/*

* Project Name : Visual Python

* Description : GUI-based Python code generator

* File Name : Chi2test.js

* Author : Black Logic

* Note : Chi-square test of independence

* License : GNU GPLv3 with Visual Python special exception

* Date : 2023. 05. 24

* Change Date :

*/

//============================================================================

// [CLASS] Chi2test

//============================================================================

define([

__VP_TEXT_LOADER__('vp_base/html/m_stats/chi2test.html'),

'vp_base/js/com/com_util',

'vp_base/js/com/com_Const',

'vp_base/js/com/com_String',

'vp_base/js/com/com_generatorV2',

'vp_base/js/com/component/PopupComponent',

'vp_base/js/com/component/DataSelector',

'vp_base/js/m_apps/Subset'

], function(nmHTML, com_util, com_Const, com_String, com_generator, PopupComponent, DataSelector, Subset) {

/**

* Chi2test

*/

class Chi2test extends PopupComponent {

_init() {

super._init();

/** Write codes executed before rendering */

this.config.sizeLevel = 2;

this.config.checkModules = ['pd'];

this.config.docs = 'https://docs.scipy.org/doc/scipy/reference/';

this.state = {

data: '',

dataType: '',

row: '',

column: '',

barplot: true,

crossTab: true,

cramersCoef: true,

...this.state

};

this.subsetEditor = null;

}

_bindEvent() {

super._bindEvent();

/** Implement binding events */

var that = this;

$(this.wrapSelector('#data')).on('change', function() {

let bindIdList = ['row', 'column'];

if (that.state.dataType === 'Series') {

// Series

bindIdList.forEach(id => {

$(that.wrapSelector('#' + id)).html('');

$(that.wrapSelector('#' + id)).prop('disabled', true);

});

} else {

// DataFrame

bindIdList.forEach(id => {

$(that.wrapSelector('#' + id)).prop('disabled', false);

});

com_generator.vp_bindColumnSource(that, 'data', bindIdList, 'select', false, false);

}

});

}

handleVariableChange(data) {

this.state.data = data;

let bindIdList = ['row', 'column'];

if (that.state.dataType === 'DataFrame') {

// DataFrame

bindIdList.forEach(id => {

$(that.wrapSelector('#' + id)).html('');

$(that.wrapSelector('#' + id)).prop('disabled', false);

});

com_generator.vp_bindColumnSource(that, 'data', bindIdList, 'select', false, false);

} else {

// Others

bindIdList.forEach(id => {

$(that.wrapSelector('#' + id)).html('');

$(that.wrapSelector('#' + id)).prop('disabled', true);

});

}

}

templateForBody() {

let page = $(nmHTML);

let that = this;

let dataSelector = new DataSelector({

pageThis: this, id: 'data', placeholder: 'Select data', required: true, boxClasses: 'vp-flex-gap5',

allowDataType: ['DataFrame'], withPopup: false,

finish: function(data, type) {

that.state.data = data;

that.state.dataType = type;

$(that.wrapSelector('#data')).trigger('change');

},

select: function(data, type) {

that.state.data = data;

that.state.dataType = type;

$(that.wrapSelector('#data')).trigger('change');

}

});

$(page).find('#data').replaceWith(dataSelector.toTagString());

return page;

}

render() {

super.render();

let that = this;

// render Subset

this.subsetEditor = new Subset({

pandasObject: '',

config: { name: 'Subset', category: this.name } },

{

useAsModule: true,

useInputColumns: true,

targetSelector: this.wrapSelector('#data'),

pageThis: this,

finish: function(code, state) {

that.state.data = code;

that.state.dataType = state.returnType;

$(that.wrapSelector('#data')).val(code);

$(that.wrapSelector('#data')).trigger('change');

}

});

// bind column if data exist

if (this.state.data !== '') {

com_generator.vp_bindColumnSource(this, 'data', ['row', 'column'], 'select', false, false);

}

}

generateCode() {

let { data, row, column, barplot, crossTab, cramersCoef } = this.state;

let codeList = [];

let code = new com_String();

code.appendFormatLine("vp_df = {0}.dropna().copy()", data);

// Display option

if (barplot === true) {

code.appendLine();

code.appendLine("# Count plot");

code.appendLine("import seaborn as sns");

code.appendLine("import warnings");

code.appendLine("with warnings.catch_warnings():");

code.appendLine(" warnings.simplefilter(action='ignore', category=Warning)");

code.appendFormatLine(" sns.countplot(data=vp_df, x={0}, hue={1})", row, column);

code.appendLine(" plt.show()");

}

code.appendLine("");

code.appendLine("# Chi-square test of independence");

code.appendLine("from IPython.display import display, Markdown");

code.appendLine("from scipy import stats");

code.appendFormatLine("_obs = pd.crosstab(index=vp_df[{0}], columns=vp_df[{1}])", row, column);

code.appendLine("_res1 = stats.chi2_contingency(_obs)");

code.appendLine("_res2 = stats.chi2_contingency(_obs, lambda_='log-likelihood')");

if (crossTab === true) {

code.appendLine("");

code.appendLine("# Cross tabulation: Count");

code.appendFormatLine("_dfc = pd.crosstab(index=vp_df[{0}],columns=vp_df[{1}],margins=True,margins_name='Total')", row, column);

code.appendLine("_dfc = _dfc.reset_index().reset_index()");

code.appendLine("_dfc[' '] = 'Count'");

code.appendLine("");

code.appendLine("# Cross tabulation: Expected count");

code.appendLine("_dfe = pd.DataFrame(_res1.expected_freq, index=_obs.index, columns=_obs.columns).round(1)");

code.appendLine("_dfe.loc['Total',:] = _dfe.sum(axis=0)");

code.appendLine("_dfe.loc[:,'Total'] = _dfe.sum(axis=1)");

code.appendLine("_dfe = _dfe.reset_index().reset_index()");

code.appendLine("_dfe[' '] = 'Expected count'");

code.appendLine("");

code.appendLine("# Cross tabulation: Count + Expected count");

code.appendLine("display(Markdown('### Cross tabulation'))");

code.appendFormatLine("display(pd.concat([_dfc, _dfe]).set_index([{0},' ']).sort_values('index').drop('index',axis=1))", row);

}

code.appendLine("");

code.appendLine("# Chi-square test");

code.appendLine("display(Markdown('### Chi-square test'))");

code.appendLine("display(pd.DataFrame(data = {'Value':[_res1.statistic,_res2.statistic,vp_df.dropna().shape[0]],");

code.appendLine(" 'df':[_res1.dof,_res2.dof,np.nan],");

code.appendLine(" 'p-value(two-sided)':[_res1.pvalue,_res2.pvalue,np.nan]},");

code.append(" index= ['Pearson Chi-square','Likelihood ratio','N of valid cases']))");

if (cramersCoef === true) {

code.appendLine("");

code.appendLine("");

code.appendLine("# Cramers' V coefficient");

code.appendLine("_X2 = stats.chi2_contingency(_obs)[0]");

code.appendLine("_sum = _obs.sum().sum()");

code.appendLine("_minDim = min(_obs.shape)-1");

code.appendLine("display(Markdown('### Cramers V coefficient'))");

code.append("display(pd.DataFrame(data={'Value':np.sqrt((_X2/_sum) / _minDim)}, index=['Cramers V coefficient']))");

}

codeList.push(code.toString());

return codeList;

}

}

return Chi2test;

});