Troubleshooting common errors
Here, I’ve collected the output messages of some of the common errors I run into while using the code. I’ve included the solutions where I’ve found them, along with more details about what caused the error. If you encounter an error, try searching for parts of the error message in this document to see if it here.
Contents
Cannot connect to host in VSCodium
Sometimes the VSCodium server on a remove machine will get corrupted, causing you to be unable to connect to the remote via VSCodium, but you will still be able to log in via terminal just fine. This can happen when logging out without saving a file or if you lose internet connection suddenly and don’t restore it within a few minutes. I highly recommend closing the remote connection in VSCodium every time you are done working on the remote.
To fix the corrupted server, log into the remote via terminal and find the .vscodium-server/ directory.
It is usually in your home directory.
Rename that directory.
username@<remote_machine>:~/$ mv .vscodium-server/ .vscodium-server_old/
This will keep the contents of your old setup, just in case.
However, since now there is no .vscodium-server/ directory, when you now log in to the remote via VSCodium, it will reconstruct a new server directory, which should solve the issue with connecting.
If that works, you can then delete the old server directory and it’s contents.
username@<remote_machine>:~/$ rm -rf .vscodium-server_old/
Be sure to reinstall all your extensions on this new version of the remote VSCodium server.
Is the virtual environment activated?
When trying to regenerate the documentation html files, you may encounter this error:
username@animus-c:~/$ make clean html
/home/<username>/miniconda3/bin/python: No module named sphinx
make: *** [Makefile:19: clean] Error 1
To fix this, activate the conda environment.
Order of the imports matters on Trillium
The error:
2025-10-20 15:32:03.597518: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-20 15:32:03.611818: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2025-10-20 15:32:03.625403: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2025-10-20 15:32:03.629447: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2025-10-20 15:32:03.641665: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI AVX512_BF16 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
This happens when you try to import tensorflow or keras before using xarray to load the data that will be used by the model.
Directory not empty
The error:
OSError: [Errno 39] Directory not empty: 'inputfiles/no2_2019_JFM/'
This happens when I try to overwrite a directory or data file where any file to be overwritten is loaded into a data structure in an active Jupyter notebook cell. This most often happens when I’m testing out functions which write input files or metadata files and I’ve loaded that file in another cell to test whether it works. The solution to this is to restart the kernel in that notebook.
Example: executing these two cells in a row:
from unox.HPC.data0.dataset import uarray
input_u_arr = uarray('no2_2019_JFM', is_input_set=True)
input_u_arr.xr
from unox.input import copy_input_files
this_output = copy_input_files(
source_input_set = 'no2_2019',
output_dir = 'no2_2019_JFM',
keep_vars = 'all',
# keep_vars = ['no2'],
start_date = '2019-01-01',
end_date = '2019-03-31',
overwrite=True,
)
this_output.xr
Errors running tests from VSCodium
Error when running a test using the GUI in VSCodium, clicking on the “run” button next to the test definition:
Test result not found for: ./tests/test_input.py::test_make_input_metadata_file
After running pytest --collect-only, I got the output
E ValueError: conflicting sizes for dimension 'time': length 192 on 'time' and length 30 on {'time': 'no2', 'lat': 'no2', 'lon': 'no2'}
which told me that I’d incorrectly set the length of the time dimension on a new example dataset.
NaN values
If encountering NaN values, take a look at the time interval over which data is being used.
For the nox variable, all values past 2020-04-24 are NaN, therefore, correlation plots between nox (or truth) over intervals which include dates past 2020-04-24 will produce the error:
ValueError: autodetected range of [nan, nan] is not finite
Matplotlib has no attribute __version_info__
Here is the error I was encountering:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[5], line 1
----> 1 from unox.plotting import plot_extent
3 extent_plot = plot_extent(sample_dataset)
File ~/checkouts/readthedocs.org/user_builds/unox/checkouts/latest/src/unox/plotting.py:1
----> 1 import matplotlib.pyplot as plt
2 import matplotlib as mpl
3 import numpy as np
File ~/checkouts/readthedocs.org/user_builds/unox/envs/latest/lib/python3.9/site-packages/matplotlib/pyplot.py:2500
2498 dict.__setitem__(rcParams, "backend", rcsetup._auto_backend_sentinel)
2499 # Set up the backend.
-> 2500 switch_backend(rcParams["backend"])
2502 # Just to be safe. Interactive mode can be turned on without
2503 # calling `plt.ion()` so register it again here.
2504 # This is safe because multiple calls to `install_repl_displayhook`
2505 # are no-ops and the registered function respect `mpl.is_interactive()`
2506 # to determine if they should trigger a draw.
2507 install_repl_displayhook()
File ~/checkouts/readthedocs.org/user_builds/unox/envs/latest/lib/python3.9/site-packages/matplotlib/pyplot.py:277, in switch_backend(newbackend)
270 # Backends are implemented as modules, but "inherit" default method
271 # implementations from backend_bases._Backend. This is achieved by
272 # creating a "class" that inherits from backend_bases._Backend and whose
273 # body is filled with the module's globals.
275 backend_name = cbook._backend_module_name(newbackend)
--> 277 class backend_mod(matplotlib.backend_bases._Backend):
278 locals().update(vars(importlib.import_module(backend_name)))
280 required_framework = _get_required_interactive_framework(backend_mod)
File ~/checkouts/readthedocs.org/user_builds/unox/envs/latest/lib/python3.9/site-packages/matplotlib/pyplot.py:278, in switch_backend.<locals>.backend_mod()
277 class backend_mod(matplotlib.backend_bases._Backend):
--> 278 locals().update(vars(importlib.import_module(backend_name)))
File ~/.asdf/installs/python/3.9.22/lib/python3.9/importlib/__init__.py:127, in import_module(name, package)
125 break
126 level += 1
--> 127 return _bootstrap._gcd_import(name[level:], package, level)
File ~/checkouts/readthedocs.org/user_builds/unox/envs/latest/lib/python3.9/site-packages/matplotlib_inline/__init__.py:1
----> 1 from . import backend_inline, config # noqa
3 __version__ = "0.2.1"
5 # we can't ''.join(...) otherwise finding the version number at build time requires
6 # import which introduces IPython and matplotlib at build time, and thus circular
7 # dependencies.
File ~/checkouts/readthedocs.org/user_builds/unox/envs/latest/lib/python3.9/site-packages/matplotlib_inline/backend_inline.py:236
231 ip.events.unregister("post_run_cell", configure_once)
233 ip.events.register("post_run_cell", configure_once)
--> 236 _enable_matplotlib_integration()
239 def _fetch_figure_metadata(fig):
240 """Get some metadata to help with displaying a figure."""
File ~/checkouts/readthedocs.org/user_builds/unox/envs/latest/lib/python3.9/site-packages/matplotlib_inline/backend_inline.py:215, in _enable_matplotlib_integration()
211 ip = get_ipython()
213 import matplotlib
--> 215 if matplotlib.__version_info__ >= (3, 10):
216 backend = matplotlib.get_backend(auto_select=False)
217 else:
AttributeError: module 'matplotlib' has no attribute '__version_info__'
This was happening in the Analysis notebook, but only when it was pushed to the Read the Docs site.
It was also occurring when someone else was trying to run a function which imported matplotlib.pyplot in a Jupyter notebook.
They were able to import just matplotlib without error.
That notebook was running fine on my Animus environment and it was also running fine when that other person imported matplotlib in the Python interpreter using the same environment.
<username>@animus-c:unox$ conda activate uplt
(uplt) <username>@animus-c:unox$ python
Python 3.9.25 (main, Nov 3 2025, 22:33:05)
[GCC 11.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import matplotlib.pyplot
>>>
Looking through the error message, I saw that the error was occurring in the backend_inline.py script in the matplotlib-inline package.
That explains why it was only occurring when running in a Jupyter notebook and not in the interpreter.
The reason it was running fine on my environment and not in Read the Docs or the other person’s notebooks is that we had different versions of matplotlib-inline.
My environment was using v0.1.7, which was released on 2024-04-15.
The other environments were using v0.2.1, which was released on 2025-10-23.
I created my environment between those two dates, so it installed v0.1.7, the most up-to-date release at the time.
I made a post about this on the matplotlib-inline GitHub, GitHub - Matplotlib-Inline Issue #60: AttributeError: module ‘matplotlib’ has no attribute ‘version_info’.
I encountered this error in the Analysis Notebook when it gets pushed to the Read the Docs site.
I don’t see the error when running the notebook on Animus.
It happens the first time matplotlib is imported.
Harshil also encountered the same error when he tried creating the input files as the input module imported matplotlib.pyplot.
I’ve since removed the import of matplotlib from the input module because it is not needed, but it is still an issue.
Disk quota exceeded
[username@trig-login01 unox]$ git pull
error: cannot open '.git/FETCH_HEAD': Disk quota exceeded
Fix: Delete some data to free up room.
I deleted a bunch of old stuff from HPC_runs/.
To check how much space is being used, try the following “disk usage” command, setting the flag for “human readable format”:
(base) username@<remote_machine>:~/unox$ du -sh HPC_runs/*
1.3G HPC_runs/co_example_run
1.3G HPC_runs/no2_example_run
4.1G HPC_runs/_test_ens_zfi3
Importing packages in the wrong order on Trillium
I have found that the order in which I import Python packages on Trillium matters. Basically, I need to load xarray and use it to import from a file before I load the keras / tensorflow modules.
On 2026-02-09, I hit this particular error which was caused by me trying to import functions from keras before loading the xarray package:
Traceback (most recent call last):
File "/scratch/<username>/Postdoc/unox/src/unox/HPC/run_model.py", line 61, in <module>
uarr = uarray(inputfiles, is_input_set=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/scratch/<username>/Postdoc/unox/src/unox/HPC/data0/dataset.py", line 50, in __init__
self.xr = get_dataset(
^^^^^^^^^^^^
File "/scratch/<username>/Postdoc/unox/src/unox/HPC/data0/dataset.py", line 150, in get_dataset
xr_dataset = load_dataset(file_path, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/scratch/<username>/Postdoc/unox/src/unox/HPC/data0/dataset.py", line 188, in load_dataset
xr_dataset = xr.open_dataset(file_path)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/<username>/.virtualenvs/unoxTrilliumNC/lib/python3.12/site-packages/xarray/backends/api.py", line 573, in open_dataset
backend_ds = backend.open_dataset(
^^^^^^^^^^^^^^^^^^^^^
File "/home/<username>/.virtualenvs/unoxTrilliumNC/lib/python3.12/site-packages/xarray/backends/netCDF4_.py", line 646, in open_dataset
store = NetCDF4DataStore.open(
^^^^^^^^^^^^^^^^^^^^^^
File "/home/<username>/.virtualenvs/unoxTrilliumNC/lib/python3.12/site-packages/xarray/backends/netCDF4_.py", line 376, in open
import netCDF4
File "/home/<username>/.virtualenvs/unoxTrilliumNC/lib/python3.12/site-packages/netCDF4/__init__.py", line 3, in <module>
from ._netCDF4 import *
ImportError: /cvmfs/soft.computecanada.ca/easybuild/software/2023/x86-64-v3/MPI/gcc12/openmpi4/netcdf-mpi/4.9.2/lib64/libnetcdf.so.19: undefined symbol: H5Pset_coll_metadata_write
I remember running into this sometime in 2025. I want to look back through my logs to see if I can find if that was the same error message that earlier time.
Cannot make clean html docs
(uplt) username@animus-c:~/unox/docs$ make clean html
Removing everything under '_build'...
Traceback (most recent call last):
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/site-packages/sphinx/__main__.py", line 7, in <module>
raise SystemExit(main(sys.argv[1:]))
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/site-packages/sphinx/cmd/build.py", line 382, in main
return make_main(argv)
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/site-packages/sphinx/cmd/build.py", line 217, in make_main
return make_mode.run_make_mode(argv[1:])
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/site-packages/sphinx/cmd/make_mode.py", line 175, in run_make_mode
return getattr(make, run_method)()
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/site-packages/sphinx/cmd/make_mode.py", line 85, in build_clean
rmtree(self.builddir_join(item))
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/site-packages/sphinx/util/osutil.py", line 256, in rmtree
shutil.rmtree(path)
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/shutil.py", line 734, in rmtree
_rmtree_safe_fd(fd, path, onerror)
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/shutil.py", line 667, in _rmtree_safe_fd
_rmtree_safe_fd(dirfd, fullname, onerror)
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/shutil.py", line 667, in _rmtree_safe_fd
_rmtree_safe_fd(dirfd, fullname, onerror)
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/shutil.py", line 690, in _rmtree_safe_fd
onerror(os.unlink, fullname, sys.exc_info())
File "/home/<username>/miniconda3/envs/uplt/lib/python3.9/shutil.py", line 688, in _rmtree_safe_fd
os.unlink(entry.name, dir_fd=topfd)
OSError: [Errno 16] Device or resource busy: '.nfs0000000d003d06560000001b'
make: *** [Makefile:19: clean] Error 1
Fix: log out and log back in.
Do you have more than one day in the data?
Need to confirm whether this actually has to do with only having one day and therefore having xarray drop the time index.
# here’s the error that i get if i try to generate the input files using this command
make_all_input_files(
output_dir='co_test',
years=[2019],
stage2=False,
chemra_path='../../users/jk/20/hneeraj/GC_v14.1.1/gc_4x5_47L_merra2_tagCO/OutputDir',
chemra_var='SpeciesConcVV_CO',
insitu_path='US_EPA/NO2/daily_NO2/daily_42602_',
era5_path='ERA5concatenated',
scale_factors={'chemra': 1e-3,
'sp': 1e-5,
'ssrd': 1e-6,
'blh': 1e-3},
stage_2_cutoff=2013,
var='EmisCO_BioBurn',
emiss_dir='/users/jk/20/hneeraj/GC_v14.1.1/gc_4x5_47L_merra2_tagCO/OutputDir',
emiss_pre='HEMCO_diagnostics.',
emiss_post='01020000.nc',
scale_factor=1e12,
)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[1], line 24
1 from unox.input import make_all_input_files
3 # make_all_input_files(
4 # output_dir='co_test',
5 # years=range(2023, 2024),
(...)
20 # scale_factor=1e12,
21 # )
---> 24 make_all_input_files(
25 output_dir='co_test',
26 years=[2019],
27 stage2=False,
28 chemra_path='../../users/jk/20/hneeraj/GC_v14.1.1/gc_4x5_47L_merra2_tagCO/OutputDir',
29 chemra_var='SpeciesConcVV_CO',
30 insitu_path='US_EPA/NO2/daily_NO2/daily_42602_',
31 era5_path='ERA5concatenated',
32 scale_factors={'chemra': 1e-3,
33 'sp': 1e-5,
34 'ssrd': 1e-6,
35 'blh': 1e-3},
36 stage_2_cutoff=2013,
37 var='EmisCO_BioBurn',
38 emiss_dir='/users/jk/20/hneeraj/GC_v14.1.1/gc_4x5_47L_merra2_tagCO/OutputDir',
39 emiss_pre='HEMCO_diagnostics.',
40 emiss_post='01020000.nc',
41 scale_factor=1e12,
42 )
File /users/jk/22/hneeraj/unox_dir/unox/src/unox/unox.py:35, in time_this.<locals>.wrap_func(*args, **kwargs)
33 t1 = datetime.now()
34 # Execute the function
---> 35 result = func(*args, **kwargs)
36 # Get the time at the end of the execution
37 t2 = datetime.now()
File /users/jk/22/hneeraj/unox_dir/unox/src/unox/input.py:998, in make_all_input_files(output_dir, sort, **kwargs)
996 # Create y input data
997 print("Creating y input data...")
--> 998 input_netcdf_xr = make_all_y_input_files(
999 output_dir=output_dir,
1000 sort=False,
1001 **kwargs,
1002 )
1003 # Create x input data
1004 print("Creating x input data...")
File /users/jk/22/hneeraj/unox_dir/unox/src/unox/input.py:868, in make_all_y_input_files(years, var, output_dir, sort, **kwargs)
866 for year in years:
867 print(f"\tCreating y input data for {var} in {year}...")
--> 868 y_data, g_attr_dict = make_y_input_file(
869 year=year,
870 var=var,
871 output_dir=output_dir,
872 write_this_year=False,
873 sort=False,
874 **kwargs,
875 )
876 y_data_array.append(y_data)
877 # Concatenate the datasets along the time dimension
File /users/jk/22/hneeraj/unox_dir/unox/src/unox/input.py:203, in make_y_input_file(year, var, emiss_dir, emiss_pre, emiss_post, scale_factor, nan_fill, stage_2_cutoff, output_dir, write_this_year, overwrite, output_format, **kwargs)
200 # Write out results
201 if not isinstance(output_dir, type(None)):
202 # Create metadata file
--> 203 meta_dict = make_input_metadata_file(
204 input_netcdf_xr,
205 output_dir=output_dir,
206 g_attrs=g_attr_dict,
207 )
208 # Save the data to file
209 # For writing out a numpy file
210 if output_format in ['npy', 'both']:
211 # Assemble the file path
File /users/jk/22/hneeraj/unox_dir/unox/src/unox/input.py:1121, in make_input_metadata_file(input_set, output_dir, g_attrs, overwrite)
1114 metadata_dict = {
1115 'years': {
1116 'x': [],
1117 'y': [],
1118 },
1119 }
1120 # Get a list of years present in the dataset
-> 1121 years = get_years(xr_dataset)
1122 # Check for global attributes
1123 if isinstance(g_attrs, type(None)):
File /users/jk/22/hneeraj/unox_dir/unox/src/unox/HPC/data0/dataset.py:366, in get_years(dataset)
364 raise TypeError(f"(get_years) `dataset` must be an xarray Dataset or DataArray. Got type: {type(dataset)}.")
365 # Get a list of years present in the dataset
--> 366 years = xr_dataset['time'].dt.year.values
367 # Sort and get unique years
368 years = sorted(list(set(years)))
File ~/miniconda3/envs/uplt/lib/python3.9/site-packages/xarray/core/common.py:285, in AttrAccessMixin.__getattr__(self, name)
283 with suppress(KeyError):
284 return source[name]
--> 285 raise AttributeError(
286 f"{type(self).__name__!r} object has no attribute {name!r}"
287 )
AttributeError: 'DataArray' object has no attribute 'dt'
Some variables aren’t defined all the way to the end of 2020
I was trying to just make a correlation plot of data from an ensemble run, but got an error:
from unox.plotting import corr_plot
this_plt = corr_plot(
'ens_reg4',
is_predict=True,
ens_mem=1,
start_date='2019-01-01',
x_vars=['pred'],
y_vars=['truth'],
)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[2], line 3
1 from unox.plotting import corr_plot
----> 3 this_plt = corr_plot(
4 'ens_reg4',
5 is_predict=True,
6 ens_mem=1,
7 start_date='2019-01-01',
8 # interval='1Y',
9 # x_vars=['pred', 'pred_s2', 'pred'],
10 # y_vars=['truth', 'truth', 'pred_s2'],
11 x_vars=['pred'],
12 y_vars=['truth'],
13 # restrict_lat_lon_to=minimal_xr0,
14 )
File ~/unox/src/unox/plotting.py:1182, in corr_plot(dataset, x_vars, y_vars, axs, restrict_lat_lon_to, ens_mem, **kwargs)
1179 y_xarr = u_arr.xr[y_var]
1181 # Plot the comparison
-> 1182 fig_q = plot_comparison(
1183 x_xarr,
1184 y_xarr,
1185 ax=ax,
1186 **kwargs,
1187 )
1188 if new_plot == True:
1189 # Add an overall title
1190 fig.suptitle(f"{u_arr.name}{title_ens_ID} {title_segment}", fontsize=title_font_size)
File ~/unox/src/unox/plotting.py:928, in plot_comparison(a_xr_arr, b_xr_arr, ax, plt_title, a_label, b_label, cmap, set_under_val, hist_params, log_scale, **kwargs)
926 # Plot the data, depending on the scale
927 if log_scale:
--> 928 this_hist, xedges, yedges, q = ax.hist2d(npy_a, npy_b, bins=hist_params['bins'], norm='log', cmap=cmap, vmin=hist_params['vmin'], vmax=hist_params['vmax'], extend='both')
929 else:
930 this_hist, xedges, yedges, q = ax.hist2d(npy_a, npy_b, bins=hist_params['bins'], norm='linear', cmap=cmap)
File ~/miniconda3/envs/uplt/lib/python3.9/site-packages/proplot/internals/process.py:284, in _preprocess_args.<locals>.decorator.<locals>._redirect_or_standardize(self, *args, **kwargs)
281 ureg.setup_matplotlib(True)
283 # Call main function
--> 284 return func(self, *args, **kwargs)
File ~/miniconda3/envs/uplt/lib/python3.9/site-packages/proplot/axes/plot.py:3805, in PlotAxes.hist2d(self, x, y, bins, **kwargs)
3803 if bins is not None:
3804 kwargs['bins'] = bins
-> 3805 return super().hist2d(x, y, default_discrete=False, **kwargs)
File ~/miniconda3/envs/uplt/lib/python3.9/site-packages/matplotlib/__init__.py:1361, in _preprocess_data.<locals>.inner(ax, data, *args, **kwargs)
1358 @functools.wraps(func)
1359 def inner(ax, *args, data=None, **kwargs):
1360 if data is None:
-> 1361 return func(ax, *map(sanitize_sequence, args), **kwargs)
1363 bound = new_sig.bind(ax, *args, **kwargs)
1364 auto_label = (bound.arguments.get(label_namer)
1365 or bound.kwargs.get(label_namer))
File ~/miniconda3/envs/uplt/lib/python3.9/site-packages/matplotlib/axes/_axes.py:7093, in Axes.hist2d(self, x, y, bins, range, density, weights, cmin, cmax, **kwargs)
6999 @_preprocess_data(replace_names=["x", "y", "weights"])
7000 @docstring.dedent_interpd
7001 def hist2d(self, x, y, bins=10, range=None, density=False, weights=None,
7002 cmin=None, cmax=None, **kwargs):
7003 """
7004 Make a 2D histogram plot.
7005
(...)
7090 `.colors.PowerNorm`.
7091 """
-> 7093 h, xedges, yedges = np.histogram2d(x, y, bins=bins, range=range,
7094 density=density, weights=weights)
7096 if cmin is not None:
7097 h[h < cmin] = None
File ~/miniconda3/envs/uplt/lib/python3.9/site-packages/numpy/lib/twodim_base.py:808, in histogram2d(x, y, bins, range, density, weights)
806 xedges = yedges = asarray(bins)
807 bins = [xedges, yedges]
--> 808 hist, edges = histogramdd([x, y], bins, range, density, weights)
809 return hist, edges[0], edges[1]
File ~/miniconda3/envs/uplt/lib/python3.9/site-packages/numpy/lib/histograms.py:1003, in histogramdd(sample, bins, range, density, weights)
1000 if bins[i] < 1:
1001 raise ValueError(
1002 '`bins[{}]` must be positive, when an integer'.format(i))
-> 1003 smin, smax = _get_outer_edges(sample[:,i], range[i])
1004 try:
1005 n = operator.index(bins[i])
File ~/miniconda3/envs/uplt/lib/python3.9/site-packages/numpy/lib/histograms.py:323, in _get_outer_edges(a, range)
321 first_edge, last_edge = a.min(), a.max()
322 if not (np.isfinite(first_edge) and np.isfinite(last_edge)):
--> 323 raise ValueError(
324 "autodetected range of [{}, {}] is not finite".format(first_edge, last_edge))
326 # expand empty range to avoid divide by zero
327 if first_edge == last_edge:
ValueError: autodetected range of [nan, nan] is not finite
The issue is, when trying to pull the truth variable (which is nox in this case), it finds a different length of time than the pred variable. Then, it tries to compare actual values of pred to the nan values of nox at the end of 2020, resulting in the above error.
This error doesn’t occur when plotting with plot_run_analysis because that by default only includes data for 1 year using interval='1Y'.
Unable to install tensorflow locally
When trying to create a conda environment on my mac:
(uplt0) Grey@Audron:unox$ poetry install
Updating dependencies
Resolving dependencies... (52.1s)
Package operations: 158 installs, 21 updates, 0 removals
- Installing attrs (25.4.0)
- Installing rpds-py (0.27.1)
...
- Installing sphinx-rtd-theme (3.1.0)
- Installing tensorflow (2.17.0): Failed
| Unable to find installation candidates for tensorflow (2.17.0)
|
| This is likely not a Poetry issue.
|
| - 16 candidate(s) were identified for the package
| - 16 wheel(s) were skipped as your project's environment does not support the identified abi tags
|
| Solutions:
| Make sure the lockfile is up-to-date. You can try one of the following;
|
| 1. Regenerate lockfile: poetry lock --no-cache --regenerate
| 2. Update package : poetry update --no-cache tensorflow
|
| If neither works, please first check to verify that the tensorflow has published wheels available from your configured source that are compatible with your environment- ie. operating system, architecture (x86_64, arm64 etc.), python interpreter.
|
| You can also run your poetry command with -v to see more information.
- Installing xarray (2024.3.0)
(uplt0) Grey@Audron:unox$ pip install tensorflow==2.17.0
ERROR: Could not find a version that satisfies the requirement tensorflow==2.17.0 (from versions: 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0rc0, 2.6.0rc1, 2.6.0rc2, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0rc0, 2.7.0rc1, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0rc0, 2.8.0rc1, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0rc0, 2.9.0rc1, 2.9.0rc2, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0rc0, 2.10.0rc1, 2.10.0rc2, 2.10.0rc3, 2.10.0, 2.10.1, 2.11.0rc0, 2.11.0rc1, 2.11.0rc2, 2.11.0, 2.11.1, 2.12.0rc0, 2.12.0rc1, 2.12.0, 2.12.1, 2.13.0rc0, 2.13.0rc1, 2.13.0rc2, 2.13.0, 2.13.1, 2.14.0rc0, 2.14.0rc1, 2.14.0, 2.14.1, 2.15.0rc0, 2.15.0rc1, 2.15.0, 2.15.1, 2.16.0rc0, 2.16.1, 2.16.2)
ERROR: No matching distribution found for tensorflow==2.17.0
I found the answer on a GitHub issue TensorFlow 2.17 for macOS x86_64 is not on PyPI #75279 which pointed to the TensorFlow 2.16 release notes:
“Mac x86 users: Mac x86 builds are being deprecated and will no longer be released as a Pip package from TF 2.17 onwards.”
So, version 2.17 just isn’t available for my local computer any more. Good to know.
I’m just gonna try doing a pip install tensorflow==2.16.2 and hope that works well enough for things I want to test locally.
pip install tensorflow==2.16.2
Collecting tensorflow==2.16.2
Downloading tensorflow-2.16.2-cp39-cp39-macosx_10_15_x86_64.whl.metadata (4.1 kB)
Requirement already satisfied: absl-py>=1.0.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (2.3.1)
Requirement already satisfied: astunparse>=1.6.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (1.6.3)
Requirement already satisfied: flatbuffers>=23.5.26 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (25.12.19)
Requirement already satisfied: gast!=0.5.0,!=0.5.1,!=0.5.2,>=0.2.1 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (0.7.0)
Requirement already satisfied: google-pasta>=0.1.1 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (0.2.0)
Requirement already satisfied: h5py>=3.10.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (3.14.0)
Requirement already satisfied: libclang>=13.0.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (18.1.1)
Collecting ml-dtypes~=0.3.1 (from tensorflow==2.16.2)
Downloading ml_dtypes-0.3.2-cp39-cp39-macosx_10_9_universal2.whl.metadata (20 kB)
Requirement already satisfied: opt-einsum>=2.3.2 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (3.4.0)
Requirement already satisfied: packaging in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (23.2)
Requirement already satisfied: protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (4.25.8)
Requirement already satisfied: requests<3,>=2.21.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (2.32.5)
Requirement already satisfied: setuptools in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (80.10.2)
Requirement already satisfied: six>=1.12.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (1.17.0)
Requirement already satisfied: termcolor>=1.1.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (3.1.0)
Requirement already satisfied: typing-extensions>=3.6.6 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (4.15.0)
Requirement already satisfied: wrapt>=1.11.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (2.1.2)
Requirement already satisfied: grpcio<2.0,>=1.24.3 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (1.78.0)
Collecting tensorboard<2.17,>=2.16 (from tensorflow==2.16.2)
Downloading tensorboard-2.16.2-py3-none-any.whl.metadata (1.6 kB)
Requirement already satisfied: keras>=3.0.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (3.10.0)
Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (0.37.1)
Requirement already satisfied: numpy<2.0.0,>=1.23.5 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorflow==2.16.2) (1.26.4)
Requirement already satisfied: charset_normalizer<4,>=2 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from requests<3,>=2.21.0->tensorflow==2.16.2) (3.4.6)
Requirement already satisfied: idna<4,>=2.5 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from requests<3,>=2.21.0->tensorflow==2.16.2) (3.11)
Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from requests<3,>=2.21.0->tensorflow==2.16.2) (2.6.3)
Requirement already satisfied: certifi>=2017.4.17 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from requests<3,>=2.21.0->tensorflow==2.16.2) (2026.2.25)
Requirement already satisfied: markdown>=2.6.8 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorboard<2.17,>=2.16->tensorflow==2.16.2) (3.9)
Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorboard<2.17,>=2.16->tensorflow==2.16.2) (0.7.2)
Requirement already satisfied: werkzeug>=1.0.1 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from tensorboard<2.17,>=2.16->tensorflow==2.16.2) (3.1.6)
Requirement already satisfied: wheel<1.0,>=0.23.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from astunparse>=1.6.0->tensorflow==2.16.2) (0.45.1)
Requirement already satisfied: rich in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from keras>=3.0.0->tensorflow==2.16.2) (14.3.3)
Requirement already satisfied: namex in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from keras>=3.0.0->tensorflow==2.16.2) (0.1.0)
Requirement already satisfied: optree in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from keras>=3.0.0->tensorflow==2.16.2) (0.19.0)
Requirement already satisfied: importlib-metadata>=4.4 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from markdown>=2.6.8->tensorboard<2.17,>=2.16->tensorflow==2.16.2) (8.7.1)
Requirement already satisfied: zipp>=3.20 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard<2.17,>=2.16->tensorflow==2.16.2) (3.23.0)
Requirement already satisfied: markupsafe>=2.1.1 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from werkzeug>=1.0.1->tensorboard<2.17,>=2.16->tensorflow==2.16.2) (3.0.3)
Requirement already satisfied: markdown-it-py>=2.2.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from rich->keras>=3.0.0->tensorflow==2.16.2) (3.0.0)
Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from rich->keras>=3.0.0->tensorflow==2.16.2) (2.19.2)
Requirement already satisfied: mdurl~=0.1 in /Users/Grey/miniconda3/envs/uplt0/lib/python3.9/site-packages (from markdown-it-py>=2.2.0->rich->keras>=3.0.0->tensorflow==2.16.2) (0.1.2)
Downloading tensorflow-2.16.2-cp39-cp39-macosx_10_15_x86_64.whl (259.5 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 259.5/259.5 MB 6.2 MB/s eta 0:00:00
Downloading ml_dtypes-0.3.2-cp39-cp39-macosx_10_9_universal2.whl (389 kB)
Downloading tensorboard-2.16.2-py3-none-any.whl (5.5 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5.5/5.5 MB 7.2 MB/s eta 0:00:00
Installing collected packages: ml-dtypes, tensorboard, tensorflow
Attempting uninstall: ml-dtypes
Found existing installation: ml-dtypes 0.4.1
Uninstalling ml-dtypes-0.4.1:
Successfully uninstalled ml-dtypes-0.4.1
Attempting uninstall: tensorboard
Found existing installation: tensorboard 2.17.1
Uninstalling tensorboard-2.17.1:
Successfully uninstalled tensorboard-2.17.1
Successfully installed ml-dtypes-0.3.2 tensorboard-2.16.2 tensorflow-2.16.2