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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
476310400 https://github.com/pydata/xarray/issues/2848#issuecomment-476310400 https://api.github.com/repos/pydata/xarray/issues/2848 MDEyOklzc3VlQ29tbWVudDQ3NjMxMDQwMA== efiring 85125 2019-03-25T17:54:32Z 2019-03-25T17:54:32Z NONE

One possibility would be for the decode_times kwarg to accept a string 'warn' argument to select the new behavior.

 
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   When decode_times fails, warn rather than failing 424545013
269561745 https://github.com/pydata/xarray/pull/1171#issuecomment-269561745 https://api.github.com/repos/pydata/xarray/issues/1171 MDEyOklzc3VlQ29tbWVudDI2OTU2MTc0NQ== efiring 85125 2016-12-29T00:09:27Z 2016-12-29T00:09:27Z NONE

It looks like what you are trying to do here is analogous to the way contour levels are chosen in matplotlib's contourf. 

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   Fix tests for upcoming matplotlib v2 196278181
269561494 https://github.com/pydata/xarray/pull/1171#issuecomment-269561494 https://api.github.com/repos/pydata/xarray/issues/1171 MDEyOklzc3VlQ29tbWVudDI2OTU2MTQ5NA== efiring 85125 2016-12-29T00:05:47Z 2016-12-29T00:05:47Z NONE

With a vmax-vmin of 4, it is using an increment of 0.6, for a span of 4.2. In other words, vmax-vmin < 7 * 0.6, and 0.6 is the smallest available increment for which this is true. This is the intended behavior; so yes, the algorithm can return up to N+2 ticks, not just N+1.

 
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   Fix tests for upcoming matplotlib v2 196278181
269553467 https://github.com/pydata/xarray/pull/1171#issuecomment-269553467 https://api.github.com/repos/pydata/xarray/issues/1171 MDEyOklzc3VlQ29tbWVudDI2OTU1MzQ2Nw== efiring 85125 2016-12-28T22:45:26Z 2016-12-28T22:45:26Z NONE

It's not a bug in the code. The purpose of a Locator is to find "nice" values for ticks. It is used in two related ways: to determine the axis limits when the pre-2.0 default of "round numbers" (meaning "landing on ticks") is use, and to find the tick locations themselves. Supporting the former application requires generating ticks beyond the specified limits; then later in the plotting process, the excess ticks might be used, or they might be trimmed off, depending on how the axis limits are determined. In no case is it intended that ticks land on specified vmin and/or vmax values, though it can happen by chance if they are "nice" numbers.

In the case of the MaxNLocator, the "N" refers to intervals, not ticks; that is, in "round-number" axis limit mode, or if vmin and vmax otherwise land on ticks, there can be N+1 ticks. (This is in the docstring; and the argument is called "nbins", not "nticks".) 

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   Fix tests for upcoming matplotlib v2 196278181

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