wx.html.HtmlWindow to provide help in our application. We can create a standalone window or we can create a window that is going to be a part of the application. The following script will create a help window using the latter idea.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | import wximport wx.html as htmlclass HelpWindow(wx.Frame): def __init__(self, parent, id, title): wx.Frame.__init__(self, parent, id, title, size=(570, 400)) toolbar = self.CreateToolBar() toolbar.AddLabelTool(1, 'Exit', wx.Bitmap('img/quit.png')) toolbar.AddLabelTool(2, 'Help', wx.Bitmap('img/help.png')) toolbar.Realize() self.splitter = wx.SplitterWindow(self, -1) self.panelLeft = wx.Panel(self.splitter, -1, style=wx.BORDER_SUNKEN) self.panelRight = wx.Panel(self.splitter, -1) vbox2 = wx.BoxSizer(wx.VERTICAL) header = wx.Panel(self.panelRight, -1, size=(-1, 20)) header.SetBackgroundColour('#6f6a59') header.SetForegroundColour('WHITE') hbox = wx.BoxSizer(wx.HORIZONTAL) st = wx.StaticText(header, -1, 'Help', (5, 5)) font = st.GetFont() font.SetPointSize(9) st.SetFont(font) hbox.Add(st, 1, wx.TOP | wx.BOTTOM | wx.LEFT, 5) close = wx.BitmapButton(header, -1, wx.Bitmap('img/quit.png', wx.BITMAP_TYPE_PNG), style=wx.NO_BORDER) close.SetBackgroundColour('#6f6a59') hbox.Add(close, 0) header.SetSizer(hbox) vbox2.Add(header, 0, wx.EXPAND) help = html.HtmlWindow(self.panelRight, -1, style=wx.NO_BORDER) help.LoadPage('help.html') vbox2.Add(help, 1, wx.EXPAND) self.panelRight.SetSizer(vbox2) self.panelLeft.SetFocus() self.splitter.SplitVertically(self.panelLeft, self.panelRight) self.splitter.Unsplit() self.Bind(wx.EVT_BUTTON, self.CloseHelp, id=close.GetId()) self.Bind(wx.EVT_TOOL, self.OnClose, id=1) self.Bind(wx.EVT_TOOL, self.OnHelp, id=2) self.Bind(wx.EVT_KEY_DOWN, self.OnKeyPressed) self.CreateStatusBar() self.Centre() self.Show(True) def OnClose(self, event): self.Close() def OnHelp(self, event): self.splitter.SplitVertically(self.panelLeft, self.panelRight) self.panelLeft.SetFocus() def CloseHelp(self, event): self.splitter.Unsplit() self.panelLeft.SetFocus() def OnKeyPressed(self, event): keycode = event.GetKeyCode() if keycode == wx.WXK_F1: self.splitter.SplitVertically(self.panelLeft, self.panelRight) self.panelLeft.SetFocus()app = wx.App()HelpWindow(None, -1, 'HelpWindow')app.MainLoop() |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | <h4>Table of Contents</h4><ul><li><a href="#basic">Basic statistics</a></li><li><a href="#advanced">Advanced statistics</a></li><li><a href="#intro">Introducing Newt</a></li><li><a href="#charts">Working with charts</a></li><li><a href="#pred">Predicting values</a></li><li><a href="#neural">Neural networks</a></li><li><a href="#glos">Glossary</a></li></ul><p><a name="basic"></a></p><h6><a name="basic">Basic Statistics</a></h6><a name="basic">Overview of elementary concepts in statistics.Variables. Correlation. Measurement scales. Statistical significance. Distributions. Normality assumption.</a><p></p><p><a name="advanced"></a></p><h6><a name="advanced">Advanced Statistics</a></h6><a name="advanced">Overview of advanced concepts in statistics. Anova. Linear regression. Estimation and hypothesis testing.Error terms.</a><p></p><p><a name="intro"></a></p><h6><a name="intro">Introducing Newt</a></h6><a name="intro">Introducing the basic functionality of the Newt application. Creating sheets. Charts. Menus and Toolbars. Importing data. Saving data in various formats. Exporting data. Shortcuts. List of methods.</a><p></p><p><a name="charts"></a></p><h6><a name="charts">Charts</a></h6><a name="charts">Working with charts. 2D charts. 3D charts. Bar, line, box, pie, range charts. Scatterplots. Histograms.</a><p></p><p><a name="pred"></a></p><h6><a name="pred">Predicting values</a></h6><a name="pred">Time series and forecasting. Trend Analysis. Seasonality. Moving averages. Univariate methods. Multivariate methods. Holt-Winters smoothing. Exponential smoothing. ARIMA. Fourier analysis.</a><p></p><p><a name="neural"></a></p><h6><a name="neural">Neural networks</a></h6><a name="neural">Overview of neural networks. Biology behind neural networks.Basic artificial Model. Training. Preprocessing. Postprocessing. Types of neural networks.</a><p></p><p><a name="glos"></a></p><h6><a name="glos">Glossary</a></h6><a name="glos">Terms and definitions in statistics.</a><p></p> |
