[Bug]: Address warnings produced during diagnostic run and integration test suite (latest `main`)

[tomvothecoder]

What happened?

Warning 1 -- xgcm.grid.py -- related to xCDAT/xcdat#513, can't address this one directly

2025-02-04 15:06:12,956 [WARNING]: warnings.py(_showwarnmsg:112) >> /home/ac.tvo/miniforge3/envs/e3sm_diags_dev_930/lib/python3.12/site-packages/xgcm/grid.py:989: FutureWarning: From version 0.8.0 the Axis computation methods will be removed, in favour of using the Grid computation methods instead. i.e. use `Grid.transform` instead of `Axis.transform`
  warnings.warn(

Warning 2 -- cartopy.mpl.geoaxes.py

2025-02-04 15:06:22,608 [WARNING]: warnings.py(_showwarnmsg:112) >> /home/ac.tvo/miniforge3/envs/e3sm_diags_dev_930/lib/python3.12/site-packages/cartopy/mpl/geoaxes.py:856: UserWarning: Attempting to set identical low and high xlims makes transformation singular; automatically expanding.
  self.set_xlim([x1, x2])

Warning 3 -- plot.taylor_diagram.py

2025-02-04 15:19:16,672 [WARNING]: warnings.py(_showwarnmsg:112) >> /gpfs/fs1/home/ac.tvo/E3SM-Project/e3sm_diags/e3sm_diags/plot/taylor_diagram.py:94: UserWarning: No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
  ax.legend(loc="center left", bbox_to_anchor=(1, 0.5))

Integration Test Suite Warnings

 =============================== warnings summary ===============================
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  <frozen importlib._bootstrap>:228: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility. Expected 16 from C header, got 96 from PyObject

tests/integration/test_all_sets_image_diffs.py: 13 warnings
  /__w/e3sm_diags/e3sm_diags/3/envs/e3sm_diags_ci/lib/python3.9/site-packages/xgcm/grid.py:1283: DeprecationWarning: The `xgcm.Axis` class will be deprecated in the future. Please make sure to use the `xgcm.Grid` methods for your work instead.
    warnings.warn(

tests/integration/test_all_sets_image_diffs.py: 13 warnings
  /__w/e3sm_diags/e3sm_diags/3/envs/e3sm_diags_ci/lib/python3.9/site-packages/xgcm/grid.py:989: FutureWarning: From version 0.8.0 the Axis computation methods will be removed, in favour of using the Grid computation methods instead. i.e. use `Grid.transform` instead of `Axis.transform`
    warnings.warn(

tests/integration/test_all_sets_image_diffs.py: 14 warnings
  /__w/e3sm_diags/e3sm_diags/3/envs/e3sm_diags_ci/lib/python3.9/site-packages/cartopy/mpl/geoaxes.py:862: UserWarning: Attempting to set identical low and high xlims makes transformation singular; automatically expanding.
    self.set_xlim([x1, x2])

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/plot/cosp_histogram_plot.py:176: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
    ax.set_xticklabels(xlabels)

tests/integration/test_all_sets_image_diffs.py: 1752 warnings
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/qbo_driver.py:357: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
    x_deseasoned[month_index] = xraw[month_index] - xclim[month]

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/qbo_driver.py:253: RuntimeWarning: divide by zero encountered in divide
    period = 1 / frequency

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/qbo_driver.py:258: ComplexWarning: Casting complex values to real discards the imaginary part
    psd_sumN[ilev] = 2 * np.nansum(fyy[(period <= 40) & (period >= 20)])

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/qbo_driver.py:310: RuntimeWarning: divide by zero encountered in divide
    period0 = 1 / frequency0

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/plot/qbo_plot.py:200: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
    plt.tight_layout()

tests/integration/test_all_sets_image_diffs.py: 22959 warnings
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/streamflow_driver.py:399: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
    export_data[i, 2] = drainage_area_error * 100

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/streamflow_driver.py:320: RuntimeWarning: Mean of empty slice
    monthly_mean[month] = np.nanmean(extracted[month_array_boolean, 2])

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/streamflow_driver.py:500: RuntimeWarning: invalid value encountered in divide
    streamflow_proportion = np.divide(streamflow_month_all_years, total_streamflow)

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/streamflow_driver.py:384: RuntimeWarning: Mean of empty slice
    monthly_mean_test = np.nanmean(mmat, axis=1)

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/plot/streamflow_plot_map.py:193: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
    cbar.ax.set_yticklabels(ticks)

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/plot/streamflow_plot_scatter.py:110: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
    cbar.ax.set_yticklabels(ticks)

tests/integration/test_all_sets_image_diffs.py: 16800 warnings
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/driver/utils/diurnal_cycle_xr.py:86: DeprecationWarning: __array__ implementation doesn't accept a copy keyword, so passing copy=False failed. __array__ must implement 'dtype' and 'copy' keyword arguments.
    lst[it, :, ilon] = (itime + start_time + lon[ilon] / 360 * 24) % 24  # type: ignore

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/plot/diurnal_cycle_plot.py:237: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
    bar_ax.set_xticklabels(["0h", "3h", "6h", "9h", "12h", "15h", "18h", "21h"])

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/plot/diurnal_cycle_plot.py:238: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
    bar_ax.set_yticklabels(["", "", f"{int(max_amp)}"])

tests/integration/test_all_sets_image_diffs.py::TestAllSetsImageDiffs::test_num_images_is_the_same_as_the_expected
  /__w/e3sm_diags/e3sm_diags/e3sm_diags/plot/arm_diags_plot.py:303: RuntimeWarning: invalid value encountered in multiply
    precip_binned = np.empty([number_of_bins, cwv.size]) * np.nan

What did you expect to happen? Are there are possible answers you came across?

No response

Minimal Complete Verifiable Example (MVCE)

Relevant log output

Anything else we need to know?

No response

Environment

Latest main and v3.0.0rc1/rc2

[tomvothecoder]

Example with zonal_mean_2d

2025-03-03 10:11:42,440 [INFO]: zonal_mean_2d_driver.py(run_diag:42) >> Variable: T
2025-03-03 10:11:43,085 [INFO]: dataset_xr.py(_get_dataset_with_derived_climo_var:713) >> Deriving the test climatology variable using the source variables: ('T_mid',)
2025-03-03 10:11:44,889 [INFO]: dataset_xr.py(_get_dataset_with_derived_ts_var:876) >> Deriving the time series variable using the source variables: ('ta',)
2025-03-03 10:13:05,656 [INFO]: zonal_mean_2d_driver.py(_run_diags_3d:87) >> Selected pressure level: [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0, 650.0, 700.0, 750.0, 800.0, 850.0, 900.0, 950.0, 1000.0]
2025-03-03 10:13:05,716 [WARNING]: warnings.py(_showwarnmsg:109) >> /global/common/software/e3sm/anaconda_envs/base/envs/e3sm_unified_1.11.0rc10_pm-cpu/lib/python3.10/site-packages/xgcm/grid.py:989: FutureWarning: From version 0.8.0 the Axis computation methods will be removed, in favour of using the Grid computation methods instead. i.e. use Grid.transform instead of Axis.transform
  warnings.warn(

2025-03-03 10:13:05,910 [WARNING]: warnings.py(_showwarnmsg:109) >> /global/common/software/e3sm/anaconda_envs/base/envs/e3sm_unified_1.11.0rc10_pm-cpu/lib/python3.10/site-packages/xgcm/grid.py:989: FutureWarning: From version 0.8.0 the Axis computation methods will be removed, in favour of using the Grid computation methods instead. i.e. use Grid.transform instead of Axis.transform
  warnings.warn(

2025-03-03 10:13:24,991 [WARNING]: warnings.py(_showwarnmsg:109) >> /global/common/software/e3sm/anaconda_envs/base/envs/e3sm_unified_1.11.0rc10_pm-cpu/lib/python3.10/site-packages/xesmf/smm.py:131: UserWarning: Input array is not C_CONTIGUOUS. Will affect performance.
  warnings.warn('Input array is not C_CONTIGUOUS. ' 'Will affect performance.')

2025-03-03 10:13:25,403 [INFO]: io.py(_save_data_metrics_and_plots:77) >> Metrics saved in /global/cfs/cdirs/e3sm/www/zhang40/tests/eamxx/eamxx_decadal_1996_0303_edv3/zonal_mean_2d/ERA5/ERA5-T-ANN-global.json
2025-03-03 10:13:25,895 [INFO]: utils.py(_save_plot:92) >> Plot saved in: /global/cfs/cdirs/e3sm/www/zhang40/tests/eamxx/eamxx_decadal_1996_0303_edv3/zonal_mean_2d/ERA5/ERA5-T-ANN-global.png

The warning UserWarning: Input array is not C_CONTIGUOUS. Will affect performance. indicates that the input array to the regridder.horizontal function is not stored in a contiguous block of memory. This can affect performance because non-contiguous arrays can be slower to process.

In NumPy, arrays can be stored in memory in different ways. A C_CONTIGUOUS array is stored in a single, contiguous block of memory, which allows for faster access and manipulation. When an array is not C_CONTIGUOUS, it means that the array elements are not stored in a single block, which can slow down operations.

To resolve this warning, you can ensure that the input array is C_CONTIGUOUS before passing it to the regridder.horizontal function. You can use the numpy.ascontiguousarray function to convert the array to a contiguous layout.