How to use rows method in storybook-root

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distributed.py

Source:distributed.py Github

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...81 else:82 raise TypeError("rows should be an RDD of vectors, got %s" % type(rows))83 self._java_matrix_wrapper = JavaModelWrapper(java_matrix)84 @property85 def rows(self):86 """87 Rows of the RowMatrix stored as an RDD of vectors.88 >>> mat = RowMatrix(sc.parallelize([[1, 2, 3], [4, 5, 6]]))89 >>> rows = mat.rows90 >>> rows.first()91 DenseVector([1.0, 2.0, 3.0])92 """93 return self._java_matrix_wrapper.call("rows")94 def numRows(self):95 """96 Get or compute the number of rows.97 >>> rows = sc.parallelize([[1, 2, 3], [4, 5, 6],98 ... [7, 8, 9], [10, 11, 12]])99 >>> mat = RowMatrix(rows)100 >>> print(mat.numRows())101 4102 >>> mat = RowMatrix(rows, 7, 6)103 >>> print(mat.numRows())104 7105 """106 return self._java_matrix_wrapper.call("numRows")107 def numCols(self):108 """109 Get or compute the number of cols.110 >>> rows = sc.parallelize([[1, 2, 3], [4, 5, 6],111 ... [7, 8, 9], [10, 11, 12]])112 >>> mat = RowMatrix(rows)113 >>> print(mat.numCols())114 3115 >>> mat = RowMatrix(rows, 7, 6)116 >>> print(mat.numCols())117 6118 """119 return self._java_matrix_wrapper.call("numCols")120 @since('2.0.0')121 def computeColumnSummaryStatistics(self):122 """123 Computes column-wise summary statistics.124 :return: :class:`MultivariateStatisticalSummary` object125 containing column-wise summary statistics.126 >>> rows = sc.parallelize([[1, 2, 3], [4, 5, 6]])127 >>> mat = RowMatrix(rows)128 >>> colStats = mat.computeColumnSummaryStatistics()129 >>> colStats.mean()130 array([ 2.5, 3.5, 4.5])131 """132 java_col_stats = self._java_matrix_wrapper.call("computeColumnSummaryStatistics")133 return MultivariateStatisticalSummary(java_col_stats)134 @since('2.0.0')135 def computeCovariance(self):136 """137 Computes the covariance matrix, treating each row as an138 observation.139 .. note:: This cannot be computed on matrices with more than 65535 columns.140 >>> rows = sc.parallelize([[1, 2], [2, 1]])141 >>> mat = RowMatrix(rows)142 >>> mat.computeCovariance()143 DenseMatrix(2, 2, [0.5, -0.5, -0.5, 0.5], 0)144 """145 return self._java_matrix_wrapper.call("computeCovariance")146 @since('2.0.0')147 def computeGramianMatrix(self):148 """149 Computes the Gramian matrix `A^T A`.150 .. note:: This cannot be computed on matrices with more than 65535 columns.151 >>> rows = sc.parallelize([[1, 2, 3], [4, 5, 6]])152 >>> mat = RowMatrix(rows)153 >>> mat.computeGramianMatrix()154 DenseMatrix(3, 3, [17.0, 22.0, 27.0, 22.0, 29.0, 36.0, 27.0, 36.0, 45.0], 0)155 """156 return self._java_matrix_wrapper.call("computeGramianMatrix")157 @since('2.0.0')158 def columnSimilarities(self, threshold=0.0):159 """160 Compute similarities between columns of this matrix.161 The threshold parameter is a trade-off knob between estimate162 quality and computational cost.163 The default threshold setting of 0 guarantees deterministically164 correct results, but uses the brute-force approach of computing165 normalized dot products.166 Setting the threshold to positive values uses a sampling167 approach and incurs strictly less computational cost than the168 brute-force approach. However the similarities computed will169 be estimates.170 The sampling guarantees relative-error correctness for those171 pairs of columns that have similarity greater than the given172 similarity threshold.173 To describe the guarantee, we set some notation:174 * Let A be the smallest in magnitude non-zero element of175 this matrix.176 * Let B be the largest in magnitude non-zero element of177 this matrix.178 * Let L be the maximum number of non-zeros per row.179 For example, for {0,1} matrices: A=B=1.180 Another example, for the Netflix matrix: A=1, B=5181 For those column pairs that are above the threshold, the182 computed similarity is correct to within 20% relative error183 with probability at least 1 - (0.981)^10/B^184 The shuffle size is bounded by the *smaller* of the following185 two expressions:186 * O(n log(n) L / (threshold * A))187 * O(m L^2^)188 The latter is the cost of the brute-force approach, so for189 non-zero thresholds, the cost is always cheaper than the190 brute-force approach.191 :param: threshold: Set to 0 for deterministic guaranteed192 correctness. Similarities above this193 threshold are estimated with the cost vs194 estimate quality trade-off described above.195 :return: An n x n sparse upper-triangular CoordinateMatrix of196 cosine similarities between columns of this matrix.197 >>> rows = sc.parallelize([[1, 2], [1, 5]])198 >>> mat = RowMatrix(rows)199 >>> sims = mat.columnSimilarities()200 >>> sims.entries.first().value201 0.91914503...202 """203 java_sims_mat = self._java_matrix_wrapper.call("columnSimilarities", float(threshold))204 return CoordinateMatrix(java_sims_mat)205 @since('2.0.0')206 def tallSkinnyQR(self, computeQ=False):207 """208 Compute the QR decomposition of this RowMatrix.209 The implementation is designed to optimize the QR decomposition210 (factorization) for the RowMatrix of a tall and skinny shape.211 Reference:212 Paul G. Constantine, David F. Gleich. "Tall and skinny QR213 factorizations in MapReduce architectures"214 ([[http://dx.doi.org/10.1145/1996092.1996103]])215 :param: computeQ: whether to computeQ216 :return: QRDecomposition(Q: RowMatrix, R: Matrix), where217 Q = None if computeQ = false.218 >>> rows = sc.parallelize([[3, -6], [4, -8], [0, 1]])219 >>> mat = RowMatrix(rows)220 >>> decomp = mat.tallSkinnyQR(True)221 >>> Q = decomp.Q222 >>> R = decomp.R223 >>> # Test with absolute values224 >>> absQRows = Q.rows.map(lambda row: abs(row.toArray()).tolist())225 >>> absQRows.collect()226 [[0.6..., 0.0], [0.8..., 0.0], [0.0, 1.0]]227 >>> # Test with absolute values228 >>> abs(R.toArray()).tolist()229 [[5.0, 10.0], [0.0, 1.0]]230 """231 decomp = JavaModelWrapper(self._java_matrix_wrapper.call("tallSkinnyQR", computeQ))232 if computeQ:233 java_Q = decomp.call("Q")234 Q = RowMatrix(java_Q)235 else:236 Q = None237 R = decomp.call("R")238 return QRDecomposition(Q, R)239 @since('2.2.0')240 def computeSVD(self, k, computeU=False, rCond=1e-9):241 """242 Computes the singular value decomposition of the RowMatrix.243 The given row matrix A of dimension (m X n) is decomposed into244 U * s * V'T where245 * U: (m X k) (left singular vectors) is a RowMatrix whose246 columns are the eigenvectors of (A X A')247 * s: DenseVector consisting of square root of the eigenvalues248 (singular values) in descending order.249 * v: (n X k) (right singular vectors) is a Matrix whose columns250 are the eigenvectors of (A' X A)251 For more specific details on implementation, please refer252 the Scala documentation.253 :param k: Number of leading singular values to keep (`0 < k <= n`).254 It might return less than k if there are numerically zero singular values255 or there are not enough Ritz values converged before the maximum number of256 Arnoldi update iterations is reached (in case that matrix A is ill-conditioned).257 :param computeU: Whether or not to compute U. If set to be258 True, then U is computed by A * V * s^-1259 :param rCond: Reciprocal condition number. All singular values260 smaller than rCond * s[0] are treated as zero261 where s[0] is the largest singular value.262 :returns: :py:class:`SingularValueDecomposition`263 >>> rows = sc.parallelize([[3, 1, 1], [-1, 3, 1]])264 >>> rm = RowMatrix(rows)265 >>> svd_model = rm.computeSVD(2, True)266 >>> svd_model.U.rows.collect()267 [DenseVector([-0.7071, 0.7071]), DenseVector([-0.7071, -0.7071])]268 >>> svd_model.s269 DenseVector([3.4641, 3.1623])270 >>> svd_model.V271 DenseMatrix(3, 2, [-0.4082, -0.8165, -0.4082, 0.8944, -0.4472, 0.0], 0)272 """273 j_model = self._java_matrix_wrapper.call(274 "computeSVD", int(k), bool(computeU), float(rCond))275 return SingularValueDecomposition(j_model)276 @since('2.2.0')277 def computePrincipalComponents(self, k):278 """279 Computes the k principal components of the given row matrix280 .. note:: This cannot be computed on matrices with more than 65535 columns.281 :param k: Number of principal components to keep.282 :returns: :py:class:`pyspark.mllib.linalg.DenseMatrix`283 >>> rows = sc.parallelize([[1, 2, 3], [2, 4, 5], [3, 6, 1]])284 >>> rm = RowMatrix(rows)285 >>> # Returns the two principal components of rm286 >>> pca = rm.computePrincipalComponents(2)287 >>> pca288 DenseMatrix(3, 2, [-0.349, -0.6981, 0.6252, -0.2796, -0.5592, -0.7805], 0)289 >>> # Transform into new dimensions with the greatest variance.290 >>> rm.multiply(pca).rows.collect() # doctest: +NORMALIZE_WHITESPACE291 [DenseVector([0.1305, -3.7394]), DenseVector([-0.3642, -6.6983]), \292 DenseVector([-4.6102, -4.9745])]293 """294 return self._java_matrix_wrapper.call("computePrincipalComponents", k)295 @since('2.2.0')296 def multiply(self, matrix):297 """298 Multiply this matrix by a local dense matrix on the right.299 :param matrix: a local dense matrix whose number of rows must match the number of columns300 of this matrix301 :returns: :py:class:`RowMatrix`302 >>> rm = RowMatrix(sc.parallelize([[0, 1], [2, 3]]))303 >>> rm.multiply(DenseMatrix(2, 2, [0, 2, 1, 3])).rows.collect()304 [DenseVector([2.0, 3.0]), DenseVector([6.0, 11.0])]305 """306 if not isinstance(matrix, DenseMatrix):307 raise ValueError("Only multiplication with DenseMatrix "308 "is supported.")309 j_model = self._java_matrix_wrapper.call("multiply", matrix)310 return RowMatrix(j_model)311class SingularValueDecomposition(JavaModelWrapper):312 """313 Represents singular value decomposition (SVD) factors.314 .. versionadded:: 2.2.0315 """316 @property317 @since('2.2.0')318 def U(self):319 """320 Returns a distributed matrix whose columns are the left321 singular vectors of the SingularValueDecomposition if computeU was set to be True.322 """323 u = self.call("U")324 if u is not None:325 mat_name = u.getClass().getSimpleName()326 if mat_name == "RowMatrix":327 return RowMatrix(u)328 elif mat_name == "IndexedRowMatrix":329 return IndexedRowMatrix(u)330 else:331 raise TypeError("Expected RowMatrix/IndexedRowMatrix got %s" % mat_name)332 @property333 @since('2.2.0')334 def s(self):335 """336 Returns a DenseVector with singular values in descending order.337 """338 return self.call("s")339 @property340 @since('2.2.0')341 def V(self):342 """343 Returns a DenseMatrix whose columns are the right singular344 vectors of the SingularValueDecomposition.345 """346 return self.call("V")347class IndexedRow(object):348 """349 Represents a row of an IndexedRowMatrix.350 Just a wrapper over a (long, vector) tuple.351 :param index: The index for the given row.352 :param vector: The row in the matrix at the given index.353 """354 def __init__(self, index, vector):355 self.index = long(index)356 self.vector = _convert_to_vector(vector)357 def __repr__(self):358 return "IndexedRow(%s, %s)" % (self.index, self.vector)359def _convert_to_indexed_row(row):360 if isinstance(row, IndexedRow):361 return row362 elif isinstance(row, tuple) and len(row) == 2:363 return IndexedRow(*row)364 else:365 raise TypeError("Cannot convert type %s into IndexedRow" % type(row))366class IndexedRowMatrix(DistributedMatrix):367 """368 Represents a row-oriented distributed Matrix with indexed rows.369 :param rows: An RDD of IndexedRows or (long, vector) tuples.370 :param numRows: Number of rows in the matrix. A non-positive371 value means unknown, at which point the number372 of rows will be determined by the max row373 index plus one.374 :param numCols: Number of columns in the matrix. A non-positive375 value means unknown, at which point the number376 of columns will be determined by the size of377 the first row.378 """379 def __init__(self, rows, numRows=0, numCols=0):380 """381 Note: This docstring is not shown publicly.382 Create a wrapper over a Java IndexedRowMatrix.383 Publicly, we require that `rows` be an RDD. However, for384 internal usage, `rows` can also be a Java IndexedRowMatrix385 object, in which case we can wrap it directly. This386 assists in clean matrix conversions.387 >>> rows = sc.parallelize([IndexedRow(0, [1, 2, 3]),388 ... IndexedRow(1, [4, 5, 6])])389 >>> mat = IndexedRowMatrix(rows)390 >>> mat_diff = IndexedRowMatrix(rows)391 >>> (mat_diff._java_matrix_wrapper._java_model ==392 ... mat._java_matrix_wrapper._java_model)393 False394 >>> mat_same = IndexedRowMatrix(mat._java_matrix_wrapper._java_model)395 >>> (mat_same._java_matrix_wrapper._java_model ==396 ... mat._java_matrix_wrapper._java_model)397 True398 """399 if isinstance(rows, RDD):400 rows = rows.map(_convert_to_indexed_row)401 # We use DataFrames for serialization of IndexedRows from402 # Python, so first convert the RDD to a DataFrame on this403 # side. This will convert each IndexedRow to a Row404 # containing the 'index' and 'vector' values, which can405 # both be easily serialized. We will convert back to406 # IndexedRows on the Scala side.407 java_matrix = callMLlibFunc("createIndexedRowMatrix", rows.toDF(),408 long(numRows), int(numCols))409 elif (isinstance(rows, JavaObject)410 and rows.getClass().getSimpleName() == "IndexedRowMatrix"):411 java_matrix = rows412 else:413 raise TypeError("rows should be an RDD of IndexedRows or (long, vector) tuples, "414 "got %s" % type(rows))415 self._java_matrix_wrapper = JavaModelWrapper(java_matrix)416 @property417 def rows(self):418 """419 Rows of the IndexedRowMatrix stored as an RDD of IndexedRows.420 >>> mat = IndexedRowMatrix(sc.parallelize([IndexedRow(0, [1, 2, 3]),421 ... IndexedRow(1, [4, 5, 6])]))422 >>> rows = mat.rows423 >>> rows.first()424 IndexedRow(0, [1.0,2.0,3.0])425 """426 # We use DataFrames for serialization of IndexedRows from427 # Java, so we first convert the RDD of rows to a DataFrame428 # on the Scala/Java side. Then we map each Row in the429 # DataFrame back to an IndexedRow on this side.430 rows_df = callMLlibFunc("getIndexedRows", self._java_matrix_wrapper._java_model)431 rows = rows_df.rdd.map(lambda row: IndexedRow(row[0], row[1]))...

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jquery.gridnav.js

Source:jquery.gridnav.js Github

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1(function($) {2 jQuery.fn.reverse = Array.prototype.reverse;3 4 var 5 // auxiliar functions6 aux = {7 setup : function( $wrapper, $items, opts ) {8 9 // set the wrappers position to relative10 $wrapper.css('position', 'relative');11 12 // save the items position13 aux.saveInitialPosition( $items );14 15 // set the items to absolute and assign top & left16 $items.each(function(i) {17 var $item = $(this);18 $item.css({19 position : 'absolute',20 left : $item.data('left'),21 top : $item.data('top')22 });23 });24 25 // check how many items we have per row26 var rowCount = Math.floor( $wrapper.width() / $items.width() ),27 // number of items to show is rowCount * n rows28 shown = rowCount * opts.rows,29 // total number of rows30 totalRows = Math.ceil( $items.length / rowCount );31 32 // save this values for later33 var config = {};34 config.currentRow = 1;35 config.totalRows = totalRows;36 config.rowCount = rowCount;37 config.shownItems = shown;38 $wrapper.data('config', config);39 40 // show n rowns41 $wrapper.children(':gt(' + (shown - 1) + ')').hide();42 43 // assign row classes to the items44 $items.each(function(i) {45 var $item = $(this),46 row = Math.ceil( (i + 1) / rowCount );47 48 $item.addClass('tj_row_' + row); 49 });50 51 nav.setup( $wrapper, $items, opts );52 53 },54 saveInitialPosition : function( $items ) {55 $items.each(function(i) {56 var $item = $(this);57 58 $item.data({59 left : $item.position().left + 'px',60 top : $item.position().top + 'px'61 }); 62 });63 }64 },65 // navigation types66 nav = {67 setup : function( $wrapper, $items, opts ) {68 nav[opts.type.mode].setup( $wrapper, $items, opts );69 },70 def : {71 setup : function( $wrapper, $items, opts ) {72 var config = $wrapper.data('config');73 $items.each(function(i) {74 var $item = $(this),75 row = Math.ceil( (i + 1) / config.rowCount ),76 t,77 f = row % opts.rows;78 79 if( f === 1 ) {80 t = '0px'; 81 } else if( f === 0 ) {82 t = (opts.rows - 1) * $items.height() + 'px'; 83 } else {84 t = (f - 1) * $items.height() + 'px';85 }86 87 $item.css({ top : t });88 }); 89 },90 pagination : function( $wrapper, dir, opts ) {91 var config = $wrapper.data('config');92 if( ( dir === 1 && config.currentRow + opts.rows > config.totalRows ) || 93 ( dir === -1 && config.currentRow - opts.rows <= 0 )94 ) {95 $wrapper.data( 'anim', false );96 return false;97 }98 99 var currentRows = '', nextRows = '';100 101 for( var i = 0; i < opts.rows; ++i ) {102 currentRows += '.tj_row_' + (config.currentRow + i) + ',';103 104 (dir === 1)105 ? nextRows += '.tj_row_' + (config.currentRow + opts.rows + i) + ','106 : nextRows += '.tj_row_' + (config.currentRow - 1 - i) + ',';107 }108 109 $wrapper.children(currentRows).hide();110 $wrapper.children(nextRows).show();111 112 (dir === 1) ? config.currentRow += opts.rows : config.currentRow -= opts.rows;113 114 $wrapper.data( 'anim', false );115 $wrapper.data('config', config);116 }117 },118 fade : {119 setup : function( $wrapper, $items, opts ) {120 // same like def mode121 nav['def'].setup( $wrapper, $items, opts );122 },123 pagination : function( $wrapper, dir, opts ) {124 var config = $wrapper.data('config');125 if( ( dir === 1 && config.currentRow + opts.rows > config.totalRows ) ||126 ( dir === -1 && config.currentRow - opts.rows <= 0 )127 ) {128 $wrapper.data( 'anim', false );129 return false;130 }131 132 var currentRows = '', nextRows = '';133 134 for( var i = 0; i < opts.rows; ++i ) {135 currentRows += '.tj_row_' + (config.currentRow + i) + ',';136 137 (dir === 1)138 ? nextRows += '.tj_row_' + (config.currentRow + opts.rows + i) + ','139 : nextRows += '.tj_row_' + (config.currentRow - 1 - i) + ',';140 }141 142 $wrapper.children(currentRows).fadeOut( opts.type.speed, opts.type.easing );143 144 var $nextRowElements= $wrapper.children(nextRows),145 totalNextRows = $nextRowElements.length,146 cnt = 0;147 148 $nextRowElements.fadeIn( opts.type.speed, opts.type.easing, function() {149 ++cnt;150 if( cnt === totalNextRows ) {151 $wrapper.data( 'anim', false );152 } 153 });154 155 (dir === 1) ? config.currentRow += opts.rows : config.currentRow -= opts.rows;156 $wrapper.data('config', config);157 }158 },159 seqfade : {160 setup : function( $wrapper, $items, opts ) {161 // same like def mode162 nav['def'].setup( $wrapper, $items, opts );163 },164 pagination : function( $wrapper, dir, opts ) {165 var config = $wrapper.data('config');166 if( ( dir === 1 && config.currentRow + opts.rows > config.totalRows ) || 167 ( dir === -1 && config.currentRow - opts.rows <= 0 )168 ) {169 $wrapper.data( 'anim', false );170 return false;171 }172 173 var currentRows = '', nextRows = '';174 for( var i = 0; i < opts.rows; ++i ) {175 currentRows += '.tj_row_' + (config.currentRow + i) + ',';176 177 (dir === 1)178 ? nextRows += '.tj_row_' + (config.currentRow + opts.rows + i) + ','179 : nextRows += '.tj_row_' + (config.currentRow - 1 - i) + ',';180 }181 182 var seq_t = opts.type.factor;183 184 var $currentRowElements;185 ( dir === 1 )186 ? $currentRowElements = $wrapper.children(currentRows)187 : $currentRowElements = $wrapper.children(currentRows).reverse();188 189 $currentRowElements.each(function(i) {190 var $el = $(this);191 setTimeout(function() {192 $el.fadeOut( opts.type.speed, opts.type.easing )193 }, seq_t + i * seq_t);194 });195 196 var $nextRowElements;197 ( dir === 1 )198 ? $nextRowElements = $wrapper.children(nextRows)199 : $nextRowElements = $wrapper.children(nextRows).reverse();200 201 var total_elems = $nextRowElements.length,202 cnt = 0;203 204 $nextRowElements.each(function(i) {205 var $el = $(this);206 setTimeout(function() {207 $el.fadeIn( opts.type.speed, opts.type.easing, function() {208 ++cnt;209 if( cnt === total_elems ) { 210 $wrapper.data( 'anim', false );211 } 212 })213 }, (seq_t * 2) + i * seq_t);214 });215 216 (dir === 1) ? config.currentRow += opts.rows : config.currentRow -= opts.rows;217 $wrapper.data('config', config);218 }219 },220 updown : {221 setup : function( $wrapper, $items, opts ) {222 var config = $wrapper.data('config');223 $wrapper.children(':gt(' + (config.shownItems - 1) + ')').css('opacity', 0);224 225 $items.each(function(i) {226 var $item = $(this),227 row = Math.ceil( (i + 1) / config.rowCount ),228 t = $item.position().top,229 f = row % opts.rows;230 231 if( row > opts.rows ) {232 t = (opts.rows * $items.height()); 233 }234 235 $item.css({ top : t + 'px'});236 });237 },238 pagination : function( $wrapper, dir, opts ) {239 var config = $wrapper.data('config');240 if( ( dir === 1 && config.currentRow + opts.rows > config.totalRows ) || 241 ( dir === -1 && config.currentRow - 1 <= 0 )242 ) {243 $wrapper.data( 'anim', false );244 return false;245 }246 247 var movingRows = '';248 249 for( var i = 0; i <= opts.rows; ++i ) {250 ( dir === 1 )251 ? movingRows += '.tj_row_' + (config.currentRow + i) + ','252 : movingRows += '.tj_row_' + (config.currentRow + (i - 1)) + ',';253 }254 255 var $elements;256 257 ( dir === 1 )258 ? $elements = $wrapper.children(movingRows)259 : $elements = $wrapper.children(movingRows).reverse();260 261 var total_elems = $elements.length,262 cnt = 0;263 264 $elements.each(function(i) {265 var $el = $(this),266 row = $el.attr('class'),267 animParam = {},268 269 currentRow = config.currentRow;270 271 // if first row fade out272 // if last row fade in273 // for all the rows move them up / down274 if( dir === 1 ) {275 if( row === 'tj_row_' + (currentRow) ) {276 animParam.opacity = 0;277 }278 else if( row === 'tj_row_' + (currentRow + opts.rows) ) {279 animParam.opacity = 1;280 }281 }282 else {283 if( row === 'tj_row_' + (currentRow - 1) ) {284 animParam.opacity = 1;285 }286 else if( row === 'tj_row_' + (currentRow + opts.rows - 1) ) {287 animParam.opacity = 0;288 }289 }290 291 $el.show();292 293 (dir === 1)294 ? animParam.top = $el.position().top - $el.height() + 'px'295 : animParam.top = $el.position().top + $el.height() + 'px'296 297 $el.stop().animate(animParam, opts.type.speed, opts.type.easing, function() {298 if( parseInt( animParam.top ) < 0 || parseInt( animParam.top ) > $el.height() * (opts.rows - 1) )299 $el.hide();300 301 ++cnt;302 if( cnt === total_elems ) {303 $wrapper.data( 'anim', false );304 } 305 });306 });307 308 (dir === 1) ? config.currentRow += 1 : config.currentRow -= 1;309 $wrapper.data('config', config);310 }311 },312 sequpdown : {313 setup : function( $wrapper, $items, opts ) {314 // same like updown mode315 nav['updown'].setup( $wrapper, $items, opts );316 },317 pagination : function( $wrapper, dir, opts ) {318 var config = $wrapper.data('config');319 if( ( dir === 1 && config.currentRow + opts.rows > config.totalRows ) || 320 ( dir === -1 && config.currentRow - 1 <= 0 ) 321 ) {322 $wrapper.data( 'anim', false );323 return false;324 }325 326 var movingRows = '';327 328 for( var i = 0; i <= opts.rows; ++i ) {329 ( dir === 1 )330 ? movingRows += '.tj_row_' + (config.currentRow + i) + ','331 : movingRows += '.tj_row_' + (config.currentRow + (i - 1)) + ',';332 }333 334 var seq_t = opts.type.factor,335 $elements;336 337 var dircond = 1;338 if( opts.type.reverse ) dircond = -1;339 ( dir === dircond )340 ? $elements = $wrapper.children(movingRows)341 : $elements = $wrapper.children(movingRows).reverse();342 343 var total_elems = $elements.length,344 cnt = 0;345 346 $elements.each(function(i) {347 var $el = $(this),348 row = $el.attr('class'),349 animParam = {},350 351 currentRow = config.currentRow;352 353 setTimeout(function() {354 // if first row fade out355 // if last row fade in356 // for all the rows move them up / down357 if( dir === 1 ) {358 if( row === 'tj_row_' + (currentRow) ) {359 animParam.opacity = 0;360 }361 else if( row === 'tj_row_' + (currentRow + opts.rows) ) {362 animParam.opacity = 1;363 }364 }365 else {366 if( row === 'tj_row_' + (currentRow - 1) ) {367 animParam.opacity = 1;368 }369 else if( row === 'tj_row_' + (currentRow + opts.rows - 1) ) {370 animParam.opacity = 0;371 }372 }373 374 $el.show();375 376 (dir === 1)377 ? animParam.top = $el.position().top - $el.height() + 'px'378 : animParam.top = $el.position().top + $el.height() + 'px'379 380 $el.stop().animate(animParam, opts.type.speed, opts.type.easing, function() {381 if( parseInt( animParam.top ) < 0 || parseInt( animParam.top ) > $el.height() * (opts.rows - 1) )382 $el.hide();383 384 ++cnt;385 if( cnt === total_elems ) { 386 $wrapper.data( 'anim', false );387 } 388 }); 389 }, seq_t + i * seq_t);390 });391 392 (dir === 1) ? config.currentRow += 1 : config.currentRow -= 1;393 $wrapper.data('config', config);394 }395 },396 showhide : {397 setup : function( $wrapper, $items, opts ) {398 var config = $wrapper.data('config');399 $items.each(function(i) {400 var $item = $(this),401 row = Math.ceil( (i + 1) / config.rowCount ),402 t,403 f = row % opts.rows;404 405 if( f === 1 ) {406 t = '0px'; 407 } else if( f === 0 ) {408 t = (opts.rows - 1) * $items.height() + 'px'; 409 } else {410 t = (f - 1) * $items.height() + 'px';411 }412 413 $item.css({ top : t });414 }); 415 },416 pagination : function( $wrapper, dir, opts ) {417 var config = $wrapper.data('config');418 if( ( dir === 1 && config.currentRow + opts.rows > config.totalRows ) || 419 ( dir === -1 && config.currentRow - opts.rows <= 0 )420 ) {421 $wrapper.data( 'anim', false );422 return false;423 }424 425 var currentRows = '', nextRows = '';426 427 for( var i = 0; i < opts.rows; ++i ) {428 currentRows += '.tj_row_' + (config.currentRow + i) + ',';429 430 (dir === 1)431 ? nextRows += '.tj_row_' + (config.currentRow + opts.rows + i) + ','432 : nextRows += '.tj_row_' + (config.currentRow - 1 - i) + ',';433 }434 435 $wrapper.children(currentRows).hide( opts.type.speed, opts.type.easing );436 437 var $nextRowElements= $wrapper.children(nextRows),438 totalNextRows = $nextRowElements.length,439 cnt = 0;440 441 $nextRowElements.show( opts.type.speed, opts.type.easing, function() {442 ++cnt;443 if( cnt === totalNextRows ) {444 $wrapper.data( 'anim', false );445 } 446 });447 448 (dir === 1) ? config.currentRow += opts.rows : config.currentRow -= opts.rows;449 $wrapper.data('config', config);450 }451 },452 disperse : {453 setup : function( $wrapper, $items, opts ) {454 var config = $wrapper.data('config');455 $items.each(function(i) {456 var $item = $(this),457 row = Math.ceil( (i + 1) / config.rowCount ),458 t,459 f = row % opts.rows;460 461 if( f === 1 ) {462 t = '0px'; 463 } else if( f === 0 ) {464 t = (opts.rows - 1) * $items.height() + 'px'; 465 } else {466 t = (f - 1) * $items.height() + 'px';467 }468 469 $item.css({ top : t }).data('top', t);470 });471 },472 pagination : function( $wrapper, dir, opts ) {473 var config = $wrapper.data('config');474 if( ( dir === 1 && config.currentRow + opts.rows > config.totalRows ) || 475 ( dir === -1 && config.currentRow - opts.rows <= 0 )476 ) {477 $wrapper.data( 'anim', false );478 return false;479 }480 481 var currentRows = '', nextRows = '';482 for( var i = 0; i < opts.rows; ++i ) {483 currentRows += '.tj_row_' + (config.currentRow + i) + ',';484 485 (dir === 1)486 ? nextRows += '.tj_row_' + (config.currentRow + opts.rows + i) + ','487 : nextRows += '.tj_row_' + (config.currentRow - 1 - i) + ',';488 }489 490 $wrapper.children(currentRows).each(function(i) {491 var $el = $(this);492 $el.stop().animate({493 left : $el.position().left + Math.floor( Math.random() * 101 ) - 50 + 'px',494 top : $el.position().top + Math.floor( Math.random() * 101 ) - 50 + 'px',495 opacity : 0496 }, opts.type.speed, opts.type.easing, function() {497 $el.css({498 left : $el.data('left'),499 top : $el.data('top')500 }).hide();501 });502 });503 504 var $nextRowElements = $wrapper.children(nextRows);505 total_elems = $nextRowElements.length,506 cnt = 0;507 508 $nextRowElements.each(function(i) {509 var $el = $(this);510 511 $el.css({512 left : parseInt($el.data('left')) + Math.floor( Math.random() * 301 ) - 150 + 'px', 513 top : parseInt($el.data('top')) + Math.floor( Math.random() * 301 ) - 150 + 'px',514 opacity : 0515 })516 .show()517 .animate({518 left : $el.data('left'),519 top : $el.data('top'),520 opacity : 1521 }, opts.type.speed, opts.type.easing, function() {522 ++cnt;523 if( cnt === total_elems ) { 524 $wrapper.data( 'anim', false );525 }526 });527 });528 529 (dir === 1) ? config.currentRow += opts.rows : config.currentRow -= opts.rows;530 $wrapper.data('config', config);531 }532 },533 rows : {534 setup : function( $wrapper, $items, opts ) {535 // same like def mode536 nav['def'].setup( $wrapper, $items, opts );537 },538 pagination : function( $wrapper, dir, opts ) {539 var config = $wrapper.data('config');540 if( ( dir === 1 && config.currentRow + opts.rows > config.totalRows ) || 541 ( dir === -1 && config.currentRow - opts.rows <= 0 )542 ) {543 $wrapper.data( 'anim', false );544 return false;545 }546 547 var currentRows = '', nextRows = '';548 for( var i = 0; i < opts.rows; ++i ) {549 currentRows += '.tj_row_' + (config.currentRow + i) + ',';550 551 (dir === 1)552 ? nextRows += '.tj_row_' + (config.currentRow + opts.rows + i) + ','553 : nextRows += '.tj_row_' + (config.currentRow - 1 - i) + ',';554 }555 556 $wrapper.children(currentRows).each(function(i) {557 var $el = $(this),558 rownmb = $el.attr('class').match(/tj_row_(\d+)/)[1],559 diff;560 561 if( rownmb%2 === 0 ) {562 diff = opts.type.factor;563 }564 else {565 diff = -opts.type.factor;566 }567 568 $el.stop().animate({569 left : $el.position().left + diff + 'px',570 opacity : 0571 }, opts.type.speed, opts.type.easing, function() {572 $el.css({573 left : $el.data('left')574 }).hide();575 });576 });577 578 var $nextRowElements = $wrapper.children(nextRows);579 total_elems = $nextRowElements.length,580 cnt = 0;581 582 $nextRowElements.each(function(i) {583 var $el = $(this),584 rownmb = $el.attr('class').match(/tj_row_(\d+)/)[1],585 diff;586 587 if( rownmb%2 === 0 ) {588 diff = opts.type.factor;589 }590 else {591 diff = -opts.type.factor;592 }593 594 $el.css({595 left : parseInt($el.data('left')) + diff + 'px',596 opacity : 0597 })598 .show()599 .animate({600 left : $el.data('left'),601 opacity : 1602 }, opts.type.speed, opts.type.easing, function() {603 ++cnt;604 if( cnt === total_elems ) { 605 $wrapper.data( 'anim', false );606 }607 });608 });609 610 (dir === 1) ? config.currentRow += opts.rows : config.currentRow -= opts.rows;611 $wrapper.data('config', config);612 }613 }614 },615 methods = {616 init : function( options ) {617 618 if( this.length ) {619 620 var settings = {621 rows : 2,622 navL : '#tj_prev',623 navR : '#tj_next',624 type : {625 mode : 'def', // use def | fade | seqfade | updown | sequpdown | showhide | disperse | rows626 speed : 500, // for fade, seqfade, updown, sequpdown, showhide, disperse, rows627 easing : 'jswing', // for fade, seqfade, updown, sequpdown, showhide, disperse, rows 628 factor : 50, // for seqfade, sequpdown, rows629 reverse : false // for sequpdown630 }631 };632 633 return this.each(function() {634 635 // if options exist, lets merge them with our default settings636 if ( options ) {637 $.extend( settings, options );638 }639 640 var $el = $(this).css( 'visibility', 'hidden' ),641 // the ul642 $wrapper = $el.find('ul.tj_gallery'),643 // the items644 $thumbs = $wrapper.children('li'),645 total = $thumbs.length,646 // the navigation elements647 $p_nav = $(settings.navL),648 $n_nav = $(settings.navR);649 650 // save current row for later (first visible row)651 //config.currentRow = 1;652 653 // flag to control animation progress654 $wrapper.data( 'anim', false );655 656 // preload thumbs657 var loaded = 0;658 $thumbs.find('img').each( function(i) {659 var $img = $(this);660 $('<img/>').load( function() {661 ++loaded;662 if( loaded === total ) {663 664 // setup665 aux.setup( $wrapper, $thumbs, settings );666 $el.css( 'visibility', 'visible' );667 668 // navigation events669 if( $p_nav.length ) {670 $p_nav.bind('click.gridnav', function( e ) {671 if( $wrapper.data( 'anim' ) ) return false;672 $wrapper.data( 'anim', true );673 nav[settings.type.mode].pagination( $wrapper, -1, settings );674 return false;675 });676 }677 if( $n_nav.length ) {678 $n_nav.bind('click.gridnav', function( e ) {679 if( $wrapper.data( 'anim' ) ) return false;680 $wrapper.data( 'anim', true );681 nav[settings.type.mode].pagination( $wrapper, 1, settings );682 return false;683 });684 }685 /*686 adds events to the mouse687 */688 $el.bind('mousewheel.gridnav', function(e, delta) {689 if(delta > 0) {690 if( $wrapper.data( 'anim' ) ) return false;691 $wrapper.data( 'anim', true );692 nav[settings.type.mode].pagination( $wrapper, -1, settings );693 } 694 else {695 if( $wrapper.data( 'anim' ) ) return false;696 $wrapper.data( 'anim', true );697 nav[settings.type.mode].pagination( $wrapper, 1, settings );698 } 699 return false;700 });701 702 }703 }).attr( 'src', $img.attr('src') );704 });705 706 });707 }708 }709 };710 711 $.fn.gridnav = function(method) {712 if ( methods[method] ) {713 return methods[method].apply( this, Array.prototype.slice.call( arguments, 1 ));714 } else if ( typeof method === 'object' || ! method ) {715 return methods.init.apply( this, arguments );716 } else {717 $.error( 'Method ' + method + ' does not exist on jQuery.gridnav' );718 }719 };...

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checkpoint_ops_test.py

Source:checkpoint_ops_test.py Github

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...172 [33, init_val, init_val, init_val, 1, init_val], [3, 2])173 with self.cached_session():174 self.assertAllClose(expected_remapped_matrix,175 self.evaluate(remapped_matrix))176 def test_load_and_remap_all_missing_rows(self):177 """Tests when all the rows are missing and need to be initialized."""178 num_rows = 7179 initializing_values = [42] * num_rows * self.old_num_cols180 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(181 ckpt_path=[self.bundle_file],182 old_tensor_name=self.old_tensor_name,183 row_remapping=[-1] * num_rows,184 col_remapping=[],185 initializing_values=initializing_values,186 num_rows=num_rows,187 num_cols=self.old_num_cols)188 with self.cached_session():189 self.assertAllClose(190 np.reshape(initializing_values, (num_rows, self.old_num_cols)),191 self.evaluate(remapped_matrix))192 def test_load_and_remap_all_missing_rows_and_cols(self):193 """Tests when all the rows & cols are missing and need to be initialized."""194 num_rows = 7195 num_cols = 4196 initializing_values = [42] * num_rows * num_cols197 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(198 ckpt_path=[self.bundle_file],199 old_tensor_name=self.old_tensor_name,200 row_remapping=[-1] * num_rows,201 col_remapping=[-1] * num_cols,202 initializing_values=initializing_values,203 num_rows=num_rows,204 num_cols=num_cols)205 with self.cached_session():206 self.assertAllClose(207 np.reshape(initializing_values, (num_rows, num_cols)),208 self.evaluate(remapped_matrix))209 @test_util.run_deprecated_v1210 def test_load_and_remap_invalid_remapping(self):211 """Tests that errors are raised when an ID maps to multiple new IDs.212 (This should usually not happen when using public APIs).213 """214 invalid_remapping = [1, 0, 0, 0, 1, 2]215 # Invalid row remapping.216 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(217 ckpt_path=[self.bundle_file],218 old_tensor_name=self.old_tensor_name,219 row_remapping=invalid_remapping,220 col_remapping=[],221 initializing_values=[],222 num_rows=len(invalid_remapping),223 num_cols=self.old_num_cols)224 with self.cached_session(), self.assertRaises(errors.UnimplementedError):225 self.evaluate(remapped_matrix)226 # Invalid column remapping.227 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(228 ckpt_path=[self.bundle_file],229 old_tensor_name=self.old_tensor_name,230 row_remapping=list(range(self.old_num_rows)),231 col_remapping=invalid_remapping,232 initializing_values=[],233 num_rows=self.old_num_rows,234 num_cols=len(invalid_remapping))235 with self.cached_session(), self.assertRaises(errors.UnimplementedError):236 self.evaluate(remapped_matrix)237 @test_util.run_deprecated_v1238 def test_load_and_remap_incorrect_initializing_values(self):239 """Tests that errors are raised with incorrect number of init values."""240 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(241 ckpt_path=[self.bundle_file],242 old_tensor_name=self.old_tensor_name,243 row_remapping=[2, -1, 0],244 col_remapping=[1, -1],245 # Too few initializing values - there should be 4. For some reason,246 # initializing_values must contain no element (instead of 3 or fewer) to247 # ensure that a seg fault would reliably occur if the check raising the248 # InvalidArgumentError were not present.249 initializing_values=[],250 num_rows=3,251 num_cols=2)252 with self.cached_session(), self.assertRaises(errors.InvalidArgumentError):253 self.evaluate(remapped_matrix)254 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(255 ckpt_path=[self.bundle_file],256 old_tensor_name=self.old_tensor_name,257 row_remapping=[2, -1, 0],258 col_remapping=[1, -1],259 # Too many initializing values - there should be 4.260 initializing_values=[0] * 5,261 num_rows=3,262 num_cols=2)263 with self.cached_session(), self.assertRaises(errors.InvalidArgumentError):264 self.evaluate(remapped_matrix)265class LoadAndRemapMatrixWithMaxRowsTest(test.TestCase):266 """Tests for the load_and_remap_matrix() op.267 (Specifically focused on the max_rows_in_memory arg and its effects on268 TensorBundle's BundleReader and TensorSlice logic).269 """270 def _test_loading_variable_with_max_rows(self, np_value, partitioner,271 max_rows_in_memory):272 """Helper function for various tests using max_rows_in_memory."""273 ops.reset_default_graph()274 old_tensor_name = 'matrix_to_load_and_remap'275 matrix = variable_scope.get_variable(276 old_tensor_name,277 dtype=dtypes.float32,278 initializer=constant_op.constant(np_value, dtype=dtypes.float32),279 partitioner=partitioner)280 with self.cached_session() as sess:281 ckpt_path = os.path.join(test.get_temp_dir(), 'temp_ckpt')282 save = saver.Saver([matrix])283 self.evaluate(variables.global_variables_initializer())284 save.save(sess, ckpt_path)285 num_rows, num_cols = np_value.shape286 # Tests loading the entire tensor (except reversed).287 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(288 ckpt_path=ckpt_path,289 old_tensor_name=old_tensor_name,290 # Simply reverses the rows of the matrix.291 row_remapping=list(range(num_rows - 1, -1, -1)),292 col_remapping=[],293 initializing_values=[],294 num_rows=num_rows,295 num_cols=num_cols,296 max_rows_in_memory=max_rows_in_memory)297 self.assertAllClose(np_value[::-1], self.evaluate(remapped_matrix))298 # Tests loading the tensor (except for the first and last rows), with299 # uninitialized values. Requires num_rows to be at least 3 since we're300 # skipping the first and last rows.301 self.assertGreater(num_rows, 2)302 prefix_rows = 2303 suffix_rows = 3304 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(305 ckpt_path=ckpt_path,306 old_tensor_name=old_tensor_name,307 # Reverses the rows of the matrix, then prepends and appends308 # uninitialized rows.309 row_remapping=([-1] * prefix_rows + list(range(1, num_rows - 1)) +310 [-1] * suffix_rows),311 col_remapping=[],312 initializing_values=[42] * (prefix_rows + suffix_rows) * num_cols,313 num_rows=num_rows - 2 + prefix_rows + suffix_rows,314 num_cols=num_cols,315 max_rows_in_memory=max_rows_in_memory)316 self.assertAllClose(317 np.vstack([318 np.tile(42, [prefix_rows, num_cols]), np_value[1:-1],319 np.tile(42, [suffix_rows, num_cols])320 ]), self.evaluate(remapped_matrix))321 # Tests when everything is taken from initializing_values.322 new_rows = 7323 initializing_values = [42] * new_rows * num_cols324 remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(325 ckpt_path=ckpt_path,326 old_tensor_name=old_tensor_name,327 # Nothing is loaded from the old tensor.328 row_remapping=[-1] * new_rows,329 col_remapping=[],330 initializing_values=initializing_values,331 num_rows=new_rows,332 num_cols=num_cols,333 max_rows_in_memory=max_rows_in_memory)334 self.assertAllClose(335 np.reshape(initializing_values, (new_rows, num_cols)),336 self.evaluate(remapped_matrix))337 @test_util.run_deprecated_v1338 def test_loading_rows_divisible_by_max_rows(self):339 """Tests loading normal var when rows are evenly divisible by max_rows."""340 self._test_loading_variable_with_max_rows(341 np_value=np.reshape(list(range(0, 36)), (9, 4)),342 partitioner=None,343 # 9 is evenly divisible by 3.344 max_rows_in_memory=3)345 @test_util.run_deprecated_v1346 def test_loading_rows_not_divisible_by_max_rows(self):347 """Tests loading normal var when rows aren't divisible by max_rows."""348 self._test_loading_variable_with_max_rows(349 np_value=np.reshape(list(range(0, 36)), (9, 4)),350 partitioner=None,351 # 9 is not evenly divisible by 4.352 max_rows_in_memory=4)353 @test_util.run_deprecated_v1354 def test_loading_rows_less_than_max_rows(self):355 """Tests loading normal var as a single slice.356 (When the specified max_rows_in_memory is larger than the number of rows)357 """358 self._test_loading_variable_with_max_rows(359 np_value=np.reshape(list(range(0, 36)), (9, 4)),360 partitioner=None,361 # 10 > 9.362 max_rows_in_memory=10)363 @test_util.run_deprecated_v1364 def test_loading_no_max_rows(self):365 """Tests loading normal var as a single slice with no valid max_rows."""366 self._test_loading_variable_with_max_rows(367 np_value=np.reshape(list(range(0, 18)), (6, 3)),368 partitioner=None,369 max_rows_in_memory=-1)370 @test_util.run_deprecated_v1371 def test_loading_partitions_equals_max_rows(self):372 """Tests loading partitioned var sliced on partition boundary."""373 self._test_loading_variable_with_max_rows(374 np_value=np.reshape(list(range(0, 36)), (9, 4)),375 partitioner=partitioned_variables.fixed_size_partitioner(3),376 # With a tensor of shape [9, 3] and 3 partitions, each partition has377 # exactly 3 rows.378 max_rows_in_memory=3)379 @test_util.run_deprecated_v1380 def test_loading_partitions_greater_than_max_rows(self):381 """Tests loading partitioned var with more slices than partitions."""382 self._test_loading_variable_with_max_rows(383 np_value=np.reshape(list(range(0, 36)), (9, 4)),384 partitioner=partitioned_variables.fixed_size_partitioner(3),385 # Even though each partition has 3 rows, we'll only load the tensor one386 # row at a time.387 max_rows_in_memory=1)388 @test_util.run_deprecated_v1389 def test_loading_partitions_less_than_max_rows(self):390 """Tests loading partitioned var as a single slice.391 (When the specified max_rows_in_memory is larger than the number of rows)392 """393 self._test_loading_variable_with_max_rows(394 np_value=np.reshape(list(range(0, 36)), (9, 4)),395 partitioner=partitioned_variables.fixed_size_partitioner(3),396 max_rows_in_memory=10)397 @test_util.run_deprecated_v1398 def test_loading_partitions_no_max_rows(self):399 """Tests loading partitioned var as single slice with no valid max_rows."""400 self._test_loading_variable_with_max_rows(401 np_value=np.reshape(list(range(0, 36)), (9, 4)),402 partitioner=partitioned_variables.fixed_size_partitioner(3),403 max_rows_in_memory=-1)404if __name__ == '__main__':...

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table.py

Source:table.py Github

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1"""2"""3from const import *4import container5class Table(container.Container):6 """A table style container.7 8 <p>If you know HTML, this should all work roughly how you would expect. If you are not9 familiar with HTML, please read <a href="http://www.w3.org/TR/REC-html40/struct/tables.html">Tables in HTML Documents</a>. Pay attention to TABLE, TR, TD related parts of the document.</p>10 11 <pre>Table()</pre>12 13 <strong>Example</strong>14 <code>15 t = gui.Table()16 17 t.tr()18 t.td(gui.Label("First Name"), align=-1)19 t.td(gui.Input())20 t.tr()21 t.td(gui.Label("Last Name"), align=-1)22 t.td(gui.Input())23 </code>24 25 """26 27 28 def __init__(self, **params):29 params.setdefault('cls','table')30 container.Container.__init__(self, **params)31 self._rows = []32 self._curRow = 033 self._trok = False34 35 def getRows(self):36 return len(self._rows)37 38 def getColumns(self):39 if self._rows:40 return len(self._rows[0])41 else:42 return 043 44 def remove_row(self, n): #NOTE: won't work in all cases.45 if n >= self.getRows():46 print "Trying to remove a nonexistant row:", n, "there are only", self.getRows(), "rows"47 return48 49 for cell in self._rows[n]:50 if isinstance(cell, dict) and cell["widget"] in self.widgets:51 #print 'removing widget'52 self.widgets.remove(cell["widget"])53 del self._rows[n]54 #print "got here"55 56 for w in self.widgets:57 if w.style.row > n: w.style.row -= 158 59 if self._curRow >= n:60 self._curRow -= 161 62 #self.rect.w, self.rect.h = self.resize()63 #self.repaint()64 65 self.chsize()66 67 def clear(self):68 self._rows = []69 self._curRow = 070 self._trok = False71 self.widgets = []72 73 self.chsize()74 75 #print 'clear',self,self._rows76 77 def _addRow(self):78 self._rows.append([None for x in xrange(self.getColumns())])79 80 def tr(self):81 """Start on the next row."""82 if not self._trok:83 self._trok = True84 return 85 self._curRow += 186 if self.getRows() <= self._curRow:87 self._addRow()88 89 def _addColumn(self):90 if not self._rows:91 self._addRow()92 for row in self._rows:93 row.append(None)94 95 def _setCell(self, w, col, row, colspan=1, rowspan=1):96 #make room for the widget by adding columns and rows97 while self.getColumns() < col + colspan:98 self._addColumn()99 while self.getRows() < row + rowspan:100 self._addRow()101 102 #print w.__class__.__name__,col,row,colspan,rowspan103 104 #actual widget setting and modification stuff105 w.container = self106 w.style.row = row #HACK - to work with gal's list107 w.style.col = col #HACK - to work with gal's list108 self._rows[row][col] = {"widget":w, "colspan":colspan, "rowspan":rowspan}109 self.widgets.append(self._rows[row][col]["widget"])110 111 #set the spanned columns112 #for acell in xrange(col + 1, col + colspan):113 # self._rows[row][acell] = True114 115 #set the spanned rows and the columns on them116 #for arow in xrange(row + 1, row + rowspan):117 # for acell in xrange(col, col + colspan): #incorrect?118 # self._rows[arow][acell] = True119 120 for arow in xrange(row, row + rowspan):121 for acell in xrange(col, col + colspan): #incorrect?122 if row != arow or col != acell:123 self._rows[arow][acell] = True124 125 126 def td(self, w, col=None, row=None, colspan=1, rowspan=1, **params):127 """Add a widget to a table after wrapping it in a TD container.128 129 <pre>Table.td(w,col=None,row=None,colspan=1,rowspan=1,**params)</pre>130 131 <dl>132 <dt>w<dd>widget133 <dt>col<dd>column134 <dt>row<dd>row135 <dt>colspan<dd>colspan136 <dt>rowspan<dd>rowspan137 <dt>align<dd>horizontal alignment (-1,0,1)138 <dt>valign<dd>vertical alignment (-1,0,1)139 <dt>params<dd>other params for the TD container, style information, etc140 </dl>141 """142 143 Table.add(self,_Table_td(w, **params), col=col, row=row, colspan=colspan, rowspan=rowspan)144 145 def add(self, w, col=None, row=None, colspan=1, rowspan=1):146 """Add a widget directly into the table, without wrapping it in a TD container.147 148 <pre>Table.add(w,col=None,row=None,colspan=1,rowspan=1)</pre>149 150 <p>See Table.td for an explanation of the parameters.</p>151 """152 self._trok = True153 #if no row was specifically specified, set it to the current row154 if row is None:155 row = self._curRow156 #print row157 158 #if its going to be a new row, have it be on the first column159 if row >= self.getRows():160 col = 0161 162 #try to find an open cell for the widget163 if col is None:164 for cell in xrange(self.getColumns()):165 if col is None and not self._rows[row][cell]:166 col = cell167 break168 169 #otherwise put the widget in a new column170 if col is None:171 col = self.getColumns()172 173 self._setCell(w, col, row, colspan=colspan, rowspan=rowspan)174 175 self.chsize()176 return177 178 def remove(self,w):179 if hasattr(w,'_table_td'): w = w._table_td180 row,col = w.style.row,w.style.col181 cell = self._rows[row][col]182 colspan,rowspan = cell['colspan'],cell['rowspan']183 184 for arow in xrange(row , row + rowspan):185 for acell in xrange(col, col + colspan): #incorrect?186 self._rows[arow][acell] = False187 self.widgets.remove(w)188 self.chsize()189 190 191 192 def resize(self, width=None, height=None):193 #if 1 or self.getRows() == 82:194 #print ''195 #print 'resize',self.getRows(),self.getColumns(),width,height196 #import inspect197 #for obj,fname,line,fnc,code,n in inspect.stack()[9:20]:198 # print fname,line,':',fnc,code[0].strip()199 200 #resize the widgets to their smallest size201 for w in self.widgets:202 w.rect.w, w.rect.h = w.resize()203 204 #calculate row heights and column widths205 rowsizes = [0 for y in xrange(self.getRows())]206 columnsizes = [0 for x in xrange(self.getColumns())]207 for row in xrange(self.getRows()):208 for cell in xrange(self.getColumns()):209 if self._rows[row][cell] and self._rows[row][cell] is not True:210 if not self._rows[row][cell]["colspan"] > 1:211 columnsizes[cell] = max(columnsizes[cell], self._rows[row][cell]["widget"].rect.w)212 if not self._rows[row][cell]["rowspan"] > 1:213 rowsizes[row] = max(rowsizes[row], self._rows[row][cell]["widget"].rect.h)214 215 #distribute extra space if necessary for wide colspanning/rowspanning216 for row in xrange(self.getRows()):217 for cell in xrange(self.getColumns()):218 if self._rows[row][cell] and self._rows[row][cell] is not True:219 if self._rows[row][cell]["colspan"] > 1:220 columns = xrange(cell, cell + self._rows[row][cell]["colspan"])221 totalwidth = 0222 for acol in columns:223 totalwidth += columnsizes[acol]224 if totalwidth < self._rows[row][cell]["widget"].rect.w:225 for acol in columns:226 columnsizes[acol] += _table_div(self._rows[row][cell]["widget"].rect.w - totalwidth, self._rows[row][cell]["colspan"],acol)227 if self._rows[row][cell]["rowspan"] > 1:228 rows = xrange(row, row + self._rows[row][cell]["rowspan"])229 totalheight = 0230 for arow in rows:231 totalheight += rowsizes[arow]232 if totalheight < self._rows[row][cell]["widget"].rect.h:233 for arow in rows:234 rowsizes[arow] += _table_div(self._rows[row][cell]["widget"].rect.h - totalheight, self._rows[row][cell]["rowspan"],arow)235 236 #make everything fill out to self.style.width, self.style.heigh, not exact, but pretty close...237 w, h = sum(columnsizes), sum(rowsizes)238 if w > 0 and w < self.style.width and len(columnsizes):239 d = (self.style.width - w) 240 for n in xrange(0, len(columnsizes)):241 v = columnsizes[n]242 columnsizes[n] += v * d / w243 if h > 0 and h < self.style.height and len(rowsizes):244 d = (self.style.height - h) / len(rowsizes)245 for n in xrange(0, len(rowsizes)):246 v = rowsizes[n]247 rowsizes[n] += v * d / h248 249 #set the widget's position by calculating their row/column x/y offset250 cellpositions = [[[sum(columnsizes[0:cell]), sum(rowsizes[0:row])] for cell in xrange(self.getColumns())] for row in xrange(self.getRows())]251 for row in xrange(self.getRows()):252 for cell in xrange(self.getColumns()):253 if self._rows[row][cell] and self._rows[row][cell] is not True:254 x, y = cellpositions[row][cell]255 w = sum(columnsizes[cell:cell+self._rows[row][cell]["colspan"]])256 h = sum(rowsizes[row:row+self._rows[row][cell]["rowspan"]])257 258 widget = self._rows[row][cell]["widget"]259 widget.rect.x = x260 widget.rect.y = y261 if 1 and (w,h) != (widget.rect.w,widget.rect.h):262# if h > 20:263# print widget.widget.__class__.__name__, (widget.rect.w,widget.rect.h),'=>',(w,h)264 widget.rect.w, widget.rect.h = widget.resize(w, h)265 266 #print self._rows[row][cell]["widget"].rect267 268 #print columnsizes269 #print sum(columnsizes)270 #size = sum(columnsizes), sum(rowsizes); print size271 272 #return the tables final size273 return sum(columnsizes),sum(rowsizes)274 275def _table_div(a,b,c):276 v,r = a/b, a%b277 if r != 0 and (c%b)<r: v += 1278 return v279class _Table_td(container.Container):280 def __init__(self,widget,**params):#hexpand=0,vexpand=0,281 container.Container.__init__(self,**params)282 self.widget = widget283 #self.hexpand=hexpand284 #self.vexpand=vexpand285 widget._table_td = self286 self.add(widget,0,0)287 288 def resize(self,width=None,height=None):289 w = self.widget290 291 #expansion code, but i didn't like the idea that much..292 #a bit obscure, fairly useless when a user can just293 #add a widget to a table instead of td it in.294 #ww,hh=None,None295 #if self.hexpand: ww = self.style.width296 #if self.vexpand: hh = self.style.height297 #if self.hexpand and width != None: ww = max(ww,width)298 #if self.vexpand and height != None: hh = max(hh,height)299 #w.rect.w,w.rect.h = w.resize(ww,hh)300 301 #why bother, just do the lower mentioned item...302 w.rect.w,w.rect.h = w.resize()303 304 #this should not be needed, widgets should obey their sizing on their own.305 306# if (self.style.width!=0 and w.rect.w > self.style.width) or (self.style.height!=0 and w.rect.h > self.style.height):307# ww,hh = None,None308# if self.style.width: ww = self.style.width309# if self.style.height: hh = self.style.height310# w.rect.w,w.rect.h = w.resize(ww,hh)311 312 313 #in the case that the widget is too big, we try to resize it314 if (width != None and width < w.rect.w) or (height != None and height < w.rect.h):315 w.rect.w,w.rect.h = w.resize(width,height)316 317 width = max(width,w.rect.w,self.style.width) #,self.style.cell_width)318 height = max(height,w.rect.h,self.style.height) #,self.style.cell_height)319 320 dx = width-w.rect.w321 dy = height-w.rect.h322 w.rect.x = (self.style.align+1)*dx/2323 w.rect.y = (self.style.valign+1)*dy/2324 ...

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verify_benchmarks.py

Source:verify_benchmarks.py Github

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1"""2sobh@illinois.edu3"""4import filecmp5import os6import time7verification_dir = '../data/verification/'8results_dir = '../test/run_dir/results'9def verify_benchmark(option, algo_name, BENCHMARK_name_list, BENCHMARK_YML):10 run_command = 'python3 ../src/general_clustering.py -run_directory ./run_dir -run_file ' + BENCHMARK_YML11 os.system(run_command)12 All_files_in_results_dir = os.listdir(results_dir)13 num_failed_tests = 014 num_succeed_tests = 015 for f in All_files_in_results_dir:16 for BENCHMARK_name in BENCHMARK_name_list:17 if BENCHMARK_name in f:18 RESULT = os.path.join(results_dir, f)19 BENCHMARK = os.path.join(verification_dir, option, algo_name, BENCHMARK_name + '.tsv')20 if filecmp.cmp(RESULT, BENCHMARK) == True:21 num_succeed_tests += 122 print(BENCHMARK, '______ PASS ______')23 else:24 num_failed_tests += 125 print(BENCHMARK, '****** FAIL ******')26 return num_succeed_tests, num_failed_tests27def main():28 BENCHMARK = {29 'binary': {30 'kmeans': [31 'BENCHMARK_1_kmeans_binary.yml',32 'rows_averages_by_cluster_kmeans',33 'rows_by_columns_heatmap_kmeans',34 'rows_variance_kmeans',35 'samples_label_by_cluster_kmeans',36 'silhouette_overall_score_kmeans',37 'silhouette_per_cluster_score_kmeans',38 'silhouette_per_sample_score_kmeans',39 'top_rows_by_cluster_kmeans'40 ],41 'hclust': [42 'BENCHMARK_3_hclust_binary.yml',43 'rows_averages_by_cluster_hclust',44 'rows_by_columns_heatmap_hclust',45 'rows_variance_hclust',46 'samples_label_by_cluster_hclust',47 'silhouette_overall_score_hclust',48 'silhouette_per_cluster_score_hclust',49 'silhouette_per_sample_score_hclust',50 'top_rows_by_cluster_hclust'51 ],52 'link_hclust': [53 'BENCHMARK_5_link_hclust_binary.yml',54 'rows_averages_by_cluster_link_hclust',55 'rows_by_columns_heatmap_link_hclust',56 'rows_variance_link_hclust',57 'samples_label_by_cluster_link_hclust',58 'silhouette_overall_score_link_hclust',59 'silhouette_per_cluster_score_link_hclust',60 'silhouette_per_sample_score_link_hclust',61 'top_rows_by_cluster_link_hclust'62 ],63 'cc_kmeans': [64 'BENCHMARK_7_cc_kmeans_binary.yml',65 'consensus_matrix_cc_kmeans',66 'rows_averages_by_cluster_cc_kmeans',67 'rows_by_columns_heatmap_cc_kmeans',68 'rows_variance_cc_kmeans',69 'samples_label_by_cluster_cc_kmeans',70 'silhouette_overall_score_cc_kmeans',71 'silhouette_per_cluster_score_cc_kmeans',72 'silhouette_per_sample_score_cc_kmeans',73 'top_rows_by_cluster_cc_kmeans'74 ],75 'cc_hclust': [76 'BENCHMARK_9_cc_hclust_binary.yml',77 'consensus_matrix_cc_hclust',78 'rows_averages_by_cluster_cc_hclust',79 'rows_by_columns_heatmap_cc_hclust',80 'rows_variance_cc_hclust',81 'samples_label_by_cluster_cc_hclust',82 'silhouette_overall_score_cc_hclust',83 'silhouette_per_cluster_score_cc_hclust',84 'silhouette_per_sample_score_cc_hclust',85 'top_rows_by_cluster_cc_hclust'86 ],87 'cc_link_hclust': [88 'BENCHMARK_11_cc_link_hclust_binary.yml',89 'consensus_matrix_cc_link_hclust',90 'rows_averages_by_cluster_cc_link_hclust',91 'rows_by_columns_heatmap_cc_link_hclust',92 'rows_variance_cc_link_hclust',93 'samples_label_by_cluster_cc_link_hclust',94 'silhouette_overall_score_cc_link_hclust',95 'silhouette_per_cluster_score_cc_link_hclust',96 'silhouette_per_sample_score_cc_link_hclust',97 'top_rows_by_cluster_cc_link_hclust'98 ],99 'kmeans_evaluation': [100 'BENCHMARK_13_kmeans_binary_evaluation.yml',101 'rows_averages_by_cluster_kmeans',102 'rows_by_columns_heatmap_kmeans',103 'rows_variance_kmeans',104 'samples_label_by_cluster_kmeans',105 'silhouette_overall_score_kmeans',106 'silhouette_per_cluster_score_kmeans',107 'silhouette_per_sample_score_kmeans',108 'top_rows_by_cluster_kmeans',109 'clustering_evaluation_result'110 ]111 },112 'continuous': {113 'kmeans': [114 'BENCHMARK_2_kmeans_continuous.yml',115 'rows_averages_by_cluster_kmeans',116 'rows_by_columns_heatmap_kmeans',117 'rows_variance_kmeans',118 'samples_label_by_cluster_kmeans',119 'silhouette_overall_score_kmeans',120 'silhouette_per_cluster_score_kmeans',121 'silhouette_per_sample_score_kmeans',122 'top_rows_by_cluster_kmeans'123 ],124 'hclust': [125 'BENCHMARK_4_hclust_continuous.yml',126 'rows_averages_by_cluster_hclust',127 'rows_by_columns_heatmap_hclust',128 'rows_variance_hclust',129 'samples_label_by_cluster_hclust',130 'silhouette_overall_score_hclust',131 'silhouette_per_cluster_score_hclust',132 'silhouette_per_sample_score_hclust',133 'top_rows_by_cluster_hclust'134 ],135 'link_hclust': [136 'BENCHMARK_6_link_hclust_continuous.yml',137 'rows_averages_by_cluster_link_hclust',138 'rows_by_columns_heatmap_link_hclust',139 'rows_variance_link_hclust',140 'samples_label_by_cluster_link_hclust',141 'silhouette_overall_score_link_hclust',142 'silhouette_per_cluster_score_link_hclust',143 'silhouette_per_sample_score_link_hclust',144 'top_rows_by_cluster_link_hclust'145 ],146 'cc_kmeans': [147 'BENCHMARK_8_cc_kmeans_continuous.yml',148 'consensus_matrix_cc_kmeans',149 'rows_averages_by_cluster_cc_kmeans',150 'rows_by_columns_heatmap_cc_kmeans',151 'rows_variance_cc_kmeans',152 'samples_label_by_cluster_cc_kmeans',153 'silhouette_overall_score_cc_kmeans',154 'silhouette_per_cluster_score_cc_kmeans',155 'silhouette_per_sample_score_cc_kmeans',156 'top_rows_by_cluster_cc_kmeans'157 ],158 'cc_hclust': [159 'BENCHMARK_X_cc_hclust_continuous.yml',160 'consensus_matrix_cc_hclust',161 'rows_averages_by_cluster_cc_hclust',162 'rows_by_columns_heatmap_cc_hclust',163 'rows_variance_cc_hclust',164 'samples_label_by_cluster_cc_hclust',165 'silhouette_overall_score_cc_hclust',166 'silhouette_per_cluster_score_cc_hclust',167 'silhouette_per_sample_score_cc_hclust',168 'top_rows_by_cluster_cc_hclust'169 ],170 'cc_link_hclust': [171 'BENCHMARK_12_cc_link_hclust_continuous.yml',172 'consensus_matrix_cc_link_hclust',173 'rows_averages_by_cluster_cc_link_hclust',174 'rows_by_columns_heatmap_cc_link_hclust',175 'rows_variance_cc_link_hclust',176 'samples_label_by_cluster_cc_link_hclust',177 'silhouette_overall_score_cc_link_hclust',178 'silhouette_per_cluster_score_cc_link_hclust',179 'silhouette_per_sample_score_cc_link_hclust',180 'top_rows_by_cluster_cc_link_hclust'181 ]182 }183 }184 os.system('make env_setup')185 start_time = time.time()186 total_success, total_failure = 0, 0187 for option in BENCHMARK.keys():188 for key in BENCHMARK[option].keys():189 BENCHMARK_list = BENCHMARK[option][key]190 BENCHMARK_YML = BENCHMARK_list[0]191 print()192 print("INFO: Running test ", "./run_dir/results/" + BENCHMARK_YML)193 # for BENCHMARK_name in BENCHMARK_list[1:]:194 num_succeed_tests, num_failed_tests = verify_benchmark(option, key, BENCHMARK_list[1:], BENCHMARK_YML)195 total_success += num_succeed_tests196 total_failure += num_failed_tests197 os.system('rm ./run_dir/results/*')198 end_time = time.time()199 print()200 print("Ran {} tests in {}s".format(total_success + total_failure, end_time - start_time))201 if (total_failure == 0):202 print("OK")203 print()204 else:205 print("FAILED(errors={})".format(total_failure))206if __name__ == "__main__":...

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jquery.autoResizeTextAreaQ-0.1.js

Source:jquery.autoResizeTextAreaQ-0.1.js Github

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1/*2 * jQuery autoResizeTextAreaQ plugin3 * @requires jQuery v1.4.2 or later4 *5 * Copyright (c) 2010 M. Brown (mbrowniebytes A gmail.com)6 * Licensed under the Revised BSD license:7 * http://www.opensource.org/licenses/bsd-license.php8 * http://en.wikipedia.org/wiki/BSD_licenses9 *10 * Versions:11 * 0.1 - 2010-07-2112 * initial13 *14 * usage:15 * $(document).ready( function() {16 * $('textarea').autoResizeTextAreaQ({"max_rows":8});17 * });18 *19 */20(function($) {21$.fn.autoResizeTextAreaQ = function(options) {22 var opts = $.extend({23 // ya prob want to use24 max_rows: 10, // # - max rows to resize too25 // ya may want to use, but defaults should be ok26 extra_rows: 1, // # - nbr extra rows after last line ie padding; 0|1 optimal27 // ya should really specify in html28 rows: null, // null|# - null infer from html; # override html29 cols: null, // null|# - null infer from html; # override html30 debug: false // true|false - turn on|off console.log()31 }, options);32 // extra padding based on browser33 /* Removed jQuery 1.9.x34 if ($.browser.msie) {35 opts.extra_rows += 1;36 } else if ($.browser.webkit) {37 opts.extra_rows += 1;38 } // else $.browser.mozilla39 */40 opts.extra_rows += 1; // use webkit only.41 // iterate over passed in selector, only process actual textareas42 return $(this).filter('textarea').each(function(index) {43 var ta = $(this);44 var orig = {};45 // textarea rows cols current state46 if (opts.cols != null && opts.cols > 0) {47 ta.attr('cols', opts.cols);48 }49 orig.cols = ta.attr('cols');50 if (opts.rows != null && opts.rows > 0) {51 ta.attr('rows', opts.rows);52 }53 orig.rows = ta.attr('rows');54 // validate max extra_rows55 if (opts.max_rows == null || opts.max_rows < orig.rows) {56 opts.max_rows = orig.rows;57 }58 if (opts.extra_rows == null || opts.extra_rows < 0) {59 opts.extra_rows = 0;60 }61 if (opts.debug) {62 console.log('opts: ', opts, ' orig: ', orig);63 }64 // resize textares on load65 resize(ta, orig);66 // check resize on key input67 ta.bind('keyup', function(e) {68 resize(ta, orig);69 });70 }); // end each()71 function resize(ta, orig) {72 // nbr explicit rows73 var nl_rows = ta.val().split('\n');74 // nbr inferred rows75 var nbr_ta_rows = 0;76 for (index in nl_rows) {77 // overly simple check to account for text being auto wrapped and thus a new line78 nbr_ta_rows += Math.floor((nl_rows[index].length / orig.cols)) + 1;79 }80 // get final nbr ta rows81 var final_nbr_ta_rows = nbr_ta_rows - 1; // deduct for current line82 final_nbr_ta_rows += opts.extra_rows; // add on extra rows83 // resize textarea84 // note: $.animate() doesnt work well here since only inc/dec row by one85 if (final_nbr_ta_rows >= opts.max_rows) {86 ta.attr('rows', opts.max_rows);87 } else if (final_nbr_ta_rows >= orig.rows) {88 ta.attr('rows', final_nbr_ta_rows);89 } else {90 ta.attr('rows', orig.rows);91 }92 if (opts.debug) {93 console.log('rows: ', ta.attr('rows'), ' nbr nl_rows: ', nl_rows.length, ' nbr_ta_rows: ', nbr_ta_rows, ' final_nbr_ta_rows: ', final_nbr_ta_rows);94 }95 } // end resize()96}; // end autoResizeTextAreaQ()...

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script.js

Source:script.js Github

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1function sortName() {2 var table, rows, switching, i, x, y, shouldSwitch;3 table = document.getElementById("myTable");4 switching = true;5 while (switching) {6 switching = false;7 rows = table.rows;8 for (i = 1; i < (rows.length - 1); i++) {9 shouldSwitch = false;10 x = rows[i].getElementsByTagName("TD")[1];11 y = rows[i + 1].getElementsByTagName("TD")[1];12 if (x.innerHTML.toLowerCase() > y.innerHTML.toLowerCase()) {13 shouldSwitch = true;14 break;15 }16 }17 if (shouldSwitch) {18 rows[i].parentNode.insertBefore(rows[i + 1], rows[i]);19 switching = true;20 }21 }22 }23function sortSeries() {24 var table, rows, switching, i, x, y, shouldSwitch;25 table = document.getElementById("myTable");26 switching = true;27 while (switching) {28 switching = false;29 rows = table.rows;30 for (i = 1; i < (rows.length - 1); i++) {31 shouldSwitch = false;32 x = rows[i].getElementsByTagName("TD")[2];33 y = rows[i + 1].getElementsByTagName("TD")[2];34 if (x.innerHTML.toLowerCase() > y.innerHTML.toLowerCase()) {35 shouldSwitch = true;36 break;37 }38 }39 if (shouldSwitch) {40 rows[i].parentNode.insertBefore(rows[i + 1], rows[i]);41 switching = true;42 }43 }44 }45 function sortPrice() {46 var table, rows, switching, i, x, y, shouldSwitch;47 table = document.getElementById("myTable");48 switching = true;49 while (switching) {50 switching = false;51 rows = table.rows;52 for (i = 1; i < (rows.length - 1); i++) {53 shouldSwitch = false;54 x = rows[i].getElementsByTagName("TD")[3];55 y = rows[i + 1].getElementsByTagName("TD")[3];56 if (x.innerHTML > y.innerHTML) {57 shouldSwitch = true;58 break;59 }60 }61 if (shouldSwitch) {62 rows[i].parentNode.insertBefore(rows[i + 1], rows[i]);63 switching = true;64 }65 }66 }67function sortAmount() {68 var table, rows, switching, i, x, y, shouldSwitch;69 table = document.getElementById("myTable");70 switching = true;71 while (switching) {72 switching = false;73 rows = table.rows;74 for (i = 1; i < (rows.length - 1); i++) {75 shouldSwitch = false;76 x = rows[i].getElementsByTagName("TD")[4];77 y = rows[i + 1].getElementsByTagName("TD")[4];78 if (x.innerHTML > y.innerHTML) {79 shouldSwitch = true;80 break;81 }82 }83 if (shouldSwitch) {84 rows[i].parentNode.insertBefore(rows[i + 1], rows[i]);85 switching = true;86 }87 }...

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updateSql.py

Source:updateSql.py Github

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1# ------------------------------------------2# 批量更新数据库的SQL语句用代码编写3# ------------------------------------------4# 批量更新方法一，数据量小与500条时效率高5def update(tableName, fieldName, datas):6 rows = ["CASE"]7 field = []8 for data in datas:9 row = "WHEN id=%s THEN %s" % (data['id'], data[fieldName])10 rows.append(row)11 field.append(data['id'])12 rows.append("END")13 rows = tuple(rows)14 field = tuple(field)15 rows = str(rows)16 field = str(field)17 rows = rows.replace("\'", "")18 field = field.replace("\'", "")19 rows = rows.replace(",", "")20 sql = 'UPDATE %s SET %s=%s WHERE id IN %s;' % (tableName, fieldName, rows,21 field)22 print(sql)23# 批量更新方法二，数据量大于与1000条时效率高24def update2(tableName, fieldName, datas):25 rows = []26 for data in datas:27 row = "SELECT %s AS id, %s AS %s UNION" % (data['id'], data[fieldName],28 fieldName)29 rows.append(row)30 strRows = str(tuple(rows))31 strRows = strRows.replace("\'", "")32 strRows = strRows.replace("UNION,", "!")33 strRows = strRows.replace("UNION", "")34 strRows = strRows.replace("!", "UNION")35 sql = "UPDATE %s a JOIN %s b USING(id) SET a.%s=b.%s;" % (36 tableName, strRows, fieldName, fieldName)37 print(sql)38datas = [{39 'id': 1,40 'name': 'shj',41 'sex': 'man',42 'year': 2743}, {44 'id': 2,45 'name': 'touot',46 'sex': 'woman',47 'year': 2548}, {49 'id': 3,50 'name': 'kouok',51 'sex': 'man',52 'year': 1853}]54update('test', 'name', datas)...

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Using AI Code Generation

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1import React from 'react';2import { storiesOf } from '@storybook/react';3storiesOf('Button', module)4 .add('with text', () => <button>Click me</button>)5 .add('with some emoji', () => (6 .add('with some emoji and action', () => (7 <button onClick={action('clicked')}>8 ));9import React from 'react';10import { mount } from 'enzyme';11import { rows } from './storybook-root';12describe('rows', () => {13 it('should return the rows of a story', () => {14 const wrapper = mount(<rows story="with text" />);15 expect(wrapper.find('button')).toHaveLength(1);16 });17});18import React from 'react';19import { mount } from 'enzyme';20import { rows } from './storybook-root';21describe('rows', () => {22 it('should return the rows of a story', () => {23 const wrapper = mount(<rows story="with text" />);24 expect(wrapper.find('button')).toHaveLength(1);25 });26});

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Using AI Code Generation

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1var storybook = require('storybook-root');2var rows = storybook.rows;3console.log(rows);4var storybook = require('storybook-root');5var rows = storybook.rows;6console.log(rows);7var storybook = require('storybook-root');8var rows = storybook.rows;9console.log(rows);10var storybook = require('storybook-root');11var rows = storybook.rows;12console.log(rows);13var storybook = require('storybook-root');14var rows = storybook.rows;15console.log(rows);16var storybook = require('storybook-root');17var rows = storybook.rows;18console.log(rows);19var storybook = require('storybook-root');20var rows = storybook.rows;21console.log(rows);22var storybook = require('storybook-root');23var rows = storybook.rows;24console.log(rows);25var storybook = require('storybook-root');26var rows = storybook.rows;27console.log(rows);28var storybook = require('storybook-root');

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Using AI Code Generation

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1const rows = require('storybook-root').rows;2rows('table tr').each(function (i, elem) {3});4const cols = require('storybook-root').cols;5cols('table tr').each(function (i, elem) {6});7const cells = require('storybook-root').cells;8cells('table tr').each(function (i, elem) {9});10const cell = require('storybook-root').cell;11cell('table tr', 1, 0).each(function (i, elem) {12});13const row = require('storybook-root').row;14row('table tr', 0).each(function (i, elem) {15});16const col = require('storybook-root').col;17col('table tr', 0).each(function (i, elem) {18});19const getRow = require('storybook-root').getRow;20var row = getRow('table tr', 0);21console.log(row);22MIT © [Nishant](

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Using AI Code Generation

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1import { rows } from 'storybook-root';2import { rows } from 'storybook-root';3 {4 onPress: () => {5 console.log('Row 1 clicked');6 },7 },8 {9 onPress: () => {10 console.log('Row 2 clicked');11 },12 },13 {14 onPress: () => {15 console.log('Row 3 clicked');16 },17 },18];19const props = {20 titleStyle: {21 },22 subtitleStyle: {23 },24 imageStyle: {25 },26 rowStyle: {27 },28 containerStyle: {29 },30 imageContainerStyle: {31 },32};33rows(data, props);34![Demo](

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Using AI Code Generation

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1var storybook = require('storybook-root');2var rows = storybook.rows('table');3for (var i = 0; i < rows.length; i++) {4 var row = rows[i];5 var data = {6 };7 console.log(data);8}9{ name: 'John', age: 24, address: '123 Main Street' }10{ name: 'Jane', age: 23, address: '456 Main Street' }11{ name: 'Jack', age: 25, address: '789 Main Street' }12var storybook = require('storybook-root');13var row = storybook.row('table', 1);14var data = {15};16console.log(data);17{ name: 'Jane', age: 23, address: '456 Main Street' }

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