ó ±éRc@s¯ddlmZddlZddlmZddlmZddlmZm Z m Z ddlm Z m Z m Z mZddlmZmZddlmZd efd „ƒYZd efd „ƒYZd „Zd„Zdefd„ƒYZdefd„ƒYZdefd„ƒYZdefd„ƒYZdefd„ƒYZdefd„ƒYZdefd„ƒYZdefd„ƒYZ defd „ƒYZ!d!efd"„ƒYZ"d#efd$„ƒYZ#d%efd&„ƒYZ$d'efd(„ƒYZ%ied)6e"d*6e%d+6Z&d,„Z'd-„Z(ee(j)ƒid.j*e'ƒƒd/6e(_)d0„Z+d1„Z,ej-j.d2d.j*ge'ƒD]Z/e0e/ƒ^q€ƒd3e,ƒj1ƒƒdS(4iÿÿÿÿ(tprint_functionN(tma(tdedent(t NullFormattertScalarFormattertLogFormatterMathtext(t NullLocatort LogLocatort AutoLocatortSymmetricalLogLocator(t TransformtIdentityTransform(t docstringt 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 tƒ‚dS(sq Return the :class:`~matplotlib.transforms.Transform` object associated with this scale. N(tNotImplementedError(tself((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyt get_transformscCs tƒ‚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((sJ/opt/xtal/ccp4-6.5-linux32/lib/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((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pytlimit_range_for_scale-s(t__name__t __module__t__doc__RRR(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR s  t LinearScalecBs/eZdZdZd„Zd„Zd„ZRS(s# The default linear scale. tlinearcKsdS(N((RRtkwargs((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyt__init__?scCsD|jtƒƒ|jtƒƒ|jtƒƒ|jtƒƒdS(sd Set the locators and formatters to reasonable defaults for linear scaling. N(tset_major_locatorRtset_major_formatterRtset_minor_locatorRtset_minor_formatterR(RR((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRBscCstƒS(sy The transform for linear scaling is just the :class:`~matplotlib.transforms.IdentityTransform`. (R (R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRLs(RRRtnameRRR(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR8s   cCs/|dk}|jƒr+tj|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#((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyt_mask_non_positivesTs  cCsd||dk<|S(NgYóøÂn¥g((R&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyt_clip_non_positives`stLogTransformBasecBs)eZdZdZeZeZd„ZRS(icCs2tj|ƒ|dkr%t|_n t|_dS(NR#(R RR't_handle_nonposR((Rtnonpos((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRks   (RRt input_dimst output_dimstTruet is_separablet has_inverseR(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR)es tLog10TransformcBs eZdZd„Zd„ZRS(g$@cCs?|j|dƒ}t|tjƒr2tj|ƒStj|ƒS(Ng$@(R*t isinstanceRR%tlog10tnp(RR&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyttransform_non_affinevs cCstƒS(N(tInvertedLog10Transform(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pytinverted|s(RRtbaseR5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR1ss R6cBs8eZdZdZeZeZdZd„Zd„Z RS(ig$@cCstjd|ƒdS(Ng$@(Rtpower(RR&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5‡scCstƒS(N(R1(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7Šs( RRR,R-R.R/R0R8R5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR6€s t Log2TransformcBs eZdZd„Zd„ZRS(g@cCsL|j|dƒ}t|tjƒr?tj|ƒtjdƒStj|ƒS(Ng@i(R*R2RR%tlogR4tlog2(RR&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5‘scCstƒS(N(tInvertedLog2Transform(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7—s(RRR8R5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR:Žs R=cBs8eZdZdZeZeZdZd„Zd„Z RS(ig@cCstjd|ƒdS(Ng@(RR9(RR&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5¢scCstƒS(N(R:(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7¥s( RRR,R-R.R/R0R8R5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR=›s tNaturalLogTransformcBs#eZejZd„Zd„ZRS(cCsB|j|tjƒ}t|tjƒr5tj|ƒStj|ƒS(N(R*R4teR2RR%R;(RR&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5¬s cCstƒS(N(tInvertedNaturalLogTransform(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7²s(RRR4R?R8R5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR>©s  R@cBs;eZdZdZeZeZejZ d„Z d„Z RS(icCstjtj|ƒtjS(N(RR9R4R?(RR&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5½scCstƒS(N(R>(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7Às( RRR,R-R.R/R0R4R?R8R5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR@¶s  t LogTransformcBs;eZdZdZeZeZd„Zd„Zd„Z RS(icCs;tj|ƒ||_|dkr.t|_n t|_dS(NR#(R RR8R'R*R((RR8R+((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRÊs     cCsb|j||jƒ}t|tjƒrEtj|ƒtj|jƒStj|ƒtj|jƒS(N(R*R8R2RR%R;R4(RR&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5ÒscCs t|jƒS(N(tInvertedLogTransformR8(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7Øs( RRR,R-R.R/R0RR5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRAÄs  RBcBs;eZdZdZeZeZd„Zd„Zd„Z RS(icCstj|ƒ||_dS(N(R RR8(RR8((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRâs cCstj|j|ƒ|jS(N(RR9R8(RR&((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5æscCs t|jƒS(N(RAR8(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7és( RRR,R-R.R/R0RR5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRBÜs  tLogScalecBsneZdZdZeZeZeZeZeZe Z e Z e Z e Z d„Z d„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`) R;cKs*|jdkrH|jddƒ}|jdd ƒ}|jddƒ}n6|jddƒ}|jdd ƒ}|jd dƒ}|dkr™td ƒ‚n|dkrº|j|ƒ|_nZ|d krÛ|j|ƒ|_n9|tjkrÿ|j |ƒ|_n|j ||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: ``[2, 3, 4, 5, 6, 7, 8, 9]`` will place 8 logarithmically spaced minor ticks between each major tick. txtbasexg$@tsubsxtnonposxR#tbaseytsubsytnonposytclips/nonposx, nonposy kwarg must be 'mask' or 'clip'g@N(smasksclip( t axis_nametpoptNonet ValueErrorR1t _transformR:R4R?R>RAR8tsubs(RRRR8RQR+((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRs$    cCs\|jt|jƒƒ|jt|jƒƒ|jt|j|jƒƒ|jtƒƒdS(sb Set the locators and formatters to specialized versions for log scaling. N( RRR8RRR RQR!R(RR((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR1scCs|jS(s Return a :class:`~matplotlib.transforms.Transform` instance appropriate for the given logarithm base. (RP(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR;scCs.|dkr|p||dkr'|p*|fS(s6 Limit the domain to positive values. g((RRRR((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRBs(RRRR"R)R1R6R:R=R>R@RARBRRRR(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRCís  ) tSymmetricalLogTransformcBs;eZdZdZeZeZd„Zd„Zd„Z RS(icCsVtj|ƒ||_||_||_|d|jd|_tj|ƒ|_dS(Ngð?iÿÿÿÿ( R RR8t linthreshtlinscalet _linscale_adjR4R;t _log_base(RR8RSRT((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRPs     cCstj|ƒ}tj||j |jdtƒ}||j|jtjtj|ƒ|jƒ|j }|j j ƒr•tj |j ||j|ƒS|SdS(Ntcopy( R4tsignRt masked_insideRStFalseRUR;tabsRVR#R$twhere(RR&RXtmaskedR;((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5Xs    (cCst|j|j|jƒS(N(tInvertedSymmetricalLogTransformR8RSRT(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7fs( RRR,R-R.R/R0RR5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRRJs  R^cBs;eZdZdZeZeZd„Zd„Zd„Z RS(icCshtj|ƒt|||ƒ}||_||_|j|ƒ|_||_|d|jd|_dS(Ngð?iÿÿÿÿ( R RRRR8RSt transformt invlinthreshRTRU(RR8RSRTtsymlog((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRqs    cCs—tj|ƒ}tj||j |jdtƒ}||jtj|j|||j|j ƒ}|j j ƒrtj |j ||j |ƒS|SdS(NRW( R4RXRRYR`RZRSR9R8RUR#R$R\(RR&RXR]texp((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR5zs cCst|j|j|jƒS(N(RRR8RSRT(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR7†s ( RRR,R-R.R/R0RR5R7(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR^ks tSymmetricalLogScalecBs;eZdZdZeZeZd„Zd„Zd„ZRS(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. The parameter *linthresh* allows the user to specify the size of this range (-*linthresh*, *linthresh*). RacKs|jdkrZ|jddƒ}|jddƒ}|jddƒ}|jddƒ}nH|jd dƒ}|jd dƒ}|jd dƒ}|jd dƒ}|dks´t‚|d ksÆt‚|dksØt‚|j|||ƒ|_||_||_||_||_ dS(sø *basex*/*basey*: The base of the logarithm *linthreshx*/*linthreshy*: The range (-*x*, *x*) within which the plot is linear (to avoid having the plot go to infinity around zero). *subsx*/*subsy*: Where to place the subticks between each major tick. Should be a sequence of integers. For example, in a log10 scale: ``[2, 3, 4, 5, 6, 7, 8, 9]`` will place 8 logarithmically spaced minor ticks between each major tick. *linscalex*/*linscaley*: This allows the linear range (-*linthresh* to *linthresh*) to be stretched relative to the logarithmic range. Its value is the number of decades to use for each half of the linear range. For example, when *linscale* == 1.0 (the default), the space used for the positive and negative halves of the linear range will be equal to one decade in the logarithmic range. RDREg$@t linthreshxg@RFt linscalexgð?RHt linthreshyRIt linscaleygN( RLRMRNtAssertionErrorRRRPR8RSRTRQ(RRRR8RSRQRT((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRšs&     cCsb|jt|jƒƒƒ|jt|jƒƒ|jt|jƒ|jƒƒ|jt ƒƒdS(sn Set the locators and formatters to specialized versions for symmetrical log scaling. N( RR RRRR8R RQR!R(RR((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRÌs  cCs|jS(sE Return a :class:`SymmetricalLogTransform` instance. (RP(R((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyR×s( RRRR"RRR^RRR(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyRc‹s  2 RR;RacCstjƒ}|jƒ|S(N(t_scale_mappingtkeystsort(tnames((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pytget_scale_namesås  cKsQ|jƒ}|dkr!d}n|tkr@td|ƒ‚nt|||S(sC Return a scale class by name. ACCEPTS: [ %(names)s ] RsUnknown scale type '%s'N(tlowerRNRiRO(tscaleRR((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pyt scale_factoryës     s | RlcCs|t|jR@RARBRCRRR^RcRiRmRpRRuRrRytinterpdtupdateRDtreprtrstrip(((sJ/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/scale.pytsJ ")    ]! S      +