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Revert ci.yml changes
Signed-off-by: Keith Battocchi <kebatt@microsoft.com>
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.github/workflows/ci.yml

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Original file line numberDiff line numberDiff line change
@@ -147,7 +147,7 @@ jobs:
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if: ${{ matrix.install_graphviz }}
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# Add verbose flag to pip installation if in debug mode
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- name: Install econml
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run: uv pip install --system .${{ matrix.extras }} ${{ fromJSON('["","-v"]')[runner.debug] }} ${{ env.use_lkg && '-r lkg-notebook.txt' }}
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run: uv pip install --system -e .${{ matrix.extras }} ${{ fromJSON('["","-v"]')[runner.debug] }} ${{ env.use_lkg && '-r lkg-notebook.txt' }}
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# Install notebook requirements (if not already done as part of lkg)
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- name: Install notebook requirements
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run: uv pip install --system jupyter jupyter-client nbconvert nbformat seaborn xgboost tqdm

econml/tests/dgp.py

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@@ -176,44 +176,3 @@ def policy_gen(Tpre, X, period):
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return self._gen_data_with_policy(n_units, policy_gen, random_seed=random_seed)
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# Auxiliary function for adding xticks and vertical lines when plotting results
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# for dynamic dml vs ground truth parameters.
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def add_vlines(n_periods, n_treatments, hetero_inds):
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locs, labels = plt.xticks([], [])
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locs += [- .501 + (len(hetero_inds) + 1) / 2]
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labels += ["\n\n$\\tau_{{{}}}$".format(0)]
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locs += [qx for qx in np.arange(len(hetero_inds) + 1)]
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labels += ["$1$"] + ["$x_{{{}}}$".format(qx) for qx in hetero_inds]
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for q in np.arange(1, n_treatments):
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plt.axvline(x=q * (len(hetero_inds) + 1) - .5,
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linestyle='--', color='red', alpha=.2)
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locs += [q * (len(hetero_inds) + 1) - .501 + (len(hetero_inds) + 1) / 2]
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labels += ["\n\n$\\tau_{{{}}}$".format(q)]
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locs += [(q * (len(hetero_inds) + 1) + qx)
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for qx in np.arange(len(hetero_inds) + 1)]
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labels += ["$1$"] + ["$x_{{{}}}$".format(qx) for qx in hetero_inds]
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locs += [- .501 + (len(hetero_inds) + 1) * n_treatments / 2]
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labels += ["\n\n\n\n$\\theta_{{{}}}$".format(0)]
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for t in np.arange(1, n_periods):
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plt.axvline(x=t * (len(hetero_inds) + 1) *
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n_treatments - .5, linestyle='-', alpha=.6)
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locs += [t * (len(hetero_inds) + 1) * n_treatments - .501 +
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(len(hetero_inds) + 1) * n_treatments / 2]
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labels += ["\n\n\n\n$\\theta_{{{}}}$".format(t)]
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locs += [t * (len(hetero_inds) + 1) *
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n_treatments - .501 + (len(hetero_inds) + 1) / 2]
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labels += ["\n\n$\\tau_{{{}}}$".format(0)]
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locs += [t * (len(hetero_inds) + 1) * n_treatments +
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qx for qx in np.arange(len(hetero_inds) + 1)]
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labels += ["$1$"] + ["$x_{{{}}}$".format(qx) for qx in hetero_inds]
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for q in np.arange(1, n_treatments):
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plt.axvline(x=t * (len(hetero_inds) + 1) * n_treatments + q * (len(hetero_inds) + 1) - .5,
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linestyle='--', color='red', alpha=.2)
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locs += [t * (len(hetero_inds) + 1) * n_treatments + q *
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(len(hetero_inds) + 1) - .501 + (len(hetero_inds) + 1) / 2]
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labels += ["\n\n$\\tau_{{{}}}$".format(q)]
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locs += [t * (len(hetero_inds) + 1) * n_treatments + (q * (len(hetero_inds) + 1) + qx)
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for qx in np.arange(len(hetero_inds) + 1)]
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labels += ["$1$"] + ["$x_{{{}}}$".format(qx) for qx in hetero_inds]
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plt.xticks(locs, labels)
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plt.tight_layout()

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