Dear all, First thank you for developping this tool, that I believe is of great interest. I am working with:

• environmental variables (e.g. temperature, salinity)
• multi-dimensional targets, that are relative abundance, with their sum = 1 for each site

Therefore, I was wondering if it is possible to implement a custom loss function in the mbtr framework, that would be adapted for proportions. Please note that I am quite new to python.

To do some testing, I tryed to dupplicate the mse loss function with another name in the losses.py file and adding the new loss in the LOSS_MAP in __inits__.py. Then I compiled the files. However, I have this error when trying to run the model from the multi_reg.py example:

>>> m = MBT(loss_type = 'mse', n_boosts=30,  min_leaf=100, lambda_weights=1e-3).fit(x_tr, y_tr, do_plot=True)
  3%|▎         | 1/30 [00:03<01:45,  3.63s/it]
>>> m = MBT(loss_type = 'custom_mse', n_boosts=30,  min_leaf=100, lambda_weights=1e-3).fit(x_tr, y_tr, do_plot=True)
  0%|          | 0/30 [00:00<?, ?it/s]KeyError: 'custom_mse'

It seems that the new loss is not recognised in LOSS_MAP:

>>> LOSS_MAP = {'custom_mse': losses.custom_MSE,
...             'mse': losses.MSE,
...             'time_smoother': losses.TimeSmoother,
...             'latent_variable': losses.LatentVariable,
...             'linear_regression': losses.LinRegLoss,
...             'fourier': losses.FourierLoss,
...             'quantile': losses.QuantileLoss,
...             'quadratic_quantile': losses.QuadraticQuantileLoss}
AttributeError: module 'mbtr.losses' has no attribute 'custom_MSE'

I guess that I missed something when trying to dupplicate and rename the mse loss. I would appreciate any help if the definition of a custom loss function is possible.

Best regards,

Hi thank you for your effort to create this. I want to try this but i cannot download nor visit the web that you provided in example multivariate_forecas.py

Is there any alternative link for that dataset? thank you regards!

I want to use MBTR in a teaching module and I need to use jupyter-lab inside a conda environment for teaching purposes. While MBTR works as expected in a vanilla python 3.8, it errors out (on the same machine) in a conda environment using python 3.10

Steps to reproduce

conda create --name testenv
conda activate testenv

conda install -c conda-forge jupyterlab
pip install --upgrade git+https://github.com/supsi-dacd-isaac/mbtr.git
# to make sure to get the latest version; but the version on pypi gives the same error 

Then

python

and in python

from mbtr.mbtr import MBT

which outputs the following error

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/mbtr/mbtr.py", line 317, in <module>
    def leaf_stats(y, edges, x, order):
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/decorators.py", line 219, in wrapper
    disp.compile(sig)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/dispatcher.py", line 965, in compile
    cres = self._compiler.compile(args, return_type)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/dispatcher.py", line 129, in compile
    raise retval
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/dispatcher.py", line 139, in _compile_cached
    retval = self._compile_core(args, return_type)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/dispatcher.py", line 152, in _compile_core
    cres = compiler.compile_extra(self.targetdescr.typing_context,
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler.py", line 716, in compile_extra
    return pipeline.compile_extra(func)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler.py", line 452, in compile_extra
    return self._compile_bytecode()
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler.py", line 520, in _compile_bytecode
    return self._compile_core()
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler.py", line 499, in _compile_core
    raise e
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler.py", line 486, in _compile_core
    pm.run(self.state)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler_machinery.py", line 368, in run
    raise patched_exception
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler_machinery.py", line 356, in run
    self._runPass(idx, pass_inst, state)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler_lock.py", line 35, in _acquire_compile_lock
    return func(*args, **kwargs)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler_machinery.py", line 311, in _runPass
    mutated |= check(pss.run_pass, internal_state)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/compiler_machinery.py", line 273, in check
    mangled = func(compiler_state)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/typed_passes.py", line 105, in run_pass
    typemap, return_type, calltypes, errs = type_inference_stage(
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/typed_passes.py", line 83, in type_inference_stage
    errs = infer.propagate(raise_errors=raise_errors)
  File "/home/myself/.conda/envs/testenv/lib/python3.10/site-packages/numba/core/typeinfer.py", line 1086, in propagate
    raise errors[0]
numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
No conversion from UniTuple(none x 2) to UniTuple(array(float64, 2d, A) x 2) for '$116return_value.7', defined at None

File ".conda/envs/testenv/lib/python3.10/site-packages/mbtr/mbtr.py", line 327:
def leaf_stats(y, edges, x, order):
    <source elided>
        s_left, s_right = None, None
    return s_left, s_right
    ^

During: typing of assignment at /home/myself/.conda/envs/testenv/lib/python3.10/site-packages/mbtr/mbtr.py (327)

File ".conda/envs/test/lib/python3.10/site-packages/mbtr/mbtr.py", line 327:
def leaf_stats(y, edges, x, order):
    <source elided>
        s_left, s_right = None, None
    return s_left, s_right
    ^

Thanks in advance for any pointer/help. The course where I want to present this is a summer course and is closing in on me 😉