/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/
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Edit: /opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyo (20254B)
Ñò …ñ™Jc @swddkZddkZddklZeiZddklZddklZl Z l Z l Z ddkl Z l Z lZlZlZddklZlZdefd„ƒYZd efd „ƒYZd „Zd „Zd efd„ƒYZdefd„ƒYZhed6ed6ed6Zd„Zd„Zeeiƒhdieƒƒd6e_d„Z d„Z!dS(iÿÿÿÿN(tma(tdedent(t NullFormattertScalarFormattertLogFormatterMathtextt Formatter(t NullLocatort LogLocatort AutoLocatortSymmetricalLogLocatort FixedLocator(t TransformtIdentityTransformt ScaleBasecBs)eZdZd„Zd„Zd„ZRS(s@ The base class for all scales. Scales are separable transformations, working on a single dimension. Any subclasses will want to override: - :attr:`name` - :meth:`get_transform` And optionally: - :meth:`set_default_locators_and_formatters` - :meth:`limit_range_for_scale` cCs t‚dS(sq Return the :class:`~matplotlib.transforms.Transform` object associated with this scale. N(tNotImplementedError(tself((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyt get_transformscCs t‚dS(s¦ Set the :class:`~matplotlib.ticker.Locator` and :class:`~matplotlib.ticker.Formatter` objects on the given axis to match this scale. N(R(Rtaxis((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyt#set_default_locators_and_formatters!scCs ||fS(sù Returns the range *vmin*, *vmax*, possibly limited to the domain supported by this scale. *minpos* should be the minimum positive value in the data. This is used by log scales to determine a minimum value. ((Rtvmintvmaxtminpos((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pytlimit_range_for_scale)s(t__name__t __module__t__doc__RRR(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR s  t LinearScalecBs/eZdZdZd„Zd„Zd„ZRS(s# The default linear scale. tlinearcKsdS(N((RRtkwargs((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyt__init__:scCsD|itƒƒ|itƒƒ|itƒƒ|itƒƒdS(sd Set the locators and formatters to reasonable defaults for linear scaling. N(tset_major_locatorRtset_major_formatterRtset_minor_locatorRtset_minor_formatterR(RR((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR=scCstƒS(sy The transform for linear scaling is just the :class:`~matplotlib.transforms.IdentityTransform`. (R (R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRGs(RRRtnameRRR(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR3s   cCs1|dj}|iƒoti|d|ƒS|S(s Return a Numpy masked array where all non-positive values are masked. If there are no non-positive values, the original array is returned. gtmask(tanyRt MaskedArray(taR#((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyt_mask_non_positivesOs  cCsd||dj<|S(NgYóøÂn¥g((R&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyt_clip_non_positivesZstLogScalecBsþeZdZdZdefd„ƒYZdefd„ƒYZdefd„ƒYZdefd „ƒYZd efd „ƒYZ d efd „ƒYZ defd„ƒYZ defd„ƒYZ defd„ƒYZ d„Zd„Zd„Zd„ZRS(sÔ A standard logarithmic scale. Care is taken so non-positive values are not plotted. For computational efficiency (to push as much as possible to Numpy C code in the common cases), this scale provides different transforms depending on the base of the logarithm: - base 10 (:class:`Log10Transform`) - base 2 (:class:`Log2Transform`) - base e (:class:`NaturalLogTransform`) - arbitrary base (:class:`LogTransform`) tlogtLogTransformBasecBs#eZdZdZeZd„ZRS(icCs4ti|ƒ|djo t|_n t|_dS(NR#(R RR't_handle_nonposR((Rtnonpos((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRts   (RRt input_dimst output_dimstTruet is_separableR(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR+ostLog10TransformcBs eZdZd„Zd„ZRS(g$@cCs>|i|dƒ}t|tƒoti|ƒSti|ƒS(Ng$@(R,t isinstanceR%Rtlog10tnp(RR&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyt transformscCs tiƒS(N(R)tInvertedLog10Transform(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pytinverted…s(RRtbaseR6R8(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR2|s R7cBs2eZdZdZeZdZd„Zd„ZRS(ig$@cCstid|ƒdS(Ng$@(Rtpower(RR&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR6ŽscCs tiƒS(N(R)R2(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR8‘s( RRR.R/R0R1R9R6R8(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR7ˆs  t Log2TransformcBs eZdZd„Zd„ZRS(g@cCsK|i|dƒ}t|tƒoti|ƒtidƒSti|ƒS(Ng@i(R,R3R%RR*R5tlog2(RR&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR6—scCs tiƒS(N(R)tInvertedLog2Transform(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR8s(RRR9R6R8(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR;”s R=cBs2eZdZdZeZdZd„Zd„ZRS(ig@cCstid|ƒdS(Ng@(RR:(RR&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR6¦scCs tiƒS(N(R)R;(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR8©s( RRR.R/R0R1R9R6R8(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR= s  tNaturalLogTransformcBs#eZeiZd„Zd„ZRS(cCsA|i|tiƒ}t|tƒoti|ƒSti|ƒS(N(R,R5teR3R%RR*(RR&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR6¯scCs tiƒS(N(R)tInvertedNaturalLogTransform(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR8µs(RRR5R?R9R6R8(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR>¬s  R@cBs5eZdZdZeZeiZd„Z d„Z RS(icCstiti|ƒtiS(N(RR:R5R?(RR&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR6¾scCs tiƒS(N(R)R>(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR8Ás( RRR.R/R0R1R5R?R9R6R8(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR@¸s   t LogTransformcBs5eZdZdZeZd„Zd„Zd„ZRS(icCs=ti|ƒ||_|djo t|_n t|_dS(NR#(R RR9R'R,R((RR9R-((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRÉs     cCsa|i||iƒ}t|tƒoti|ƒti|iƒSti|ƒti|iƒS(N(R,R9R3R%RR*R5(RR&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR6ÑscCsti|iƒS(N(R)tInvertedLogTransformR9(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR8×s( RRR.R/R0R1RR6R8(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRAÄs   RBcBs5eZdZdZeZd„Zd„Zd„ZRS(icCsti|ƒ||_dS(N(R RR9(RR9((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRßs cCsti|i|ƒ|iS(N(RR:R9(RR&((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR6ãscCsti|iƒS(N(R)RAR9(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR8æs( RRR.R/R0R1RR6R8(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRBÚs   cKs4|idjo:|iddƒ}|idd ƒ}|iddƒ}n7|iddƒ}|idd ƒ}|id dƒ}|djotd ƒ‚n|djo|i|ƒ|_n_|d jo|i|ƒ|_n<|tijo|i |ƒ|_n|i ||ƒ|_||_ ||_ d S(s) *basex*/*basey*: The base of the logarithm *nonposx*/*nonposy*: ['mask' | 'clip' ] non-positive values in *x* or *y* can be masked as invalid, or clipped to a very small positive number *subsx*/*subsy*: Where to place the subticks between each major tick. Should be a sequence of integers. For example, in a log10 scale: ``[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]`` will place 10 logarithmically spaced minor ticks between each major tick. txtbasexg$@tsubsxtnonposxR#tbaseytsubsytnonposytclips/nonposx, nonposy kwarg must be 'mask' or 'clip'g@N(smaskRJ( t axis_nametpoptNonet ValueErrorR2t _transformR;R5R?R>RAR9tsubs(RRRR9RPR-((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRês$    cCs\|it|iƒƒ|it|iƒƒ|it|i|iƒƒ|itƒƒdS(sb Set the locators and formatters to specialized versions for log scaling. N( RRR9RRR RPR!R(RR((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRscCs|iS(s Return a :class:`~matplotlib.transforms.Transform` instance appropriate for the given logarithm base. (RO(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRscCs2|djo|p||djo|p|fS(s6 Limit the domain to positive values. g((RRRR((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR$s(RRRR"R R+R2R7R;R=R>R@RARBRRRR(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR)^s         ) tSymmetricalLogScalecBs[eZdZdZdefd„ƒYZdefd„ƒYZd„Zd„Zd„Z RS( sh The symmetrical logarithmic scale is logarithmic in both the positive and negative directions from the origin. Since the values close to zero tend toward infinity, there is a need to have a range around zero that is linear. 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Should be a sequence of integers. For example, in a log10 scale: ``[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]`` will place 10 logarithmically spaced minor ticks between each major tick. RCRDg$@t linthreshxg@RERGt linthreshyRHN(RKRLRMRSROR9RTRP(RRRR9RTRP((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRks  cCsb|it|iƒƒƒ|it|iƒƒ|it|iƒ|iƒƒ|it ƒƒdS(sn Set the locators and formatters to specialized versions for symmetrical log scaling. N( RR RRRR9R RPR!R(RR((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR‹scCs|iS(sE Return a :class:`SymmetricalLogTransform` instance. (RO(R((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyR•s( RRRR"R RSR_RRR(((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyRQ,s  RR*RRcCstiƒ}|iƒ|S(N(t_scale_mappingtkeystsort(tnames((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pytget_scale_names¢s  cKsU|iƒ}|djo d}n|tjotd|ƒ‚nt|||S(sC Return a scale class by name. ACCEPTS: [ %(names)s ] RsUnknown scale type '%s'N(tlowerRMRcRN(tscaleRR((sC/opt/alt/python27/lib64/python2.7/site-packages/matplotlib/scale.pyt scale_factory§s     s | RfcCs|t|is.   "(( Îq