axis & grid tick interval issue

[fred4ets]

Running the following complete minimal example (from cmap_image_plot.py) with arg t >= 20 shows the trick: the x axis tick interval (every 2 h) does not match the x grid tick interval (every 3 h):

#!/usr/bin/env python3
"""
Draws a colormapped image plot
 - 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 exp, linspace, meshgrid
from sys import argv
# 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, viridis, Plot
from chaco.tools.api import PanTool, ZoomTool

from chaco.scales.api import CalendarScaleSystem, ScaleSystem
from chaco.scales.time_scale import HMSScales, MDYScales
from chaco.scales_tick_generator import ScalesTickGenerator

# ===============================================================================
# # Create the Chaco plot.
# ===============================================================================
def _create_plot_component():
    # Create a scalar field to colormap
    t = int(argv[1])
    xs = linspace(0, t*3600, 600) - 3600
    ys = linspace(0, 5, 600)
    x, y = meshgrid(xs, ys)
    z = exp(-((x/xs.max()) ** 2 + y ** 2) / 100)

    # Create a plot data object 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=(xs.min(), xs.max()),
        ybounds=(0, 5),
        colormap=viridis
    )[0]

    xgrid, ygrid, xaxis, yaxis = plot.underlays
    print([a.orientation for a in plot.underlays])
    xgrid.tick_generator = ScalesTickGenerator(scale=CalendarScaleSystem(scales=HMSScales))
    xgrid.visible = True
    xaxis.tick_generator = ScalesTickGenerator(scale=CalendarScaleSystem(scales=HMSScales))
      ygrid.visible = xgrid.visible
    xgrid.line_color = ygrid.line_color = (0, 0, 0)

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

    return plot


# ===============================================================================
# Attributes to use for the plot view.
size = (1200, 800)
title = "Basic Colormapped Image Plot"

# ===============================================================================
# # 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), 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()```

Any idea?