diff --git a/html/component/dataSelector.html b/html/component/dataSelector.html
index a11f498d..acafb388 100644
--- a/html/component/dataSelector.html
+++ b/html/component/dataSelector.html
@@ -1,16 +1,26 @@
-
-
-
-
+
+
+
+ 
-
-
+
- - -
-->
+
+
-
+
+
+
+
+ Option Page
+
-
+
\ No newline at end of file
diff --git a/html/fileNavigation.html b/html/component/fileNavigation.html
similarity index 100%
rename from html/fileNavigation.html
rename to html/component/fileNavigation.html
diff --git a/html/popupComponent.html b/html/component/popupComponent.html
similarity index 100%
rename from html/popupComponent.html
rename to html/component/popupComponent.html
diff --git a/html/m_apps/subset.html b/html/m_apps/subset.html
index aedc61a4..33d8da33 100644
--- a/html/m_apps/subset.html
+++ b/html/m_apps/subset.html
@@ -31,6 +31,7 @@
+
diff --git a/html/m_ml/evaluation.html b/html/m_ml/evaluation.html
index 73129fb6..88979916 100644
--- a/html/m_ml/evaluation.html
+++ b/html/m_ml/evaluation.html
@@ -39,15 +39,14 @@
-
+
+
+
+
- - -
+
+
+
-
+
diff --git a/html/m_ml/fitPredict.html b/html/m_ml/fitPredict.html
index f80d7559..280eb960 100644
--- a/html/m_ml/fitPredict.html
+++ b/html/m_ml/fitPredict.html
@@ -7,13 +7,13 @@
-
-
+
-
@@ -22,7 +22,7 @@
-
+
-
+
Action
diff --git a/html/m_ml/modelInfo.html b/html/m_ml/modelInfo.html
index 58abd6eb..9e1309b1 100644
--- a/html/m_ml/modelInfo.html
+++ b/html/m_ml/modelInfo.html
@@ -7,13 +7,13 @@
-
-
+
-
@@ -22,7 +22,7 @@
-
+
-
+
Info
diff --git a/html/m_visualize/chartSetting.html b/html/m_visualize/chartSetting.html
index 0c95c13c..28f364d9 100644
--- a/html/m_visualize/chartSetting.html
+++ b/html/m_visualize/chartSetting.html
@@ -1,5 +1,5 @@
-
+
-
@@ -12,4 +12,8 @@
+
\ No newline at end of file
diff --git a/html/m_visualize/seaborn.html b/html/m_visualize/seaborn.html
index 8b3cc9b9..01e7cef6 100644
--- a/html/m_visualize/seaborn.html
+++ b/html/m_visualize/seaborn.html
@@ -49,7 +49,7 @@
Setting
+
@@ -110,10 +110,6 @@
'); // VP_DS_SELECT_LEFT
// row select - buttons
@@ -213,7 +226,7 @@ define([
// row select - right
tag.appendFormatLine('
-
+
+
-
-
-
diff --git a/js/board/BoardFrame.js b/js/board/BoardFrame.js
index f366c6a9..96c2d817 100644
--- a/js/board/BoardFrame.js
+++ b/js/board/BoardFrame.js
@@ -724,9 +724,6 @@ define([
this.clearBoard();
}
clearBoard() {
- // TODO: alert before clearing
- let that = this;
-
// clear board
this.blockList.forEach(block => {
block.popup.remove();
diff --git a/js/com/com_Config.js b/js/com/com_Config.js
index c017b2b9..33b1070b 100644
--- a/js/com/com_Config.js
+++ b/js/com/com_Config.js
@@ -437,6 +437,10 @@ define([
})
}
+ getDataTypes() {
+ return Config.DATA_TYPES;
+ }
+
getMLDataDict(key = '') {
if (key == '') {
return Config.ML_DATA_DICT;
@@ -482,6 +486,24 @@ define([
Config.MENU_BOARD_SPACING = 5;
Config.VP_MIN_WIDTH = Config.MENU_MIN_WIDTH + Config.BOARD_MIN_WIDTH + Config.MENU_BOARD_SPACING; // = MENU_MIN_WIDTH + BOARD_MIN_WIDTH + MENU_BOARD_SPACING
+ /**
+ * Data types
+ */
+ Config.DATA_TYPES = [
+ // pandas object
+ 'DataFrame', 'Series', 'Index', 'Period', 'GroupBy', 'Timestamp'
+ // Index type object
+ , 'RangeIndex', 'CategoricalIndex', 'MultiIndex', 'IntervalIndex', 'DatetimeIndex', 'TimedeltaIndex', 'PeriodIndex', 'Int64Index', 'UInt64Index', 'Float64Index'
+ // GroupBy type object
+ , 'DataFrameGroupBy', 'SeriesGroupBy'
+ // Plot type
+ , 'Figure', 'AxesSubplot'
+ // Numpy
+ , 'ndarray'
+ // Python variable
+ , 'str', 'int', 'float', 'bool', 'dict', 'list', 'tuple'
+ ]
+
/**
* Data types using for searching model variables
*/
diff --git a/js/com/com_generator.js b/js/com/com_generator.js
index 2239886c..2bffe0de 100644
--- a/js/com/com_generator.js
+++ b/js/com/com_generator.js
@@ -18,6 +18,11 @@ define([
*/
var _VP_SHOW_RESULT = true;
+ const _VP_BOOL_OPTIONS = [
+ { label: 'True', value: 'True' },
+ { label: 'False', value: 'False' }
+ ]
+
/**
* Generate page interface based on package configuration
* @param {*} package
@@ -107,11 +112,31 @@ define([
// create as component type
switch (obj.component) {
case 'bool_checkbox':
- // FIXME: True False select box
- var select = $(``);
- select.append($(''))
- .append($(''));
- $(tblInput).append(select);
+ // True False select box
+ var optSlct = $(``);
+ _VP_BOOL_OPTIONS.forEach((opt, idx) => {
+ var option = $(``).attr({
+ // 'id':opt,
+ 'index':obj.index,
+ 'name':obj.name,
+ 'value':(obj.default==opt.value?'':opt.value)
+ });
+ // cell metadata test
+ if (getValue && obj.value != undefined) {
+ // set as saved value
+ if (obj.value == opt) {
+ $(option).attr({
+ 'selected':'selected'
+ });
+ }
+ } else if (obj.default == opt.value) {
+ $(option).attr({
+ 'selected':'selected'
+ });
+ }
+ optSlct.append(option);
+ });
+ $(tblInput).append(optSlct);
break;
case 'option_select':
var optSlct = document.createElement('select');
diff --git a/js/com/com_generatorV2.js b/js/com/com_generatorV2.js
index a8256500..92356462 100644
--- a/js/com/com_generatorV2.js
+++ b/js/com/com_generatorV2.js
@@ -657,12 +657,13 @@ define([
* @param {array} columnInputIdList
* @param {string} tagType input / select (tag type)
* @param {array/boolean} columnWithEmpty boolean array or value to decide whether select tag has empty space
+ * @param {array/boolean} columnWithIndex boolean array or value to decide whether select tag has index option
* Usage :
* $(document).on('change', this.wrapSelector('#dataframe_tag_id'), function() {
* pdGen.vp_bindColumnSource(that.wrapSelector(), this, ['column_input_id'], 'select', [true, true, true]);
* });
*/
- var vp_bindColumnSource = function(selector, target, columnInputIdList, tagType="input", columnWithEmpty=false) {
+ var vp_bindColumnSource = function(selector, target, columnInputIdList, tagType="input", columnWithEmpty=false, columnWithIndex=false) {
var varName = '';
if ($(target).length > 0) {
varName = $(target).val();
@@ -702,6 +703,20 @@ define([
let { result, type, msg } = resultObj;
var varResult = JSON.parse(result);
+ // check if it needs to add index option
+ let addIndex = false;
+ if (Array.isArray(columnWithIndex)) {
+ addIndex = columnWithIndex[idx];
+ } else {
+ addIndex = columnWithIndex;
+ }
+ if (addIndex == true) {
+ varResult = [
+ {value: varName + '.index', label: 'index'},
+ ...varResult
+ ]
+ }
+
// check if it needs to add empty option
let addEmpty = false;
if (Array.isArray(columnWithEmpty)) {
@@ -711,7 +726,7 @@ define([
}
if (addEmpty == true) {
varResult = [
- {value: '', label: ''},
+ {value: '', label: 'Select option...'},
...varResult
]
}
diff --git a/js/com/component/DataSelector.js b/js/com/component/DataSelector.js
index 8f0c63f9..0bc90693 100644
--- a/js/com/component/DataSelector.js
+++ b/js/com/component/DataSelector.js
@@ -23,33 +23,94 @@ define([
class DataSelector extends Component {
/**
- *
- * @param {string} frameSelector query for parent component
- * @param {Object} config parent:[], selectedList=[], includeList=[]
+ * Constructor
+ * @param {Object} state { type, ... }
*/
- constructor(frameSelector, config) {
- super(frameSelector, config, {});
+ constructor(state) {
+ super($('#site'), state);
}
_init() {
- this.frameSelector = this.$target;
+ super._init();
- // configuration
- this.config = this.state;
+ this.state = {
+ type: 'data', // selector type : data / column
+ target: null, // target jquery object
+ finish: null, // callback after selection
+ data: '',
+ dataType: '',
+ ...this.state
+ }
- var { mode, type, parent, selectedList=[], includeList=[], excludeList=[] } = this.config;
- this.mode = mode;
- this.parent = parent;
- this.selectedList = selectedList;
- this.includeList = includeList;
- this.excludeList = excludeList;
+ }
+
+ _bindEvent() {
+ let that = this;
+
+ // Click X to close
+ $(that.wrapSelector('.vp-inner-popup-close')).on('click', function() {
+ that.close();
+ });
+
+ // Click ok
+ $(that.wrapSelector('#vp_dsOk')).on('click', function() {
+ // TODO: set target value
+ let newValue = that.state.data;
+
+ $(that.state.target).val(newValue);
+ $(that.state.target).data('type', that.state.dataType);
+ that.state.finish(newValue);
+ that.close();
+ });
+
+ }
+
+ /**
+ * Bind event for items created dynamically
+ */
+ _bindEventForItem() {
+ let that = this;
+ // Click variable item
+ $(that.wrapSelector('.vp-ds-var-item')).off('click');
+ $(that.wrapSelector('.vp-ds-var-item')).on('click', function() {
+ $(that.wrapSelector('.vp-ds-var-item')).removeClass('selected');
+ $(this).addClass('selected');
+ let data = $(this).find('.vp-ds-var-data').text();
+ let dataType = $(this).find('.vp-ds-var-type').text();
+ that.state.data = data;
+ that.state.dataType = dataType;
+
+ // TODO: load preview
+ });
}
- load() {
- $(this.frameSelector).html(this.render());
- this.bindEvent();
+ loadVariables() {
+ let that = this;
+ // Searchable variable types
+ let types = [
+ ...vpConfig.getDataTypes(),
+ // ML Data types
+ ...vpConfig.getMLDataTypes()
+ ];
+
+ vpKernel.getDataList(types).then(function(resultObj) {
+ var varList = JSON.parse(resultObj.result);
+
+ let varTags = new com_String();
+ varList && varList.forEach((varObj, idx) => {
+ varTags.appendFormatLine('
-
-
+
', 'vp-ds-var-item', 'vp-grid-col-p50');
+ varTags.appendFormatLine('
');
+ });
+
+ $(that.wrapSelector('.vp-ds-variable-box')).html(varTags.toString());
+
+ that._bindEventForItem();
+
+ });
}
template() {
@@ -57,13 +118,17 @@ define([
}
render() {
-
- }
+ super.render();
- bindEvent() {
- let that = this;
+ this.loadVariables();
+ }
+ open() {
+ $(this.wrapSelector()).show();
+ }
+ close() {
+ $(this.wrapSelector()).remove();
}
}
diff --git a/js/com/component/FileNavigation.js b/js/com/component/FileNavigation.js
index 17d5d963..6b41aad2 100644
--- a/js/com/component/FileNavigation.js
+++ b/js/com/component/FileNavigation.js
@@ -13,8 +13,8 @@
// [CLASS] FileNavigation
//============================================================================
define([
- 'text!vp_base/html/fileNavigation.html!strip',
- 'css!vp_base/css/fileNavigation.css',
+ 'text!vp_base/html/component/fileNavigation.html!strip',
+ 'css!vp_base/css/component/fileNavigation.css',
'vp_base/js/com/com_String',
'vp_base/js/com/com_util',
'vp_base/js/com/component/Component'
@@ -75,7 +75,7 @@ define([
extensions: [], // extensions list ex) png, jpg, gif
multiSelect: false, // multi selection
showAll: false, // show other extension files also
- finsh: null, // callback after selection
+ finish: null, // callback after selection
...this.state
};
@@ -380,7 +380,7 @@ define([
if (filePath == '') {
filePath = './' + fileName;
}
- that.setSelectedFile(fileName, filePath);
+ that.handleSelectFile(filePath, fileName);
});
// bind save cancel event
$(this.wrapSelector('.vp-filenavi-btn')).on('click', function() {
diff --git a/js/com/component/PopupComponent.js b/js/com/component/PopupComponent.js
index 548adffe..036cf448 100644
--- a/js/com/component/PopupComponent.js
+++ b/js/com/component/PopupComponent.js
@@ -13,8 +13,8 @@
// [CLASS] PopupComponent
//============================================================================
define([
- 'text!vp_base/html/popupComponent.html!strip',
- 'css!vp_base/css/popupComponent.css',
+ 'text!vp_base/html/component/popupComponent.html!strip',
+ 'css!vp_base/css/component/popupComponent.css',
'../com_util',
'../com_Const',
'../com_String',
@@ -302,14 +302,16 @@ define([
// Click import library
$(this.wrapSelector('#popupImport')).on('click', function() {
// add import codes
- var code = that.generateImportCode();
- // create block and run it
- $('#vp_wrapper').trigger({
- type: 'create_option_page',
- blockType: 'block',
- menuId: 'lgExe_code',
- menuState: { taskState: { code: code } },
- afterAction: 'run'
+ var codes = that.generateImportCode();
+ codes && codes.forEach(code => {
+ // create block and run it
+ $('#vp_wrapper').trigger({
+ type: 'create_option_page',
+ blockType: 'block',
+ menuId: 'lgExe_code',
+ menuState: { taskState: { code: code } },
+ afterAction: 'run'
+ });
});
});
@@ -598,7 +600,7 @@ define([
generateImportCode() {
/** Implementation needed - Generated on clicking Import Library button */
- return '';
+ return [];
}
generateCode() {
@@ -631,13 +633,11 @@ define([
switch(tagName) {
case 'INPUT':
let inputType = $(tag).prop('type');
- if (inputType == 'text' || inputType == 'number' || inputType == 'hidden') {
- newValue = $(tag).val();
- break;
- }
if (inputType == 'checkbox') {
newValue = $(tag).prop('checked');
- break;
+ } else {
+ // inputType == 'text' || inputType == 'number' || inputType == 'hidden' || inputType == 'color' || inputType == 'range'
+ newValue = $(tag).val();
}
break;
case 'TEXTAREA':
diff --git a/js/com/component/VarSelector2.js b/js/com/component/VarSelector2.js
index 1c80e58c..2decd620 100644
--- a/js/com/component/VarSelector2.js
+++ b/js/com/component/VarSelector2.js
@@ -8,7 +8,7 @@ define([
* @constructor
*/
class VarSelector extends Component{
- constructor(parentTag, dataTypes=[], defaultType='', showOthers=true, showFilterbox=true) {
+ constructor(parentTag, dataTypes=['DataFrame', 'Series', 'ndarray', 'list', 'dict'], defaultType='', showOthers=true, showFilterbox=true) {
super(null, {parentTag: parentTag, dataTypes: dataTypes, defaultType: defaultType, showOthers: showOthers, showFilterbox: showFilterbox});
}
@@ -234,8 +234,12 @@ define([
}
}
+ } else {
+ dataTypes = [];
}
+ vpLog.display(VP_LOG_TYPE.DEVELOP, 'VarSelector2 - reload ', dataTypes, excludeTypes);
+
return new Promise(function(resolve, reject) {
vpKernel.getDataList(dataTypes, excludeTypes).then(function (resultObj) {
try {
diff --git a/js/m_apps/File.js b/js/m_apps/File.js
index c744627b..a456a6f1 100644
--- a/js/m_apps/File.js
+++ b/js/m_apps/File.js
@@ -270,6 +270,7 @@ define([
}
// render interface
+ // pdGen.vp_showInterfaceOnPage(this.wrapSelector('#vp_file' + pageType), thisPkg);
pdGen.vp_showInterfaceOnPage(this.wrapSelector('#vp_file' + pageType), thisPkg);
// prepend file type selector
diff --git a/js/m_apps/PDF.js b/js/m_apps/PDF.js
index 15f3bd78..cac45e19 100644
--- a/js/m_apps/PDF.js
+++ b/js/m_apps/PDF.js
@@ -30,6 +30,37 @@ import fitz
import nltk
nltk.download('punkt')`;
+ const PDF_FUNC = `def vp_pdf_get_sentence(fname_lst):
+ '''
+ Get sentence from pdf file by PyMuPDF
+ '''
+ df = pd.DataFrame()
+ for fname in fname_lst:
+ if fname.split('.')[-1] != 'pdf': continue
+ try:
+ doc = fitz.open(fname)
+ sentence_lst = []
+ for page in doc:
+ block_lst = page.get_text('blocks')
+
+ text_lst = [block[4] for block in block_lst if block[6] == 0]
+ text = '\\n'.join(text_lst)
+
+ sentence_lst.extend([sentence for sentence in nltk.sent_tokenize(text)])
+
+ doc.close()
+ except Exception as e:
+ print(e)
+ continue
+
+ df_doc = pd.DataFrame({
+ 'fname': fname.split('/')[-1],
+ 'sentence': sentence_lst
+ })
+ df = pd.concat([df,df_doc])
+
+ return df.reset_index().drop('index', axis=1)`;
+
const PDF_CMD = 'df = vp_pdf_get_sentence(pdf_lst)\ndf'
/**
* PDF
@@ -93,7 +124,10 @@ nltk.download('punkt')`;
}
generateImportCode() {
- return PDF_IMPORT;
+ return [
+ PDF_IMPORT,
+ PDF_FUNC
+ ];
}
generateCode() {
diff --git a/js/m_apps/Profiling.js b/js/m_apps/Profiling.js
index 5e82048b..c57442d7 100644
--- a/js/m_apps/Profiling.js
+++ b/js/m_apps/Profiling.js
@@ -147,7 +147,9 @@ define([
}
generateImportCode() {
- return 'from pandas_profiling import ProfileReport';
+ return [
+ 'from pandas_profiling import ProfileReport'
+ ];
}
generateCode() {
diff --git a/js/m_apps/SampleApp.js b/js/m_apps/SampleApp.js
index 864678e9..b497c82b 100644
--- a/js/m_apps/SampleApp.js
+++ b/js/m_apps/SampleApp.js
@@ -16,8 +16,9 @@ define([
'vp_base/js/com/com_util',
'vp_base/js/com/com_Const',
'vp_base/js/com/com_String',
- 'vp_base/js/com/component/PopupComponent'
-], function(com_util, com_Const, com_String, PopupComponent) {
+ 'vp_base/js/com/component/PopupComponent',
+ 'vp_base/js/com/component/DataSelector'
+], function(com_util, com_Const, com_String, PopupComponent, DataSelector) {
/**
* SampleApp
@@ -32,22 +33,29 @@ define([
super._bindEvent();
/** Implement binding events */
var that = this;
- this.$target.on('click', function(evt) {
- var target = evt.target;
- if ($(that.wrapSelector()).find(target).length > 0) {
- // Sample : getDataList from Kernel
- vpKernel.getDataList().then(function(resultObj) {
- vpLog.display(VP_LOG_TYPE.DEVELOP, resultObj);
- }).catch(function(err) {
- vpLog.display(VP_LOG_TYPE.DEVELOP, err);
- });
- }
+
+ $(this.wrapSelector('#sample')).on('click', function() {
+ let dataSelector = new DataSelector({
+ type: 'data',
+ target: $(that.wrapSelector('#sample')),
+ finish: function() {
+
+ }
+ });
+ dataSelector.open();
});
}
templateForBody() {
/** Implement generating template */
- return 'This is sample.';
+ return `This is sample.
+ `;
+ }
+
+ render() {
+ super.render();
+
+
}
generateCode() {
diff --git a/js/m_apps/Subset.js b/js/m_apps/Subset.js
index 74ad9cac..6b80f0ac 100644
--- a/js/m_apps/Subset.js
+++ b/js/m_apps/Subset.js
@@ -59,9 +59,7 @@ define([
useCopy: false,
toFrame: false,
- subsetType: 'loc',
-
- tabPage: 'subset',
+ subsetType: 'loc', // subset / loc / iloc / query
rowType: 'condition',
rowList: [],
@@ -139,6 +137,21 @@ define([
$(this.targetSelector).parent().append(buttonTag.toString());
}
}
+ renderSubsetType(dataType) {
+ var subsetType = this.state.subsetType;
+
+ var tag = new com_String();
+ tag.appendFormatLine('');
+
+ return tag.toString();
+ }
renderRowSubsetType(subsetType, timestamp = false) {
var tag = new com_String();
tag.appendFormatLine('{1}
', 'vp-ds-var-data', varObj.varName);
+ varTags.appendFormatLine('{1}
', 'vp-ds-var-type', varObj.varType);
+ varTags.appendLine('', VP_DS_SELECT_RIGHT);
- tag.appendFormatLine('
'); // VP_DS_SELECT_CONTAINER
@@ -229,7 +242,7 @@ define([
*/
renderRowSelectionBox(rowList) {
var tag = new com_String();
- tag.appendFormatLine('', VP_DS_SELECT_BOX, 'right', VP_DS_DROPPABLE, 'no-selection');
+ tag.appendFormatLine('
'); // VP_DS_SELECT_RIGHT
tag.appendLine('', VP_DS_SELECT_BOX, 'right', VP_DS_DROPPABLE, 'vp-scrollbar no-selection');
tag.appendLine('
'); // VP_DS_SELECT_BOX
tag.appendLine('', VP_DS_SELECT_BOX, 'left', VP_DS_DROPPABLE, 'no-selection');
+ tag.appendFormatLine('
', VP_DS_SELECT_BOX, 'left', VP_DS_DROPPABLE, 'vp-scrollbar no-selection');
// get row data and make draggable items
rowList.forEach((row, idx) => {
@@ -313,7 +326,7 @@ define([
tag.appendLine(vpSearchSuggest.toTagString());
tag.appendFormatLine('');
- tag.appendFormatLine('', VP_DS_SELECT_BOX, 'left', VP_DS_DROPPABLE, 'no-selection');
+ tag.appendFormatLine('', VP_DS_SELECT_BOX, 'left', VP_DS_DROPPABLE, 'vp-scrollbar no-selection');
tag.appendLine('
'); // VP_DS_SELECT_LEFT
// col select - buttons
@@ -328,7 +341,7 @@ define([
// col select - right
tag.appendFormatLine('', VP_DS_SELECT_RIGHT);
- tag.appendFormatLine('
'); // VP_DS_SELECT_CONTAINER
@@ -344,7 +357,7 @@ define([
*/
renderColumnSelectionBox(colList) {
var tag = new com_String();
- tag.appendFormatLine('', VP_DS_SELECT_BOX, 'right', VP_DS_DROPPABLE, 'no-selection');
+ tag.appendFormatLine('
'); // VP_DS_SELECT_RIGHT
tag.appendLine('', VP_DS_SELECT_BOX, 'right', VP_DS_DROPPABLE, 'vp-scrollbar no-selection');
tag.appendLine('
'); // VP_DS_SELECT_BOX
tag.appendLine('', VP_DS_SELECT_BOX, 'left', VP_DS_DROPPABLE, 'no-selection');
+ tag.appendFormatLine('
', VP_DS_SELECT_BOX, 'left', VP_DS_DROPPABLE, 'vp-scrollbar no-selection');
// get col data and make draggable items
colList.forEach((col, idx) => {
// col.array parsing
@@ -638,12 +651,18 @@ define([
return that.renderSubsetType(dataType);
});
}
+ /**
+ * Load Row & Column option page based on subsetType
+ * @param {string} subsetType subset / loc / iloc / query
+ * @param {boolean} timestamp use timestamp? true / false
+ */
loadRowColumnSubsetType(subsetType, timestamp = false) {
var that = this;
// get current subset type of row & column
var rowSubset = this.state.rowType;
var colSubset = this.state.colType;
+ // render row & column option page
that.renderRowSubsetType(subsetType, timestamp);
that.renderColumnSubsetType(subsetType);
@@ -997,7 +1016,7 @@ define([
return;
}
- // that.loadSubsetType(that.state.dataType);
+ that.loadSubsetType(that.state.dataType);
if (that.state.dataType == 'DataFrame') {
// get result and load column list
vpKernel.getColumnList(varName).then(function (resultObj) {
@@ -1073,13 +1092,6 @@ define([
that.state.subsetType = subsetType;
that.reloadSubsetData();
- // that.loadRowColumnSubsetType(subsetType, that.state.isTimestamp);
- // // data page
- // if (that.state.tabPage == 'data') {
- // that.loadDataPage();
- // } else {
- // that.generateCode();
- // }
});
// to frame
@@ -1398,6 +1410,7 @@ define([
* 1) subset - rowSelection & colSelection using 'indexing' type
* 2) loc - subset type 'loc'
* 3) iloc - subset type 'iloc'
+ * 4) query - subset type 'query'
* - consider use copy option
*/
generateCodeForSubset(allocation = true, applyPreview = true) {
@@ -1461,13 +1474,16 @@ define([
rowSelection.append(connector);
}
- if (varType == 'DataFrame') {
- rowSelection.appendFormat('({0}', varName);
- if (colName && colName != '') {
- if (colName == '.index') {
- rowSelection.appendFormat('{0}', colName);
+ if (this.state.subsetType == 'query') {
+ if (condList.length > 1) {
+ rowSelection.append('(');
+ }
+ let colValue = colTag.find('.vp-col-list').val();
+ if (colValue && colValue != '') {
+ if (colValue == '.index') {
+ rowSelection.append('index');
} else {
- rowSelection.appendFormat('[{0}]', colName);
+ rowSelection.appendFormat('{0}', colValue);
}
}
oper && rowSelection.appendFormat(' {0}', oper);
@@ -1479,23 +1495,45 @@ define([
rowSelection.appendFormat(" {0}", cond);
}
}
- rowSelection.append(')');
+ if (condList.length > 1) {
+ rowSelection.append(')');
+ }
} else {
- rowSelection.appendFormat('({0}', varName);
- oper && rowSelection.appendFormat(' {0}', oper);
- if (cond) {
- // condition value as text
- if (useText) {
- rowSelection.appendFormat(" '{0}'", cond);
- } else {
- rowSelection.appendFormat(" {0}", cond);
+ if (varType == 'DataFrame') {
+ rowSelection.appendFormat('({0}', varName);
+ if (colName && colName != '') {
+ if (colName == '.index') {
+ rowSelection.appendFormat('{0}', colName);
+ } else {
+ rowSelection.appendFormat('[{0}]', colName);
+ }
+ }
+ oper && rowSelection.appendFormat(' {0}', oper);
+ if (cond) {
+ // condition value as text
+ if (useText) {
+ rowSelection.appendFormat(" '{0}'", cond);
+ } else {
+ rowSelection.appendFormat(" {0}", cond);
+ }
+ }
+ rowSelection.append(')');
+ } else {
+ rowSelection.appendFormat('({0}', varName);
+ oper && rowSelection.appendFormat(' {0}', oper);
+ if (cond) {
+ // condition value as text
+ if (useText) {
+ rowSelection.appendFormat(" '{0}'", cond);
+ } else {
+ rowSelection.appendFormat(" {0}", cond);
+ }
}
+ rowSelection.append(')');
}
- rowSelection.append(')');
}
useCondition = true;
}
-
if (rowSelection.toString() == '') {
rowSelection.append(':');
}
@@ -1572,6 +1610,13 @@ define([
} else {
code.appendFormat('.iloc[{0}]', rowSelection.toString());
}
+ } else if (this.state.subsetType == 'query') {
+ if (rowSelection.toString() != ':' && rowSelection.toString() != '') {
+ code.appendFormat('.query("{0}")', rowSelection.toString());
+ }
+ if (colSelection.toString() != ':' && colSelection.toString() != '') {
+ code.appendFormat('[{0}]', colSelection.toString());
+ }
}
// use copy
diff --git a/js/m_apps/Variable.js b/js/m_apps/Variable.js
index 09c42b80..6d0e175a 100644
--- a/js/m_apps/Variable.js
+++ b/js/m_apps/Variable.js
@@ -66,20 +66,9 @@ define([
// Searchable variable types
var types = [
- // pandas object
- 'DataFrame', 'Series', 'Index', 'Period', 'GroupBy', 'Timestamp'
- // Index type object
- , 'RangeIndex', 'CategoricalIndex', 'MultiIndex', 'IntervalIndex', 'DatetimeIndex', 'TimedeltaIndex', 'PeriodIndex', 'Int64Index', 'UInt64Index', 'Float64Index'
- // GroupBy type object
- , 'DataFrameGroupBy', 'SeriesGroupBy'
- // Plot type
- , 'Figure', 'AxesSubplot'
- // Numpy
- , 'ndarray'
- // Python variable
- , 'str', 'int', 'float', 'bool', 'dict', 'list', 'tuple'
+ ...vpConfig.getDataTypes(),
// ML Data types
- , ...vpConfig.getMLDataTypes()
+ ...vpConfig.getMLDataTypes()
];
var tagTable = this.wrapSelector('#vp_var_variableBox table tbody');
diff --git a/js/m_ml/AutoML.js b/js/m_ml/AutoML.js
index 614c82cf..88d2b4d7 100644
--- a/js/m_ml/AutoML.js
+++ b/js/m_ml/AutoML.js
@@ -138,13 +138,13 @@ define([
// render option page
$(page).find('.vp-model-option-box').html(this.templateForOption(this.state.modelType));
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('featureData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.featureData);
$(page).find('#featureData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.targetData);
diff --git a/js/m_ml/Classification.js b/js/m_ml/Classification.js
index b8aa9529..b53d5257 100644
--- a/js/m_ml/Classification.js
+++ b/js/m_ml/Classification.js
@@ -138,13 +138,13 @@ define([
// render option page
$(page).find('.vp-model-option-box').html(this.templateForOption(this.state.modelType));
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('featureData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.featureData);
$(page).find('#featureData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.targetData);
diff --git a/js/m_ml/Clustering.js b/js/m_ml/Clustering.js
index efc469c0..a636bfc5 100644
--- a/js/m_ml/Clustering.js
+++ b/js/m_ml/Clustering.js
@@ -141,13 +141,13 @@ define([
// render option page
$(page).find('.vp-model-option-box').html(this.templateForOption(this.state.modelType));
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('featureData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.featureData);
$(page).find('#featureData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.targetData);
diff --git a/js/m_ml/DataPrep.js b/js/m_ml/DataPrep.js
index 32f8a36f..0cc70917 100644
--- a/js/m_ml/DataPrep.js
+++ b/js/m_ml/DataPrep.js
@@ -197,13 +197,13 @@ define([
// render option page
$(page).find('.vp-model-option-box').html(this.templateForOption(this.state.modelType));
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('featureData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.featureData);
$(page).find('#featureData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.targetData);
diff --git a/js/m_ml/DimensionReduction.js b/js/m_ml/DimensionReduction.js
index 642f12c9..f11a82b9 100644
--- a/js/m_ml/DimensionReduction.js
+++ b/js/m_ml/DimensionReduction.js
@@ -137,13 +137,13 @@ define([
// render option page
$(page).find('.vp-model-option-box').html(this.templateForOption(this.state.modelType));
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('featureData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.featureData);
$(page).find('#featureData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.targetData);
diff --git a/js/m_ml/FitPredict.js b/js/m_ml/FitPredict.js
index 1366c913..b6afc1ef 100644
--- a/js/m_ml/FitPredict.js
+++ b/js/m_ml/FitPredict.js
@@ -152,8 +152,6 @@ define([
super.render();
this.loadModelList(this.state.category);
-
- this.reload();
}
loadModelList(category='') {
@@ -173,17 +171,21 @@ define([
vpKernel.getModelList(category).then(function(resultObj) {
let { result } = resultObj;
var modelList = JSON.parse(result);
- modelList && modelList.forEach(model => {
+ modelList && modelList.forEach((model, idx) => {
let selectFlag = '';
- if (model.varName == that.state.model) {
+ // if this item is pre-selected model or first item of model list
+ if ((model.varName == that.state.model)
+ || (that.state.model == '' && idx == 0)) {
selectFlag = 'selected';
+ that.state.model = model.varName;
+ that.state.modelType = model.varType;
}
modelOptionTag.appendFormatLine('{5} ({6}) ',
'vp-ins-select-item', selectFlag, model.varName, model.varType, model.varName, model.varName, model.varType);
});
$(that.wrapSelector('.vp-ins-select-list.model')).html(modelOptionTag.toString());
- // click model
+ // click model event
$(that.wrapSelector('.vp-ins-select-list.model .vp-ins-select-item')).on('click', function() {
let model = $(this).data('var-name');
let modelType = $(this).data('var-type');
@@ -196,9 +198,14 @@ define([
that.reload();
});
+
+ that.reload();
});
}
+ /**
+ * Load options for selected model
+ */
reload() {
// reset option page
try {
@@ -354,8 +361,8 @@ define([
code: '${model}.fit(${fit_featureData}, ${fit_targetData})',
description: 'Perform modeling from features, or distance matrix.',
options: [
- { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X_train' },
- { name: 'fit_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'y_train' }
+ { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X_train' },
+ { name: 'fit_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y_train' }
]
},
'predict': {
@@ -364,7 +371,7 @@ define([
code: '${pred_allocate} = ${model}.predict(${pred_featureData})',
description: 'Predict the closest target data X belongs to.',
options: [
- { name: 'pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X_test' },
+ { name: 'pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X_test' },
{ name: 'pred_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'pred' }
]
},
@@ -374,7 +381,7 @@ define([
code: '${pred_prob_allocate} = ${model}.predict_proba(${pred_prob_featureData})',
description: 'Predict class probabilities for X.',
options: [
- { name: 'pred_prob_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X_test' },
+ { name: 'pred_prob_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X_test' },
{ name: 'pred_prob_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'pred' }
]
},
@@ -384,7 +391,7 @@ define([
code: '${trans_allocate} = ${model}.transform(${trans_featureData})',
description: 'Apply dimensionality reduction to X.',
options: [
- { name: 'trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
}
@@ -399,7 +406,7 @@ define([
code: '${model}.fit(${fit_featureData})',
description: 'Fit Encoder/Scaler to X.',
options: [
- { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' }
+ { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' }
]
},
'fit_transform': {
@@ -408,7 +415,7 @@ define([
code: '${fit_trans_allocate} = ${model}.fit_transform(${fit_trans_featureData})',
description: 'Fit Encoder/Scaler to X, then transform X.',
options: [
- { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'fit_trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
},
@@ -427,7 +434,7 @@ define([
code: '${inverse_allocate} = ${model}.inverse_transform(${inverse_featureData})',
description: 'Transform binary labels back to multi-class labels.',
options: [
- { name: 'inverse_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'inverse_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'inverse_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'inv_trans' }
]
}
@@ -455,7 +462,7 @@ define([
code: '${dec_allocate} = ${model}.decision_function(${dec_featureData})',
description: 'Compute the decision function of X.',
options: [
- { name: 'dec_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'dec_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'dec_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable' }
]
}
@@ -472,7 +479,7 @@ define([
code: '${fit_pred_allocate} = ${model}.fit_predict(${fit_pred_featureData})',
description: 'Fit and predict.',
options: [
- { name: 'fit_pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'fit_pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'fit_pred_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'pred' }
]
},
@@ -489,7 +496,7 @@ define([
code: '${model}.fit(${fit_featureData})',
description: 'Perform clustering from features, or distance matrix.',
options: [
- { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' }
+ { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' }
]
},
'fit_predict': {
@@ -498,7 +505,7 @@ define([
code: '${fit_pred_allocate} = ${model}.fit_predict(${fit_pred_featureData})',
description: 'Compute clusters from a data or distance matrix and predict labels.',
options: [
- { name: 'fit_pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'fit_pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'fit_pred_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'pred' }
]
}
@@ -512,7 +519,7 @@ define([
code: '${model}.fit(${fit_featureData})',
description: 'Compute clustering.',
options: [
- { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' }
+ { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' }
]
},
'predict': {
@@ -521,7 +528,7 @@ define([
code: '${pred_allocate} = ${model}.predict(${pred_featureData})',
description: 'Predict the closest target data X belongs to.',
options: [
- { name: 'pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'pred_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'pred' }
]
},
@@ -531,7 +538,7 @@ define([
code: '${fit_pred_allocate} = ${model}.fit_predict(${fit_pred_featureData})',
description: 'Compute cluster centers and predict cluster index for each sample.',
options: [
- { name: 'fit_pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'fit_pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'fit_pred_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'pred' }
]
}
@@ -545,7 +552,7 @@ define([
code: '${fit_trans_allocate} = ${model}.fit_transform(${fit_trans_featureData})',
description: 'Compute clustering and transform X to cluster-distance space.',
options: [
- { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'fit_trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
},
@@ -555,7 +562,7 @@ define([
code: '${trans_allocate} = ${model}.transform(${trans_featureData})',
description: 'Transform X to a cluster-distance space.',
options: [
- { name: 'trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
}
@@ -571,7 +578,7 @@ define([
code: '${model}.fit(${fit_featureData})',
description: 'Fit X into an embedded space.',
options: [
- { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' }
+ { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' }
]
},
'fit_transform': {
@@ -580,7 +587,7 @@ define([
code: '${fit_trans_allocate} = ${model}.fit_transform(${fit_trans_featureData})',
description: 'Fit X into an embedded space and return that transformed output.',
options: [
- { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'fit_trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
}
@@ -595,8 +602,8 @@ define([
code: '${model}.fit(${fit_featureData}, ${fit_targetData})',
description: 'Fit the Linear Discriminant Analysis model.',
options: [
- { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
- { name: 'fit_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'y' }
+ { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
+ { name: 'fit_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y' }
]
},
'fit_transform': {
@@ -605,8 +612,8 @@ define([
code: '${fit_trans_allocate} = ${model}.fit_transform(${fit_trans_featureData}${fit_trans_targetData})',
description: 'Fit to data, then transform it.',
options: [
- { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
- { name: 'fit_trans_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'y' },
+ { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
+ { name: 'fit_trans_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y' },
{ name: 'fit_trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
},
@@ -616,7 +623,7 @@ define([
code: '${pred_allocate} = ${model}.predict(${pred_featureData})',
description: 'Predict class labels for samples in X.',
options: [
- { name: 'pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'pred_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'pred_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'pred' }
]
},
@@ -626,7 +633,7 @@ define([
code: '${trans_allocate} = ${model}.transform(${trans_featureData})',
description: 'Project data to maximize class separation.',
options: [
- { name: 'trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
}
@@ -640,7 +647,7 @@ define([
code: '${model}.fit(${fit_featureData})',
description: 'Fit X into an embedded space.',
options: [
- { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' }
+ { name: 'fit_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' }
]
},
'fit_transform': {
@@ -649,7 +656,7 @@ define([
code: '${fit_trans_allocate} = ${model}.fit_transform(${fit_trans_featureData})',
description: 'Fit the model with X and apply the dimensionality reduction on X.',
options: [
- { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'fit_trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'fit_trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
},
@@ -659,7 +666,7 @@ define([
code: '${inverse_allocate} = ${model}.inverse_transform(${inverse_featureData})',
description: 'Transform data back to its original space.',
options: [
- { name: 'inverse_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'inverse_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'inverse_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'inv_trans' }
]
},
@@ -669,7 +676,7 @@ define([
code: '${trans_allocate} = ${model}.transform(${trans_featureData})',
description: 'Apply dimensionality reduction to X.',
options: [
- { name: 'trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'trans_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'trans_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'trans' }
]
}
diff --git a/js/m_ml/ModelInfo.js b/js/m_ml/ModelInfo.js
index 2d945da3..97d06a99 100644
--- a/js/m_ml/ModelInfo.js
+++ b/js/m_ml/ModelInfo.js
@@ -152,8 +152,6 @@ define([
super.render();
this.loadModelList(this.state.category);
-
- this.reload();
}
loadModelList(category='') {
@@ -173,17 +171,21 @@ define([
vpKernel.getModelList(category).then(function(resultObj) {
let { result } = resultObj;
var modelList = JSON.parse(result);
- modelList && modelList.forEach(model => {
+ modelList && modelList.forEach((model, idx) => {
let selectFlag = '';
- if (model.varName == that.state.model) {
+ // if this item is pre-selected model or first item of model list
+ if ((model.varName == that.state.model)
+ || (that.state.model == '' && idx == 0)) {
selectFlag = 'selected';
+ that.state.model = model.varName;
+ that.state.modelType = model.varType;
}
modelOptionTag.appendFormatLine('{5} ({6}) ',
'vp-ins-select-item', selectFlag, model.varName, model.varType, model.varName, model.varName, model.varType);
});
$(that.wrapSelector('.vp-ins-select-list.model')).html(modelOptionTag.toString());
- // click model
+ // click model event
$(that.wrapSelector('.vp-ins-select-list.model .vp-ins-select-item')).on('click', function() {
let model = $(this).data('var-name');
let modelType = $(this).data('var-type');
@@ -196,9 +198,14 @@ define([
that.reload();
});
+
+ that.reload();
});
}
+ /**
+ * Load options for selected model
+ */
reload() {
// reset option page
try {
@@ -355,8 +362,8 @@ define([
code: '${score_allocate} = ${model}.score(${score_featureData}, ${score_targetData})',
description: '',
options: [
- { name: 'score_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
- { name: 'score_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'y' },
+ { name: 'score_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
+ { name: 'score_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y' },
{ name: 'score_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'scores' }
]
},
@@ -377,8 +384,8 @@ define([
code: '${importance_allocate} = permutation_importance(${model}, ${importance_featureData}, ${importance_targetData}${scoring}${random_state}${etc})',
description: 'Permutation importance for feature evaluation.',
options: [
- { name: 'importance_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X_train' },
- { name: 'importance_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'y_train' },
+ { name: 'importance_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X_train' },
+ { name: 'importance_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y_train' },
{ name: 'scoring', component: ['input'], usePair: true },
{ name: 'random_state', component: ['input_number'], placeholder: '123', usePair: true },
{ name: 'importance_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'importances' }
@@ -475,8 +482,8 @@ define([
code: '${cvs_allocate} = cross_val_score(${model}, ${cvs_featureData}, ${cvs_targetData}${scoring}${cv})',
description: 'Evaluate a score by cross-validation.',
options: [
- { name: 'cvs_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
- { name: 'cvs_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'y' },
+ { name: 'cvs_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
+ { name: 'cvs_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y' },
{ name: 'scoring', component: ['option_select'], usePair: true, type: 'text',
options: [
'',
@@ -522,8 +529,8 @@ define([
code: '${cvs_allocate} = cross_val_score(${model}, ${cvs_featureData}, ${cvs_targetData}${scoring}${cv})',
description: 'Evaluate a score by cross-validation.',
options: [
- { name: 'cvs_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
- { name: 'cvs_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'y' },
+ { name: 'cvs_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
+ { name: 'cvs_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y' },
{ name: 'scoring', component: ['option_select'], usePair: true, type: 'text',
options: [
'',
@@ -535,8 +542,56 @@ define([
{ name: 'cvs_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'scores' }
]
},
+ 'roc_curve': {
+ name: 'roc_curve',
+ label: 'ROC Curve',
+ import: 'from sklearn import metrics',
+ code: "fpr, tpr, thresholds = metrics.roc_curve(${roc_targetData}, ${model}.predict_proba(${roc_featureData})[:, 1])\n\
+plt.plot(fpr, tpr, label='ROC Curve')\n\
+plt.xlabel('Sensitivity')\n\
+plt.ylabel('Specificity')\n\
+plt.show()",
+ description: '',
+ options: [
+ { name: 'roc_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y_test' },
+ { name: 'roc_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X_test' }
+ ]
+ },
+ 'auc': {
+ name: 'auc',
+ label: 'AUC',
+ import: 'from sklearn import metrics',
+ code: 'metrics.roc_auc_score(${auc_targetData}, ${model}.predict_proba(${auc_featureData})[:, 1])',
+ description: '',
+ options: [
+ { name: 'auc_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y_test' },
+ { name: 'auc_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X_test' }
+ ]
+ },
'permutation_importance': defaultInfos['permutation_importance']
}
+
+ // use decision_function on ROC, AUC
+ let decisionFunctionTypes = [
+ 'LogisticRegression', 'SVC', 'GradientBoostingClassifier'
+ ];
+ if (decisionFunctionTypes.includes(modelType)) {
+ infos = {
+ ...infos,
+ 'roc_curve': {
+ ...infos['roc_curve'],
+ code: "fpr, tpr, thresholds = metrics.roc_curve(${roc_targetData}, ${model}.decision_function(${roc_featureData}))\n\
+plt.plot(fpr, tpr, label='ROC Curve')\n\
+plt.xlabel('Sensitivity')\n\
+plt.ylabel('Specificity')\n\
+plt.show()"
+ },
+ 'auc': {
+ ...infos['auc'],
+ code: 'metrics.roc_auc_score(${auc_targetData}, ${model}.decision_function(${auc_featureData}))',
+ }
+ }
+ }
break;
case 'Auto ML':
infos = {
@@ -609,8 +664,8 @@ define([
code: '${score_allocate} = ${model}.score(${score_featureData}, ${score_targetData})',
description: 'Return the average log-likelihood of all samples.',
options: [
- { name: 'score_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
- { name: 'score_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'y' },
+ { name: 'score_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
+ { name: 'score_targetData', label: 'Target Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'y' },
{ name: 'score_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'scores' }
]
}
@@ -638,7 +693,7 @@ define([
code: '${score_allocate} = ${model}.score(${score_featureData})',
description: 'Return the average log-likelihood of all samples.',
options: [
- { name: 'score_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series'], value: 'X' },
+ { name: 'score_featureData', label: 'Feature Data', component: ['var_select'], var_type: ['DataFrame', 'Series', 'ndarray', 'list', 'dict'], value: 'X' },
{ name: 'score_allocate', label: 'Allocate to', component: ['input'], placeholder: 'New variable', value: 'scores' }
]
}
diff --git a/js/m_ml/Regression.js b/js/m_ml/Regression.js
index a2c73291..4b46ccd4 100644
--- a/js/m_ml/Regression.js
+++ b/js/m_ml/Regression.js
@@ -138,13 +138,13 @@ define([
// render option page
$(page).find('.vp-model-option-box').html(this.templateForOption(this.state.modelType));
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('featureData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.featureData);
$(page).find('#featureData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.targetData);
diff --git a/js/m_ml/dataSplit.js b/js/m_ml/dataSplit.js
index 0361f213..6005e748 100644
--- a/js/m_ml/dataSplit.js
+++ b/js/m_ml/dataSplit.js
@@ -102,21 +102,21 @@ define([
$(page).find('#testSize').html(sizeOptions);
// varselector TEST:
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('featureData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.featureData);
varSelector.setPlaceholder('Select feature data');
$(page).find('#featureData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.targetData);
varSelector.setPlaceholder('Select target data');
$(page).find('#targetData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('stratify');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.stratify);
diff --git a/js/m_ml/evaluation.js b/js/m_ml/evaluation.js
index 26ea1eed..47cdd360 100644
--- a/js/m_ml/evaluation.js
+++ b/js/m_ml/evaluation.js
@@ -40,8 +40,6 @@ define([
// classification
confusion_matrix: true, report: true,
accuracy: false, precision: false, recall: false, f1_score: false,
- roc_curve: false, auc: false,
- model: '',
// clustering
clusteredIndex: 'clusters',
silhouetteScore: true, ari: false, nmi: false,
@@ -77,19 +75,19 @@ define([
} else if (modelType == 'clf') {
// Classification - model selection
- if (that.checkToShowModel('roc-auc') == true) {
- $(that.wrapSelector('.vp-ev-model.roc-auc')).prop('disabled', false);
- } else {
- $(that.wrapSelector('.vp-ev-model.roc-auc')).prop('disabled', true);
- }
+ // if (that.checkToShowSelector('roc-auc') == true) {
+ // $(that.wrapSelector('.vp-ev-model.roc-auc')).prop('disabled', false);
+ // } else {
+ // $(that.wrapSelector('.vp-ev-model.roc-auc')).prop('disabled', true);
+ // }
} else {
// Clustering
- if (that.checkToShowModel('silhouette') == true) {
+ if (that.checkToShowSelector('silhouette') == true) {
$(that.wrapSelector('.vp-ev-model.silhouette')).prop('disabled', false);
} else {
$(that.wrapSelector('.vp-ev-model.silhouette')).prop('disabled', true);
}
- if (that.checkToShowModel('ari-nmi') == true) {
+ if (that.checkToShowSelector('ari-nmi') == true) {
$(that.wrapSelector('.vp-ev-model.ari-nmi')).prop('disabled', false);
} else {
$(that.wrapSelector('.vp-ev-model.ari-nmi')).prop('disabled', true);
@@ -97,7 +95,7 @@ define([
}
});
- // open model selection show
+ // check to enable/disable selector
$(this.wrapSelector('.vp-eval-check')).on('change', function() {
let checked = $(this).prop('checked');
let type = $(this).data('type');
@@ -105,7 +103,7 @@ define([
if (checked) {
$(that.wrapSelector('.vp-ev-model.' + type)).prop('disabled', false);
} else {
- if (that.checkToShowModel(type) == false) {
+ if (that.checkToShowSelector(type) == false) {
$(that.wrapSelector('.vp-ev-model.' + type)).prop('disabled', true);
}
}
@@ -116,7 +114,7 @@ define([
* Check if anything checked available ( > 0)
* @returns
*/
- checkToShowModel(type) {
+ checkToShowSelector(type) {
let checked = $(this.wrapSelector('.vp-eval-check[data-type="' + type + '"]:checked')).length;
if (checked > 0) {
return true;
@@ -131,59 +129,37 @@ define([
$(page).find('.vp-eval-'+this.state.modelType).show();
// varselector
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('predictData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.predictData);
$(page).find('#predictData').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.targetData);
$(page).find('#targetData').replaceWith(varSelector.toTagString());
// Clustering - data selection
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('clusteredIndex');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.clusteredIndex);
$(page).find('#clusteredIndex').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('featureData2');
varSelector.addClass('vp-state vp-input vp-ev-model silhouette');
varSelector.setValue(this.state.featureData2);
$(page).find('#featureData2').replaceWith(varSelector.toTagString());
- varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'list', 'str']);
+ varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('targetData2');
varSelector.addClass('vp-state vp-input vp-ev-model ari-nmi');
varSelector.setValue(this.state.targetData2);
$(page).find('#targetData2').replaceWith(varSelector.toTagString());
- // model
- // set model list
- let modelOptionTag = new com_String();
- vpKernel.getModelList('Classification').then(function(resultObj) {
- let { result } = resultObj;
- var modelList = JSON.parse(result);
- modelList && modelList.forEach(model => {
- let selectFlag = '';
- if (model.varName == that.state.model) {
- selectFlag = 'selected';
- }
- modelOptionTag.appendFormatLine('',
- model.varName, model.varType, selectFlag, model.varName, model.varType);
- });
- $(page).find('#model').html(modelOptionTag.toString());
- $(that.wrapSelector('#model')).html(modelOptionTag.toString());
-
- if (!that.state.model || that.state.model == '') {
- that.state.model = $(that.wrapSelector('#model')).val();
- }
- });
-
// load state
let that = this;
Object.keys(this.state).forEach(key => {
@@ -221,9 +197,9 @@ define([
} else if (this.state.modelType == 'clf') {
// Classification
- if (this.state.roc_curve == false && this.state.auc == false) {
- $(page).find('.vp-ev-model.roc-auc').prop('disabled', true);
- }
+ // if (this.state.roc_curve == false && this.state.auc == false) {
+ // $(page).find('.vp-ev-model.roc-auc').prop('disabled', true);
+ // }
} else {
// Clustering
if (this.state.silhouetteScore == false) {
@@ -238,17 +214,18 @@ define([
}
generateImportCode() {
- return 'from sklearn import metrics';
+ return ['from sklearn import metrics'];
}
generateCode() {
- let codeCells = [];
+ let codeCells = [
+ ...this.generateImportCode() // run import codes
+ ];
let code = new com_String();
let {
modelType, predictData, targetData,
// classification
- confusion_matrix, report, accuracy, precision, recall, f1_score, roc_curve, auc,
- model,
+ confusion_matrix, report, accuracy, precision, recall, f1_score,
// regression
coefficient, intercept, r_squared, mae, mape, rmse, scatter_plot,
// clustering
@@ -296,21 +273,21 @@ define([
code.appendFormat("metrics.f1_score({0}, {1}, average='weighted')", targetData, predictData);
codeCells.push(code.toString());
}
- if (roc_curve) {
- code = new com_String();
- code.appendLine("# ROC Curve");
- code.appendFormatLine("fpr, tpr, thresholds = metrics.roc_curve({0}, {1}.decision_function({2}))", predictData, model, targetData);
- code.appendLine("plt.plot(fpr, tpr, label='ROC Curve')");
- code.appendLine("plt.xlabel('Sensitivity') ");
- code.append("plt.ylabel('Specificity') ")
- codeCells.push(code.toString());
- }
- if (auc) {
- code = new com_String();
- code.appendLine("# AUC");
- code.appendFormat("metrics.roc_auc_score({0}, {1}.decision_function({2}))", predictData, model, targetData);
- codeCells.push(code.toString());
- }
+ // if (roc_curve) {
+ // code = new com_String();
+ // code.appendLine("# ROC Curve");
+ // code.appendFormatLine("fpr, tpr, thresholds = metrics.roc_curve({0}, {1}.decision_function({2}))", predictData, model, targetData);
+ // code.appendLine("plt.plot(fpr, tpr, label='ROC Curve')");
+ // code.appendLine("plt.xlabel('Sensitivity') ");
+ // code.append("plt.ylabel('Specificity') ")
+ // codeCells.push(code.toString());
+ // }
+ // if (auc) {
+ // code = new com_String();
+ // code.appendLine("# AUC");
+ // code.appendFormat("metrics.roc_auc_score({0}, {1}.decision_function({2}))", predictData, model, targetData);
+ // codeCells.push(code.toString());
+ // }
}
//====================================================================
diff --git a/js/m_visualize/Chart.js b/js/m_visualize/Chart.js
index 53c4a62d..bbaa0b36 100644
--- a/js/m_visualize/Chart.js
+++ b/js/m_visualize/Chart.js
@@ -775,7 +775,7 @@ define([
}
code.append("rcParams['axes.unicode_minus'] = False");
- return code.toString();
+ return [code.toString()];
}
diff --git a/js/m_visualize/ChartSetting.js b/js/m_visualize/ChartSetting.js
index a41ef089..6b13b7d8 100644
--- a/js/m_visualize/ChartSetting.js
+++ b/js/m_visualize/ChartSetting.js
@@ -42,7 +42,18 @@ define([
super._bindEvent();
let that = this;
-
+ // setting popup - set default
+ $(this.wrapSelector('#setDefault')).on('change', function() {
+ let checked = $(this).prop('checked');
+
+ if (checked) {
+ // disable input
+ $(that.wrapSelector('.vp-chart-setting-body input')).prop('disabled', true);
+ } else {
+ // enable input
+ $(that.wrapSelector('.vp-chart-setting-body input')).prop('disabled', false);
+ }
+ });
}
templateForBody() {
@@ -113,31 +124,40 @@ define([
generateImportCode() {
var code = new com_String();
code.appendLine('import matplotlib.pyplot as plt');
- code.append('import seaborn as sns');
- return code.toString();
+ code.appendLine('import seaborn as sns');
+ code.append('%matplotlib inline');
+ return [code.toString()];
}
generateCode() {
var code = new com_String();
// get parameters
- let { figureWidth, figureHeight, styleSheet, fontName, fontSize } = this.state;
-
- code.appendLine('import matplotlib.pyplot as plt');
- code.appendFormatLine("plt.rc('figure', figsize=({0}, {1}))", figureWidth, figureHeight);
- if (styleSheet && styleSheet.length > 0) {
- code.appendFormatLine("plt.style.use('{0}')", styleSheet);
- }
- code.appendLine();
-
- code.appendLine('from matplotlib import rcParams');
- if (fontName && fontName.length > 0) {
- code.appendFormatLine("rcParams['font.family'] = '{0}'", fontName);
- }
- if (fontSize && fontSize.length > 0) {
- code.appendFormatLine("rcParams['font.size'] = {0}", fontSize);
+ let setDefault = $(this.wrapSelector('#setDefault')).prop('checked');
+ if (setDefault == true) {
+ code.appendLine('from matplotlib import rcParams, rcParamsDefault');
+ code.append('rcParams.update(rcParamsDefault)');
+ } else {
+ // get parameters
+ let { figureWidth, figureHeight, styleSheet, fontName, fontSize } = this.state;
+
+ code.appendLine('import matplotlib.pyplot as plt');
+ code.appendLine('import seaborn as sns');
+ code.appendFormatLine("plt.rc('figure', figsize=({0}, {1}))", figureWidth, figureHeight);
+ if (styleSheet && styleSheet.length > 0) {
+ code.appendFormatLine("plt.style.use('{0}')", styleSheet);
+ }
+ code.appendLine();
+
+ code.appendLine('from matplotlib import rcParams');
+ if (fontName && fontName.length > 0) {
+ code.appendFormatLine("rcParams['font.family'] = '{0}'", fontName);
+ }
+ if (fontSize && fontSize.length > 0) {
+ code.appendFormatLine("rcParams['font.size'] = {0}", fontSize);
+ }
+ code.append("rcParams['axes.unicode_minus'] = False");
}
- code.append("rcParams['axes.unicode_minus'] = False");
return code.toString();
}
diff --git a/js/m_visualize/Seaborn.js b/js/m_visualize/Seaborn.js
index 4e509b1d..3efd8ed9 100644
--- a/js/m_visualize/Seaborn.js
+++ b/js/m_visualize/Seaborn.js
@@ -48,11 +48,11 @@ define([
title: '',
x_label: '',
y_label: '',
- useLegend: 'False',
legendPos: '',
// style options
- useGrid: 'False',
- useMarker: 'False',
+ color: '',
+ useGrid: '',
+ gridColor: '',
markerStyle: '',
// setting options
x_limit_from: '',
@@ -75,13 +75,22 @@ define([
}
this.legendPosList = [
- 'best', 'upper right', 'upper left', 'lower left', 'lower right',
- 'center left', 'center right', 'lower center', 'upper center', 'center'
+ {label: 'Select option...', value: ''},
+ {label: 'best', value: 'best'},
+ {label: 'upper right', value: 'upper right'},
+ {label: 'upper left', value: 'upper left'},
+ {label: 'lower left', value: 'lower left'},
+ {label: 'lower right', value: 'lower right'},
+ {label: 'center left', value: 'center left'},
+ {label: 'center right', value: 'center right'},
+ {label: 'lower center', value: 'lower center'},
+ {label: 'upper center', value: 'upper center'},
+ {label: 'center', value: 'center'},
];
this.markerList = [
// 'custom': { label: 'Custom', value: 'marker' },
- { label: ' ', value: ' ', title: 'select marker style'},
+ { label: 'Select option...', value: '', title: 'select marker style'},
{ label: '.', value: '.', title: 'point' },
{ label: ',', value: ',', title: 'pixel' },
{ label: 'o', value: 'o', title: 'circle' },
@@ -200,12 +209,6 @@ define([
}
evt.stopPropagation();
});
-
- // set preview size
- $(this.wrapSelector('#previewSize')).on('change', function() {
- that.loadPreview();
- });
-
}
templateForBody() {
@@ -232,7 +235,7 @@ define([
$(page).find('#chartType').html(chartTypeTag.toString());
// chart variable
- let varSelector = new VarSelector2(this.wrapSelector(), ['DataFrame', 'Series', 'list']);
+ let varSelector = new VarSelector2(this.wrapSelector());
varSelector.setComponentID('data');
varSelector.addClass('vp-state vp-input');
varSelector.setValue(this.state.data);
@@ -246,7 +249,7 @@ define([
$(that.wrapSelector('#hue')).prop('disabled', false);
// bind column source using selected dataframe
- com_generator.vp_bindColumnSource(that.wrapSelector(), $(that.wrapSelector('#data')), ['x', 'y', 'hue'], 'select', true);
+ com_generator.vp_bindColumnSource(that.wrapSelector(), $(that.wrapSelector('#data')), ['x', 'y', 'hue'], 'select', true, true);
} else {
$(that.wrapSelector('#x')).prop('disabled', true);
$(that.wrapSelector('#y')).prop('disabled', true);
@@ -259,11 +262,11 @@ define([
let legendPosTag = new com_String();
this.legendPosList.forEach(pos => {
let selectedFlag = '';
- if (pos == that.state.legendPos) {
+ if (pos.value == that.state.legendPos) {
selectedFlag = 'selected';
}
legendPosTag.appendFormatLine('',
- pos, selectedFlag, pos, pos == 'best'?' (default)':'');
+ pos.value, selectedFlag, pos.label, pos.value == 'best'?' (default)':'');
});
$(page).find('#legendPos').html(legendPosTag.toString());
@@ -305,13 +308,11 @@ define([
switch(tagName) {
case 'INPUT':
let inputType = $(tag).prop('type');
- if (inputType == 'text' || inputType == 'number' || inputType == 'hidden') {
- $(tag).val(value);
- break;
- }
if (inputType == 'checkbox') {
$(tag).prop('checked', value);
- break;
+ } else {
+ // if (inputType == 'text' || inputType == 'number' || inputType == 'hidden') {
+ $(tag).val(value);
}
break;
case 'TEXTAREA':
@@ -491,6 +492,7 @@ define([
var fontSize = $(this.wrapSelector('#fontSize')).val();
code.appendLine('import matplotlib.pyplot as plt');
+ code.appendLine('import seaborn as sns');
code.appendFormatLine("plt.rc('figure', figsize=({0}, {1}))", figWidth, figHeight);
if (styleName && styleName.length > 0) {
code.appendFormatLine("plt.style.use('{0}')", styleName);
@@ -507,14 +509,14 @@ define([
code.append("rcParams['axes.unicode_minus'] = False");
}
- return code.toString();
+ return [code.toString()];
}
generateCode(preview=false) {
let {
chartType, data, userOption='',
- title, x_label, y_label, useLegend, legendPos,
- useGrid, useMarker, markerStyle,
+ title, x_label, y_label, legendPos,
+ color, useGrid, gridColor, markerStyle,
x_limit_from, x_limit_to, y_limit_from, y_limit_to,
useSampling, sampleCount
} = this.state;
@@ -527,7 +529,10 @@ define([
let chartCode = new com_String();
let etcOptionCode = []
- if (useMarker == 'True') {
+ if (color != '') {
+ etcOptionCode.push(com_util.formatString("color='{0}'", color));
+ }
+ if (markerStyle != '') {
// TODO: marker to seaborn argument (ex. marker='+' / markers={'Lunch':'s', 'Dinner':'X'})
etcOptionCode.push(com_util.formatString("marker='{0}'", markerStyle));
}
@@ -562,13 +567,20 @@ define([
if (y_limit_from != '' && y_limit_to != '') {
chartCode.appendFormatLine("plt.ylim(({0}, {1}))", y_limit_from, y_limit_to);
}
- if (useLegend == 'True' && legendPos != '') {
+ if (legendPos != '') {
chartCode.appendFormatLine("plt.legend(loc='{0}')", legendPos);
}
- if (useGrid == 'True') {
- chartCode.appendLine("plt.grid(True)");
- // TODO: grid types
- // plt.grid(True, axis='x', color='red', alpha=0.5, linestyle='--')
+ // Style - Grid
+ // plt.grid(True, axis='x', color='red', alpha=0.5, linestyle='--')
+ let gridCodeList = [];
+ if (useGrid != '') {
+ gridCodeList.push(useGrid);
+ }
+ if (gridColor != '') {
+ gridCodeList.push(com_util.formatString("color='{0}'", gridColor));
+ }
+ if (gridCodeList.length > 0) {
+ chartCode.appendFormatLine("plt.grid({0})", gridCodeList.join(', '));
}
chartCode.append('plt.show()');
@@ -583,15 +595,14 @@ define([
code.appendFormatLine("{0}warnings.simplefilter('ignore')", indent);
// set figure size for preview chart
- let defaultWidth = 5;
- let defaultHeight = 4;
- let previewSize = parseInt($(this.wrapSelector('#previewSize')).val());
- code.appendFormatLine('{0}plt.figure(figsize=({1}, {2}))', indent, defaultWidth + previewSize, defaultHeight + previewSize);
+ let defaultWidth = 8;
+ let defaultHeight = 6;
+ code.appendFormatLine('{0}plt.figure(figsize=({1}, {2}))', indent, defaultWidth, defaultHeight);
if (useSampling) {
// data sampling code for preview
convertedData = data + '.sample(n=' + sampleCount + ', random_state=0)';
// replace pre-defined options
- generatedCode = generatedCode.replace(data, convertedData);
+ generatedCode = generatedCode.replaceAll(data, convertedData);
}
code.appendFormatLine("{0}{1}", indent, generatedCode);
@@ -602,7 +613,8 @@ define([
code.appendLine(chartCode.toString());
}
- return code.toString();
+ // remove last Enter(\n) from code and then run it
+ return code.toString().replace(/\n+$/, "");
}
}