Wow - thanks for the detailed update. I feel bad for making you type that much :)
Thanks for fixing that problem. Ted > -----Original Message----- > From: John Hunter [mailto:jdh2...@gmail.com] > Sent: Sunday, September 20, 2009 7:35 PM > To: Drain, Theodore R (343P) > Cc: Andrew Straw; matplotlib development list > Subject: Re: [matplotlib-devel] empty date formatter unit tests > > On Sun, Sep 20, 2009 at 6:50 PM, Drain, Theodore R (343P) > <theodore.r.dr...@jpl.nasa.gov> wrote: > > > I've run into this problem quite a few times and I'd love to figure > out some way to fix it. As an example, here's the kind of scenario > this occurs in: > > > > I embed MPL in a few different GUI's that plot data either in real- > time or via the user selecting things. There is a saved state which > contains preferences like auto-scaling, legend on/off, axis formatting, > etc. When the app starts up, I need to create a plot to put on the > screen and configure it. What I'd like to do is this: > > > > - create widget > > - apply format (date formatter, etc) > > - apply settings (autoscale, etc) > > - wait for data (either via real time feed or user clicking on > things) > > > > But this is impossible because of this kind of bug. Instead, I have > to create a plot with a fake date range and test every operation to see > if it's actually setting data before applying the settings like > autoscale. In addition, if the user removes data from the plot (via > menu or selectable lists), I have to either start over or "unset" the > settings back to something safe so this error won't occur. It really > makes coding something like this a royal pain. > > > > I don't have a suggestion as of yet... Perhaps it could just return > "N/A" or something like that. > > > > I think part of the problem might be the default ranges used by the > autoscaling algorithm when there is no data are invalid for certain > formatters and locators. That suggests that possible solutions might be > one of: > > > > 1) require autoscaling or scaling algorithms to return ranges that > will be OK for known scalers/formatters. Perhaps some system that > allows different autoscaling algorithms to be set which can configure > the default? > > 2) require scalers/formatters to be robust for any range or engineer > the system to allow them to report "errors" in a way that allows the > plot do something reasonable and not trigger an exception (perhaps some > changeable behavior w/ the default as an exception?). > > > > I'll think about this a little this week and see if any other ideas > come to mind. > > I think we have this problem mostly licked. The problem I was writing > about in my email is a 2nd tier problem. For example, in svn HEAD, > you can specify an "empty" date plot as long as you inform mpl of you > intentions.. From the test_date_empty unit test:: > > fig = plt.figure() > ax = fig.add_subplot(1,1,1) > ax.xaxis_date() > fig.savefig('date_empty') > > Here we are fine, because we call ax.axaxis_date, which informs mpl > that you intend to pass in datetime instances. The key piece which > makes this possible, which you allude to in your post, is the default > xlimits, which is new in svn HEAD. In particular, the default > converter provides an AxisInfo which now supports an optional > attribute > > default_limits: the default min, max of the axis if no data is > present > > which is overridden in the DateConverter: > > def axisinfo(unit, axis): > 'return the unit AxisInfo' > # make sure that the axis does not start at 0 > > majloc = AutoDateLocator(tz=unit) > majfmt = AutoDateFormatter(majloc, tz=unit) > datemin = datetime.date(2000, 1, 1) > datemax = datetime.date(2010, 1, 1) > > return units.AxisInfo( majloc=majloc, majfmt=majfmt, label='', > default_limits=(datemin, datemax)) > > > while the min/max are arbitrary, the important thing is that custom > types can now handle the default min/max limits, so when you present a > new type to mpl, the type can request a certain default view/data lim > if no data are presented. Additionally, because of the > "ignore"setting on the limts argument, we can detect whether the > limits we are applying are defaults or actively set by the user. > > The complication that motivated the sf bug > http://sourceforge.net/tracker/?func=detail&aid=2861426&group_id=80706&; > atid=560720 > is a bit more subtle. Here no data type is presented to mpl -- either > through "plot" or "fill" or "set_xlim" or whatever. If the user had > passed any data in, or manually expressed their intent through > "ax.xaxis_date" we would be fine. The difficulty is that they passed > no data in but declared their intention to use a "YearFormatter". My > original inclination, and the one that failed the unit tests, was to > trigger a call to Axis.axis_date (a new method) on a call to > ax.xaxis.set_major_formatter (or locator) where the argument was a > DateLocator or DateFormatter. This seemed to be an imminently > reasonable and helpful thing to do -- if they want a date locator or > formatter presumably they will be passing in dates -- but the unit > tests told me this was wrong. > > The locators and formatters work on *converted* units. The > EpochConverter and DateConverter both convert their native types to > floating point days since 0000-00-00. So here are two custom > converter interfaces which both end up with the same floating point > representation. The conclusion is: mpl cannot use the > locator/formatter type to infer what the basic type that users will be > passing in. Just because two classes end up with the same floating > point representation does not indicate that they want the same > conversion pipeline from type -> float. > > Nonetheless, we can, and already do in svn HEAD, handle the cases that > I think you are worried about in this email. As long as you know what > type you will be passing into mpl (regardless of whether you have any > data available right now) you can inform the units interface with > > ax.xaxis.update_units(someval) > > where someval is an instance of the type you plan to pass in. Doing > so will not affect your current data or view limits, but will trigger > the conversion interface and importantly will trigger the > units.AxisInfo.default_limits scaling which was recently added to > avoid the kinds of problems we have been seeing with date conversion > when no data is passed in. > > > So despite this long winded email, the current infrastructure should > support > > * create axes, etc > > * set your current formatter/locator > > * ax.xaxis.update_units(myInstance) > > where myInstance is an object of the type you expect to pass in. As > long as you have registered a converter from type(myInstance) -> > ConversionInterface, you can now specify the default limits through > the ConversionInterface.default_limits method:: > > @staticmethod > def default_units(x, axis): > 'return the default unit for x or None for the given axis' > return None > > > As an example in matplotlib.dates, we choose an arbitrary interval, > which while arbitrary avoids the 0..1 problem we have been having:: > > class DateConverter(units.ConversionInterface): > """The units are equivalent to the timezone.""" > > @staticmethod > def axisinfo(unit, axis): > 'return the unit AxisInfo' > # make sure that the axis does not start at 0 > > majloc = AutoDateLocator(tz=unit) > majfmt = AutoDateFormatter(majloc, tz=unit) > datemin = datetime.date(2000, 1, 1) > datemax = datetime.date(2010, 1, 1) > > return units.AxisInfo( majloc=majloc, majfmt=majfmt, label='', > default_limits=(datemin, datemax)) > > JDH > > No virus found in this incoming message. > Checked by AVG - www.avg.com > Version: 8.5.409 / Virus Database: 270.13.110/2385 - Release Date: > 09/20/09 17:51:00 ------------------------------------------------------------------------------ Come build with us! 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