over all combinations of the specified axis shifts. Notes ----- Cycle spinning was proposed as a way to approach shift-invariance via performing several circular shifts of a shift-variant transform [1]_. For a n-level discrete wavelet transforms, one may wish to perform all shifts up to ``max_shifts = 2**n - 1``. In practice, much of the benefit can often be realized with only a small number of shifts per axis. For transforms such as the blockwise discrete cosine transform, one may wish to evaluate shifts up to the block size used by the transform. References ---------- .. [1] R.R. Coifman and D.L. Donoho. "Translation-Invariant De-Noising". Wavelets and Statistics, Lecture Notes in Statistics, vol.103. Springer, New York, 1995, pp.125-150. DOI:10.1007/978-1-4612-2544-7_9 Examples -------- >>> import skimage.data >>> from skimage import img_as_float >>> from skimage.restoration import denoise_wavelet, cycle_spin >>> img = img_as_float(skimage.data.camera()) >>> sigma = 0.1 >>> img = img + sigma * np.random.standard_normal(img.shape) >>> denoised = cycle_spin(img, func=denoise_wavelet, max_shifts=3) c s5tˆ|ƒ}ˆ|ˆ}t|tj|ƒ ƒS(N(RRR (tshifttxsttmp(tfunctfunc_kwR(s>lib/python2.7/site-packages/skimage/restoration/_cycle_spin.pyt_run_one_shiftsiiÿÿÿÿNsldask is required for parallel computation, but it is not available. Computation will be performed serially.it num_workers( Rt asanyarrayRR tlisttdaskt ImportErrortwarningstwarnRtdelayedtsumtcompute(RR RRR#R R!t all_shiftsR"R&R(tmeanRRtfutures((R R!Rs>lib/python2.7/site-packages/skimage/restoration/_cycle_spin.pyt cycle_spinGs,A       (( t __future__Rt itertoolsRtnumpyRRRRtFalseR0(((s>lib/python2.7/site-packages/skimage/restoration/_cycle_spin.pyts   %