added save functionality for mpl, test array line plot for mpl
This commit is contained in:
Shital Shah
Родитель
dc0f2e01de
Коммит
bbf601d57f
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@ -1,169 +1,173 @@
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT license.
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#from IPython import get_ipython, display
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#if get_ipython():
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# get_ipython().magic('matplotlib notebook')
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#import matplotlib
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#if os.name == 'posix' and "DISPLAY" not in os.environ:
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# matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
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#from ipywidgets.widgets.interaction import show_inline_matplotlib_plots
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#from ipykernel.pylab.backend_inline import flush_figures
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from ..vis_base import VisBase
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import sys, logging
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from abc import abstractmethod
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from .. import utils
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class BaseMplPlot(VisBase):
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def __init__(self, cell:VisBase.widgets.Box=None, title:str=None, show_legend:bool=None, is_3d:bool=False,
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stream_name:str=None, console_debug:bool=False, **vis_args):
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super(BaseMplPlot, self).__init__(VisBase.widgets.Output(), cell, title, show_legend,
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stream_name=stream_name, console_debug=console_debug, **vis_args)
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self._fig_init_done = False
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self.show_legend = show_legend
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self.is_3d = is_3d
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if is_3d:
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# this is needed for some reason
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from mpl_toolkits.mplot3d import Axes3D
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# graph objects
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self.figure = None
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self._ax_main = None
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# matplotlib animation
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self.animation = None
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self.anim_interval = None
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#print(matplotlib.get_backend())
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#display.display(self.cell)
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# anim_interval in seconds
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def init_fig(self, anim_interval:float=1.0):
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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"""(for derived class) Initializes matplotlib figure"""
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if self._fig_init_done:
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return False
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# create figure and animation
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self.figure = plt.figure(figsize=(8, 3))
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self.anim_interval = anim_interval
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# default color pallet
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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plt.set_cmap('Dark2')
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plt.rcParams['image.cmap']='Dark2'
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self._fig_init_done = True
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return True
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def get_main_axis(self):
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# if we don't yet have main axis, create one
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if not self._ax_main:
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# by default assign one subplot to whole graph
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self._ax_main = self.figure.add_subplot(111,
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projection=None if not self.is_3d else '3d')
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self._ax_main.grid(self.is_show_grid())
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# change the color of the top and right spines to opaque gray
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self._ax_main.spines['right'].set_color((.8,.8,.8))
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self._ax_main.spines['top'].set_color((.8,.8,.8))
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if self.title is not None:
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title = self._ax_main.set_title(self.title)
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title.set_weight('bold')
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return self._ax_main
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# overridable
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def is_show_grid(self):
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return True
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def _on_update(self, frame): # pylint: disable=unused-argument
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try:
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self._update_stream_plots()
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except Exception as ex:
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# when exception occurs here, animation will stop and there
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# will be no further plot updates
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# TODO: may be we don't need all of below but none of them
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# are popping up exception in Jupyter Notebook because these
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# exceptions occur in background?
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self.last_ex = ex
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logging.exception('Exception in matplotlib update loop')
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def show(self, blocking=False):
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if not self.is_shown and self.anim_interval:
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from matplotlib.animation import FuncAnimation # function-level import as this one is expensive
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self.animation = FuncAnimation(self.figure, self._on_update, interval=self.anim_interval*1000.0)
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super(BaseMplPlot, self).show(blocking)
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def _post_update_stream_plot(self, stream_vis):
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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utils.debug_log("Plot updated", stream_vis.stream.stream_name, verbosity=5)
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if self.layout_dirty:
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# do not do tight_layout() call on every update
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# that would jumble up the graphs! it should only called
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# once each time there is change in layout
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self.figure.tight_layout()
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self.layout_dirty = False
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# below forces redraw and it was helpful to
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# repaint even if there was error in interval loop
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# but it does work in native UX and not in Jupyter Notebook
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#self.figure.canvas.draw()
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#self.figure.canvas.flush_events()
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if self._use_hbox and VisBase.get_ipython():
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self.widget.clear_output(wait=True)
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with self.widget:
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plt.show(self.figure)
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# everything else that doesn't work
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#self.figure.show()
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#display.clear_output(wait=True)
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#display.display(self.figure)
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#flush_figures()
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#plt.show()
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#show_inline_matplotlib_plots()
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#elif not get_ipython():
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# self.figure.canvas.draw()
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def _post_add_subscription(self, stream_vis, **stream_vis_args):
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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# make sure figure is initialized
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self.init_fig()
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self.init_stream_plot(stream_vis, **stream_vis_args)
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# redo the legend
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#self.figure.legend(loc='center right', bbox_to_anchor=(1.5, 0.5))
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if self.show_legend:
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self.figure.legend(loc='lower right')
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plt.subplots_adjust(hspace=0.6)
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def _show_widget_native(self, blocking:bool):
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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#plt.ion()
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#plt.show()
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return plt.show(block=blocking)
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def _show_widget_notebook(self):
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# no need to return anything because %matplotlib notebook will
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# detect spawning of figure and paint it
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# if self.figure is returned then you will see two of them
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return None
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#plt.show()
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#return self.figure
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def _can_update_stream_plots(self):
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return False # we run interval timer which will flush the key
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@abstractmethod
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def init_stream_plot(self, stream_vis, **stream_vis_args):
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"""(for derived class) Create new plot info for this stream"""
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pass
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT license.
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#from IPython import get_ipython, display
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#if get_ipython():
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# get_ipython().magic('matplotlib notebook')
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#import matplotlib
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#if os.name == 'posix' and "DISPLAY" not in os.environ:
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# matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
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#from ipywidgets.widgets.interaction import show_inline_matplotlib_plots
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#from ipykernel.pylab.backend_inline import flush_figures
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from ..vis_base import VisBase
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import sys, logging
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from abc import abstractmethod
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from .. import utils
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class BaseMplPlot(VisBase):
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def __init__(self, cell:VisBase.widgets.Box=None, title:str=None, show_legend:bool=None, is_3d:bool=False,
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stream_name:str=None, console_debug:bool=False, **vis_args):
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super(BaseMplPlot, self).__init__(VisBase.widgets.Output(), cell, title, show_legend,
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stream_name=stream_name, console_debug=console_debug, **vis_args)
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self._fig_init_done = False
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self.show_legend = show_legend
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self.is_3d = is_3d
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if is_3d:
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# this is needed for some reason
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from mpl_toolkits.mplot3d import Axes3D
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# graph objects
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self.figure = None
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self._ax_main = None
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# matplotlib animation
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self.animation = None
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self.anim_interval = None
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#print(matplotlib.get_backend())
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#display.display(self.cell)
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# anim_interval in seconds
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def init_fig(self, anim_interval:float=1.0):
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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"""(for derived class) Initializes matplotlib figure"""
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if self._fig_init_done:
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return False
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# create figure and animation
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self.figure = plt.figure(figsize=(8, 3))
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self.anim_interval = anim_interval
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# default color pallet
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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plt.set_cmap('Dark2')
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plt.rcParams['image.cmap']='Dark2'
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self._fig_init_done = True
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return True
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def get_main_axis(self):
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# if we don't yet have main axis, create one
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if not self._ax_main:
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# by default assign one subplot to whole graph
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self._ax_main = self.figure.add_subplot(111,
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projection=None if not self.is_3d else '3d')
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self._ax_main.grid(self.is_show_grid())
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# change the color of the top and right spines to opaque gray
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self._ax_main.spines['right'].set_color((.8,.8,.8))
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self._ax_main.spines['top'].set_color((.8,.8,.8))
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if self.title is not None:
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title = self._ax_main.set_title(self.title)
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title.set_weight('bold')
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return self._ax_main
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# overridable
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def is_show_grid(self):
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return True
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def _on_update(self, frame): # pylint: disable=unused-argument
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try:
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self._update_stream_plots()
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except Exception as ex:
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# when exception occurs here, animation will stop and there
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# will be no further plot updates
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# TODO: may be we don't need all of below but none of them
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# are popping up exception in Jupyter Notebook because these
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# exceptions occur in background?
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self.last_ex = ex
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logging.exception('Exception in matplotlib update loop')
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def show(self, blocking=False):
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if not self.is_shown and self.anim_interval:
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from matplotlib.animation import FuncAnimation # function-level import as this one is expensive
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self.animation = FuncAnimation(self.figure, self._on_update, interval=self.anim_interval*1000.0)
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super(BaseMplPlot, self).show(blocking)
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def _post_update_stream_plot(self, stream_vis):
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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utils.debug_log("Plot updated", stream_vis.stream.stream_name, verbosity=5)
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if self.layout_dirty:
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# do not do tight_layout() call on every update
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# that would jumble up the graphs! it should only called
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# once each time there is change in layout
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self.figure.tight_layout()
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self.layout_dirty = False
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|
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# below forces redraw and it was helpful to
|
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# repaint even if there was error in interval loop
|
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# but it does work in native UX and not in Jupyter Notebook
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#self.figure.canvas.draw()
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#self.figure.canvas.flush_events()
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if self._use_hbox and VisBase.get_ipython():
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self.widget.clear_output(wait=True)
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with self.widget:
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plt.show(self.figure)
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# everything else that doesn't work
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#self.figure.show()
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#display.clear_output(wait=True)
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#display.display(self.figure)
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#flush_figures()
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#plt.show()
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#show_inline_matplotlib_plots()
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#elif not get_ipython():
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# self.figure.canvas.draw()
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def _post_add_subscription(self, stream_vis, **stream_vis_args):
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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# make sure figure is initialized
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self.init_fig()
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self.init_stream_plot(stream_vis, **stream_vis_args)
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# redo the legend
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#self.figure.legend(loc='center right', bbox_to_anchor=(1.5, 0.5))
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if self.show_legend:
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self.figure.legend(loc='lower right')
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plt.subplots_adjust(hspace=0.6)
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def _show_widget_native(self, blocking:bool):
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import matplotlib.pyplot as plt # delayed import due to matplotlib threading issue
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#plt.ion()
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#plt.show()
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return plt.show(block=blocking)
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def _show_widget_notebook(self):
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# no need to return anything because %matplotlib notebook will
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# detect spawning of figure and paint it
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# if self.figure is returned then you will see two of them
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return None
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#plt.show()
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#return self.figure
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def _can_update_stream_plots(self):
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return False # we run interval timer which will flush the key
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@abstractmethod
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def init_stream_plot(self, stream_vis, **stream_vis_args):
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"""(for derived class) Create new plot info for this stream"""
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pass
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def _save_widget(self, filepath:str)->None:
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self._update_stream_plots()
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self.figure.savefig(filepath)
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@ -1,180 +1,185 @@
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT license.
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import sys, time, threading, queue, functools
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from typing import Any
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from types import MethodType
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from abc import ABCMeta, abstractmethod
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from .lv_types import StreamVisInfo, StreamItem
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from . import utils
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from .stream import Stream
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class VisBase(Stream, metaclass=ABCMeta):
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# these are expensive import so we attach to base class so derived class can use them
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from IPython import get_ipython, display
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import ipywidgets as widgets
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def __init__(self, widget, cell:widgets.Box, title:str, show_legend:bool, stream_name:str=None, console_debug:bool=False, **vis_args):
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super(VisBase, self).__init__(stream_name=stream_name, console_debug=console_debug)
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self.lock = threading.Lock()
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self._use_hbox = True
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#utils.set_default(vis_args, 'cell_width', '100%')
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self.widget = widget
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self.cell = cell or VisBase.widgets.HBox(layout=VisBase.widgets.Layout(\
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width=vis_args.get('cell_width', None))) if self._use_hbox else None
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if self._use_hbox:
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self.cell.children += (self.widget,)
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self._stream_vises = {}
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self.is_shown = cell is not None
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self.title = title
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self.last_ex = None
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self.layout_dirty = False
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self.q_last_processed = 0
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def subscribe(self, stream:Stream, title=None, clear_after_end=False, clear_after_each=False,
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show:bool=False, history_len=1, dim_history=True, opacity=None, **stream_vis_args):
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# in this ovedrride we don't call base class method
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with self.lock:
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self.layout_dirty = True
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stream_vis = StreamVisInfo(stream, title, clear_after_end,
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clear_after_each, history_len, dim_history, opacity,
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len(self._stream_vises), stream_vis_args, 0)
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stream_vis._clear_pending = False
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stream_vis._pending_items = queue.Queue()
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self._stream_vises[stream.stream_name] = stream_vis
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self._post_add_subscription(stream_vis, **stream_vis_args)
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super(VisBase, self).subscribe(stream)
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if show or (show is None and not self.is_shown):
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return self.show()
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def show(self, blocking:bool=False):
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self.is_shown = True
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if VisBase.get_ipython():
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if self._use_hbox:
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VisBase.display.display(self.cell) # this method doesn't need returns
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#return self.cell
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else:
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return self._show_widget_notebook()
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else:
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return self._show_widget_native(blocking)
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def write(self, val:Any, from_stream:'Stream'=None):
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stream_item = self.to_stream_item(val)
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stream_vis:StreamVisInfo = None
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if from_stream:
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stream_vis = self._stream_vises.get(from_stream.stream_name, None)
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if not stream_vis: # select the first one we have
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stream_vis = next(iter(self._stream_vises.values()))
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VisBase.write_stream_plot(self, stream_vis, stream_item)
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super(VisBase, self).write(stream_item)
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@staticmethod
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def write_stream_plot(vis, stream_vis:StreamVisInfo, stream_item:StreamItem):
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with vis.lock: # this could be from separate thread!
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#if stream_vis is None:
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# utils.debug_log('stream_vis not specified in VisBase.write')
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# stream_vis = next(iter(vis._stream_vises.values())) # use first as default
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utils.debug_log("Stream received: {}".format(stream_item.stream_name), verbosity=5)
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stream_vis._pending_items.put(stream_item)
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# if we accumulated enough of pending items then let's process them
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if vis._can_update_stream_plots():
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vis._update_stream_plots()
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def _extract_results(self, stream_vis):
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stream_items, clear_current, clear_history = [], False, False
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while not stream_vis._pending_items.empty():
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stream_item = stream_vis._pending_items.get()
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if stream_item.stream_reset:
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utils.debug_log("Stream reset", stream_item.stream_name)
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stream_items.clear() # no need to process these events
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||||
clear_current, clear_history = True, True
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else:
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# check if there was an exception
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if stream_item.exception is not None:
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#TODO: need better handling here?
|
||||
print(stream_item.exception, file=sys.stderr)
|
||||
raise stream_item.exception
|
||||
|
||||
# state management for _clear_pending
|
||||
# if we need to clear plot before putting in data, do so
|
||||
if stream_vis._clear_pending:
|
||||
stream_items.clear()
|
||||
clear_current = True
|
||||
stream_vis._clear_pending = False
|
||||
if stream_vis.clear_after_each or (stream_item.ended and stream_vis.clear_after_end):
|
||||
stream_vis._clear_pending = True
|
||||
|
||||
stream_items.append(stream_item)
|
||||
|
||||
return stream_items, clear_current, clear_history
|
||||
|
||||
def _extract_vals(self, stream_items):
|
||||
vals = []
|
||||
for stream_item in stream_items:
|
||||
if stream_item.ended or stream_item.value is None:
|
||||
pass # no values to add
|
||||
else:
|
||||
if utils.is_array_like(stream_item.value, tuple_is_array=False):
|
||||
vals.extend(stream_item.value)
|
||||
else:
|
||||
vals.append(stream_item.value)
|
||||
return vals
|
||||
|
||||
@abstractmethod
|
||||
def clear_plot(self, stream_vis, clear_history):
|
||||
"""(for derived class) Clears the data in specified plot before new data is redrawn"""
|
||||
pass
|
||||
@abstractmethod
|
||||
def _show_stream_items(self, stream_vis, stream_items):
|
||||
"""Paint the given stream_items in to visualizer. If visualizer is dirty then return False else True.
|
||||
"""
|
||||
|
||||
pass
|
||||
@abstractmethod
|
||||
def _post_add_subscription(self, stream_vis, **stream_vis_args):
|
||||
pass
|
||||
|
||||
# typically we want to batch up items for performance
|
||||
def _can_update_stream_plots(self):
|
||||
return True
|
||||
|
||||
@abstractmethod
|
||||
def _post_update_stream_plot(self, stream_vis):
|
||||
pass
|
||||
|
||||
def _update_stream_plots(self):
|
||||
with self.lock:
|
||||
self.q_last_processed = time.time()
|
||||
for stream_vis in self._stream_vises.values():
|
||||
stream_items, clear_current, clear_history = self._extract_results(stream_vis)
|
||||
|
||||
if clear_current:
|
||||
self.clear_plot(stream_vis, clear_history)
|
||||
|
||||
# if we have something to render
|
||||
dirty = not self._show_stream_items(stream_vis, stream_items)
|
||||
if dirty:
|
||||
self._post_update_stream_plot(stream_vis)
|
||||
stream_vis.last_update = time.time()
|
||||
|
||||
@abstractmethod
|
||||
def _show_widget_native(self, blocking:bool):
|
||||
pass
|
||||
@abstractmethod
|
||||
def _show_widget_notebook(self):
|
||||
pass
|
||||
# Copyright (c) Microsoft Corporation.
|
||||
# Licensed under the MIT license.
|
||||
|
||||
import sys, time, threading, queue, functools
|
||||
from typing import Any
|
||||
from types import MethodType
|
||||
from abc import ABCMeta, abstractmethod
|
||||
|
||||
from .lv_types import StreamVisInfo, StreamItem
|
||||
from . import utils
|
||||
from .stream import Stream
|
||||
|
||||
|
||||
class VisBase(Stream, metaclass=ABCMeta):
|
||||
# these are expensive import so we attach to base class so derived class can use them
|
||||
from IPython import get_ipython, display
|
||||
import ipywidgets as widgets
|
||||
|
||||
def __init__(self, widget, cell:widgets.Box, title:str, show_legend:bool, stream_name:str=None, console_debug:bool=False, **vis_args):
|
||||
super(VisBase, self).__init__(stream_name=stream_name, console_debug=console_debug)
|
||||
|
||||
self.lock = threading.Lock()
|
||||
self._use_hbox = True
|
||||
#utils.set_default(vis_args, 'cell_width', '100%')
|
||||
|
||||
self.widget = widget
|
||||
|
||||
self.cell = cell or VisBase.widgets.HBox(layout=VisBase.widgets.Layout(\
|
||||
width=vis_args.get('cell_width', None))) if self._use_hbox else None
|
||||
if self._use_hbox:
|
||||
self.cell.children += (self.widget,)
|
||||
self._stream_vises = {}
|
||||
self.is_shown = cell is not None
|
||||
self.title = title
|
||||
self.last_ex = None
|
||||
self.layout_dirty = False
|
||||
self.q_last_processed = 0
|
||||
|
||||
def subscribe(self, stream:Stream, title=None, clear_after_end=False, clear_after_each=False,
|
||||
show:bool=False, history_len=1, dim_history=True, opacity=None, **stream_vis_args):
|
||||
# in this ovedrride we don't call base class method
|
||||
with self.lock:
|
||||
self.layout_dirty = True
|
||||
|
||||
stream_vis = StreamVisInfo(stream, title, clear_after_end,
|
||||
clear_after_each, history_len, dim_history, opacity,
|
||||
len(self._stream_vises), stream_vis_args, 0)
|
||||
stream_vis._clear_pending = False
|
||||
stream_vis._pending_items = queue.Queue()
|
||||
self._stream_vises[stream.stream_name] = stream_vis
|
||||
|
||||
self._post_add_subscription(stream_vis, **stream_vis_args)
|
||||
|
||||
super(VisBase, self).subscribe(stream)
|
||||
|
||||
if show or (show is None and not self.is_shown):
|
||||
return self.show()
|
||||
|
||||
def show(self, blocking:bool=False):
|
||||
self.is_shown = True
|
||||
if VisBase.get_ipython():
|
||||
if self._use_hbox:
|
||||
VisBase.display.display(self.cell) # this method doesn't need returns
|
||||
#return self.cell
|
||||
else:
|
||||
return self._show_widget_notebook()
|
||||
else:
|
||||
return self._show_widget_native(blocking)
|
||||
|
||||
def save(self, filepath:str)->None:
|
||||
self._save_widget(filepath)
|
||||
|
||||
def write(self, val:Any, from_stream:'Stream'=None):
|
||||
stream_item = self.to_stream_item(val)
|
||||
|
||||
stream_vis:StreamVisInfo = None
|
||||
if from_stream:
|
||||
stream_vis = self._stream_vises.get(from_stream.stream_name, None)
|
||||
|
||||
if not stream_vis: # select the first one we have
|
||||
stream_vis = next(iter(self._stream_vises.values()))
|
||||
|
||||
VisBase.write_stream_plot(self, stream_vis, stream_item)
|
||||
|
||||
super(VisBase, self).write(stream_item)
|
||||
|
||||
|
||||
@staticmethod
|
||||
def write_stream_plot(vis, stream_vis:StreamVisInfo, stream_item:StreamItem):
|
||||
with vis.lock: # this could be from separate thread!
|
||||
#if stream_vis is None:
|
||||
# utils.debug_log('stream_vis not specified in VisBase.write')
|
||||
# stream_vis = next(iter(vis._stream_vises.values())) # use first as default
|
||||
utils.debug_log("Stream received: {}".format(stream_item.stream_name), verbosity=5)
|
||||
stream_vis._pending_items.put(stream_item)
|
||||
|
||||
# if we accumulated enough of pending items then let's process them
|
||||
if vis._can_update_stream_plots():
|
||||
vis._update_stream_plots()
|
||||
|
||||
def _extract_results(self, stream_vis):
|
||||
stream_items, clear_current, clear_history = [], False, False
|
||||
while not stream_vis._pending_items.empty():
|
||||
stream_item = stream_vis._pending_items.get()
|
||||
if stream_item.stream_reset:
|
||||
utils.debug_log("Stream reset", stream_item.stream_name)
|
||||
stream_items.clear() # no need to process these events
|
||||
clear_current, clear_history = True, True
|
||||
else:
|
||||
# check if there was an exception
|
||||
if stream_item.exception is not None:
|
||||
#TODO: need better handling here?
|
||||
print(stream_item.exception, file=sys.stderr)
|
||||
raise stream_item.exception
|
||||
|
||||
# state management for _clear_pending
|
||||
# if we need to clear plot before putting in data, do so
|
||||
if stream_vis._clear_pending:
|
||||
stream_items.clear()
|
||||
clear_current = True
|
||||
stream_vis._clear_pending = False
|
||||
if stream_vis.clear_after_each or (stream_item.ended and stream_vis.clear_after_end):
|
||||
stream_vis._clear_pending = True
|
||||
|
||||
stream_items.append(stream_item)
|
||||
|
||||
return stream_items, clear_current, clear_history
|
||||
|
||||
def _extract_vals(self, stream_items):
|
||||
vals = []
|
||||
for stream_item in stream_items:
|
||||
if stream_item.ended or stream_item.value is None:
|
||||
pass # no values to add
|
||||
else:
|
||||
if utils.is_array_like(stream_item.value, tuple_is_array=False):
|
||||
vals.extend(stream_item.value)
|
||||
else:
|
||||
vals.append(stream_item.value)
|
||||
return vals
|
||||
|
||||
@abstractmethod
|
||||
def clear_plot(self, stream_vis, clear_history):
|
||||
"""(for derived class) Clears the data in specified plot before new data is redrawn"""
|
||||
pass
|
||||
@abstractmethod
|
||||
def _show_stream_items(self, stream_vis, stream_items):
|
||||
"""Paint the given stream_items in to visualizer. If visualizer is dirty then return False else True.
|
||||
"""
|
||||
|
||||
pass
|
||||
@abstractmethod
|
||||
def _post_add_subscription(self, stream_vis, **stream_vis_args):
|
||||
pass
|
||||
|
||||
# typically we want to batch up items for performance
|
||||
def _can_update_stream_plots(self):
|
||||
return True
|
||||
|
||||
@abstractmethod
|
||||
def _post_update_stream_plot(self, stream_vis):
|
||||
pass
|
||||
|
||||
def _update_stream_plots(self):
|
||||
with self.lock:
|
||||
self.q_last_processed = time.time()
|
||||
for stream_vis in self._stream_vises.values():
|
||||
stream_items, clear_current, clear_history = self._extract_results(stream_vis)
|
||||
|
||||
if clear_current:
|
||||
self.clear_plot(stream_vis, clear_history)
|
||||
|
||||
# if we have something to render
|
||||
dirty = not self._show_stream_items(stream_vis, stream_items)
|
||||
if dirty:
|
||||
self._post_update_stream_plot(stream_vis)
|
||||
stream_vis.last_update = time.time()
|
||||
|
||||
@abstractmethod
|
||||
def _show_widget_native(self, blocking:bool):
|
||||
pass
|
||||
@abstractmethod
|
||||
def _show_widget_notebook(self):
|
||||
pass
|
||||
def _save_widget(self, filepath:str)->None:
|
||||
raise NotImplementedError('Save functionality is not implemented')
|
||||
|
|
@ -1,88 +1,91 @@
|
|||
# Copyright (c) Microsoft Corporation.
|
||||
# Licensed under the MIT license.
|
||||
|
||||
from .stream import Stream
|
||||
from .vis_base import VisBase
|
||||
from . import mpl
|
||||
from . import plotly
|
||||
|
||||
class Visualizer:
|
||||
"""Constructs visualizer for specified vis_type.
|
||||
|
||||
NOTE: If you modify arguments here then also sync VisArgs contructor.
|
||||
"""
|
||||
def __init__(self, stream:Stream, vis_type:str=None, host:'Visualizer'=None,
|
||||
cell:'Visualizer'=None, title:str=None,
|
||||
clear_after_end=False, clear_after_each=False, history_len=1, dim_history=True, opacity=None,
|
||||
|
||||
rows=2, cols=5, img_width=None, img_height=None, img_channels=None,
|
||||
colormap=None, viz_img_scale=None,
|
||||
|
||||
# these image params are for hover on point for t-sne
|
||||
hover_images=None, hover_image_reshape=None, cell_width:str=None, cell_height:str=None,
|
||||
|
||||
only_summary=False, separate_yaxis=True, xtitle=None, ytitle=None, ztitle=None, color=None,
|
||||
xrange=None, yrange=None, zrange=None, draw_line=True, draw_marker=False,
|
||||
|
||||
# histogram
|
||||
bins=None, normed=None, histtype='bar', edge_color=None, linewidth=None, bar_width=None,
|
||||
|
||||
# pie chart
|
||||
autopct=None, shadow=None,
|
||||
|
||||
vis_args={}, stream_vis_args={})->None:
|
||||
|
||||
cell = cell._host_base.cell if cell is not None else None
|
||||
|
||||
if host:
|
||||
self._host_base = host._host_base
|
||||
else:
|
||||
self._host_base = self._get_vis_base(vis_type, cell, title, hover_images=hover_images, hover_image_reshape=hover_image_reshape,
|
||||
cell_width=cell_width, cell_height=cell_height,
|
||||
**vis_args)
|
||||
|
||||
self._host_base.subscribe(stream, show=False, clear_after_end=clear_after_end, clear_after_each=clear_after_each,
|
||||
history_len=history_len, dim_history=dim_history, opacity=opacity,
|
||||
only_summary=only_summary if vis_type is None or 'summary' != vis_type else True,
|
||||
separate_yaxis=separate_yaxis, xtitle=xtitle, ytitle=ytitle, ztitle=ztitle, color=color,
|
||||
xrange=xrange, yrange=yrange, zrange=zrange,
|
||||
draw_line=draw_line if vis_type is not None and 'scatter' in vis_type else True,
|
||||
draw_marker=draw_marker,
|
||||
rows=rows, cols=cols, img_width=img_width, img_height=img_height, img_channels=img_channels,
|
||||
colormap=colormap, viz_img_scale=viz_img_scale,
|
||||
bins=bins, normed=normed, histtype=histtype, edge_color=edge_color, linewidth=linewidth, bar_width = bar_width,
|
||||
autopct=autopct, shadow=shadow,
|
||||
**stream_vis_args)
|
||||
|
||||
stream.load()
|
||||
|
||||
def show(self):
|
||||
return self._host_base.show()
|
||||
|
||||
def _get_vis_base(self, vis_type, cell:VisBase.widgets.Box, title, hover_images=None, hover_image_reshape=None, cell_width=None, cell_height=None, **vis_args)->VisBase:
|
||||
if vis_type is None or vis_type in ['line',
|
||||
'mpl-line', 'mpl-line3d', 'mpl-scatter3d', 'mpl-scatter']:
|
||||
return mpl.line_plot.LinePlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height,
|
||||
is_3d=vis_type is not None and vis_type.endswith('3d'), **vis_args)
|
||||
if vis_type in ['image', 'mpl-image']:
|
||||
return mpl.image_plot.ImagePlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height, **vis_args)
|
||||
if vis_type in ['bar', 'bar3d']:
|
||||
return mpl.bar_plot.BarPlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height,
|
||||
is_3d=vis_type.endswith('3d'), **vis_args)
|
||||
if vis_type in ['histogram']:
|
||||
return mpl.histogram.Histogram(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height, **vis_args)
|
||||
if vis_type in ['pie']:
|
||||
return mpl.pie_chart.PieChart(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height, **vis_args)
|
||||
if vis_type in ['text', 'summary']:
|
||||
from .text_vis import TextVis
|
||||
return TextVis(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height, **vis_args)
|
||||
if vis_type in ['line3d', 'scatter', 'scatter3d',
|
||||
'plotly-line', 'plotly-line3d', 'plotly-scatter', 'plotly-scatter3d', 'mesh3d']:
|
||||
return plotly.line_plot.LinePlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height,
|
||||
is_3d=vis_type.endswith('3d'), **vis_args)
|
||||
if vis_type in ['tsne', 'embeddings', 'tsne2d', 'embeddings2d']:
|
||||
return plotly.embeddings_plot.EmbeddingsPlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height,
|
||||
is_3d='2d' not in vis_type,
|
||||
hover_images=hover_images, hover_image_reshape=hover_image_reshape, **vis_args)
|
||||
else:
|
||||
raise ValueError('Render vis_type parameter has invalid value: "{}"'.format(vis_type))
|
||||
# Copyright (c) Microsoft Corporation.
|
||||
# Licensed under the MIT license.
|
||||
|
||||
from .stream import Stream
|
||||
from .vis_base import VisBase
|
||||
from . import mpl
|
||||
from . import plotly
|
||||
|
||||
class Visualizer:
|
||||
"""Constructs visualizer for specified vis_type.
|
||||
|
||||
NOTE: If you modify arguments here then also sync VisArgs contructor.
|
||||
"""
|
||||
def __init__(self, stream:Stream, vis_type:str=None, host:'Visualizer'=None,
|
||||
cell:'Visualizer'=None, title:str=None,
|
||||
clear_after_end=False, clear_after_each=False, history_len=1, dim_history=True, opacity=None,
|
||||
|
||||
rows=2, cols=5, img_width=None, img_height=None, img_channels=None,
|
||||
colormap=None, viz_img_scale=None,
|
||||
|
||||
# these image params are for hover on point for t-sne
|
||||
hover_images=None, hover_image_reshape=None, cell_width:str=None, cell_height:str=None,
|
||||
|
||||
only_summary=False, separate_yaxis=True, xtitle=None, ytitle=None, ztitle=None, color=None,
|
||||
xrange=None, yrange=None, zrange=None, draw_line=True, draw_marker=False,
|
||||
|
||||
# histogram
|
||||
bins=None, normed=None, histtype='bar', edge_color=None, linewidth=None, bar_width=None,
|
||||
|
||||
# pie chart
|
||||
autopct=None, shadow=None,
|
||||
|
||||
vis_args={}, stream_vis_args={})->None:
|
||||
|
||||
cell = cell._host_base.cell if cell is not None else None
|
||||
|
||||
if host:
|
||||
self._host_base = host._host_base
|
||||
else:
|
||||
self._host_base = self._get_vis_base(vis_type, cell, title, hover_images=hover_images, hover_image_reshape=hover_image_reshape,
|
||||
cell_width=cell_width, cell_height=cell_height,
|
||||
**vis_args)
|
||||
|
||||
self._host_base.subscribe(stream, show=False, clear_after_end=clear_after_end, clear_after_each=clear_after_each,
|
||||
history_len=history_len, dim_history=dim_history, opacity=opacity,
|
||||
only_summary=only_summary if vis_type is None or 'summary' != vis_type else True,
|
||||
separate_yaxis=separate_yaxis, xtitle=xtitle, ytitle=ytitle, ztitle=ztitle, color=color,
|
||||
xrange=xrange, yrange=yrange, zrange=zrange,
|
||||
draw_line=draw_line if vis_type is not None and 'scatter' in vis_type else True,
|
||||
draw_marker=draw_marker,
|
||||
rows=rows, cols=cols, img_width=img_width, img_height=img_height, img_channels=img_channels,
|
||||
colormap=colormap, viz_img_scale=viz_img_scale,
|
||||
bins=bins, normed=normed, histtype=histtype, edge_color=edge_color, linewidth=linewidth, bar_width = bar_width,
|
||||
autopct=autopct, shadow=shadow,
|
||||
**stream_vis_args)
|
||||
|
||||
stream.load()
|
||||
|
||||
def show(self):
|
||||
return self._host_base.show()
|
||||
|
||||
def save(self, filepath:str)->None:
|
||||
self._host_base.save(filepath)
|
||||
|
||||
def _get_vis_base(self, vis_type, cell:VisBase.widgets.Box, title, hover_images=None, hover_image_reshape=None, cell_width=None, cell_height=None, **vis_args)->VisBase:
|
||||
if vis_type is None or vis_type in ['line',
|
||||
'mpl-line', 'mpl-line3d', 'mpl-scatter3d', 'mpl-scatter']:
|
||||
return mpl.line_plot.LinePlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height,
|
||||
is_3d=vis_type is not None and vis_type.endswith('3d'), **vis_args)
|
||||
if vis_type in ['image', 'mpl-image']:
|
||||
return mpl.image_plot.ImagePlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height, **vis_args)
|
||||
if vis_type in ['bar', 'bar3d']:
|
||||
return mpl.bar_plot.BarPlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height,
|
||||
is_3d=vis_type.endswith('3d'), **vis_args)
|
||||
if vis_type in ['histogram']:
|
||||
return mpl.histogram.Histogram(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height, **vis_args)
|
||||
if vis_type in ['pie']:
|
||||
return mpl.pie_chart.PieChart(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height, **vis_args)
|
||||
if vis_type in ['text', 'summary']:
|
||||
from .text_vis import TextVis
|
||||
return TextVis(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height, **vis_args)
|
||||
if vis_type in ['line3d', 'scatter', 'scatter3d',
|
||||
'plotly-line', 'plotly-line3d', 'plotly-scatter', 'plotly-scatter3d', 'mesh3d']:
|
||||
return plotly.line_plot.LinePlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height,
|
||||
is_3d=vis_type.endswith('3d'), **vis_args)
|
||||
if vis_type in ['tsne', 'embeddings', 'tsne2d', 'embeddings2d']:
|
||||
return plotly.embeddings_plot.EmbeddingsPlot(cell=cell, title=title, cell_width=cell_width, cell_height=cell_height,
|
||||
is_3d='2d' not in vis_type,
|
||||
hover_images=hover_images, hover_image_reshape=hover_image_reshape, **vis_args)
|
||||
else:
|
||||
raise ValueError('Render vis_type parameter has invalid value: "{}"'.format(vis_type))
|
||||
|
|
|
|||
|
|
@ -0,0 +1,7 @@
|
|||
import tensorwatch as tw
|
||||
|
||||
stream = tw.ArrayStream([(i, i*i) for i in range(50)])
|
||||
img_plot = tw.Visualizer(stream, vis_type='mpl-line', viz_img_scale=3, xtitle='Epochs', ytitle='Gain')
|
||||
# img_plot.show()
|
||||
# tw.plt_loop()
|
||||
img_plot.save(r'c:\temp\fig1.png')
|
||||
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Ссылка в новой задаче