dq0ddlmZddlZddlmZddlmZmZmZm Z ddl m Z m Z m Z ddlZddlZddlmZmZmZddlmZmZddlmZdd lmZmZdd lmZdd l m!Z!m"Z"d Z#d Z$e rYddl%m&Z&ddl'm(Z(e)e)edfe e*e*fZ+e edfZ,ee e"fZ-e e e fZ.e e/eedfZ0e e(e&fZ1dBdZ2dCdDdZ3dCdEdZ4dFdZ5dCdGdZ6 dHdId#Z7 dJdKd-Z8dLd0Z9dLd1Z: dMdNd8Z; dMdOd<Z< dPdQd>Z=d?Z>d@Z?dAZ@dS)R) annotationsN) defaultdict)HashableIterableMappingMutableMapping) TYPE_CHECKINGAnyUnion)stringstimes variables)SerializationWarningpop_to)indexing)_contains_datetime_like_objectscontains_cftime_datetimes)is_duck_dask_array) IndexVariableVariable) bounds grid_mapping climatologygeometrynode_coordinates node_countpart_node_count interior_ring cell_measures formula_terms)rr AbstractDataStoreDataset.varrreturn T_VarTuplec~|j|j|j|jfSN)dimsdataattrscopyencoding)r%s 2lib/python3.11/site-packages/xarray/conventions.py _var_as_tupler03s/ 8SXsy~~//1B1B1D1D DDnameT_Namenp.dtypec|jjdkrtd|jdkrt jt S|d|jz}t|trtj tSt|trtj tSt j |j}|jdkr|Std|)z]Given an object array with no missing values, infer its dtype from its first element Oz1infer_type must be called on a dtype=object arrayr)rzXunable to infer dtype on variable {!r}; xarray cannot serialize arbitrary Python objects)dtypekind TypeErrorsizenpfloatndim isinstancebytesr create_vlen_dtypestrarray ValueErrorformat)rBr2elementr7s r/ _infer_dtyperF7s {3KLLL zQxD5:%&G'5!!.(/// GS ! !.(--- HW   #E zS  44:F4LL  r1Nonect|trNt|tjr$t d|dSdS)Nzvariable {!r} is a MultiIndex, which cannot yet be serialized to netCDF files. Instead, either use reset_index() to convert MultiIndex levels into coordinate variables instead or use https://cf-xarray.readthedocs.io/en/latest/coding.html.)r>rto_indexpd MultiIndexNotImplementedErrorrD)r%r2s r/ensure_not_multiindexrMSss#}%% *S\\^^R]*S*S ! MNTVNN        r1r7np.typing.DTypeLikecDtj|j|}||d<|S)zCreate a copy of an array with the given dtype. We use this instead of np.array() to ensure that custom object dtypes end up on the resulting array. .)r;emptyshape)r+r7results r/_copy_with_dtyperS_s% Xdj% ( (FF3K Mr1c|jjdkrt|\}}}}tj|j|St |rAt jd|t| }tj |}| r||}t||}tj|rd} nntj|rd} nWt#j|t"jst#jt(}|t"j} t/||}| ||<nt/|t||}|jjdks|jjsJt3||||d}|S)Nr6avariable {} has data in the form of a dask array with dtype=object, which means it is being loaded into memory to determine a data type that can be safely stored on disk. To avoid this, coerce this variable to a fixed-size dtype with astype() before saving it.r1)r7T)fastpath)r7r8r0r check_vlen_dtyperwarningswarnrDrcomputerJisnullanyrFis_bytes_dtypeis_unicode_dtyper; issubdtypefloatingr<typenanrSmetadatar) r%r2r*r+r,r.missingnon_missing_valuesinferred_dtype fill_values r/ensure_dtype_not_objectrhjs y~&3C&8&8#dE8  #DJ / / ;J d # # " M239&,,$    <<>>D)D// ;;== J!%wh )* "hello" mask_and_scale : bool Lazily scale (using scale_factor and add_offset) and mask (using _FillValue). If the _Unsigned attribute is present treat integer arrays as unsigned. decode_times : bool Decode cf times ("hours since 2000-01-01") to np.datetime64. decode_endianness : bool Decode arrays from non-native to native endianness. stack_char_dim : bool Whether to stack characters into bytes along the last dimension of this array. Passed as an argument because we need to look at the full dataset to figure out if this is appropriate. use_cftime : bool, optional Only relevant if encoded dates come from a standard calendar (e.g. "gregorian", "proleptic_gregorian", "standard", or not specified). If None (default), attempt to decode times to ``np.datetime64[ns]`` objects; if this is not possible, decode times to ``cftime.datetime`` objects. If True, always decode times to ``cftime.datetime`` objects, regardless of whether or not they can be represented using ``np.datetime64[ns]`` objects. If False, always decode times to ``np.datetime64[ns]`` objects; if this is not possible raise an error. Returns ------- out : Variable A variable holding the decoded equivalent of var. Nrl)rr7T)r.rV)rr7r CharacterArrayCoderdecodeEncodedStringCoderrrqrpror rnrmisnative EndianCoderrtunpack_for_decoding setdefaultrrLazilyIndexedArrayr)r2r%rzr{r|r}r~rroriginal_dtyperw dimensionsr+ attributesr.s r/decode_cf_variablersr's++ YN'7  G-//66s6FFC(**11#66/  * , ,  ! # #  ( * *  / /E ,,s,..CC>$&&--c-==R#z:::AA#DAQQ#!3##%%,,S11  " " ) )# . .C-6-J3-O-O*Jj( 000 d # #1*400 Jj8d S S SSr1r T_VariablescR|jD]}|j}|d}t|tod|v}|r]d|vrY|d|vrO||dj}|d|dd|vr|d|ddS)aAdds time attributes to time bounds variables. Variables handling time bounds ("Cell boundaries" in the CF conventions) do not necessarily carry the necessary attributes to be decoded. This copies the attributes from the time variable to the associated boundaries. See Also: http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/ cf-conventions.html#cell-boundaries https://github.com/pydata/xarray/issues/2565 unitssincercalendarN)valuesr,getr>rAr)rvr,rhas_date_units bounds_attrss r/_update_bounds_attributesr+s"Y    K K '""#E3//DGu4D  Kh%//X)++(x9? ''w@@@&& ++Jj8IJJJ K Kr1c|jD]\}}|j}|j}d|vo d|dv}tj|jtjpt|}|rD|sBd|vr>|d|vr4tj d ||dt|r]d|vrY|d|vrO||dj}| d|dd|vr| d|ddS)aAdds time encoding to time bounds variables. Variables handling time bounds ("Cell boundaries" in the CF conventions) do not necessarily carry the necessary attributes to be decoded. This copies the encoding from the time variable to the associated bounds variable so that we write CF-compliant files. See Also: http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/ cf-conventions.html#cell-boundaries https://github.com/pydata/xarray/issues/2565 rrra3Variable '{0}' has datetime type and a bounds variable but {0}.encoding does not have units specified. The units encodings for '{0}' and '{1}' will be determined independently and may not be equal, counter to CF-conventions. If this is a concern, specify a units encoding for '{0}' before writing to a file.rN) itemsr,r.r;r_r7 datetime64rrXrYrD UserWarningr)rr2rr,r.ris_datetime_typebounds_encodings r/_update_bounds_encodingrHsY"#9?$$QQa: H,MHW.stackablesW )  5#C(  Aw|s""cQVBZ&7&7uu'8tr1NS1rr)rzr{r|r~rrzFailed to decode variable z: )T coordinatesallrc3 K|]}|vV dSr)).0krs r/ z&decode_cf_variables..s'??!qI~??????r1rc@g|]}|D]}|Sr)split)rpart role_or_names r/ z'decode_cf_variables..sG+++ $04 ++!-)++++r1:z Attribute sz malformed stacklevelc3 K|]}|vV dSr)r)rvar_namers r/rz&decode_cf_variables..s(KKX8y0KKKKKKr1cg|]}|v| Srr)r proj_namers r/rz'decode_cf_variables..s.<<< )( 99&999r1zVariable(s) referenced in z not in variables: )rrr&rj)rlistrr*appendsetr>rArrr7r=r Exceptionrar,rrr.updatervCF_RELATED_DATA_NEEDS_PARSINGlenrXrYrdictpop)rrrzr{r|rrrrrdr coord_namesnew_varsrr~e var_attrs coord_strvar_coord_namesrxattr_val var_namesroles_and_names referenced_vars_not_in_variablescrdsrs` @r/decode_cf_variablesrzsN %T** Y   ,, , ,A q ! ( ( + + + + ,%%K.#&&()  ((N-!),,,H !!>->-1      &4 &  & !&*%%  C,"3-)-%!1   HQKK C C C$q''AqAAaAABB B C 8 8 8  )I ))%m4 "+//"3"3?????????8:CHQK(7!-0&&777 E ! !, - -  ))(3H (EEE$,NN$4$4 ++(0s(;(;+++ //!3q88$M DY D D D DQR%4ADqD$9 KKKKKKKKK :B ,Y7#**95555<<<<-6<<<8 ! }}}}Yy}}'("),)JNN=$$G$GMM)*%% ~~m,,4::<<((( Z ,,s+D D3D..D3objT_DatasetOrAbstractstorer$c `ddlm}ddlm} t || r1|j} |j} t|j} |j } |j }n`t ||rA| \} } t} |j } | }ntdt| | ||||||| \} } }| | | }||| | }|| ||_ |S)aDecode the given Dataset or Datastore according to CF conventions into a new Dataset. Parameters ---------- obj : Dataset or DataStore Object to decode. concat_characters : bool, optional Should character arrays be concatenated to strings, for example: ["h", "e", "l", "l", "o"] -> "hello" mask_and_scale : bool, optional Lazily scale (using scale_factor and add_offset) and mask (using _FillValue). decode_times : bool, optional Decode cf times (e.g., integers since "hours since 2000-01-01") to np.datetime64. decode_coords : bool or {"coordinates", "all"}, optional Controls which variables are set as coordinate variables: - "coordinates" or True: Set variables referred to in the ``'coordinates'`` attribute of the datasets or individual variables as coordinate variables. - "all": Set variables referred to in ``'grid_mapping'``, ``'bounds'`` and other attributes as coordinate variables. drop_variables : str or iterable, optional A variable or list of variables to exclude from being parsed from the dataset. This may be useful to drop variables with problems or inconsistent values. use_cftime : bool, optional Only relevant if encoded dates come from a standard calendar (e.g. "gregorian", "proleptic_gregorian", "standard", or not specified). If None (default), attempt to decode times to ``np.datetime64[ns]`` objects; if this is not possible, decode times to ``cftime.datetime`` objects. If True, always decode times to ``cftime.datetime`` objects, regardless of whether or not they can be represented using ``np.datetime64[ns]`` objects. If False, always decode times to ``np.datetime64[ns]`` objects; if this is not possible raise an error. decode_timedelta : bool, optional If True, decode variables and coordinates with time units in {"days", "hours", "minutes", "seconds", "milliseconds", "microseconds"} into timedelta objects. If False, leave them encoded as numbers. If None (default), assume the same value of decode_time. Returns ------- decoded : Dataset rr!r#z,can only decode Dataset or DataStore objects)rrr)r,)xarray.backends.commonr"xarray.core.datasetr$r> _variablesr,rcoords_closer.loadclose get_encodingr9r set_coordsunion intersection set_close)rrzr{r|rrrrr"r$varsr, extra_coordsrr.rdss r/ decode_cfrsWt988888++++++#w H~ 3:  < C* + +Hhhjj euu  ##%%FGGG2  %)   D% U # # #B {((66CCDII J JBLLBK Ir1tuple[T_Variables, T_Attrs]c8t|||||\}}}||fS)a{ Decode a set of CF encoded variables and attributes. Parameters ---------- variables : dict A dictionary mapping from variable name to xarray.Variable attributes : dict A dictionary mapping from attribute name to value concat_characters : bool Should character arrays be concatenated to strings, for example: ["h", "e", "l", "l", "o"] -> "hello" mask_and_scale : bool Lazily scale (using scale_factor and add_offset) and mask (using _FillValue). decode_times : bool Decode cf times ("hours since 2000-01-01") to np.datetime64. Returns ------- decoded_variables : dict A dictionary mapping from variable name to xarray.Variable objects. decoded_attributes : dict A dictionary mapping from attribute name to values. See Also -------- decode_cf_variable )r)rrrzr{r|_s r/ cf_decoderrMs4H 3:0.,  Iz1 j  r1ct|}t|D]_}t|trHd|vrDt jd|td||`| }tt}t|D]|j }|j D]\}||vrI|j vr@t|tj kr|| tfdtDr* |d|j D}t}|j D]\}} | j} | j} d| vrd| vrt%d|d d| vr| dd| vrB| d-| dd| ddt+| | dp| d} | s6||r.dfd ||D} | r| | d<d| vr-|| d|||r]t5|}d|vrt jd |d tn+dt7t||d<||fS) N zcoordinate {!r} has a space in its name, which means it cannot be marked as a coordinate on disk and will be saved as a data variable insteadrc3bK|])}|jvoj|vV*dSr))r.r)rrx coord_namers r/rz&_encode_coordinates..sVQZ'SJ!*..:S:S,Sr1cBi|]\}}||dS)F)deep)r-rrrs r/ z'_encode_coordinates..s,EEE41aAFFF&&EEEr1rz<'coordinates' found in both attrs and encoding for variable .c3>K|]}|vt|VdSr))rA)rrnot_technically_coordinatess r/rz&_encode_coordinates..sA((%@@@J@@@@((r1z$cannot serialize global coordinates zu because the global attribute 'coordinates' already exists. This may prevent faithful roundtrippingof xarray datasets)rrr>rArXrYrDrdiscardr-rr*raddr\rvr.r,rCrrrjoinrrdifference_updatermap)rrnon_dim_coord_namesr2global_coordinatesvariable_coordinates target_dimsrwritten_coordsr%r.r, coords_strcoordinates_textrrrs @@@r/_encode_coordinatesr ws122()) . . dC  .SD[[ M3396$<<$      ' ' - - -,1133&s++"%%%)77  +0 #IO%% 7 7DAq,,,QVOO $$AF 33$Q'++J777!0 7,// ;;;"**:666 7FE?9?3D3DEEEIUUN$Y_&&!@!@ c<  E ! !mx&?&?XtXXX  U " " -((0(( ]++3 IImT * * * LL - - -  He];;Wuyy?W?W  8248 8"xx(((("6t"<(((      8'7m$ E ! !  ! !% "6"<"<">"> ? ? ?((888 O*%% J & & M&7I&&&%     ),S:L1M1M(N(NJ} % j  r1ct|jt|jz }t|j|j|S)a1Encode coordinates on the given dataset object into variable specific and global attributes. When possible, this is done according to CF conventions. Parameters ---------- dataset : Dataset Object to encode. Returns ------- variables : dict attrs : dict )r)rrr*r rr,)datasetrs r/encode_dataset_coordinatesr sG gn--GL0A0AA GM?R   r1ct|d|jD}|D]}d|jvr |jdnd}|rc||vr_dD]\}|||jvrK||jvrB||j||j|kr ||j|]||fS)a Encode a set of CF encoded variables and attributes. Takes a dicts of variables and attributes and encodes them to conform to CF conventions as much as possible. This includes masking, scaling, character array handling, and CF-time encoding. Parameters ---------- variables : dict A dictionary mapping from variable name to xarray.Variable attributes : dict A dictionary mapping from attribute name to value Returns ------- encoded_variables : dict A dictionary mapping from variable name to xarray.Variable, encoded_attributes : dict A dictionary mapping from attribute name to value See Also -------- decode_cf_variable, encode_cf_variable c8i|]\}}|t||S)rl)ryrs r/rzcf_encoder.. s,OOOTQ%aa000OOOr1rN) r standard_nameaxispositiver long_name leap_month leap_year month_lengths)rrrr,r)rrrr%rattrs r/ cf_encoderrs8I&&&OO_Y_=N=NOOOH  99(0CI(=(=8$$4  9f((  9 98F+111dci6G6G'-d3syFF (.224888 Z r1)r%rr&r'r))r2r3r&r4)r%rr2r3r&rG)r7rN)r%rr2r3r&r)TN)r%rrirjr2r3r&r)TTTTTNN)r2rr%rrzrjr{rjr|rjr}rjr~rjrrrrr&r)rrr&rG)TTTTNNN)rrrrrzrjr{rjr|rjrrjrrrrrrr&r)rrrzrjr{rjr|rjrrjrrrrrrr&r$)TTT) rrrrrzrjr{rjr|rjr&r)A __future__rrX collectionsrcollections.abcrrrrtypingr r r numpyr;pandasrJ xarray.codingr r rxarray.coding.variablesrr xarray.corerxarray.core.commonrrxarray.core.pycompatrxarray.core.variablerrrvrrr"rr$tuplerr'r3rrrArrr0rFrMrSrhryrrrrrrr r rrr1r/r&s""""""######GGGGGGGGGGGG,,,,,,,,,,3333333333@@@@@@@@ 43333388888888 !  A888888++++++uXs]+S$<=J 8T> "F#x-(KS#X&GC(!3T9:O$W.?%?@EEEE8      /////f<@)))))^#""$(`T`T`T`T`TFKKKK:/Q/Q/Q/Qj#&*"$(p-p-p-p-p-j#&*"$(]]]]]F# '!'!'!'!'!T]!]!]!@,4 4 4 4 4 r1