python - 带有灰度数据的 Enthought Canopy Chaco img_plot

Question

我终于开始尝试 Chaco，所以这个问题可能很天真。目前，我正在尝试绘制类型为 numpy.uint8 的非常大的 8 位(也称为灰度或单 channel )图像。似乎无论我做什么，图像都是彩色的。这是我基于 Chaco 附带的 image_plot.py 示例的代码:

#!/usr/bin/env python
"""
Draws an simple RGB image
 - Left-drag pans the plot.
 - Mousewheel up and down zooms the plot in and out.
 - Pressing "z" brings up the Zoom Box, and you can click-drag a rectangular
   region to zoom.  If you use a sequence of zoom boxes, pressing alt-left-arrow
   and alt-right-arrow moves you forwards and backwards through the "zoom
   history".
"""

# Major library imports
from numpy import zeros, uint8



# Enthought library imports
from enable.api import Component, ComponentEditor
from traits.api import HasTraits, Instance
from traitsui.api import Item, Group, View

# Chaco imports
from chaco.api import ArrayPlotData, Plot, ImageData
from chaco.tools.api import PanTool, ZoomTool
from chaco.tools.image_inspector_tool import ImageInspectorTool, \
     ImageInspectorOverlay

#===============================================================================
# # Create the Chaco plot.
#===============================================================================
def _create_plot_component():

    # Create some uint8 image data
    imageSize = 10000
    image = zeros((imageSize,imageSize), dtype=uint8)
    for x in range(0,imageSize):
        image[x,x] = 255

    print image.shape
    print type(image[0][0])

    # Create a plot data obect and give it this data
    pd = ArrayPlotData()
    pd.set_data("imagedata", image)

    # Create the plot
    plot = Plot(pd, default_origin="top left")
    plot.x_axis.orientation = "top"
    img_plot = plot.img_plot("imagedata")[0]

    # Tweak some of the plot properties
    plot.bgcolor = "white"

    # Attach some tools to the plot
    plot.tools.append(PanTool(plot, constrain_key="shift"))
    plot.overlays.append(ZoomTool(component=plot,
                                    tool_mode="box", always_on=False))

    # imgtool = ImageInspectorTool(img_plot)
    # img_plot.tools.append(imgtool)
    # plot.overlays.append(ImageInspectorOverlay(component=img_plot,
    #                                            image_inspector=imgtool))
    return plot

#===============================================================================
# Attributes to use for the plot view.
size = (600, 600)
title="Simple image plot"
bg_color="lightgray"

#===============================================================================
# # Demo class that is used by the demo.py application.
#===============================================================================
class Demo(HasTraits):
    plot = Instance(Component)

    traits_view = View(
                    Group(
                        Item('plot', editor=ComponentEditor(size=size,
                                                            bgcolor=bg_color),
                             show_label=False),
                        orientation = "vertical"),
                    resizable=True, title=title
                    )

    def _plot_default(self):
         return _create_plot_component()

demo = Demo()

if __name__ == "__main__":
    demo.configure_traits()

#--EOF---

Answer 1

您看到的只是伪彩色:2D 图像需要通过某种方式从像素值变为“颜色”(在这种情况下，灰度仍然是彩色)。默认颜色图是彩色的，但您可以指定 colormap 关键字参数来获取灰度图像。这是一个简化的示例:

import numpy as np

from enable.api import Component, ComponentEditor
from traits.api import HasTraits, Instance
from traitsui.api import UItem, View

from chaco.api import ArrayPlotData, Plot, gray


class Demo(HasTraits):

    plot = Instance(Component)

    traits_view = View(
        UItem('plot', editor=ComponentEditor(size=(600, 600))),
        resizable=True, title="Simple image plot"
    )

    def _plot_default(self):
        image = np.random.random_integers(0, 255, size=(100, 100))
        image = image.astype(np.uint8)
        data = ArrayPlotData(imagedata=image)

        plot = Plot(data, default_origin="top left")
        plot.img_plot("imagedata", colormap=gray)
        return plot


demo = Demo()
demo.configure_traits()