3 d:@sdZddlZddlmZmZddlmZddlmZddl m Z ddl m Z m Z mZmZdadad d ZGd d d e ZGd ddeZGdddeZGdddeZdS)z1 Trait definitions related to the numpy library. N)ComparisonMode DefaultValue) SequenceTypes) TraitError) TraitType)StrAnyIntFloatcCsJddl}|j|jdkrtS|j|jdkr0tS|jddkrBtStSdS)z4 Get the corresponding trait for a numpy dtype. rNr Z AllIntegerS)numpychar typecodesTFloatTIntrr )dtyper r6/tmp/pip-build-7vycvbft/traits/traits/trait_numeric.py dtype2traitsrcsXeZdZdZdddfdd Zdd Zd d Zd d ZddZddZ ddZ Z S) AbstractArrayz: Abstract base class for defining numpy-based arrays. NFunsafe)castingc  sy ddl}Wntk r(tdYnXddlmamad|d<|jdtj|dk rtj dt |dk r~||kr~tdn|}|dk ry|j |}Wn t k rtd |YnX|dk rpt |trhx|D]} | dkst| tkst | trZt| d krZt| dtkrZ| ddkrZ| d dkst| d tkrZ| d| d krZqtd qWntd |dkr|j||}||_ ||_||_||_tj|f|dS) NrzMUsing Array or CArray trait types requires the numpy package to be installed.)asarrayndarrayTarraycomparison_modez4typecode is a deprecated argument; use dtype insteadzHInconsistent usage of the dtype and typecode arguments; use dtype alone.z%could not convert %r to a numpy dtyperzshape should be a list or tuple)r ImportErrorrrr setdefaultridentitywarningswarnDeprecationWarningr TypeError isinstancertypeintlen_default_for_dtype_and_shapeshapecoercersuper__init__) selfrr*valuer+typecodermetadatar item) __class__rrr-3sX           zAbstractArray.__init__c Cs"yt|tsFt|ts&|j||||jdk r>t||j}nt|}|jdk rn|j|jkrn|j|j|jd}|j}|dkr|S|j}t |t |krxft |D]V\}}||}|dk rt |t kr||krPq||dks|ddk r||dkrPqW|SWn YnX|j|||dS)z4 Validates that the value is a valid array. N)rrr) r%rrerrorrrZastyperr*r( enumerater&r') r.objectnamer/Z trait_shapeZ value_shapeiZdimr2rrrvalidates6     zAbstractArray.validatecCsd}}|jdk rzg}xT|jD]J}|dkr0d}n.t|tk r^|ddkrVd|d}nd|}|j|qWdt|f}|jdk rd |j}d ||fS) z: Returns descriptive information about the trait. N*rz%d..rz%d..%dz with shape %sz of %s valuesz an array%s%s)r*r&r'appendtupler)r.rr*r2rrrinfos      zAbstractArray.infocCsd}d}|jdkrd}|jpd}|jdk rRt|jdkrRddlm}|||d}nDddlm}|jdkrnt}n t |j}|||j pg|j pd ||d }|S) z6 Returns the default UI editor for the trait. NFTrr) ArrayEditor)auto_set enter_set) TupleEditorr)typeslabelscolsr@rA) r@rAr*r(Z traitsui.apir?rBrr rrDrE)r.Zeditorr@rAr?rBrCrrr create_editors&      zAbstractArray.create_editorcCs tj|j|jdd|jfdffS)zh Returns the default value constructor for the type (called from the trait factory. N)rcallable_and_argscopy_default_valuer9 default_value)r.rrrget_default_valueszAbstractArray.get_default_valuecCs|jS)z Returns a copy of the default value (called from the C code on first reference to a trait with no current value). )copy)r.r/rrrrHsz AbstractArray.copy_default_valuecCs~ddlm}|dkrt}n|}|dkr2|d|}nHg}x8|D]0}|dkrNd}nt|tkrb|d}|j|q Invent a suitable default value for a given dtype and shape. r)zerosNr)r)r rLr'r&rr<)r.rr*rLdtr/sizer2rrrr)s     z*AbstractArray._default_for_dtype_and_shape)NNNFN) __name__ __module__ __qualname____doc__r-r9r>rFrJrHr) __classcell__rr)r3rr/sP*  rcs(eZdZdZdddfdd ZZS)Arraya A trait type whose value must be a NumPy array. An Array trait allows only upcasting of assigned values that are already numpy arrays. It automatically casts tuples and lists of the right shape to the specified *dtype* (just like numpy's **array** does). The default value is either the *value* argument or ``zeros(min(shape))``, where ``min(shape)`` refers to the minimum shape allowed by the array. If *shape* is not specified, the minimum shape is (0,). Parameters ---------- dtype : a numpy dtype (e.g., int32) The type of elements in the array; if omitted, no type-checking is performed on assigned values. shape : a tuple Describes the required shape of any assigned value. Wildcards and ranges are allowed. The value None within the *shape* tuple means that the corresponding dimension is not checked. (For example, ``shape=(None,3)`` means that the first dimension can be any size, but the second must be 3.) A two-element tuple within the *shape* tuple means that the dimension must be in the specified range. The second element can be None to indicate that there is no upper bound. (For example, ``shape=((3,5),(2,None))`` means that the first dimension must be in the range 3 to 5 (inclusive), and the second dimension must be at least 2.) value : numpy array A default value for the array. casting : str Casting rule for the array's dtype. If ``dtype`` is set, a value can only be assigned if it passes the casting rule. Values can be: - "no": No casting is allowed - "equiv": Only byte-order changes are allowed - "safe": Only allow casting that fully preserves values (e.g. "float32" to "float64") - "same-kind": Only safe casts or casts within a kind (e.g. "float64" to "float32") are allowed - "unsafe": Any casting is allowed Default is "unsafe". Nr)rc s$tj|||df||d|dS)NF)r0r)r,r-)r.rr*r/r0rr1)r3rrr-Gs zArray.__init__)NNNN)rOrPrQrRr-rSrr)r3rrTs ,rTcs(eZdZdZdddfdd ZZS)CArraya A coercing trait type whose value is a NumPy array. The trait returned by CArray() is similar to that returned by Array(), except that it allows both upcasting and downcasting of assigned values that are already numpy arrays. It automatically casts tuples and lists of the right shape to the specified *dtype* (just like numpy's **array** does). The default value is either the *value* argument or ``zeros(min(shape))``, where ``min(shape)`` refers to the minimum shape allowed by the array. If *shape* is not specified, the minimum shape is (0,). Parameters ---------- dtype : a numpy dtype (e.g., int32) The type of elements in the array. shape : a tuple Describes the required shape of any assigned value. Wildcards and ranges are allowed. The value None within the *shape* tuple means that the corresponding dimension is not checked. (For example, ``shape=(None,3)`` means that the first dimension can be any size, but the second must be 3.) A two-element tuple within the *shape* tuple means that the dimension must be in the specified range. The second element can be None to indicate that there is no upper bound. (For example, ``shape=((3,5),(2,None))`` means that the first dimension must be in the range 3 to 5 (inclusive), and the second dimension must be at least 2.) value : numpy array A default value for the array. casting : str Casting rule for the array's dtype. If ``dtype`` is set, a value can only be assigned if it passes the casting rule. Values can be: - "no": No casting is allowed - "equiv": Only byte-order changes are allowed - "safe": Only allow casting that fully preserves values (e.g. "float32" to "float64") - "same-kind": Only safe casts or casts within a kind (e.g. "float64" to "float32") are allowed - "unsafe": Any casting is allowed Default is "unsafe". Nr)rc s$tj|||df||d|dS)NT)r0r)r,r-)r.rr*r/r0rr1)r3rrr-s zCArray.__init__)NNNN)rOrPrQrRr-rSrr)r3rrU\s ,rUcs<eZdZdZfddZfddZddZdd ZZS) ArrayOrNonez A coercing trait whose value may be either a NumPy array or None. This trait is designed to avoid the comparison issues with numpy arrays that can arise from the use of constructs like Union(None, Array). The default value is None. cs |jdtjtj||dS)Nr)rrr r,r-)r.argsr1)r3rrr-szArrayOrNone.__init__cs|dkr |Stj|||S)N)r,r9)r.r6r7r/)r3rrr9szArrayOrNone.validatecCs:|j}|dkrtj|fStj|j|jdd|fdffSdS)N)rIrZconstantrGrHr9)r.ZdvrrrrJs zArrayOrNone.get_default_valuecCsdS)Nr)r.rr*rrrr)sz(ArrayOrNone._default_for_dtype_and_shape) rOrPrQrRr-r9rJr)rSrr)r3rrVs   rV)rRr! constantsrrZ trait_baserZ trait_errorsrZ trait_typerZ trait_typesrr r rr rrrrrrTrUrVrrrr s   kCC