Commons Math example source code file (MessagesResources_fr.java)
The Commons Math MessagesResources_fr.java source code/*
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* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math;
import java.util.ListResourceBundle;
/**
* French localization message resources for the commons-math library.
* @version $Revision: 927009 $ $Date: 2010-03-24 07:14:07 -0400 (Wed, 24 Mar 2010) $
* @since 1.2
*/
public class MessagesResources_fr
extends ListResourceBundle {
/** Non-translated/translated messages arrays. */
private static final Object[][] CONTENTS = {
// org.apache.commons.math.util.MathUtils
{ "must have n >= k for binomial coefficient (n,k), got n = {0}, k = {1}",
"n doit \u00eatre sup\u00e9rieur ou \u00e9gal \u00e0 k " +
"pour le coefficient du bin\u00f4me (n,k), or n = {0}, k = {1}" },
{ "must have n >= 0 for binomial coefficient (n,k), got n = {0}",
"n doit \u00eatre positif pour le coefficient du bin\u00f4me (n,k), or n = {0}" },
{ "must have n >= 0 for n!, got n = {0}",
"n doit \u00eatre positif pour le calcul de n!, or n = {0}" },
{ "overflow: gcd({0}, {1}) is 2^31",
"d\u00e9passement de capacit\u00e9 : le PGCD de {0} et {1} vaut 2^31" },
{ "overflow: gcd({0}, {1}) is 2^63",
"d\u00e9passement de capacit\u00e9 : le PGCD de {0} et {1} vaut 2^63" },
{ "overflow: lcm({0}, {1}) is 2^31",
"d\u00e9passement de capacit\u00e9 : le MCM de {0} et {1} vaut 2^31" },
{ "overflow: lcm({0}, {1}) is 2^63",
"d\u00e9passement de capacit\u00e9 : le MCM de {0} et {1} vaut 2^63" },
{ "cannot raise an integral value to a negative power ({0}^{1})",
"impossible d''\u00e9lever une valeur enti\u00e8re " +
"\u00e0 une puissance n\u00e9gative ({0}^{1})" },
{ "invalid rounding method {0}, valid methods: {1} ({2}), {3} ({4}), {5} ({6}), {7} ({8}), {9} ({10}), {11} ({12}), {13} ({14}), {15} ({16})",
"m\u00e9thode d''arondi {0} invalide, m\u00e9thodes valides : {1} ({2}), {3} ({4}), {5} ({6}), {7} ({8}), {9} ({10}), {11} ({12}), {13} ({14}), {15} ({16})" },
{ "Cannot normalize to an infinite value",
"impossible de normaliser vers une valeur infinie" },
{ "Cannot normalize to NaN",
"impossible de normaliser vers NaN" },
{ "Array contains an infinite element, {0} at index {1}",
"le tableau contient l''\u00e9l\u00e9ment infini {0} \u00e0 l''index {1}" },
// org.apache.commons.math.FunctionEvaluationException
{ "evaluation failed for argument = {0}",
"erreur d''\u00e9valuation pour l''argument {0}" },
// org.apache.commons.math.DuplicateSampleAbscissaException
{ "Abscissa {0} is duplicated at both indices {1} and {2}",
"Abscisse {0} dupliqu\u00e9e aux indices {1} et {2}" },
// org.apache.commons.math.ConvergenceException
{ "Convergence failed",
"\u00c9chec de convergence" },
// org.apache.commons.math.ArgumentOutsideDomainException
{ "Argument {0} outside domain [{1} ; {2}]",
"Argument {0} hors du domaine [{1} ; {2}]" },
// org.apache.commons.math.MaxIterationsExceededException
{ "Maximal number of iterations ({0}) exceeded",
"Nombre maximal d''it\u00e9rations ({0}) d\u00e9pass\u00e9" },
// org.apache.commons.math.MaxEvaluationsExceededException
{ "Maximal number of evaluations ({0}) exceeded",
"Nombre maximal d''\u00e9valuations ({0}) d\u00e9pass\u00e9" },
// org.apache.commons.math.analysis.interpolation.SplineInterpolator
// org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
// org.apache.commons.math.DimensionMismatchException
// org.apache.commons.math.optimization.LeastSquaresConverter
// org.apache.commons.math.optimization.direct.DirectSearchOptimizer
// org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
// org.apache.commons.math.ode.ContinuousOutputModel
// org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
// org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
// org.apache.commons.math.stat.inference.ChiSquareTestImpl
// org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
{ "dimension mismatch {0} != {1}",
"dimensions incompatibles {0} != {1}" },
// org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
{ "no data",
"aucune donn\u00e9e" },
// org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
{ "brightness exponent should be positive or null, but got {0}",
"l''exposant de brillance devrait \u00eatre positif ou null, or e = {0}" },
{ "number of microsphere elements must be positive, but got {0}",
"le nombre d''\u00e9l\u00e9ments de la microsph\u00e8re devrait \u00eatre positif, or n = {0}" },
// org.apache.commons.math.linear.decomposition.NotPositiveDefiniteMatrixException
{ "not positive definite matrix",
"matrice non d\u00e9finie positive" },
// org.apache.commons.math.linear.decomposition.NotSymmetricMatrixException
{ "not symmetric matrix",
"matrice non symm\u00e9trique" },
// org.apache.commons.math.fraction.FractionConversionException
{ "Unable to convert {0} to fraction after {1} iterations",
"Impossible de convertir {0} en fraction apr\u00e8s {1} it\u00e9rations" },
{ "Overflow trying to convert {0} to fraction ({1}/{2})",
"D\u00e9passement de capacit\u00e9 lors de la conversion de {0} en fraction ({1}/{2})" },
// org.apache.commons.math.fraction.BigFraction
{ "numerator is null",
"le num\u00e9rateur est null" },
{ "denimonator is null",
"le d\u00e9nominateur est null" },
{ "denominator must be different from 0",
"le d\u00e9nominateur doit \u00eatre diff\u00e9rent de 0" },
{ "cannot convert NaN value",
"les valeurs NaN ne peuvent \u00eatre converties" },
{ "cannot convert infinite value",
"les valeurs infinies ne peuvent \u00eatre converties" },
// org.apache.commons.math.fraction.AbstractFormat
{ "denominator format can not be null",
"le format du d\u00e9nominateur ne doit pas \u00eatre nul" },
{ "numerator format can not be null",
"le format du num\u00e9rateur ne doit pas \u00eatre nul" },
// org.apache.commons.math.fraction.FractionFormat
{ "cannot convert given object to a fraction number: {0}",
"impossible de convertir l''objet sous forme d''un nombre rationnel : {0}" },
// org.apache.commons.math.fraction.FractionFormat
// org.apache.commons.math.fraction.BigFractionFormat
{ "unparseable fraction number: \"{0}\"",
"\u00e9chec d''analyse du nombre rationnel \"{0}\"" },
{ "cannot format given object as a fraction number",
"impossible de formater l''objet sous forme d''un nombre rationnel" },
// org.apache.commons.math.fraction.ProperFractionFormat
// org.apache.commons.math.fraction.ProperBigFractionFormat
{ "whole format can not be null",
"le format complet ne doit pas \u00eatre nul" },
// org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
{ "function is null",
"la fonction est nulle" },
{ "bad value for maximum iterations number: {0}",
"valeur invalide pour le nombre maximal d''it\u00e9rations : {0}" },
{ "invalid bracketing parameters: lower bound={0}, initial={1}, upper bound={2}",
"param\u00e8tres d''encadrement invalides : borne inf\u00e9rieure = {0}, valeur initiale = {1}, borne sup\u00e9rieure = {2}" },
{ "number of iterations={0}, maximum iterations={1}, initial={2}, lower bound={3}, upper bound={4}," +
" final a value={5}, final b value={6}, f(a)={7}, f(b)={8}",
"nombre d''it\u00e9rations = {0}, it\u00e9rations maximum = {1}, valeur initiale = {2}," +
" borne inf\u00e9rieure = {3}, borne sup\u00e9rieure = {4}," +
" valeur a finale = {5}, valeur b finale = {6}, f(a) = {7}, f(b) = {8}" },
// org.apache.commons.math.analysis.solvers.LaguerreSolver
{ "polynomial degree must be positive: degree={0}",
"le polyn\u00f4me doit \u00eatre de degr\u00e9 positif : degr\u00e9 = {0}" },
// org.apache.commons.math.analysis.solvers.SecantSolver
{ "function values at endpoints do not have different signs, endpoints: [{0}, {1}], values: [{2}, {3}]",
"les valeurs de la fonctions aux bornes sont de m\u00eame signe, bornes : [{0}, {1}], valeurs : [{2}, {3}]" },
// org.apache.commons.math.analysis.interpolation.SplineInterpolator
// org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
{ "{0} points are required, got only {1}",
"{0} sont n\u00e9cessaires, seuls {1} ont \u00e9t\u00e9 fournis" },
// org.apache.commons.math.analysis.interpolation.SplineInterpolator
{ "points {0} and {1} are not strictly increasing ({2} >= {3})",
"les points {0} et {1} ne sont pas strictement croissants ({2} >= {3})" },
{ "points {0} and {1} are not strictly decreasing ({2} <= {3})",
"les points {0} et {1} ne sont pas strictement d\u00e9croissants ({2} <= {3})" },
{ "points {0} and {1} are not increasing ({2} > {3})",
"les points {0} et {1} ne sont pas croissants ({2} > {3})" },
{ "points {0} and {1} are not decreasing ({2} < {3})",
"les points {0} et {1} ne sont pas d\u00e9croissants ({2} < {3})" },
// org.apache.commons.math.analysis.interpolation.LoessInterpolator
{ "bandwidth must be in the interval [0,1], but got {0}",
"la largeur de bande doit \u00eatre dans l''intervalle [0, 1], alors qu'elle vaut {0}" },
{ "the number of robustness iterations must be non-negative, but got {0}",
"le nombre d''it\u00e9rations robuste ne peut \u00eatre n\u00e9gatif, alors qu''il est de {0}" },
{ "Loess expects the abscissa and ordinate arrays to be of the same size, " +
"but got {0} abscissae and {1} ordinatae",
"la r\u00e9gression Loess n\u00e9cessite autant d''abscisses que d''ordonn\u00e9es, " +
"mais {0} abscisses et {1} ordonn\u00e9es ont \u00e9t\u00e9 fournies" },
{ "Loess expects at least 1 point",
"la r\u00e9gression Loess n\u00e9cessite au moins un point" },
{ "the bandwidth must be large enough to accomodate at least 2 points. There are {0} " +
" data points, and bandwidth must be at least {1} but it is only {2}",
"la largeur de bande doit \u00eatre assez grande pour supporter au moins 2 points. Il y a {0}" +
"donn\u00e9es et la largeur de bande doit \u00eatre au moins de {1}, or elle est seulement de {2}" },
{ "all abscissae must be finite real numbers, but {0}-th is {1}",
"toutes les abscisses doivent \u00eatre des nombres r\u00e9els finis, mais l''abscisse {0} vaut {1}" },
{ "all ordinatae must be finite real numbers, but {0}-th is {1}",
"toutes les ordonn\u00e9es doivent \u00eatre des nombres r\u00e9els finis, mais l''ordonn\u00e9e {0} vaut {1}" },
{ "all weights must be finite real numbers, but {0}-th is {1}",
"tous les poids doivent \u00eatre des nombres r\u00e9els finis, mais le poids {0} vaut {1}" },
{ "the abscissae array must be sorted in a strictly increasing order, " +
"but the {0}-th element is {1} whereas {2}-th is {3}",
"les abscisses doivent \u00eatre en ordre strictement croissant, " +
"mais l''\u00e9l\u00e9ment {0} vaut {1} alors que l''\u00e9l\u00e9ment {2} vaut {3}" },
// org.apache.commons.math.util.ContinuedFraction
{ "Continued fraction convergents diverged to +/- infinity for value {0}",
"Divergence de fraction continue \u00e0 l''infini pour la valeur {0}" },
{ "Continued fraction convergents failed to converge for value {0}",
"\u00c9chec de convergence de fraction continue pour la valeur {0}" },
{ "Continued fraction diverged to NaN for value {0}",
"Divergence de fraction continue \u00e0 NaN pour la valeur {0}"},
// org.apache.commons.math.util.DefaultTransformer
{ "Conversion Exception in Transformation, Object is null",
"Exception de conversion dans une transformation, l''objet est nul" },
{ "Conversion Exception in Transformation: {0}",
"Exception de conversion dans une transformation : {0}" },
// org.apache.commons.math.optimization.MultiStartOptimizer
{ "no optimum computed yet",
"aucun optimum n''a encore \u00e9t\u00e9 calcul\u00e9" },
// org.apache.commons.math.optimization.direct.DirectSearchOptimizer
{ "simplex must contain at least one point",
"le simplex doit contenir au moins un point" },
{ "equal vertices {0} and {1} in simplex configuration",
"sommets {0} et {1} \u00e9gaux dans la configuration du simplex" },
// org.apache.commons.math.estimation.AbstractEstimation
{ "maximal number of evaluations exceeded ({0})",
"nombre maximal d''\u00e9valuations d\u00e9pass\u00e9 ({0})" },
// org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
{ "unable to compute covariances: singular problem",
"impossible de calculer les covariances : probl\u00e8me singulier"},
{ "no degrees of freedom ({0} measurements, {1} parameters)",
"aucun degr\u00e9 de libert\u00e9 ({0} mesures, {1} param\u00e8tres)" },
// org.apache.commons.math.optimization.general.GaussNewtonOptimizer
{ "unable to solve: singular problem",
"r\u00e9solution impossible : probl\u00e8me singulier" },
// org.apache.commons.math.optimization.general.LevenbergMarquardtEstimator
{ "cost relative tolerance is too small ({0}), no further reduction in the sum of squares is possible",
"trop petite tol\u00e9rance relative sur le co\u00fbt ({0}), aucune r\u00e9duction de la somme des carr\u00e9s n''est possible" },
{ "parameters relative tolerance is too small ({0}), no further improvement in the approximate solution is possible",
"trop petite tol\u00e9rance relative sur les param\u00e8tres ({0}), aucune am\u00e9lioration de la solution approximative n''est possible" },
{ "orthogonality tolerance is too small ({0}), solution is orthogonal to the jacobian",
"trop petite tol\u00e9rance sur l''orthogonalit\u00e9 ({0}), la solution est orthogonale \u00e0 la jacobienne" },
{ "unable to perform Q.R decomposition on the {0}x{1} jacobian matrix",
"impossible de calculer la factorisation Q.R de la matrice jacobienne {0}x{1}" },
// org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
{ "unable to bracket optimum in line search",
"impossible d''encadrer l''optimum lors de la recherche lin\u00e9aire" },
// org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
{ "unable to first guess the harmonic coefficients",
"impossible de faire une premi\u00e8re estimation des coefficients harmoniques" },
// org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
{ "sample contains {0} observed points, at least {1} are required",
"l''\u00e9chantillon ne contient que {0} points alors qu''au moins {1} sont n\u00e9cessaires" },
// org.apache.commons.math.optimization.linear.NoFeasibleSolutionException
{ "no feasible solution",
"aucune solution r\u00e9alisable" },
// org.apache.commons.math.optimization.linear.UnboundedSolutionException
{ "unbounded solution",
"solution non born\u00e9e" },
// org.apache.commons.math.geometry.CardanEulerSingularityException
{ "Cardan angles singularity",
"singularit\u00e9 d''angles de Cardan" },
{ "Euler angles singularity",
"singularit\u00e9 d''angles d''Euler" },
// org.apache.commons.math.geometry.Rotation
{ "a {0}x{1} matrix cannot be a rotation matrix",
"une matrice {0}x{1} ne peut pas \u00eatre une matrice de rotation" },
{ "the closest orthogonal matrix has a negative determinant {0}",
"la matrice orthogonale la plus proche a un d\u00e9terminant n\u00e9gatif {0}" },
{ "unable to orthogonalize matrix in {0} iterations",
"impossible de rendre la matrice orthogonale en {0} it\u00e9rations" },
// org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
{ "minimal step size ({0,number,0.00E00}) reached, integration needs {1,number,0.00E00}",
"pas minimal ({0,number,0.00E00}) atteint, l''int\u00e9gration n\u00e9cessite {1,number,0.00E00}" },
{ "dimensions mismatch: state vector has dimension {0}, absolute tolerance vector has dimension {1}",
"incompatibilit\u00e9 de dimensions entre le vecteur d''\u00e9tat ({0}), et le vecteur de tol\u00e9rance absolue ({1})" },
{ "dimensions mismatch: state vector has dimension {0}, relative tolerance vector has dimension {1}",
"incompatibilit\u00e9 de dimensions entre le vecteur d''\u00e9tat ({0}), et le vecteur de tol\u00e9rance relative ({1})" },
// org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator,
// org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
{ "dimensions mismatch: ODE problem has dimension {0}, initial state vector has dimension {1}",
"incompatibilit\u00e9 de dimensions entre le probl\u00e8me ODE ({0}), et le vecteur d''\u00e9tat initial ({1})" },
{ "dimensions mismatch: ODE problem has dimension {0}, final state vector has dimension {1}",
"incompatibilit\u00e9 de dimensions entre le probl\u00e8me ODE ({0}), et le vecteur d''\u00e9tat final ({1})" },
{ "too small integration interval: length = {0}",
"intervalle d''int\u00e9gration trop petit : {0}" },
// org.apache.commons.math.ode.MultistepIntegrator
{ "{0} method needs at least one previous point",
"la m\u00e9thode {0} n\u00e9cessite au moins un point pr\u00e9c\u00e9dent" },
// org.apache.commons.math.ode.ContinuousOutputModel
// org.apache.commons.math.optimization.direct.DirectSearchOptimizer
{ "unexpected exception caught",
"exception inattendue lev\u00e9e" },
{ "propagation direction mismatch",
"directions de propagation incoh\u00e9rentes" },
{ "{0} wide hole between models time ranges",
"trou de longueur {0} entre les domaines temporels des mod\u00e8les" },
// org.apache.commons.math.optimization.direct.DirectSearchOptimizer
{ "none of the {0} start points lead to convergence",
"aucun des {0} points de d\u00e9part n''aboutit \u00e0 une convergence" },
// org.apache.commons.math.random.ValueServer
{ "unknown mode {0}, known modes: {1} ({2}), {3} ({4}), {5} ({6}), {7} ({8}), {9} ({10}) and {11} ({12})",
"mode {0} inconnu, modes connus : {1} ({2}), {3} ({4}), {5} ({6}), {7} ({8}), {9} ({10}) et {11} ({12})" },
{ "digest not initialized",
"mod\u00e8le empirique non initialis\u00e9" },
// org.apache.commons.math.random.EmpiricalDistributionImpl
{ "distribution not loaded",
"aucune distribution n''a \u00e9t\u00e9 charg\u00e9e" },
{ "no bin selected",
"aucun compartiment s\u00e9lectionn\u00e9" },
{ "input data comes from unsupported datasource: {0}, supported sources: {1}, {2}",
"les donn\u00e9es d''entr\u00e9e proviennent " +
"d''une source non support\u00e9e : {0}, sources support\u00e9es : {1}, {2}" },
// org.apache.commons.math.random.EmpiricalDistributionImpl
// org.apache.commons.math.random.ValueServer
{ "URL {0} contains no data",
"l''adresse {0} ne contient aucune donn\u00e9e" },
// org.apache.commons.math.random.AbstractRandomGenerator
// org.apache.commons.math.random.BitsStreamGenerator
{ "upper bound must be positive ({0})",
"la borne sup\u00e9rieure doit \u00eatre positive ({0})" },
// org.apache.commons.math.random.RandomDataImpl
{ "length must be positive ({0})",
"la longueur doit \u00eatre positive ({0})" },
{ "upper bound ({0}) must be greater than lower bound ({1})",
"la borne sup\u00e9rieure ({0}) doit \u00eatre sup\u00e9rieure" +
" \u00e0 la borne inf\u00e9rieure ({1})" },
{ "permutation k ({0}) exceeds n ({1})",
"la permutation k ({0}) d\u00e9passe n ({1})" },
{ "permutation k ({0}) must be positive",
"la permutation k ({0}) doit \u00eatre positive" },
{ "sample size ({0}) exceeds collection size ({1})",
"la taille de l''\u00e9chantillon ({0}) d\u00e9passe la taille de la collection ({1})" },
// org.apache.commons.math.linear.decomposition.EigenDecompositionImpl
{ "cannot solve degree {0} equation",
"impossible de r\u00e9soudre une \u00e9quation de degr\u00e9 {0}" },
{ "eigen decomposition of assymetric matrices not supported yet",
"la d\u00e9composition en valeurs/vecteurs propres de matrices " +
"non sym\u00e9triques n''est pas encore disponible" },
// org.apache.commons.math.linear.decomposition.NonSquareMatrixException
// org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
{ "a {0}x{1} matrix was provided instead of a square matrix",
"une matrice {0}x{1} a \u00e9t\u00e9 fournie \u00e0 la place d''une matrice carr\u00e9e" },
// org.apache.commons.math.linear.decomposition.SingularMatrixException
{ "matrix is singular",
"matrice singuli\u00e8re" },
// org.apache.commons.math.linear.decomposition.SingularValueDecompositionImpl
{ "cutoff singular value is {0}, should be at most {1}",
"la valeur singuli\u00e8re de coupure vaut {0}, elle ne devrait pas d\u00e9passer {1}" },
// org.apache.commons.math.linear.decomposition.CholeskyDecompositionImpl
// org.apache.commons.math.linear.decomposition.EigenDecompositionImpl
// org.apache.commons.math.linear.decomposition.LUDecompositionImpl
// org.apache.commons.math.linear.decomposition.QRDecompositionImpl
// org.apache.commons.math.linear.decomposition.SingularValueDecompositionImpl
{ "dimensions mismatch: got {0}x{1} but expected {2}x{3}",
"dimensions incoh\u00e9rentes : {0}x{1} \u00e0 la place de {2}x{3}" },
// org.apache.commons.math.linear.decomposition.CholeskyDecompositionImpl
// org.apache.commons.math.linear.decomposition.EigenDecompositionImpl
// org.apache.commons.math.linear.decomposition.LUDecompositionImpl
// org.apache.commons.math.linear.decomposition.QRDecompositionImpl
// org.apache.commons.math.linear.decomposition.SingularValueDecompositionImpl
// org.apache.commons.math.linear.ArrayRealVector
// org.apache.commons.math.linear.SparseRealVector
{ "vector length mismatch: got {0} but expected {1}",
"taille de vecteur invalide : {0} au lieu de {1} attendue" },
// org.apache.commons.math.linear.ArrayRealVector
// org.apache.commons.math.linear.ArrayFieldVector
// org.apache.commons.math.linear.SparseRealVector
{ "index {0} out of allowed range [{1}, {2}]",
"index {0} hors de la plage autoris\u00e9e [{1}, {2}]" },
{ "vector must have at least one element",
"un vecteur doit comporter au moins un \u00e9l\u00e9ment" },
{ "position {0} and size {1} don't fit to the size of the input array {2}",
"la position {0} et la taille {1} sont incompatibles avec la taille du tableau d''entr\u00e9e {2}"},
// org.apache.commons.math.linear.AbstractRealMatrix
// org.apache.commons.math.linear.AbstractFieldMatrix
{ "invalid row dimension: {0} (must be positive)",
"nombre de lignes invalide : {0} (doit \u00eatre positif)" },
{ "invalid column dimension: {0} (must be positive)",
"nombre de colonnes invalide : {0} (doit \u00eatre positif)" },
{ "matrix must have at least one row",
"une matrice doit comporter au moins une ligne" },
{ "matrix must have at least one column",
"une matrice doit comporter au moins une colonne" },
// org.apache.commons.math.linear.AbstractRealMatrix
// org.apache.commons.math.linear.AbstractFieldMatrix
// org.apache.commons.math.stat.inference.ChiSquareTestImpl
{ "some rows have length {0} while others have length {1}",
"certaines lignes ont une longueur de {0} alors que d''autres ont une longueur de {1}" },
// org.apache.commons.math.linear.MatrixUtils
{ "row index {0} out of allowed range [{1}, {2}]",
"index de ligne {0} hors de la plage autoris\u00e9e [{1}, {2}]" },
{ "column index {0} out of allowed range [{1}, {2}]",
"index de colonne {0} hors de la plage autoris\u00e9e [{1}, {2}]" },
{ "initial row {0} after final row {1}",
"ligne initiale {0} apr\u00e8s la ligne finale {1}" },
{ "initial column {0} after final column {1}",
"colonne initiale {0} apr\u00e8s la colonne finale {1}" },
{ "empty selected row index array",
"tableau des indices de lignes s\u00e9lectionn\u00e9es vide" },
{ "empty selected column index array",
"tableau des indices de colonnes s\u00e9lectionn\u00e9es vide" },
{ "{0}x{1} and {2}x{3} matrices are not addition compatible",
"les dimensions {0}x{1} et {2}x{3} sont incompatibles pour l'addition matricielle" },
{ "{0}x{1} and {2}x{3} matrices are not subtraction compatible",
"les dimensions {0}x{1} et {2}x{3} sont incompatibles pour la soustraction matricielle" },
{ "{0}x{1} and {2}x{3} matrices are not multiplication compatible",
"les dimensions {0}x{1} et {2}x{3} sont incompatibles pour la multiplication matricielle" },
// org.apache.commons.math.linear.BlockRealMatrix
{ "wrong array shape (block length = {0}, expected {1})",
"forme de tableau erron\u00e9e (bloc de longueur {0} au lieu des {1} attendus)" },
// org.apache.commons.math.complex.Complex
{ "cannot compute nth root for null or negative n: {0}",
"impossible de calculer la racine ni\u00e8me pour n n\u00e9gatif ou nul : {0}" },
// org.apache.commons.math.complex.ComplexFormat
{ "unparseable complex number: \"{0}\"",
"\u00e9chec d''analyse du nombre complexe \"{0}\"" },
{ "cannot format a {0} instance as a complex number",
"impossible de formater une instance de {0} comme un nombre complexe" },
{ "empty string for imaginary character",
"cha\u00eene vide pour le caract\u00e8 imaginaire" },
{ "null imaginary format",
"format imaginaire nul" },
{ "null real format",
"format r\u00e9el nul" },
// org.apache.commons.math.complex.ComplexUtils
{ "negative complex module {0}",
"module n\u00e9gatif ({0}) pour un nombre complexe" },
// org.apache.commons.math.geometry.Vector3DFormat
{ "unparseable 3D vector: \"{0}\"",
"\u00e9chec d''analyse du vecteur de dimension 3 \"{0}\"" },
{ "cannot format a {0} instance as a 3D vector",
"impossible de formater une instance de {0} comme un vecteur de dimension 3" },
// org.apache.commons.math.linear.RealVectorFormat
{ "unparseable real vector: \"{0}\"",
"\u00e9chec d''analyse du vecteur r\u00e9el \"{0}\"" },
{ "cannot format a {0} instance as a real vector",
"impossible de formater une instance de {0} comme un vecteur r\u00e9el" },
// org.apache.commons.math.util.ResizableDoubleArray
{ "the index specified: {0} is larger than the current maximal index {1}",
"l''index sp\u00e9cifi\u00e9 ({0}) d\u00e9passe l''index maximal courant ({1})" },
{ "elements cannot be retrieved from a negative array index {0}",
"impossible d''extraire un \u00e9l\u00e9ment \u00e0 un index n\u00e9gatif ({0})" },
{ "cannot set an element at a negative index {0}",
"impossible de mettre un \u00e9l\u00e9ment \u00e0 un index n\u00e9gatif ({0})" },
{ "cannot substitute an element from an empty array",
"impossible de substituer un \u00e9l\u00e9ment dans un tableau vide" },
{ "contraction criteria ({0}) smaller than the expansion factor ({1}). This would " +
"lead to a never ending loop of expansion and contraction as a newly expanded " +
"internal storage array would immediately satisfy the criteria for contraction.",
"crit\u00e8re de contraction ({0}) inf\u00e9rieur au facteur d''extension. Ceci " +
"induit une boucle infinie d''extensions/contractions car tout tableau de stockage " +
"fra\u00eechement \u00e9tendu respecte imm\u00e9diatement le crit\u00e8re de contraction."},
{ "contraction criteria smaller than one ({0}). This would lead to a never ending " +
"loop of expansion and contraction as an internal storage array length equal " +
"to the number of elements would satisfy the contraction criteria.",
"crit\u00e8re de contraction inf\u00e9rieur \u00e0 un ({0}). Ceci induit une boucle " +
"infinie d''extensions/contractions car tout tableau de stockage de longueur \u00e9gale " +
"au nombre d''\u00e9l\u00e9ments respecte le crit\u00e8re de contraction." },
{ "expansion factor smaller than one ({0})",
"facteur d''extension inf\u00e9rieur \u00e0 un ({0})"},
{ "cannot discard {0} elements from a {1} elements array",
"impossible d''enlever {0} \u00e9l\u00e9ments d''un tableau en contenant {1}"},
{ "cannot discard a negative number of elements ({0})",
"impossible d''enlever un nombre d''\u00e9l\u00e9ments{0} n\u00e9gatif"},
{ "unsupported expansion mode {0}, supported modes are {1} ({2}) and {3} ({4})",
"mode d''extension {0} no support\u00e9, les modes support\u00e9s sont {1} ({2}) et {3} ({4})" },
{ "initial capacity ({0}) is not positive",
"la capacit\u00e9 initiale ({0}) n''est pas positive" },
{ "index ({0}) is not positive",
"l''indice ({0}) n''est pas positif" },
// org.apache.commons.math.analysis.polynomials.PolynomialFunction
// org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
{ "empty polynomials coefficients array",
"tableau de coefficients polyn\u00f4miaux vide" },
// org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
{ "array sizes should have difference 1 ({0} != {1} + 1)",
"les tableaux devraient avoir une diff\u00e9rence de taille de 1 ({0} != {1} + 1)" },
// org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
{ "identical abscissas x[{0}] == x[{1}] == {2} cause division by zero",
"division par z\u00e9ro caus\u00e9e par les abscisses identiques x[{0}] == x[{1}] == {2}" },
// org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
{ "spline partition must have at least {0} points, got {1}",
"une partiction spline n\u00e9cessite au moins {0} points, seuls {1} ont \u00e9t\u00e9 fournis" },
{ "knot values must be strictly increasing",
"les n\u0153uds d''interpolation doivent \u00eatre strictement croissants" },
{ "number of polynomial interpolants must match the number of segments ({0} != {1} - 1)",
"le nombre d''interpolants polyn\u00f4miaux doit correspondre au nombre de segments ({0} != {1} - 1)" },
// org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
{ "function to solve cannot be null",
"la fonction \u00e0 r\u00e9soudre ne peux pas \u00eatre nulle" },
{ "invalid interval, initial value parameters: lower={0}, initial={1}, upper={2}",
"param\u00e8tres de l''intervalle initial invalides : borne inf = {0}, valeur initiale = {1}, borne sup = {2}" },
// org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
// org.apache.commons.math.analysis.solvers.BrentSolver
{ "function values at endpoints do not have different signs. Endpoints: [{0}, {1}], Values: [{2}, {3}]",
"les valeurs de la fonction aux bornes n''ont pas des signes diff\u00e9rents. Bornes : [{0}, {1}], valeurs : [{2}, {3}]" },
// org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
// org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
// org.apache.commons.math.transform.FastFourierTransformer
{ "endpoints do not specify an interval: [{0}, {1}]",
"les extr\u00e9mit\u00e9s ne constituent pas un intervalle : [{0}, {1}]" },
// org.apache.commons.math.analysis.solvers.LaguerreSolver
{ "function is not polynomial",
"la fonction n''est pas p\u00f4lynomiale" },
// org.apache.commons.math.analysis.solvers.NewtonSolver
{ "function is not differentiable",
"la fonction n''est pas diff\u00e9rentiable" },
// org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
{ "invalid iteration limits: min={0}, max={1}",
"limites d''it\u00e9rations invalides : min = {0}, max = {1}" },
// org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
{ "{0} points Legendre-Gauss integrator not supported," +
" number of points must be in the {1}-{2} range",
"int\u00e9grateur de Legendre-Gauss non support\u00e9 en {0} points, " +
"le nombre de points doit \u00eatre entre {1} et {2}" },
// org.apache.commons.math.fraction.Fraction
{ "zero denominator in fraction {0}/{1}",
"d\u00e9nominateur null dans le nombre rationnel {0}/{1}" },
{ "overflow in fraction {0}/{1}, cannot negate",
"d\u00e9passement de capacit\u00e9 pour la fraction {0}/{1}, son signe ne peut \u00eatre chang\u00e9" },
{ "overflow, numerator too large after multiply: {0}",
"d\u00e9passement de capacit\u00e9 pour le num\u00e9rateur apr\u00e8s multiplication : {0}" },
{ "the fraction to divide by must not be zero: {0}/{1}",
"division par un nombre rationnel nul : {0}/{1}" },
{ "null fraction",
"fraction nulle" },
// org.apache.commons.math.geometry.Rotation
{ "zero norm for rotation axis",
"norme nulle pour un axe de rotation" },
{ "zero norm for rotation defining vector",
"norme nulle pour un axe de d\u00e9finition de rotation" },
// org.apache.commons.math.geometry.Vector3D
// org.apache.commons.math.linear.ArrayRealVector
{ "cannot normalize a zero norm vector",
"impossible de normer un vecteur de norme nulle" },
{ "zero norm",
"norme nulle" },
// org.apache.commons.math.ConvergingAlgorithmImpl
{ "no result available",
"aucun r\u00e9sultat n''est disponible" },
// org.apache.commons.math.linear.BigMatrixImpl
{ "first {0} rows are not initialized yet",
"les {0} premi\u00e8res lignes ne sont pas encore initialis\u00e9es" },
{ "first {0} columns are not initialized yet",
"les {0} premi\u00e8res colonnes ne sont pas encore initialis\u00e9es" },
// org.apache.commons.math.stat.Frequency
{ "class ({0}) does not implement Comparable",
"la classe ({0}) n''implante pas l''interface Comparable" },
{ "instance of class {0} not comparable to existing values",
"l''instance de la classe {0} n''est pas comparable aux valeurs existantes" },
// org.apache.commons.math.stat.StatUtils
{ "input arrays must have the same positive length ({0} and {1})",
"les tableaux d''entr\u00e9e doivent avoir la m\u00eame taille positive ({0} et {1})" },
{ "input arrays must have the same length and at least two elements ({0} and {1})",
"les tableaux d''entr\u00e9e doivent avoir la m\u00eame taille" +
" et au moins deux \u00e9l\u00e9ments ({0} et {1})" },
// org.apache.commons.math.stat.correlation.Covariance
{ "arrays must have the same length and both must have at " +
"least two elements. xArray has size {0}, yArray has {1} elements",
"les tableaux doivent avoir la m\u00eame taille " +
"et comporter au moins deux \u00e9l\u00e9ments. " +
"xArray a une taille de {0}, yArray a {1} \u00e9l\u00e9ments"},
{ "insufficient data: only {0} rows and {1} columns.",
"donn\u00e9es insuffisantes : seulement {0} lignes et {1} colonnes." },
// org.apache.commons.math.stat.correlation.PearsonsCorrelation
{ "covariance matrix is null",
"la matrice de covariance est nulle" },
{ "invalid array dimensions. xArray has size {0}; yArray has {1} elements",
"dimensions de tableaux invalides. xArray a une taille de {0}, " +
"yArray a {1} \u00e9l\u00e9ments" },
// org.apache.commons.math.stat.descriptive.DescriptiveStatistics
{ "window size must be positive ({0})",
"la taille de la fen\u00eatre doit \u00eatre positive ({0})" },
{ "percentile implementation {0} does not support {1}",
"l''implantation de pourcentage {0} ne dispose pas de la m\u00e9thode {1}" },
{ "cannot access {0} method in percentile implementation {1}",
"acc\u00e8s impossible \u00e0 la m\u00e9thode {0}" +
" dans l''implantation de pourcentage {1}" },
{ "out of bounds quantile value: {0}, must be in (0, 100]",
"valeur de quantile {0} hors bornes, doit \u00eatre dans l''intervalle ]0, 100]" },
// org.apache.commons.math.stat.descriptive.moment.Variance
// org.apache.commons.math.stat.descriptive.moment.SemiVariance
// org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
// org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
{ "input values array is null",
"le tableau des valeurs d''entr\u00e9es est nul" },
// org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
{ "start position cannot be negative ({0})",
"la position de d\u00e9part ne peut pas \u00eatre n\u00e9gative" },
{ "length cannot be negative ({0})",
"la longueur ne peut pas \u00eatre n\u00e9gative" },
{ "subarray ends after array end",
"le sous-tableau se termine apr\u00e8s la fin du tableau" },
// org.apache.commons.math.stat.descriptive.moment.GeometricMean
// org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
// org.apache.commons.math.stat.descriptive.SummaryStatistics
{ "{0} values have been added before statistic is configured",
"{0} valeurs ont \u00e9t\u00e9 ajout\u00e9es " +
"avant que la statistique ne soit configur\u00e9e" },
// org.apache.commons.math.stat.descriptive.moment.Kurtosis
{ "statistics constructed from external moments cannot be incremented",
"les statistiques bas\u00e9es sur des moments externes ne peuvent pas \u00eatre incr\u00e9ment\u00e9es" },
{ "statistics constructed from external moments cannot be cleared",
"les statistiques bas\u00e9es sur des moments externes ne peuvent pas \u00eatre remises \u00e0 z\u00e9ro" },
// org.apache.commons.math.stat.inference.ChiSquareTestImpl
{ "expected array length = {0}, must be at least 2",
"le tableau des valeurs attendues a une longueur de {0}, elle devrait \u00eatre au moins de 2" },
{ "observed array length = {0}, must be at least 2",
"le tableau des valeurs observ\u00e9es a une longueur de {0}, elle devrait \u00eatre au moins de 2" },
{ "observed counts are all 0 in first observed array",
"aucune occurrence dans le premier tableau des observations" },
{ "observed counts are all 0 in second observed array",
"aucune occurrence dans le second tableau des observations" },
{ "observed counts are both zero for entry {0}",
"les occurrences observ\u00e9es sont toutes deux nulles pour l'entr\u00e9e {0}" },
{ "invalid row dimension: {0} (must be at least 2)",
"nombre de lignes invalide : {0} (doit \u00eatre au moins de 2)" },
{ "invalid column dimension: {0} (must be at least 2)",
"nombre de colonnes invalide : {0} (doit \u00eatre au moins de 2)" },
{ "element {0} is not positive: {1}",
"l''\u00e9l\u00e9ment {0} n''est pas positif : {1}" },
{ "element {0} is negative: {1}",
"l''\u00e9l\u00e9ment {0} est n\u00e9gatif : {1}" },
{ "element ({0}, {1}) is negative: {2}",
"l''\u00e9l\u00e9ment ({0}, {1}) est n\u00e9gatif : {2}" },
// org.apache.commons.math.stat.inference.OneWayAnovaImpl
{ "two or more categories required, got {0}",
"deux cat\u00e9gories ou plus sont n\u00e9cessaires, il y en a {0}" },
{ "two or more values required in each category, one has {0}",
"deux valeurs ou plus sont n\u00e9cessaires pour chaque cat\u00e9gorie, une cat\u00e9gorie en a {0}" },
// org.apache.commons.math.stat.inference.TTestImpl
{ "insufficient data for t statistic, needs at least 2, got {0}",
"deux valeurs ou plus sont n\u00e9cessaires pour la statistique t, il y en a {0}" },
// org.apache.commons.math.stat.inference.ChiSquareTestImpl
// org.apache.commons.math.stat.inference.TTestImpl
// org.apache.commons.math.stat.inference.OneWayAnovaImpl
// org.apache.commons.math.stat.Regression
{ "out of bounds significance level {0}, must be between {1} and {2}",
"niveau de signification {0} hors domaine, doit \u00eatre entre {1} et {2}" },
// org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
{ "not enough data ({0} rows) for this many predictors ({1} predictors)",
"pas assez de donn\u00e9es ({0} lignes) pour {1} pr\u00e9dicteurs" },
// org.apache.commons.math.distribution.AbstractContinuousDistribution
// org.apache.commons.math.distribution.AbstractIntegerDistribution
// org.apache.commons.math.distribution.ExponentialDistributionImpl
// org.apache.commons.math.distribution.BinomialDistributionImpl
// org.apache.commons.math.distribution.CauchyDistributionImpl
// org.apache.commons.math.distribution.PascalDistributionImpl
// org.apache.commons.math.distribution.WeibullDistributionImpl
{ "{0} out of [{1}, {2}] range",
"{0} hors du domaine [{1}, {2}]" },
// org.apache.commons.math.distribution.AbstractDistribution
// org.apache.commons.math.distribution.AbstractIntegerDistribution
{ "lower endpoint ({0}) must be less than or equal to upper endpoint ({1})",
"la borne inf\u00e9rieure ({0}) devrait \u00eatre inf\u00e9rieure " +
"ou \u00e9gale \u00e0 la borne sup\u00e9rieure ({1})" },
// org.apache.commons.math.distribution.AbstractContinuousDistribution
{ "Cumulative probability function returned NaN for argument {0} p = {1}",
"Fonction de probabilit\u00e9 cumulative retourn\u00e9 NaN \u00e0 l''argument de {0} p = {1}" },
{ "This distribution does not have a density function implemented",
"La fonction de densit\u00e9 pour cette distribution n'a pas \u00e9t\u00e9 mis en oeuvre" },
// org.apache.commons.math.distribution.AbstractIntegerDistribution
{ "Discrete cumulative probability function returned NaN for argument {0}",
"Discr\u00e8tes fonction de probabilit\u00e9 cumulative retourn\u00e9 NaN \u00e0 l''argument de {0}" },
// org.apache.commons.math.distribution.BinomialDistributionImpl
{ "number of trials must be non-negative ({0})",
"le nombre d''essais ne doit pas \u00eatre n\u00e9gatif ({0})" },
// org.apache.commons.math.distribution.ExponentialDistributionImpl
// org.apache.commons.math.random.RandomDataImpl
{ "mean must be positive ({0})",
"la moyenne doit \u00eatre positive ({0})" },
// org.apache.commons.math.distribution.FDistributionImpl
// org.apache.commons.math.distribution.TDistributionImpl
{ "degrees of freedom must be positive ({0})",
"les degr\u00e9s de libert\u00e9 doivent \u00eatre positifs ({0})" },
// org.apache.commons.math.distribution.GammaDistributionImpl
{ "alpha must be positive ({0})",
"alpha doit \u00eatre positif ({0})" },
{ "beta must be positive ({0})",
"beta doit \u00eatre positif ({0})" },
// org.apache.commons.math.distribution.HypergeometricDistributionImpl
{ "number of successes ({0}) must be less than or equal to population size ({1})",
"le nombre de succ\u00e8s doit \u00eatre inf\u00e9rieur " +
"ou \u00e9gal \u00e0 la taille de la population ({1})" },
{ "sample size ({0}) must be less than or equal to population size ({1})",
"la taille de l''\u00e9chantillon doit \u00eatre inf\u00e9rieure " +
"ou \u00e9gale \u00e0 la taille de la population ({1})" },
{ "population size must be positive ({0})",
"la taille de la population doit \u00eatre positive ({0})" },
// org.apache.commons.math.distribution.HypergeometricDistributionImpl
// org.apache.commons.math.random.RandomDataImpl
{ "sample size must be positive ({0})",
"la taille de l''\u00e9chantillon doit \u00eatre positive ({0})" },
// org.apache.commons.math.distribution.HypergeometricDistributionImpl
// org.apache.commons.math.distribution.PascalDistributionImpl
{ "number of successes must be non-negative ({0})",
"le nombre de succ\u00e8s ne doit pas \u00eatre n\u00e9gatif ({0})" },
// org.apache.commons.math.distribution.NormalDistributionImpl
// org.apache.commons.math.random.RandomDataImpl
{ "standard deviation must be positive ({0})",
"l''\u00e9cart type doit \u00eatre positif ({0})" },
// org.apache.commons.math.distribution.PoissonDistributionImpl
// org.apache.commons.math.random.RandomDataImpl
{ "the Poisson mean must be positive ({0})",
"la moyenne de Poisson doit \u00eatre positive ({0})" },
// org.apache.commons.math.distribution.WeibullDistributionImpl
{ "shape must be positive ({0})",
"le facteur de forme doit \u00eatre positif ({0})" },
// org.apache.commons.math.distribution.WeibullDistributionImpl
// org.apache.commons.math.distribution.CauchyDistributionImpl
{ "scale must be positive ({0})",
"l''\u00e9chelle doit \u00eatre positive ({0})" },
// org.apache.commons.math.distribution.ZipfDistributionImpl
{ "invalid number of elements {0} (must be positive)",
"nombre d''\u00e9l\u00e9ments {0} invalide (doit \u00eatre positif)" },
{ "invalid exponent {0} (must be positive)",
"exposant {0} invalide (doit \u00eatre positif)" },
// org.apache.commons.math.transform.FastHadamardTransformer
{ "{0} is not a power of 2",
"{0} n''est pas une puissance de 2" },
// org.apache.commons.math.transform.FastFourierTransformer
{ "cannot compute 0-th root of unity, indefinite result",
"impossible de calculer la racine z\u00e9roi\u00e8me de l''unit\u00e9, " +
"r\u00e9sultat ind\u00e9fini" },
{ "roots of unity have not been computed yet",
"les racines de l''unit\u00e9 n''ont pas encore \u00e9t\u00e9 calcul\u00e9es" },
{ "out of range root of unity index {0} (must be in [{1};{2}])",
"index de racine de l''unit\u00e9 hors domaine (devrait \u00eatre dans [{1}; {2}])" },
{ "number of sample is not positive: {0}",
"le nombre d''\u00e9chantillons n''est pas positif : {0}" },
{ "{0} is not a power of 2, consider padding for fix",
"{0} n''est pas une puissance de 2, ajoutez des \u00e9l\u00e9ments pour corriger" },
{ "some dimensions don't match: {0} != {1}",
"certaines dimensions sont incoh\u00e9rentes : {0} != {1}" },
// org.apache.commons.math.transform.FastCosineTransformer
{ "{0} is not a power of 2 plus one",
"{0} n''est pas une puissance de 2 plus un" },
// org.apache.commons.math.transform.FastSineTransformer
{ "first element is not 0: {0}",
"le premier \u00e9l\u00e9ment n''est pas nul : {0}" },
// org.apache.commons.math.util.OpenIntToDoubleHashMap
{ "map has been modified while iterating",
"la table d''adressage a \u00e9t\u00e9 modifi\u00e9e pendant l''it\u00e9ration" },
{ "iterator exhausted",
"it\u00e9ration achev\u00e9e" },
// org.apache.commons.math.MathRuntimeException
{ "internal error, please fill a bug report at {0}",
"erreur interne, veuillez signaler l''erreur \u00e0 {0}" }
};
/**
* Simple constructor.
*/
public MessagesResources_fr() {
}
/**
* Get the non-translated/translated messages arrays from this resource bundle.
* @return non-translated/translated messages arrays
*/
@Override
public Object[][] getContents() {
return CONTENTS.clone();
}
}
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