py: Install with numpy >= 2.0 (#85)

grf-labs · Nov 3, 2024 · 5b79614 · 5b79614
1 parent e23af47
commit 5b79614
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Showing 4 changed files with 6 additions and 4 deletions.
diff --git a/azure-pipelines.yml b/azure-pipelines.yml
@@ -94,6 +94,8 @@ jobs:
     workingDirectory: 'python-package'
     displayName: 'Test Python bindings'
   - script: |
+      NONINTERACTIVE=1 /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
+      brew install libomp
       pip install -I causalml xgboost matplotlib jupyter
       jupyter nbconvert --execute --to 'notebook' introduction.ipynb
     workingDirectory: 'python-package/notebooks'

diff --git a/python-package/maq/maq.py b/python-package/maq/maq.py
@@ -157,7 +157,7 @@ class MAQ:
     Get an estimate of gain at a given spend along with standard errors.
 
     >>> mq.average_gain(spend=0.1)
-    (0.005729002695991717, 0.019814651108894354)
+    (np.float64(0.005729002695991717), np.float64(0.019814651108894354))
 
     Get the underlying treatment allocation matrix at a given spend, a n x K array.
 

diff --git a/python-package/maq/maqbindings.pyx b/python-package/maq/maqbindings.pyx
@@ -49,8 +49,8 @@ cpdef solver_cpp(np.ndarray[double, ndim=2, mode="c"] reward,
     spend = np.empty(path_len, dtype="double")
     gain = np.empty(path_len, dtype="double")
     std_err = np.empty(path_len, dtype="double")
-    ipath = np.empty(path_len, dtype="int")
-    kpath = np.empty(path_len, dtype="int")
+    ipath = np.empty(path_len, dtype="long")
+    kpath = np.empty(path_len, dtype="long")
     if paired_inference:
         gain_bs = np.empty((n_bootstrap, path_len), dtype="double")
     else:

diff --git a/python-package/pyproject.toml b/python-package/pyproject.toml
@@ -3,5 +3,5 @@ requires = [
     "setuptools",
     "wheel",
     "cython",
-    "oldest-supported-numpy"
+    "numpy >= 2.0"
 ]