def to_Altair(self) -> str:
"""
Generate minimal Altair code to visualize the Vis
Returns
-------
str
String version of the Altair code. Need to print out the string to apply formatting.
"""
from lux.vislib.altair.AltairRenderer import AltairRenderer
renderer = AltairRenderer(output_type="Altair")
self.code = renderer.create_vis(self)
return self.code
def to_altair(self, standalone=False) -> str:
"""
Generate minimal Altair code to visualize the Vis
Parameters
----------
standalone : bool, optional
Flag to determine if outputted code uses user-defined variable names or can be run independently, by default False
Returns
-------
str
String version of the Altair code. Need to print out the string to apply formatting.
"""
from lux.vislib.altair.AltairRenderer import AltairRenderer
renderer = AltairRenderer(output_type="Altair")
self._code = renderer.create_vis(self, standalone)
if lux.config.executor.name == "PandasExecutor":
function_code = "def plot_data(source_df, vis):\n"
function_code += "\timport altair as alt\n"
function_code += "\tvisData = create_chart_data(source_df, vis)\n"
else:
function_code = "def plot_data(tbl, vis):\n"
function_code += "\timport altair as alt\n"
function_code += "\tvisData = create_chart_data(tbl, vis)\n"
vis_code_lines = self._code.split("\n")
for i in range(2, len(vis_code_lines) - 1):
function_code += "\t" + vis_code_lines[i] + "\n"
function_code += "\treturn chart\n#plot_data(your_df, vis) this creates an Altair plot using your source data and vis specification"
function_code = function_code.replace("alt.Chart(tbl)",
"alt.Chart(visData)")
if "mark_circle" in function_code:
function_code = function_code.replace("plot_data",
"plot_scatterplot")
elif "mark_bar" in function_code:
function_code = function_code.replace("plot_data", "plot_barchart")
elif "mark_line" in function_code:
function_code = function_code.replace("plot_data",
"plot_linechart")
elif "mark_rect" in function_code:
function_code = function_code.replace("plot_data", "plot_heatmap")
return function_code
def to_VegaLite(self, prettyOutput=True) -> Union[dict, str]:
"""
Generate minimal Vega-Lite code to visualize the Vis
Returns
-------
Union[dict,str]
String or Dictionary of the VegaLite JSON specification
"""
import json
from lux.vislib.altair.AltairRenderer import AltairRenderer
renderer = AltairRenderer(output_type="VegaLite")
self._code = renderer.create_vis(self)
if (prettyOutput):
return "** Remove this comment -- Copy Text Below to Vega Editor(vega.github.io/editor) to visualize and edit **\n" + json.dumps(
self._code, indent=2)
else:
return self._code
def to_Altair(self, standalone=False) -> str:
"""
Generate minimal Altair code to visualize the Vis
Parameters
----------
standalone : bool, optional
Flag to determine if outputted code uses user-defined variable names or can be run independently, by default False
Returns
-------
str
String version of the Altair code. Need to print out the string to apply formatting.
"""
from lux.vislib.altair.AltairRenderer import AltairRenderer
renderer = AltairRenderer(output_type="Altair")
self._code = renderer.create_vis(self, standalone)
return self._code
def get_Altair_vis_code(self, standalone=False) -> str:
"""
Returns code specific to the visualization without styling
Parameters
----------
standalone : bool, optional
Flag to determine if outputted code uses user-defined variable names or can be run independently, by default False
Returns
-------
str
String version of the Altair code. Need to print out the string to apply formatting.
"""
from lux.vislib.altair.AltairRenderer import AltairRenderer
renderer = AltairRenderer(output_type="Altair")
self._code = renderer.create_vis(self, standalone)
return self._code
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"
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)
fig, ax = matplotlib_setup(4.5, 4)
if vis.mark == "histogram":
chart = Histogram(vis, fig, ax)
elif vis.mark == "bar":
chart = BarChart(vis, fig, ax)
elif vis.mark == "scatter":
chart = ScatterChart(vis, fig, ax)
elif vis.mark == "line":
chart = LineChart(vis, fig, ax)
elif vis.mark == "heatmap":
chart = Heatmap(vis, fig, ax)
elif vis.mark == "geographical":
return AltairRenderer().create_vis(vis, False)
else:
chart = None
return chart
if chart:
plt.tight_layout()
if lux.config.plotting_style and (
lux.config.plotting_backend == "matplotlib"
or lux.config.plotting_backend == "matplotlib_code"):
chart.ax = lux.config.plotting_style(chart.fig, chart.ax)
plt.tight_layout()
tmpfile = BytesIO()
chart.fig.savefig(tmpfile, format="png")
chart.chart = base64.b64encode(tmpfile.getvalue()).decode("utf-8")
plt.clf()
plt.close("all")
if self.output_type == "matplotlib":
return {"config": chart.chart, "vislib": "matplotlib"}
if self.output_type == "matplotlib_code":
if lux.config.plotting_style:
import inspect
chart.code += "\n".join(
inspect.getsource(
lux.config.plotting_style).split("\n ")[1:-1])
chart.code += "\nfig"
chart.code = chart.code.replace("\n\t\t", "\n")
return chart.code
