Issue using partial_fit

[bdpedigo]

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Description

Errors when trying to use partial_fit in a variety of ways - I am getting this with int or string values for y and with and without providing classes to partial_fit. Could you point me to what I'm doing wrong here?

import numpy as np
from treeple import PatchObliqueRandomForestClassifier

X = np.array([[1, 2, 3]]).T
y = np.array(["x", "y", "z"])
classes = y
porf = PatchObliqueRandomForestClassifier()
porf.fit(X, y, classes=classes)
porf.partial_fit(X, y, classes=classes)

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
File /Users/ben.pedigo/code/meshrep/meshrep/sandbox/view_model.py:9
      [7](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/meshrep/sandbox/view_model.py:7) classes = y
      [8](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/meshrep/sandbox/view_model.py:8) porf = PatchObliqueRandomForestClassifier()
----> [9](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/meshrep/sandbox/view_model.py:9) porf.fit(X, y, classes=classes)
     [10](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/meshrep/sandbox/view_model.py:10) porf.partial_fit(X, y, classes=classes)

File ~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/base.py:1473, in _fit_context.<locals>.decorator.<locals>.wrapper(estimator, *args, **kwargs)
   [1466](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/base.py:1466)     estimator._validate_params()
   [1468](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/base.py:1468) with config_context(
   [1469](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/base.py:1469)     skip_parameter_validation=(
   [1470](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/base.py:1470)         prefer_skip_nested_validation or global_skip_validation
   [1471](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/base.py:1471)     )
   [1472](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/base.py:1472) ):
-> [1473](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/base.py:1473)     return fit_method(estimator, *args, **kwargs)

File ~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:595, in BaseForest.fit(self, X, y, sample_weight, classes)
    [592](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:592)         random_state.randint(MAX_INT, size=len(self.estimators_))
    [594](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:594)     # construct the trees in parallel
--> [595](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:595)     self._construct_trees(
    [596](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:596)         X,
    [597](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:597)         y,
    [598](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:598)         sample_weight,
    [599](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:599)         random_state,
    [600](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:600)         n_samples_bootstrap,
    [601](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:601)         missing_values_in_feature_mask,
    [602](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:602)         classes,
    [603](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:603)         n_more_estimators,
    [604](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:604)     )
    [606](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:606) if self.oob_score and (
    [607](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:607)     n_more_estimators > 0 or not hasattr(self, "oob_score_")
    [608](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:608) ):
    [609](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:609)     y_type = type_of_target(y)

File ~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:661, in BaseForest._construct_trees(self, X, y, sample_weight, random_state, n_samples_bootstrap, missing_values_in_feature_mask, classes, n_more_estimators)
    [650](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:650) trees = [
    [651](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:651)     self._make_estimator(append=False, random_state=random_state)
    [652](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:652)     for i in range(n_more_estimators)
    [653](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:653) ]
    [655](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:655) # Parallel loop: we prefer the threading backend as the Cython code
    [656](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:656) # for fitting the trees is internally releasing the Python GIL
    [657](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:657) # making threading more efficient than multiprocessing in
    [658](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:658) # that case. However, for joblib 0.12+ we respect any
    [659](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:659) # parallel_backend contexts set at a higher level,
    [660](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:660) # since correctness does not rely on using threads.
--> [661](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:661) trees = Parallel(
    [662](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:662)     n_jobs=self.n_jobs,
    [663](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:663)     verbose=self.verbose,
    [664](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:664)     prefer="threads",
    [665](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:665) )(
    [666](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:666)     delayed(_parallel_build_trees)(
    [667](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:667)         t,
    [668](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:668)         self.bootstrap,
    [669](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:669)         X,
    [670](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:670)         y,
    [671](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:671)         sample_weight,
    [672](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:672)         i,
    [673](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:673)         len(trees),
    [674](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:674)         verbose=self.verbose,
    [675](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:675)         class_weight=self.class_weight,
    [676](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:676)         n_samples_bootstrap=n_samples_bootstrap,
    [677](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:677)         missing_values_in_feature_mask=missing_values_in_feature_mask,
    [678](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:678)         classes=classes,
    [679](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:679)     )
    [680](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:680)     for i, t in enumerate(trees)
    [681](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:681) )
    [683](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:683) # Collect newly grown trees
    [684](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/ensemble/_forest.py:684) self.estimators_.extend(trees)

File ~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/utils/parallel.py:74, in Parallel.__call__(self, iterable)
     [69](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/utils/parallel.py:69) config = get_config()
     [70](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/utils/parallel.py:70) iterable_with_config = (
     [71](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/utils/parallel.py:71)     (_with_config(delayed_func, config), args, kwargs)
     [72](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/utils/parallel.py:72)     for delayed_func, args, kwargs in iterable
     [73](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/utils/parallel.py:73) )
---> [74](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/sklearn/utils/parallel.py:74) return super().__call__(iterable_with_config)

File ~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1918, in Parallel.__call__(self, iterable)
   [1916](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1916)     output = self._get_sequential_output(iterable)
   [1917](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1917)     next(output)
-> [1918](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1918)     return output if self.return_generator else list(output)
   [1920](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1920) # Let's create an ID that uniquely identifies the current call. If the
   [1921](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1921) # call is interrupted early and that the same instance is immediately
   [1922](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1922) # re-used, this id will be used to prevent workers that were
   [1923](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1923) # concurrently finalizing a task from the previous call to run the
   [1924](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1924) # callback.
   [1925](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1925) with self._lock:

File ~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1847, in Parallel._get_sequential_output(self, iterable)
   [1845](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1845) self.n_dispatched_batches += 1
   [1846](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1846) self.n_dispatched_tasks += 1
-> [1847](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1847) res = func(*args, **kwargs)
   [1848](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1848) self.n_completed_tasks += 1
   [1849](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/joblib/parallel.py:1849) self.print_progress()
...
    [324](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/tree/_classes.py:324)             ]
    [325](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/tree/_classes.py:325) else:
    [326](https://file+.vscode-resource.vscode-cdn.net/Users/ben.pedigo/code/meshrep/~/code/meshrep/meshrep/.venv/lib/python3.11/site-packages/treeple/_lib/sklearn/tree/_classes.py:326)     for k in range(self.n_outputs_):

IndexError: index 0 is out of bounds for axis 0 with size 0

Environment

OS: Mac

Python version: 3.11
Treeple 0.9.1

[adam2392]

Hey @bdpedigo thanks for reporting the issue. So the PatchObliquDTC could be rewritten. There are some weird issues because I implemented it in a naive way. In addition, partial_fit is an experimental feature we added that hasn't been fully tested.

To understand the bug, does fit work?

[bdpedigo]

fit does work yes!

[bdpedigo]

in the example I posted I think it fails when I pass in classes as well, but it was working without that