issues

What happened:

When using xarray.DataArray.plot.pcolormesh with yscale="log" the output figure distorts the y axis and thus doesn't plot the data correctly. I think the problem is related to the inference of the intervals through the xarray.plot.utils._infer_intervals_breaks() function.

What you expected to happen:

I expect the yscale="log" argument to correctly display the y axis in a logscale while precisley plotting the data. In my opinion, the inference of the intervals for the pcolormesh should be also done in log scales.

Minimal Complete Verifiable Example:

```python import numpy as np import xarray as xr import matplotlib.pyplot as plt

x = np.linspace(-3, 4, 15) y = np.logspace(-4, 3, 8)

xx, yy = np.meshgrid(x, y) z = np.exp(-(xx ** 2) - np.log10(yy) ** 2) - np.exp( -((xx - 1) ** 2) - (np.log10(yy) - 1) ** 2 )

da = xr.DataArray( z, coords={"x": x, "y": y}, dims=("y", "x"), )

da.plot(yscale="log") plt.show()

```

Output:

Anything else we need to know?:

I pass infer_intervals=False I get a plot that looks more to the expected one:

```python import numpy as np import xarray as xr import matplotlib.pyplot as plt

x = np.linspace(-3, 4, 15) y = np.logspace(-4, 3, 8)

xx, yy = np.meshgrid(x, y) z = np.exp(-(xx ** 2) - np.log10(yy) ** 2) - np.exp( -((xx - 1) ** 2) - (np.log10(yy) - 1) ** 2 )

da = xr.DataArray( z, coords={"x": x, "y": y}, dims=("y", "x"), )

da.plot(yscale="log", infer_intervals=False) plt.show()

```

The problem with deactivating the infer_intervals is that matplotlib crops the last row and column of the 2d grid, because we would be selectingshading="flat", getting the following deprecation warning from matplotlib: /home/santi/git/xarray/xarray/plot/plot.py:1033: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3. Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading']. This will become an error two minor releases later. primitive = ax.pcolormesh(x, y, z, **kwargs)

That's why I think that the inference of the breaks should also be done in log scales.

Environment:

Problem Description

When using xarray.open_rasterio for loading the Bedmap2 dataset from geoTIFF files we are getting an ImportError after xarray tries to import gdal_version from rasterio._base. The error is raised after uploading rasterio to 1.0.25. When using rasterio 1.0.24, the problem does not exist.

This error was caught by @ChetGoerzen and originally reported on https://github.com/fatiando/rockhound/issues/53.

python import xarray as xr xr.open_rasterio("bedmap2_bed.tif") python-traceback Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/santi/.miniconda3/envs/rockhound/lib/python3.7/site-packages/xarray/backends/rasterio_.py", line 214, in open_rasterio import rasterio File "/home/santi/.miniconda3/envs/rockhound/lib/python3.7/site-packages/rasterio/__init__.py", line 22, in <module> from rasterio._base import gdal_version ImportError: libtiledb.so.1.6.0: cannot open shared object file: No such file or directory

Expected Output

python-traceback <xarray.DataArray (band: 1, y: 6667, x: 6667)> [44448889 values with dtype=int16] Coordinates: * band (band) int64 1 * y (y) float64 3.333e+06 3.332e+06 3.331e+06 ... -3.332e+06 -3.333e+06 * x (x) float64 -3.333e+06 -3.332e+06 ... 3.332e+06 3.333e+06 Attributes: transform: (1000.0, 0.0, -3333500.0, 0.0, -1000.0, 3333500.0) crs: +init=epsg:3031 res: (1000.0, 1000.0) is_tiled: 1 nodatavals: (32767.0,) scales: (1.0,) offsets: (0.0,)

Output of xr.show_versions()

Output of conda list