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Contains convenience functions to create ready-made PlotRenderer
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and PlotFrame instances of various types.
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from numpy import array, ndarray, transpose, cos, sin
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# Local relative imports
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from abstract_data_source import AbstractDataSource
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from array_data_source import ArrayDataSource
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from axis import PlotAxis
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from barplot import BarPlot
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from data_range_1d import DataRange1D
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from grid import PlotGrid
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from linear_mapper import LinearMapper
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from scatterplot import ScatterPlot
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from polar_mapper import PolarMapper
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from lineplot import LinePlot
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from polar_line_renderer import PolarLineRenderer
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def _create_data_sources(data, index_sort="none"):
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Returns datasources for index and value based on the inputs. Assumes that
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the index data is unsorted unless otherwise specified.
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if (type(data) == ndarray) or (len(data) == 2):
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if type(index) in (list, tuple, ndarray):
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index = ArrayDataSource(array(index), sort_order=index_sort)
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elif not isinstance(index, AbstractDataSource):
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raise RuntimeError, "Need an array or list of values or a DataSource, got %s instead." % type(index)
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if type(value) in (list, tuple, ndarray):
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value = ArrayDataSource(array(value))
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elif not isinstance(value, AbstractDataSource):
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raise RuntimeError, "Need an array or list of values or a DataSource, got %s instead." % type(index)
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raise RuntimeError, "Unable to create datasources."
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def create_scatter_plot(data=[], index_bounds=None, value_bounds=None,
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orientation="h", color="green", marker="square",
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bgcolor="transparent", outline_color="black",
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add_grid=False, add_axis=False,
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Creates a ScatterPlot from a single Nx2 data array or a tuple of
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two length-N 1-D arrays. The data must be sorted on the index if any
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reverse-mapping tools are to be used.
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Pre-existing "index" and "value" datasources can be passed in.
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index, value = _create_data_sources(data)
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if index_bounds is not None:
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index_range = DataRange1D(low=index_bounds[0], high=index_bounds[1])
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index_range = DataRange1D()
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index_range.add(index)
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index_mapper = LinearMapper(range=index_range)
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if value_bounds is not None:
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value_range = DataRange1D(low=value_bounds[0], high=value_bounds[1])
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value_range = DataRange1D()
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value_range.add(value)
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value_mapper = LinearMapper(range=value_range)
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plot = ScatterPlot(index=index, value=value,
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index_mapper=index_mapper,
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value_mapper=value_mapper,
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orientation=orientation,
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marker_size=marker_size,
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outline_color=outline_color,
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border_visible=border_visible,)
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add_default_grids(plot, orientation)
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add_default_axes(plot, orientation)
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def create_line_plot(data=[], index_bounds=None, value_bounds=None,
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orientation="h", color="red", width=1.0,
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dash="solid", value_mapper_class=LinearMapper,
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bgcolor="transparent", border_visible=False,
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add_grid=False, add_axis=False,
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index, value = _create_data_sources(data, index_sort)
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if index_bounds is not None:
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index_range = DataRange1D(low=index_bounds[0], high=index_bounds[1])
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index_range = DataRange1D()
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index_range.add(index)
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index_mapper = LinearMapper(range=index_range)
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if value_bounds is not None:
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value_range = DataRange1D(low=value_bounds[0], high=value_bounds[1])
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value_range = DataRange1D()
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value_range.add(value)
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value_mapper = value_mapper_class(range=value_range)
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plot = LinePlot(index=index, value=value,
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index_mapper = index_mapper,
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value_mapper = value_mapper,
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orientation = orientation,
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border_visible=border_visible)
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add_default_grids(plot, orientation)
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add_default_axes(plot, orientation)
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def create_bar_plot(data=[], index_bounds=None, value_bounds=None,
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orientation="h", color="red", bar_width=10.0,
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value_mapper_class=LinearMapper,
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fill_color="red", line_width=1,
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bgcolor="transparent", border_visible=False,
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add_grid=False, add_axis=False):
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index, value = _create_data_sources(data)
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if index_bounds is not None:
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index_range = DataRange1D(low=index_bounds[0], high=index_bounds[1])
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index_range = DataRange1D()
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index_range.add(index)
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index_mapper = LinearMapper(range=index_range)
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if value_bounds is not None:
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value_range = DataRange1D(low=value_bounds[0], high=value_bounds[1])
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value_range = DataRange1D()
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value_range.add(value)
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value_mapper = value_mapper_class(range=value_range)
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plot = BarPlot(index=index,
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value_mapper=value_mapper,
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index_mapper=index_mapper,
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orientation=orientation,
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line_color=line_color,
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fill_color=fill_color,
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line_width=line_width,
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antialias=antialias,)
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add_default_grids(plot, orientation)
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add_default_axes(plot, orientation)
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def create_polar_plot(data, orientation='h', color='black', width=1.0,
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dash="solid", grid="dot", value_mapper_class=PolarMapper):
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if (type(data) != ndarray) and (len(data) == 2):
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data = transpose(array(data))
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r_data, t_data = transpose(data)
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index_data= r_data*cos(t_data)
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value_data= r_data*sin(t_data)
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index = ArrayDataSource(index_data, sort_order='ascending')
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# Typically the value data is unsorted
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value = ArrayDataSource(value_data)
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index_range = DataRange1D()
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index_range.add(index)
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index_mapper = PolarMapper(range=index_range)
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value_range = DataRange1D()
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value_range.add(value)
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value_mapper = value_mapper_class(range=value_range)
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plot = PolarLineRenderer(index=index, value=value,
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index_mapper = index_mapper,
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value_mapper = value_mapper,
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orientation = orientation,
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def add_default_axes(plot, orientation="normal", vtitle="",htitle=""):
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Creates left and bottom axes for a plot. Assumes that the index is
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horizontal and value is vertical by default; set *orientation* to
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something other than "normal" if they are flipped.
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if orientation in ("normal", "h"):
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v_mapper = plot.value_mapper
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h_mapper = plot.index_mapper
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v_mapper = plot.index_mapper
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h_mapper = plot.value_mapper
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left = PlotAxis(orientation='left',
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bottom = PlotAxis(orientation='bottom',
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plot.underlays.append(left)
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plot.underlays.append(bottom)
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def add_default_grids(plot, orientation="normal"):
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Creates horizontal and vertical gridlines for a plot. Assumes that the
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index is horizontal and value is vertical by default; set orientation to
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something other than "normal" if they are flipped.
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if orientation in ("normal", "h"):
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v_mapper = plot.index_mapper
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h_mapper = plot.value_mapper
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v_mapper = plot.value_mapper
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h_mapper = plot.index_mapper
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vgrid = PlotGrid(mapper=v_mapper, orientation='vertical',
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line_color="lightgray", line_style="dot")
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hgrid = PlotGrid(mapper=h_mapper, orientation='horizontal',
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line_color="lightgray", line_style="dot")
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plot.underlays.append(vgrid)
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plot.underlays.append(hgrid)
added
removed
enthought/chaco/plot_factory.py
