On Fri, Dec 11, 2009 at 2:34 PM, Ryan Neve <[email protected]> wrote:
> Thank you for your help. I found the problem. It was caused by using
> pyplot.title(). It is working better now.
> I next have to figure out how to do the following within AxesGrid:
>
> 1. How to convert the x axis labels from an integer value representing
> epoch seconds to a nicely formatted date. I think this has something to do
> with matplotlib.dates.DateFormatter. I hope that this will remove the
> 1.25325e9 from the plot.
>
> 2. How to minimize or eliminate the white bands on the right and bottom
> of each axes caused by the axis scale exceeding the data values.
>
> 3. How to eliminate (or hide) the first major tic label on the y axis
> (always 0) so it doesn't overlap with the last tick from the previous y
> axis.
>
> It seems like there may be a different way to approach this than with
> subplot()
>
While there are certain differences, most of the usual matplotlib command
supposed to work. So, I recommend you to read the matplotlib documentation
first.
1. There are lots of examples in the gallery. Please take a look.
2. see the code below.
3. this kind of thing is difficult to do with axes_grid toolkit. but see
below.
First, you need to change the x-values to date (not seconds).
Then, add the code below inside your for loop.
Other than ax.axis["bottom"].. thing, these are just normal matplotlib
command.
Also, I should have mentioned it earlier, but I don't see any need of
axes_grid toolkit in your code. You'd better simply use subplot, which is
recommended if you're not familiar with matplotlib.
Regards,
-JJ
ax = my_grid[i]
ax.autoscale_view(tight=True) # adjust xlim and ylim
# you can manually call ax.set_xlim and ax.set_ylim.
ax.xaxis_date() # tick format as date and time
ax.axis["bottom"].major_ticklabels.set_rotation(30)
ax.axis["bottom"].major_ticklabels.set_ha("right")
ax.axis["bottom"].major_ticklabels.set_va("top")
# with axes_grid toolkit, it is difficult to make a certain
# ticklabel invisible (without disabling the tick line). The
# below line of code slightly adjust the ylim so that y=0 ticks
# are not shown
ax.set_ylim(ymax=-0.001)
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