Exemplo n.º 1
0
    def create_vis(self, view):
        """
		Input DataObject and return a visualization specification
		
		Parameters
		----------
		view: lux.vis.Vis
			Input Vis (with data)
		
		Returns
		-------
		chart : altair.Chart
			Output Altair Chart Object
		"""
        # If a column has a Period dtype, or contains Period objects, convert it back to Datetime
        if view.data is not None:
            for attr in list(view.data.columns):
                if pd.api.types.is_period_dtype(
                        view.data.dtypes[attr]) or isinstance(
                            view.data[attr].iloc[0], pd.Period):
                    dateColumn = view.data[attr]
                    view.data[attr] = pd.PeriodIndex(
                        dateColumn.values).to_timestamp()

        if (view.mark == "histogram"):
            chart = Histogram(view)
        elif (view.mark == "bar"):
            chart = BarChart(view)
        elif (view.mark == "scatter"):
            chart = ScatterChart(view)
        elif (view.mark == "line"):
            chart = LineChart(view)
        else:
            chart = None

        if (chart):
            if (self.output_type == "VegaLite"):
                if (view.plot_config):
                    chart.chart = view.plot_config(chart.chart)
                chart_dict = chart.chart.to_dict()
                # this is a bit of a work around because altair must take a pandas dataframe and we can only generate a luxDataFrame
                # chart["data"] =  { "values": view.data.to_dict(orient='records') }
                # chart_dict["width"] = 160
                # chart_dict["height"] = 150
                return chart_dict
            elif (self.output_type == "Altair"):
                import inspect
                if (view.plot_config):
                    chart.code += '\n'.join(
                        inspect.getsource(
                            view.plot_config).split('\n    ')[1:-1])
                chart.code += "\nchart"
                chart.code = chart.code.replace('\n\t\t', '\n')
                return chart.code
Exemplo n.º 2
0
    def create_vis(self, vis, standalone=True):
        """
		Input DataObject and return a visualization specification
		
		Parameters
		----------
		vis: lux.vis.Vis
			Input Vis (with data)
		standalone: bool
			Flag to determine if outputted code uses user-defined variable names or can be run independently
		Returns
		-------
		chart : altair.Chart
			Output Altair Chart Object
		"""
        # If a column has a Period dtype, or contains Period objects, convert it back to Datetime
        if vis.data is not None:
            for attr in list(vis.data.columns):
                if pd.api.types.is_period_dtype(
                        vis.data.dtypes[attr]) or isinstance(
                            vis.data[attr].iloc[0], pd.Period):
                    dateColumn = vis.data[attr]
                    vis.data[attr] = pd.PeriodIndex(
                        dateColumn.values).to_timestamp()

        if (vis.mark == "histogram"):
            chart = Histogram(vis)
        elif (vis.mark == "bar"):
            chart = BarChart(vis)
        elif (vis.mark == "scatter"):
            chart = ScatterChart(vis)
        elif (vis.mark == "line"):
            chart = LineChart(vis)
        else:
            chart = None

        if (chart):
            if (self.output_type == "VegaLite"):
                if (vis.plot_config):
                    chart.chart = vis.plot_config(chart.chart)
                chart_dict = chart.chart.to_dict()
                # this is a bit of a work around because altair must take a pandas dataframe and we can only generate a luxDataFrame
                # chart["data"] =  { "values": vis.data.to_dict(orient='records') }
                # chart_dict["width"] = 160
                # chart_dict["height"] = 150
                return chart_dict
            elif (self.output_type == "Altair"):
                import inspect
                if (vis.plot_config):
                    chart.code += '\n'.join(
                        inspect.getsource(
                            vis.plot_config).split('\n    ')[1:-1])
                chart.code += "\nchart"
                chart.code = chart.code.replace('\n\t\t', '\n')

                var = vis._source
                if var is not None:
                    all_vars = []
                    for f_info in inspect.getouterframes(
                            inspect.currentframe()):
                        local_vars = f_info.frame.f_back
                        if local_vars:
                            callers_local_vars = local_vars.f_locals.items()
                            possible_vars = [
                                var_name
                                for var_name, var_val in callers_local_vars
                                if var_val is var
                            ]
                            all_vars.extend(possible_vars)
                    found_variable = [
                        possible_var for possible_var in all_vars
                        if possible_var[0] != '_'
                    ][0]
                else:  # if vis._source was not set when the Vis was created
                    found_variable = "df"
                if standalone:
                    chart.code = chart.code.replace(
                        "placeholder_variable",
                        f"pd.DataFrame({str(vis.data.to_dict())})")
                else:
                    chart.code = chart.code.replace(
                        "placeholder_variable", found_variable
                    )  # TODO: Placeholder (need to read dynamically via locals())
                return chart.code
Exemplo n.º 3
0
    def create_vis(self, vis, standalone=True):
        """
        Input Vis object and return a visualization specification

        Parameters
        ----------
        vis: lux.vis.Vis
                Input Vis (with data)
        standalone: bool
                Flag to determine if outputted code uses user-defined variable names or can be run independently
        Returns
        -------
        chart : altair.Chart
                Output Altair Chart Object
        """
        # Lazy Evaluation for 2D Binning
        if vis.mark == "scatter" and vis._postbin:
            vis._mark = "heatmap"
            from lux.executor.PandasExecutor import PandasExecutor

            PandasExecutor.execute_2D_binning(vis)
        # If a column has a Period dtype, or contains Period objects, convert it back to Datetime
        if vis.data is not None:
            for attr in list(vis.data.columns):
                if pd.api.types.is_period_dtype(
                        vis.data.dtypes[attr]) or isinstance(
                            vis.data[attr].iloc[0], pd.Period):
                    dateColumn = vis.data[attr]
                    vis.data[attr] = pd.PeriodIndex(
                        dateColumn.values).to_timestamp()
                if pd.api.types.is_interval_dtype(
                        vis.data.dtypes[attr]) or isinstance(
                            vis.data[attr].iloc[0], pd.Interval):
                    vis.data[attr] = vis.data[attr].astype(str)
                if isinstance(attr, str):
                    if "." in attr:
                        attr_clause = vis.get_attr_by_attr_name(attr)[0]
                        # Suppress special character ".", not displayable in Altair
                        # attr_clause.attribute = attr_clause.attribute.replace(".", "")
                        vis._vis_data = vis.data.rename(
                            columns={attr: attr.replace(".", "")})
        if vis.mark == "histogram":
            chart = Histogram(vis)
        elif vis.mark == "bar":
            chart = BarChart(vis)
        elif vis.mark == "scatter":
            chart = ScatterChart(vis)
        elif vis.mark == "line":
            chart = LineChart(vis)
        elif vis.mark == "heatmap":
            chart = Heatmap(vis)
        elif vis.mark == "geographical":
            chart = Choropleth(vis)
        else:
            chart = None

        if chart:
            if lux.config.plotting_style and (
                    lux.config.plotting_backend == "vegalite"
                    or lux.config.plotting_backend == "altair"):
                chart.chart = lux.config.plotting_style(chart.chart)
            if self.output_type == "VegaLite":
                chart_dict = chart.chart.to_dict()
                # this is a bit of a work around because altair must take a pandas dataframe and we can only generate a luxDataFrame
                # chart["data"] =  { "values": vis.data.to_dict(orient='records') }
                # chart_dict["width"] = 160
                # chart_dict["height"] = 150
                chart_dict["vislib"] = "vegalite"
                return chart_dict
            elif self.output_type == "Altair":
                import inspect

                source = ""
                if lux.config.plotting_style:
                    if "def custom_config(chart):" in lux.config.plotting_style_code:
                        source = lux.config.plotting_style_code
                    else:
                        source = inspect.getsource(lux.config.plotting_style)
                    default_vis_style_code = "# Default Lux Style \nchart = chart.configure_title(fontWeight=500,fontSize=13,font='Helvetica Neue')\n"
                    default_vis_style_code += "chart = chart.configure_axis(titleFontWeight=500,titleFontSize=11,titleFont='Helvetica Neue',\n"
                    default_vis_style_code += "\t\t\t\t\tlabelFontWeight=400,labelFontSize=9,labelFont='Helvetica Neue',labelColor='#505050')\n"
                    default_vis_style_code += "chart = chart.configure_legend(titleFontWeight=500,titleFontSize=10,titleFont='Helvetica Neue',\n"
                    default_vis_style_code += (
                        "\t\t\t\t\tlabelFontWeight=400,labelFontSize=9,labelFont='Helvetica Neue')\n"
                    )
                    default_vis_style_code += "chart = chart.properties(width=160,height=150)\n"
                    vis_style_code = "\n# Custom Style Additions"
                    # TODO: improve parsing such that it splits based on line of logic instead of line of code
                    for line in source.split("\n    ")[1:-1]:
                        if line.strip() not in default_vis_style_code:
                            vis_style_code += "\n" + line
                    if vis_style_code == "\n# Custom Style Additions":
                        vis_style_code = default_vis_style_code
                    else:
                        vis_style_code = default_vis_style_code + vis_style_code
                    vis_style_code = vis_style_code.replace("\n\t\t", "\n")
                    vis_style_code = vis_style_code.replace("\n        ", "\n")
                    lux.config.plotting_style_code = vis_style_code
                chart.code = chart.code.replace("\n\t\t", "\n")
                chart.code = chart.code.replace("\n        ", "\n")

                var = vis._source
                if var is not None:
                    all_vars = []
                    for f_info in inspect.getouterframes(
                            inspect.currentframe()):
                        local_vars = f_info.frame.f_back
                        if local_vars:
                            callers_local_vars = local_vars.f_locals.items()
                            possible_vars = [
                                var_name
                                for var_name, var_val in callers_local_vars
                                if var_val is var
                            ]
                            all_vars.extend(possible_vars)
                    found_variable = [
                        possible_var for possible_var in all_vars
                        if possible_var[0] != "_"
                    ][0]
                else:  # if vis._source was not set when the Vis was created
                    found_variable = "df"
                if standalone:
                    chart.code = chart.code.replace(
                        "placeholder_variable",
                        f"pd.DataFrame({str(vis.data.to_dict())})",
                    )
                else:
                    # TODO: Placeholder (need to read dynamically via locals())
                    chart.code = chart.code.replace("placeholder_variable",
                                                    found_variable)
                return chart.code
Exemplo n.º 4
0
    def create_vis(self, vis, standalone=True):
        """
        Input Vis object and return a visualization specification

        Parameters
        ----------
        vis: lux.vis.Vis
                Input Vis (with data)
        standalone: bool
                Flag to determine if outputted code uses user-defined variable names or can be run independently
        Returns
        -------
        chart : altair.Chart
                Output Altair Chart Object
        """
        # Lazy Evaluation for 2D Binning
        if vis.mark == "scatter" and vis._postbin:
            vis._mark = "heatmap"
            from lux.executor.PandasExecutor import PandasExecutor

            PandasExecutor.execute_2D_binning(vis)
        # If a column has a Period dtype, or contains Period objects, convert it back to Datetime
        if vis.data is not None:
            for attr in list(vis.data.columns):
                if pd.api.types.is_period_dtype(
                        vis.data.dtypes[attr]) or isinstance(
                            vis.data[attr].iloc[0], pd.Period):
                    dateColumn = vis.data[attr]
                    vis.data[attr] = pd.PeriodIndex(
                        dateColumn.values).to_timestamp()
                if pd.api.types.is_interval_dtype(
                        vis.data.dtypes[attr]) or isinstance(
                            vis.data[attr].iloc[0], pd.Interval):
                    vis.data[attr] = vis.data[attr].astype(str)
                if isinstance(attr, str):
                    if "." in attr:
                        attr_clause = vis.get_attr_by_attr_name(attr)[0]
                        # Suppress special character ".", not displayable in Altair
                        # attr_clause.attribute = attr_clause.attribute.replace(".", "")
                        vis._vis_data = vis.data.rename(
                            columns={attr: attr.replace(".", "")})
        if vis.mark == "histogram":
            chart = Histogram(vis)
        elif vis.mark == "bar":
            chart = BarChart(vis)
        elif vis.mark == "scatter":
            chart = ScatterChart(vis)
        elif vis.mark == "line":
            chart = LineChart(vis)
        elif vis.mark == "heatmap":
            chart = Heatmap(vis)
        else:
            chart = None

        if chart:
            if lux.config.plot_config:
                chart.chart = lux.config.plot_config(chart.chart)
            if self.output_type == "VegaLite":
                chart_dict = chart.chart.to_dict()
                # this is a bit of a work around because altair must take a pandas dataframe and we can only generate a luxDataFrame
                # chart["data"] =  { "values": vis.data.to_dict(orient='records') }
                # chart_dict["width"] = 160
                # chart_dict["height"] = 150
                return chart_dict
            elif self.output_type == "Altair":
                import inspect

                if lux.config.plot_config:
                    chart.code += "\n".join(
                        inspect.getsource(
                            lux.config.plot_config).split("\n    ")[1:-1])
                chart.code += "\nchart"
                chart.code = chart.code.replace("\n\t\t", "\n")

                var = vis._source
                if var is not None:
                    all_vars = []
                    for f_info in inspect.getouterframes(
                            inspect.currentframe()):
                        local_vars = f_info.frame.f_back
                        if local_vars:
                            callers_local_vars = local_vars.f_locals.items()
                            possible_vars = [
                                var_name
                                for var_name, var_val in callers_local_vars
                                if var_val is var
                            ]
                            all_vars.extend(possible_vars)
                    found_variable = [
                        possible_var for possible_var in all_vars
                        if possible_var[0] != "_"
                    ][0]
                else:  # if vis._source was not set when the Vis was created
                    found_variable = "df"
                if standalone:
                    chart.code = chart.code.replace(
                        "placeholder_variable",
                        f"pd.DataFrame({str(vis.data.to_dict())})",
                    )
                else:
                    # TODO: Placeholder (need to read dynamically via locals())
                    chart.code = chart.code.replace("placeholder_variable",
                                                    found_variable)
                return chart.code