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update deprecated numpy types int and integer #9

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update deprecated numpy types int and integer #9

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2 changes: 1 addition & 1 deletion examples/module_examples/M3_BPS/demo_balance_scheduling_full.py
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Original file line number Diff line number Diff line change
Expand Up @@ -147,7 +147,7 @@ def _partition_estimators(n_estimators, n_jobs):

# Partition estimators between jobs
n_estimators_per_job = np.full(n_jobs, n_estimators // n_jobs,
dtype=np.int)
dtype=int)
n_estimators_per_job[:n_estimators % n_jobs] += 1
starts = np.cumsum(n_estimators_per_job)

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2 changes: 1 addition & 1 deletion examples/module_examples/M3_BPS/demo_balanced_scheduling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -144,7 +144,7 @@ def _partition_estimators(n_estimators, n_jobs):

# Partition estimators between jobs
n_estimators_per_job = np.full(n_jobs, n_estimators // n_jobs,
dtype=np.int)
dtype=int)
n_estimators_per_job[:n_estimators % n_jobs] += 1
starts = np.cumsum(n_estimators_per_job)

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3 changes: 2 additions & 1 deletion suod/models/base.py
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Expand Up @@ -246,7 +246,8 @@ def fit(self, X):
n_samples, n_features = X.shape[0], X.shape[1]

# Validate target_dim_frac for random projection
if isinstance(self.target_dim_frac, (numbers.Integral, np.integer)):
if isinstance(self.target_dim_frac,
(numbers.Integral, int, np.int32, np.int64)):
self.target_dim_frac_ = self.target_dim_frac
else: # float
self.target_dim_frac_ = int(self.target_dim_frac * n_features)
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2 changes: 1 addition & 1 deletion suod/models/parallel_processes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -116,7 +116,7 @@ def _partition_estimators(n_estimators, n_jobs, verbose=False):

# Partition estimators between jobs
n_estimators_per_job = np.full(n_jobs, n_estimators // n_jobs,
dtype=np.int)
dtype=int)
n_estimators_per_job[:n_estimators % n_jobs] += 1
starts = np.cumsum(n_estimators_per_job)

Expand Down