Ncg_ dZddlZddlmZej ej ejejejejejejejejf ZeDcic]9}|ej!|j"ej!|j$f;c}Zej(dej*dej,dej.diZej3eej5Zej3dej9Dej3ddd eej(eej.d dd Zd Zdd Zycc}w)zVendored code from scikit-image in order to limit the number of dependencies Extracted from scikit-image/skimage/exposure/exposure.py N)warn)FT)c#>K|]\}}|j|fyw)N)__name__).0dlimitss V/var/www/html/bid-api/venv/lib/python3.12/site-packages/plotly/express/imshow_utils.py r s M9LIAvAJJ'9Ls)ri)ri)ri?)uint10uint12uint14boolfloatc|dk(r|jj}|dk(r.tj|}tj|}||fS|t vrt |\}}|rd}||fS|\}}||fS)afReturn image intensity range (min, max) based on desired value type. Parameters ---------- image : array Input image. range_values : str or 2-tuple, optional The image intensity range is configured by this parameter. The possible values for this parameter are enumerated below. 'image' Return image min/max as the range. 'dtype' Return min/max of the image's dtype as the range. dtype-name Return intensity range based on desired `dtype`. Must be valid key in `DTYPE_RANGE`. Note: `image` is ignored for this range type. 2-tuple Return `range_values` as min/max intensities. Note that there's no reason to use this function if you just want to specify the intensity range explicitly. This option is included for functions that use `intensity_range` to support all desired range types. clip_negative : bool, optional If True, clip the negative range (i.e. return 0 for min intensity) even if the image dtype allows negative values. dtypeimager)rtypenpminmax DTYPE_RANGE)r range_values clip_negativei_mini_maxs r intensity_ranger,s8w{{'' wu u  %<  $"<0 u E %<$ u %<cRt|tttjfvrtj St|tk(r|S|t vr tj|jStdt|z#t$rtjcYSwxYw)aODetermine the output dtype for rescale_intensity. The dtype is determined according to the following rules: - if ``dtype_or_range`` is a dtype, that is the output dtype. - if ``dtype_or_range`` is a dtype string, that is the dtype used, unless it is not a NumPy data type (e.g. 'uint12' for 12-bit unsigned integers), in which case the data type that can contain it will be used (e.g. uint16 in this case). - if ``dtype_or_range`` is a pair of values, the output data type will be float. Parameters ---------- dtype_or_range : type, string, or 2-tuple of int/float The desired range for the output, expressed as either a NumPy dtype or as a (min, max) pair of numbers. Returns ------- out_dtype : type The data type appropriate for the desired output. z]Incorrect value for out_range, should be a valid image data type or a pair of values, got %s.) rlisttuplerndarrayfloat_rr TypeErroruint16 ValueErrorstr)dtype_or_ranges r _output_dtyper*Ws. NeRZZ88yy Nt#$ 88N+00 0  025n2E F   99  sB B&%B&c *|dvr t|jj}n t|}ttt ||\}}ttt |||dk\\}}t jt j||||gr tddt j|||}||k7r+||z ||z z }t j|||z z|z|St j|||j|S)a Return image after stretching or shrinking its intensity levels. The desired intensity range of the input and output, `in_range` and `out_range` respectively, are used to stretch or shrink the intensity range of the input image. See examples below. Parameters ---------- image : array Image array. in_range, out_range : str or 2-tuple, optional Min and max intensity values of input and output image. The possible values for this parameter are enumerated below. 'image' Use image min/max as the intensity range. 'dtype' Use min/max of the image's dtype as the intensity range. dtype-name Use intensity range based on desired `dtype`. Must be valid key in `DTYPE_RANGE`. 2-tuple Use `range_values` as explicit min/max intensities. Returns ------- out : array Image array after rescaling its intensity. This image is the same dtype as the input image. Notes ----- .. versionchanged:: 0.17 The dtype of the output array has changed to match the output dtype, or float if the output range is specified by a pair of floats. See Also -------- equalize_hist Examples -------- By default, the min/max intensities of the input image are stretched to the limits allowed by the image's dtype, since `in_range` defaults to 'image' and `out_range` defaults to 'dtype': >>> image = np.array([51, 102, 153], dtype=np.uint8) >>> rescale_intensity(image) array([ 0, 127, 255], dtype=uint8) It's easy to accidentally convert an image dtype from uint8 to float: >>> 1.0 * image array([ 51., 102., 153.]) Use `rescale_intensity` to rescale to the proper range for float dtypes: >>> image_float = 1.0 * image >>> rescale_intensity(image_float) array([0. , 0.5, 1. ]) To maintain the low contrast of the original, use the `in_range` parameter: >>> rescale_intensity(image_float, in_range=(0, 255)) array([0.2, 0.4, 0.6]) If the min/max value of `in_range` is more/less than the min/max image intensity, then the intensity levels are clipped: >>> rescale_intensity(image_float, in_range=(0, 102)) array([0.5, 1. , 1. ]) If you have an image with signed integers but want to rescale the image to just the positive range, use the `out_range` parameter. In that case, the output dtype will be float: >>> image = np.array([-10, 0, 10], dtype=np.int8) >>> rescale_intensity(image, out_range=(0, 127)) array([ 0. , 63.5, 127. ]) To get the desired range with a specific dtype, use ``.astype()``: >>> rescale_intensity(image, out_range=(0, 127)).astype(np.int8) array([ 0, 63, 127], dtype=int8) If the input image is constant, the output will be clipped directly to the output range: >>> image = np.array([130, 130, 130], dtype=np.int32) >>> rescale_intensity(image, out_range=(0, 127)).astype(np.int32) array([127, 127, 127], dtype=int32) )rrr)rzOne or more intensity levels are NaN. Rescaling will broadcast NaN to the full image. Provide intensity levels yourself to avoid this. E.g. with np.nanmin(image), np.nanmax(image).) stacklevel)r) r*rrmaprrranyisnanrclipasarrayastype)rin_range out_range out_dtypeiminimaxominomaxs r rescale_intensityr;sx&&!%++"2"23 !), UOE8<=JD$ ui KJD$ vvbhhdD$/01  H   GGE4 &E t|$+.zz%4$;/$6iHHwwudD)00;;r)rF)rr) __doc__numpyrwarningsrbyteubyteshortushortintcuintcint_uintlonglong ulonglong_integer_typesiinforr_integer_rangesbool_float16float32float64 dtype_rangeupdatecopyritemsrr*r;)ts0r rUsPGGHHHHIIGGHHGGGGKKLL CQQ.Q1rxx{ 88.QHHmJJJJJJ   ?# M9J9J9LMM    BHH%RZZ( (V) Xt<]Rs>E8