例如，在chaco / examples / demo / basic / image_inspector.py中，如何设置缩放系数，使1个阵列点对应1个屏幕像素（100％缩放）。似乎ZoomTool方法（zoom_in，zoom_out，...）仅处理缩放系数变化，而不是绝对因子设置。
答案 0 :(得分：1)
我会尝试使用plot.range2d.low，plot.range2d.high和plot.outer_bounds。前两个涉及数据空间，而后者涉及图像区域的大小。通过使用图片区域设置数据空间的限制，您可以将1个像素映射到1个数据单元。这是一个例子，有趣的位在_zoom_100_percent方法中：
import numpy as np
from chaco.api import Plot, ArrayPlotData
from chaco.tools.api import PanTool, ZoomTool
from enable.api import ComponentEditor
from traits.api import Button, HasTraits, Instance, on_trait_change
from traitsui.api import Item, View
class HundredPercentZoom(HasTraits):
plot = Instance(Plot)
zoom_button = Button('100% Zoom')
traits_view = View(
Item('plot', editor=ComponentEditor(), show_label=False),
'zoom_button',
width=800,
height=600,
)
def _plot_default(self):
t = np.linspace(0, 1000, 200)
y = 400 * (np.sin(t) + 0.1 * np.sin(t * 100))
plot = Plot(ArrayPlotData(t=t, y=y))
plot.plot(('t', 'y'))
plot.tools.append(PanTool(plot))
plot.tools.append(ZoomTool(plot))
return plot
@on_trait_change('zoom_button')
def _zoom_100_percent(self):
low = self.plot.range2d.low
bounds = self.plot.outer_bounds
print(bounds)
self.plot.range2d.high = (low[0] + bounds[0], low[1] + bounds[1])
if __name__ == "__main__":
hpz = HundredPercentZoom()
hpz.configure_traits()
我在那里添加了print语句，因此您可以看到绘图区域与窗口区域不同，即800x600。我还添加了一个PanTool和ZoomTool，因此您可以在放大后进行平移。只要您的绘图具有ZoomTool，您就可以使用Escape键返回原始缩放状态。
答案 1 :(得分：0)
我已经到达的解决方案，从原始示例image_inspector.py开始。按钮允许在选择作为缩放中心的点周围具有100％缩放系数。
所有内容都在Demo课程中的 _btn_fired 方法中。
可能仍然存在1没有被减去或添加到某些界限或限制的问题，因为按钮操作不是严格意义上的（第二次按下不应该做任何事情）。
更简单吗？
#!/usr/bin/env python
"""
Demonstrates the ImageInspectorTool and overlay on a colormapped image
plot. The underlying plot is similar to the one in cmap_image_plot.py.
- 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".
- Pressing "p" will toggle the display of the image inspector overlay.
"""
# Major library imports
from numpy import linspace, meshgrid, pi, sin, divide, multiply
# Enthought library imports
from enable.api import Component, ComponentEditor
from traits.api import HasTraits, Instance, Button, Float
from traitsui.api import Item, Group, View, HGroup
# Chaco imports
from chaco.api import ArrayPlotData, jet, Plot
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 a scalar field to colormap
xbounds = (-2*pi, 2*pi, 600)
ybounds = (-1.5*pi, 1.5*pi, 300)
xs = linspace(*xbounds)
ys = linspace(*ybounds)
x, y = meshgrid(xs,ys)
z = sin(x)*y
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("imagedata", z)
# Create the plot
plot = Plot(pd)
img_plot = plot.img_plot("imagedata",
xbounds = xbounds[:2],
ybounds = ybounds[:2],
colormap=jet)[0]
# Tweak some of the plot properties
plot.title = "My First Image Plot"
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
imgtool = ImageInspectorTool(img_plot)
img_plot.tools.append(imgtool)
overlay = ImageInspectorOverlay(component=img_plot, image_inspector=imgtool,
bgcolor="white", border_visible=True)
img_plot.overlays.append(overlay)
return plot
#===============================================================================
# Attributes to use for the plot view.
size = (800, 600)
title="Inspecting a Colormapped Image Plot"
#===============================================================================
# # Demo class that is used by the demo.py application.
#===============================================================================
class Demo(HasTraits):
plot = Instance(Component)
center_x = Float
center_y = Float
btn = Button('100 %')
def _btn_fired(self):
img_plot, = self.plot.plots['plot0']
zoom_center = (self.center_x, self.center_y)
# Size of plot in screen pixels
plot_size = img_plot.bounds
# Zoom center in screen space
zoom_center_screen, = img_plot.map_screen(zoom_center)
# Get actual bounds in data space
low, high = (img_plot.index_mapper.range.low,
img_plot.index_mapper.range.high)
# Get data space x and y units in terms of x and y array indices
sizes = [item.get_size() for item in img_plot.index.get_data()]
(min_x, min_y), (max_x, max_y) = img_plot.index.get_bounds()
unit = divide((max_x - min_x, max_y - min_y), sizes)
# Calculate new bounds
new_low = zoom_center - multiply(zoom_center_screen, unit)
new_high = new_low + multiply(plot_size, unit)
# Set new bounds
img_plot.index_mapper.range.set_bounds(new_low,new_high)
traits_view = View(
Group(
Item('plot', editor=ComponentEditor(size=size),
show_label=False),
HGroup('center_x', 'center_y', 'btn'),
orientation = "vertical"
),
resizable=True, title=title
)
def _plot_default(self):
return _create_plot_component()
demo = Demo()
if __name__ == "__main__":
demo.configure_traits()