IR-e50dZddlZddlZddlmZddlmZmZmZm Z m Z ddl m Z m Z mZmZmZmZmZ ddlZddlmZddlmZn#e$rGd d ZYnwxYwgd Zd d giZGddeZ ddZejeZddZdS)zK Normalization class for Matplotlib that can be used to produce colorbars. N)ma)AsymmetricPercentileInterval BaseIntervalManualIntervalMinMaxIntervalPercentileInterval) AsinhStretch BaseStretch LinearStretch LogStretch PowerStretch SinhStretch SqrtStretch)pyplot) NormalizeceZdZdZdS)rc td)Nz2matplotlib is required in order to use this class.) ImportError)selfargskwargss Clib/python3.11/site-packages/astropy/visualization/mpl_normalize.py__init__zNormalize.__init__#sRSS SN)__name__ __module__ __qualname__rrrrr"s( T T T T Trr)ImageNormalize simple_norm imshow_norm* matplotlibcXeZdZdZddddeddffd ZdZd dZd dZxZ S) r a Normalization class to be used with Matplotlib. Parameters ---------- data : ndarray, optional The image array. This input is used only if ``interval`` is also input. ``data`` and ``interval`` are used to compute the vmin and/or vmax values only if ``vmin`` or ``vmax`` are not input. interval : `~astropy.visualization.BaseInterval` subclass instance, optional The interval object to apply to the input ``data`` to determine the ``vmin`` and ``vmax`` values. This input is used only if ``data`` is also input. ``data`` and ``interval`` are used to compute the vmin and/or vmax values only if ``vmin`` or ``vmax`` are not input. vmin, vmax : float, optional The minimum and maximum levels to show for the data. The ``vmin`` and ``vmax`` inputs override any calculated values from the ``interval`` and ``data`` inputs. stretch : `~astropy.visualization.BaseStretch` subclass instance The stretch object to apply to the data. The default is `~astropy.visualization.LinearStretch`. clip : bool, optional If `True`, data values outside the [0:1] range are clipped to the [0:1] range. invalid : None or float, optional Value to assign NaN values generated by this class. NaNs in the input ``data`` array are not changed. For matplotlib normalization, the ``invalid`` value should map to the matplotlib colormap "under" value (i.e., any finite value < 0). If `None`, then NaN values are not replaced. This keyword has no effect if ``clip=True``. NFct|||||_||_|t dt |t std||_|$t |tstd||_ |j |_ ||_ ||_|||dSdS)N)vminvmaxclipzstretch must be inputz5stretch must be an instance of a BaseStretch subclassz7interval must be an instance of a BaseInterval subclass)superrr(r) ValueError isinstancer TypeErrorstretchrintervalinverseinverse_stretchr*invalid _set_limits) rdatar0r(r)r/r*r3 __class__s rrzImageNormalize.__init__Ps dD999  ?455 5';// USTT T   8\(J(J UVV V  &       T " " " " "  rc|j |jdS|jt|j1tj|tj||_|j3tj|tj||_dSdS|j|\}}|j||_|j ||_dSdSN)r(r)r0npminisfinitemax get_limits)rr5_vmin_vmaxs rr4zImageNormalize._set_limitsrs 9 TY%: F = y F4 D(9(9#:;; y F4 D(9(9#:;; !  =33D99LE5y ! y ! ! rc||j}||j}t|tjr'|rd}n|j}||j}nd}tj |rtj |gt}ntj |dt}| |tj ||j|tj||j|jz ||rtj|dd|}|jjr|||d| }n|||d }tj || S) ar Transform values using this normalization. Parameters ---------- values : array-like The input values. clip : bool, optional If `True`, values outside the [0:1] range are clipped to the [0:1] range. If `None` then the ``clip`` value from the `ImageNormalize` instance is used (the default of which is `False`). invalid : None or float, optional Value to assign NaN values generated by this class. NaNs in the input ``data`` array are not changed. For matplotlib normalization, the ``invalid`` value should map to the matplotlib colormap "under" value (i.e., any finite value < 0). If `None`, then the `ImageNormalize` instance value is used. This keyword has no effect if ``clip=True``. NF)dtypeT)copyrA)out?)rCr*r3)rCr*)mask)r*r3r-r MaskedArrayrFfilledr)r9isscalararrayfloatr4subtractr( true_divider/_supports_invalid_kw)rvaluesr*r3rFs r__call__zImageNormalize.__call__sp* <9D ?lG fbn - -  #{]]49--FFD ;v   >Xvhe444FFXf4u===F     FDI62222 vty494&AAAA  ;WVS#6:::F < , B\\&f5'\RRFF\\&f5\AAFxT****rc|jjr||d|}n||d}||j|jz z|jzS)NF)r*r3)r*)r2rNr)r()rrOr3 values_norms rr1zImageNormalize.inversesb   4 C..vE7.SSKK..vE.BBKdi$)34ty@@r)NNr8) rrr__doc__r rr4rPr1 __classcell__)r6s@rr r ,s!!J     # # # # # #D""""=+=+=+=+~AAAAAAAArr linearrE皙?Fr&333333?c  |t|} n<||t|pd|pd} n#||t||} nt} |dkrt }n|dkrt }nk|dkrt |}nU|dkrt| }n?|dkrt|}n)|d krt| }ntd |d | |\}}t|||| | S) a Return a Normalization class that can be used for displaying images with Matplotlib. This function enables only a subset of image stretching functions available in `~astropy.visualization.mpl_normalize.ImageNormalize`. This function is used by the ``astropy.visualization.scripts.fits2bitmap`` script. Parameters ---------- data : ndarray The image array. stretch : {'linear', 'sqrt', 'power', log', 'asinh', 'sinh'}, optional The stretch function to apply to the image. The default is 'linear'. power : float, optional The power index for ``stretch='power'``. The default is 1.0. asinh_a : float, optional For ``stretch='asinh'``, the value where the asinh curve transitions from linear to logarithmic behavior, expressed as a fraction of the normalized image. Must be in the range between 0 and 1. The default is 0.1. min_cut : float, optional The pixel value of the minimum cut level. Data values less than ``min_cut`` will set to ``min_cut`` before stretching the image. The default is the image minimum. ``min_cut`` overrides ``min_percent``. max_cut : float, optional The pixel value of the maximum cut level. Data values greater than ``min_cut`` will set to ``min_cut`` before stretching the image. The default is the image maximum. ``max_cut`` overrides ``max_percent``. min_percent : float, optional The percentile value used to determine the pixel value of minimum cut level. The default is 0.0. ``min_percent`` overrides ``percent``. max_percent : float, optional The percentile value used to determine the pixel value of maximum cut level. The default is 100.0. ``max_percent`` overrides ``percent``. percent : float, optional The percentage of the image values used to determine the pixel values of the minimum and maximum cut levels. The lower cut level will set at the ``(100 - percent) / 2`` percentile, while the upper cut level will be set at the ``(100 + percent) / 2`` percentile. The default is 100.0. ``percent`` is ignored if either ``min_percent`` or ``max_percent`` is input. clip : bool, optional If `True`, data values outside the [0:1] range are clipped to the [0:1] range. log_a : float, optional The log index for ``stretch='log'``. The default is 1000. invalid : None or float, optional Value to assign NaN values generated by the normalization. NaNs in the input ``data`` array are not changed. For matplotlib normalization, the ``invalid`` value should map to the matplotlib colormap "under" value (i.e., any finite value < 0). If `None`, then NaN values are not replaced. This keyword has no effect if ``clip=True``. sinh_a : float, optional The scaling parameter for ``stretch='sinh'``. The default is 0.3. Returns ------- result : `ImageNormalize` instance An `ImageNormalize` instance that can be used for displaying images with Matplotlib. NrDgY@rUsqrtpowerlogasinhsinhzUnknown stretch: .)r(r)r/r*r3) r rrrr rrr r rr,r=r )r5r/r[asinh_amin_cutmax_cut min_percent max_percentpercentr*log_ar3sinh_ar0r(r)s rr!r!sUD%g..  K$;/  3 4u     3!'733!##(// F  -- G  u%% E  U## G  w'' F  f%%7W777888$$T**JD$  gD'   rc Bd|vrtdd|vrtdt|}d|i}tjD]}||vr||||<t di||d<|t j|fi|}n|j|fi|}||dfS)a*A convenience function to call matplotlib's `matplotlib.pyplot.imshow` function, using an `ImageNormalize` object as the normalization. Parameters ---------- data : 2D or 3D array-like The data to show. Can be whatever `~matplotlib.pyplot.imshow` and `ImageNormalize` both accept. See `~matplotlib.pyplot.imshow`. ax : None or `~matplotlib.axes.Axes`, optional If None, use pyplot's imshow. Otherwise, calls ``imshow`` method of the supplied axes. **kwargs : dict, optional All other keyword arguments are parsed first by the `ImageNormalize` initializer, then to `~matplotlib.pyplot.imshow`. Returns ------- result : tuple A tuple containing the `~matplotlib.image.AxesImage` generated by `~matplotlib.pyplot.imshow` as well as the `ImageNormalize` instance. Notes ----- The ``norm`` matplotlib keyword is not supported. Examples -------- .. plot:: :include-source: import numpy as np import matplotlib.pyplot as plt from astropy.visualization import (imshow_norm, MinMaxInterval, SqrtStretch) # Generate and display a test image image = np.arange(65536).reshape((256, 256)) fig = plt.figure() ax = fig.add_subplot(1, 1, 1) im, norm = imshow_norm(image, ax, origin='lower', interval=MinMaxInterval(), stretch=SqrtStretch()) fig.colorbar(im) Xz#Cannot give both ``X`` and ``data``normzoThere is no point in using imshow_norm if you give the ``norm`` keyword - use imshow directly if you want that.r5Nr)r,dict _norm_sig parameterspopr pltimshow)r5axr imshow_kwargs norm_kwargspname imshow_results rr"r"Ts^ f}}>???     LLM4.K%:: F??!.!2!25!9!9K *99[99M& z 499=99 ! $88-88 -/ //r) rUrErVNNNNNFrWr&rXr8) rSinspectnumpyr9rr0rrrrr r/r r r r rrrr$rromatplotlib.colorsrr__all____doctest_requires__r r! signaturerlr"rrrr|s8 T((((((+++++++TTTTTTTTTTTTTT ; : :l^,^A^A^A^A^AY^A^A^AF         @@@@H G n - - G0G0G0G0G0G0sAAA