DOC: Fix many aliases #602
Merged
Azure Pipelines / bashtage.linearmodels
succeeded
Jul 19, 2024 in 32m 43s
Build #20240719.2 had test failures
Details
- Failed: 4 (0.00%)
- Passed: 162,305 (83.26%)
- Other: 32,619 (16.73%)
- Total: 194,928
- 17235 of 17288 line covered (99.69%)
Annotations
Check failure on line 953 in Build log
azure-pipelines / bashtage.linearmodels
Build log #L953
Bash exited with code '1'.
Check failure on line 1 in test_notebook[iv_advanced-examples]
azure-pipelines / bashtage.linearmodels
test_notebook[iv_advanced-examples]
nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
------------------
from statsmodels.api import OLS, add_constant
data["const"] = 1
controls = ["const"] + controls
------------------
#x1B[0;31m---------------------------------------------------------------------------#x1B[0m
#x1B[0;31mValueError#x1B[0m Traceback (most recent call last)
Cell #x1B[0;32mIn[6], line 1#x1B[0m
#x1B[0;32m----> 1#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01mstatsmodels#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m OLS, add_constant
#x1B[1;32m 3#x1B[0m data[#x1B[38;5;124m"#x1B[39m#x1B[38;5;124mconst#x1B[39m#x1B[38;5;124m"#x1B[39m] #x1B[38;5;241m=#x1B[39m #x1B[38;5;241m1#x1B[39m
#x1B[1;32m 4#x1B[0m controls #x1B[38;5;241m=#x1B[39m [#x1B[38;5;124m"#x1B[39m#x1B[38;5;124mconst#x1B[39m#x1B[38;5;124m"#x1B[39m] #x1B[38;5;241m+#x1B[39m controls
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/api.py:123#x1B[0m
#x1B[1;32m 112#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgenmod#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m api #x1B[38;5;28;01mas#x1B[39;00m genmod
#x1B[1;32m 113#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgenmod#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m (
#x1B[1;32m 114#x1B[0m GEE,
#x1B[1;32m 115#x1B[0m GLM,
#x1B[0;32m (...)#x1B[0m
#x1B[1;32m 121#x1B[0m families,
#x1B[1;32m 122#x1B[0m )
#x1B[0;32m--> 123#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgraphics#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m api #x1B[38;5;28;01mas#x1B[39;00m graphics
#x1B[1;32m 124#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgraphics#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgofplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m ProbPlot, qqline, qqplot, qqplot_2samples
#x1B[1;32m 125#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mimputation#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mbayes_mi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m MI, BayesGaussMI
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/graphics/api.py:9#x1B[0m
#x1B[1;32m 7#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgofplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m qqplot
#x1B[1;32m 8#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mplottools#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m rainbow
#x1B[0;32m----> 9#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mregressionplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m (
#x1B[1;32m 10#x1B[0m abline_plot,
#x1B[1;32m 11#x1B[0m influence_plot,
#x1B[1;32m 12#x1B[0m plot_ccpr,
#x1B[1;32m 13#x1B[0m plot_ccpr_grid,
#x1B[1;32m 14#x1B[0m plot_fit,
#x1B[1;32m 15#x1B[0m plot_leverage_resid2,
#x1B[1;32m 16#x1B[0m plot_partregress,
#x1B[1;32m 17#x1B[0m plot_partregress_grid,
#x1B[1;32m 18#x1B[0m plot_regress_exog,
#x1B[1;32m 19#x1B[0m )
#x1B[1;32m 21#x1B[0m __all__ #x1B[38;5;241m=#x1B[39m [
#x1B[1;32m 22#x1B[0m #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mabline_plot#x1B[39m#x1B[38;5;124m"#x1B[39m,
#x1B[1;32m 23#x1B[0m #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mbeanplot#x1B[39m#x1B[38;5;124m"#x1B[39m,
#x1B[0;32m (...)#x1B[0m
#x1B[1;32m 42#x1B[0m #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mviolinplot#x1B[39m#x1B[38;5;124m"#x1B[39m,
#x1B[1;32m 43#x1B[0m ]
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/graphics/regressionplots.py:23#x1B[0m
#x1B[1;32m 21#x1B[0m #
Raw output
notebook = '/home/vsts/work/1/s/examples/iv_advanced-examples.ipynb'
@pytest.mark.slow
@pytest.mark.example
@pytest.mark.skipif(SKIP, reason="Required packages not available")
def test_notebook(notebook):
nb_name = os.path.split(notebook)[-1]
if MISSING_XARRAY and nb_name in NOTEBOOKS_USING_XARRAY:
pytest.skip(f"xarray is required to test {notebook}")
nb = nbformat.read(notebook, as_version=4)
ep = ExecutePreprocessor(allow_errors=False, timeout=120, kernel_name=kernel_name)
> ep.preprocess(nb, {"metadata": {"path": NOTEBOOK_DIR}})
linearmodels/tests/test_examples.py:68:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbconvert/preprocessors/execute.py:103: in preprocess
self.preprocess_cell(cell, resources, index)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbconvert/preprocessors/execute.py:124: in preprocess_cell
cell = self.execute_cell(cell, index, store_history=True)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/jupyter_core/utils/__init__.py:165: in wrapped
return loop.run_until_complete(inner)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/asyncio/base_events.py:687: in run_until_complete
return future.result()
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbclient/client.py:1062: in async_execute_cell
await self._check_raise_for_error(cell, cell_index, exec_reply)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <nbconvert.preprocessors.execute.ExecutePreprocessor object at 0x7f9a9bf09f70>
cell = {'cell_type': 'code', 'execution_count': 6, 'metadata': {'execution': {'iopub.status.busy': '2024-07-19T07:43:39.91743...t']}], 'source': 'from statsmodels.api import OLS, add_constant\n\ndata["const"] = 1\ncontrols = ["const"] + controls'}
cell_index = 12
exec_reply = {'buffers': [], 'content': {'ename': 'ValueError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'ef23f4c9-d710-4363...e, 'engine': 'ef23f4c9-d710-4363-87a7-8077988def6b', 'started': '2024-07-19T07:43:39.919895Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
self, cell: NotebookNode, cell_index: int, exec_reply: dict[str, t.Any] | None
) -> None:
if exec_reply is None:
return None
exec_reply_content = exec_reply["content"]
if exec_reply_content["status"] != "error":
return None
cell_allows_errors = (not self.force_raise_errors) and (
self.allow_errors
or exec_reply_content.get("ename") in self.allow_error_names
or "raises-exception" in cell.metadata.get("tags", [])
)
await run_hook(
self.on_cell_error, cell=cell, cell_index=cell_index, execute_reply=exec_reply
)
if not cell_allows_errors:
> raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)
E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E from statsmodels.api import OLS, add_constant
E
E data["const"] = 1
E controls = ["const"] + controls
E ------------------
E
E
E #x1B[0;31m---------------------------------------------------------------------------#x1B[0m
E #x1B[0;31mValueError#x1B[0m Traceback (most recent call last)
E Cell #x1B[0;32mIn[6], line 1#x1B[0m
E #x1B[0;32m----> 1#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01mstatsmodels#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m OLS, add_constant
E #x1B[1;32m 3#x1B[0m data[#x1B[38;5;124m"#x1B[39m#x1B[38;5;124mconst#x1B[39m#x1B[38;5;124m"#x1B[39m]
Check failure on line 1 in test_notebook[iv_basic-examples]
azure-pipelines / bashtage.linearmodels
test_notebook[iv_basic-examples]
nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
------------------
import numpy as np
from linearmodels.datasets import mroz
from statsmodels.api import add_constant
print(mroz.DESCR)
data = mroz.load()
data = data.dropna()
data = add_constant(data, has_constant="add")
------------------
#x1B[0;31m---------------------------------------------------------------------------#x1B[0m
#x1B[0;31mValueError#x1B[0m Traceback (most recent call last)
Cell #x1B[0;32mIn[1], line 3#x1B[0m
#x1B[1;32m 1#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mnumpy#x1B[39;00m #x1B[38;5;28;01mas#x1B[39;00m #x1B[38;5;21;01mnp#x1B[39;00m
#x1B[1;32m 2#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01mlinearmodels#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mdatasets#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m mroz
#x1B[0;32m----> 3#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01mstatsmodels#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m add_constant
#x1B[1;32m 5#x1B[0m #x1B[38;5;28mprint#x1B[39m(mroz#x1B[38;5;241m.#x1B[39mDESCR)
#x1B[1;32m 6#x1B[0m data #x1B[38;5;241m=#x1B[39m mroz#x1B[38;5;241m.#x1B[39mload()
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/api.py:123#x1B[0m
#x1B[1;32m 112#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgenmod#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m api #x1B[38;5;28;01mas#x1B[39;00m genmod
#x1B[1;32m 113#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgenmod#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m (
#x1B[1;32m 114#x1B[0m GEE,
#x1B[1;32m 115#x1B[0m GLM,
#x1B[0;32m (...)#x1B[0m
#x1B[1;32m 121#x1B[0m families,
#x1B[1;32m 122#x1B[0m )
#x1B[0;32m--> 123#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgraphics#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m api #x1B[38;5;28;01mas#x1B[39;00m graphics
#x1B[1;32m 124#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgraphics#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgofplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m ProbPlot, qqline, qqplot, qqplot_2samples
#x1B[1;32m 125#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mimputation#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mbayes_mi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m MI, BayesGaussMI
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/graphics/api.py:9#x1B[0m
#x1B[1;32m 7#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgofplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m qqplot
#x1B[1;32m 8#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mplottools#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m rainbow
#x1B[0;32m----> 9#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mregressionplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m (
#x1B[1;32m 10#x1B[0m abline_plot,
#x1B[1;32m 11#x1B[0m influence_plot,
#x1B[1;32m 12#x1B[0m plot_ccpr,
#x1B[1;32m 13#x1B[0m plot_ccpr_grid,
#x1B[1;32m 14#x1B[0m plot_fit,
#x1B[1;32m 15#x1B[0m plot_leverage_resid2,
#x1B[1;32m 16#x1B[0m plot_partregress,
#x1B[1;32m 17#x1B[0m plot_partregress_grid,
#x1B[1;32m 18#x1B[0m plot_regress_exog,
#x1B[1;32m 19#x1B[0m )
#x1B[1;32m 21#x1B[0m __all__ #x1B[38;5;241m=#x1B[39m [
#x1B[1;32m 22#x1B[0m #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mabline_plot#x1B[39m#x1B[38;5;124m"#x1B[39m,
#x1B[1;32m 23#x1B[0m #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mbeanplot#x1B[39m#x1B[38;5;124m"#x1B[39m,
#x1B[0;32m (.
Raw output
notebook = '/home/vsts/work/1/s/examples/iv_basic-examples.ipynb'
@pytest.mark.slow
@pytest.mark.example
@pytest.mark.skipif(SKIP, reason="Required packages not available")
def test_notebook(notebook):
nb_name = os.path.split(notebook)[-1]
if MISSING_XARRAY and nb_name in NOTEBOOKS_USING_XARRAY:
pytest.skip(f"xarray is required to test {notebook}")
nb = nbformat.read(notebook, as_version=4)
ep = ExecutePreprocessor(allow_errors=False, timeout=120, kernel_name=kernel_name)
> ep.preprocess(nb, {"metadata": {"path": NOTEBOOK_DIR}})
linearmodels/tests/test_examples.py:68:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbconvert/preprocessors/execute.py:103: in preprocess
self.preprocess_cell(cell, resources, index)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbconvert/preprocessors/execute.py:124: in preprocess_cell
cell = self.execute_cell(cell, index, store_history=True)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/jupyter_core/utils/__init__.py:165: in wrapped
return loop.run_until_complete(inner)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/asyncio/base_events.py:687: in run_until_complete
return future.result()
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbclient/client.py:1062: in async_execute_cell
await self._check_raise_for_error(cell, cell_index, exec_reply)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <nbconvert.preprocessors.execute.ExecutePreprocessor object at 0x7f9a9c497c20>
cell = {'cell_type': 'code', 'execution_count': 1, 'metadata': {'execution': {'iopub.status.busy': '2024-07-19T07:43:45.68038...onstant\n\nprint(mroz.DESCR)\ndata = mroz.load()\ndata = data.dropna()\ndata = add_constant(data, has_constant="add")'}
cell_index = 3
exec_reply = {'buffers': [], 'content': {'ename': 'ValueError', 'engine_info': {'engine_id': -1, 'engine_uuid': '226e4948-a990-41d6...e, 'engine': '226e4948-a990-41d6-8c14-6fa60eba76d9', 'started': '2024-07-19T07:43:45.681454Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
self, cell: NotebookNode, cell_index: int, exec_reply: dict[str, t.Any] | None
) -> None:
if exec_reply is None:
return None
exec_reply_content = exec_reply["content"]
if exec_reply_content["status"] != "error":
return None
cell_allows_errors = (not self.force_raise_errors) and (
self.allow_errors
or exec_reply_content.get("ename") in self.allow_error_names
or "raises-exception" in cell.metadata.get("tags", [])
)
await run_hook(
self.on_cell_error, cell=cell, cell_index=cell_index, execute_reply=exec_reply
)
if not cell_allows_errors:
> raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)
E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E import numpy as np
E from linearmodels.datasets import mroz
E from statsmodels.api import add_constant
E
E print(mroz.DESCR)
E data = mroz.load()
E data = data.dropna()
E data = add_constant(data, has_constant="add")
E ------------------
E
E
E #x1B[0;31m---------------------------------------------------------------------------#x1B[0m
E #x1B[0;31mValueError#x1B[0m Traceback (most recent call last)
E Cell #x1B[0;32mIn[1], line 3#x1B[0m
E #x1B[1;32m 1#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mnumpy#x1B[39;00m #x1B[38;5;28;01mas#x1B[39;00m #x1B[38;5;21;01mnp#x1B[39;00m
E #x1B[1;
Check failure on line 1 in test_notebook[panel_examples]
azure-pipelines / bashtage.linearmodels
test_notebook[panel_examples]
nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
------------------
import statsmodels.api as sm
from linearmodels.panel import PooledOLS
exog_vars = ["black", "hisp", "exper", "expersq", "married", "educ", "union", "year"]
exog = sm.add_constant(data[exog_vars])
mod = PooledOLS(data.lwage, exog)
pooled_res = mod.fit()
print(pooled_res)
------------------
#x1B[0;31m---------------------------------------------------------------------------#x1B[0m
#x1B[0;31mValueError#x1B[0m Traceback (most recent call last)
Cell #x1B[0;32mIn[2], line 1#x1B[0m
#x1B[0;32m----> 1#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mstatsmodels#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mas#x1B[39;00m #x1B[38;5;21;01msm#x1B[39;00m
#x1B[1;32m 2#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01mlinearmodels#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mpanel#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m PooledOLS
#x1B[1;32m 4#x1B[0m exog_vars #x1B[38;5;241m=#x1B[39m [#x1B[38;5;124m"#x1B[39m#x1B[38;5;124mblack#x1B[39m#x1B[38;5;124m"#x1B[39m, #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mhisp#x1B[39m#x1B[38;5;124m"#x1B[39m, #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mexper#x1B[39m#x1B[38;5;124m"#x1B[39m, #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mexpersq#x1B[39m#x1B[38;5;124m"#x1B[39m, #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mmarried#x1B[39m#x1B[38;5;124m"#x1B[39m, #x1B[38;5;124m"#x1B[39m#x1B[38;5;124meduc#x1B[39m#x1B[38;5;124m"#x1B[39m, #x1B[38;5;124m"#x1B[39m#x1B[38;5;124munion#x1B[39m#x1B[38;5;124m"#x1B[39m, #x1B[38;5;124m"#x1B[39m#x1B[38;5;124myear#x1B[39m#x1B[38;5;124m"#x1B[39m]
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/api.py:123#x1B[0m
#x1B[1;32m 112#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgenmod#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m api #x1B[38;5;28;01mas#x1B[39;00m genmod
#x1B[1;32m 113#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgenmod#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m (
#x1B[1;32m 114#x1B[0m GEE,
#x1B[1;32m 115#x1B[0m GLM,
#x1B[0;32m (...)#x1B[0m
#x1B[1;32m 121#x1B[0m families,
#x1B[1;32m 122#x1B[0m )
#x1B[0;32m--> 123#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgraphics#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m api #x1B[38;5;28;01mas#x1B[39;00m graphics
#x1B[1;32m 124#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgraphics#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgofplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m ProbPlot, qqline, qqplot, qqplot_2samples
#x1B[1;32m 125#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mimputation#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mbayes_mi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m MI, BayesGaussMI
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/graphics/api.py:9#x1B[0m
#x1B[1;32m 7#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgofplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m qqplot
#x1B[1;32m 8#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mplottools#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m rainbow
#x1B[0;32m----> 9#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mregressionplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m (
#x1B[1;32m 10#x1B[0m abline_plot,
#x1B[1;32m 11#x1B[0m influence_plot,
#x1B[1;32m 12#x1B[0m plot_ccpr,
#x1B[1;32m 13#x1B[0m plot_ccpr_grid,
#x1B[1;32m 14#x1B[0m plot_fit,
#x1B[1;32m 15#x1B[0m plot_leverage_resid2,
#x1B[1;32m 16#x1B[0m plot_partregress
Raw output
notebook = '/home/vsts/work/1/s/examples/panel_examples.ipynb'
@pytest.mark.slow
@pytest.mark.example
@pytest.mark.skipif(SKIP, reason="Required packages not available")
def test_notebook(notebook):
nb_name = os.path.split(notebook)[-1]
if MISSING_XARRAY and nb_name in NOTEBOOKS_USING_XARRAY:
pytest.skip(f"xarray is required to test {notebook}")
nb = nbformat.read(notebook, as_version=4)
ep = ExecutePreprocessor(allow_errors=False, timeout=120, kernel_name=kernel_name)
> ep.preprocess(nb, {"metadata": {"path": NOTEBOOK_DIR}})
linearmodels/tests/test_examples.py:68:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbconvert/preprocessors/execute.py:103: in preprocess
self.preprocess_cell(cell, resources, index)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbconvert/preprocessors/execute.py:124: in preprocess_cell
cell = self.execute_cell(cell, index, store_history=True)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/jupyter_core/utils/__init__.py:165: in wrapped
return loop.run_until_complete(inner)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/asyncio/base_events.py:687: in run_until_complete
return future.result()
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbclient/client.py:1062: in async_execute_cell
await self._check_raise_for_error(cell, cell_index, exec_reply)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <nbconvert.preprocessors.execute.ExecutePreprocessor object at 0x7f9a9c487c80>
cell = {'cell_type': 'code', 'execution_count': 2, 'metadata': {'execution': {'iopub.status.busy': '2024-07-19T07:44:10.11978...exog = sm.add_constant(data[exog_vars])\nmod = PooledOLS(data.lwage, exog)\npooled_res = mod.fit()\nprint(pooled_res)'}
cell_index = 4
exec_reply = {'buffers': [], 'content': {'ename': 'ValueError', 'engine_info': {'engine_id': -1, 'engine_uuid': '3e197fa3-ba25-4c77...e, 'engine': '3e197fa3-ba25-4c77-a513-3a3937e00e44', 'started': '2024-07-19T07:44:10.120573Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
self, cell: NotebookNode, cell_index: int, exec_reply: dict[str, t.Any] | None
) -> None:
if exec_reply is None:
return None
exec_reply_content = exec_reply["content"]
if exec_reply_content["status"] != "error":
return None
cell_allows_errors = (not self.force_raise_errors) and (
self.allow_errors
or exec_reply_content.get("ename") in self.allow_error_names
or "raises-exception" in cell.metadata.get("tags", [])
)
await run_hook(
self.on_cell_error, cell=cell, cell_index=cell_index, execute_reply=exec_reply
)
if not cell_allows_errors:
> raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)
E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E import statsmodels.api as sm
E from linearmodels.panel import PooledOLS
E
E exog_vars = ["black", "hisp", "exper", "expersq", "married", "educ", "union", "year"]
E exog = sm.add_constant(data[exog_vars])
E mod = PooledOLS(data.lwage, exog)
E pooled_res = mod.fit()
E print(pooled_res)
E ------------------
E
E
E #x1B[0;31m---------------------------------------------------------------------------#x1B[0m
E #x1B[0;31mValueError#x1B[0m Traceback (most recent call last)
E Cell #x1B[0;32mIn[2], line 1#x1B[0m
E #x1B[0;32m----> 1#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mstatsmodels#x1B[39;00m#x1B[38;5
Check failure on line 1 in test_notebook[system_examples]
azure-pipelines / bashtage.linearmodels
test_notebook[system_examples]
nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
------------------
# Common libraries
%matplotlib inline
import numpy as np
import pandas as pd
import statsmodels.api as sm
------------------
#x1B[0;31m---------------------------------------------------------------------------#x1B[0m
#x1B[0;31mValueError#x1B[0m Traceback (most recent call last)
Cell #x1B[0;32mIn[1], line 5#x1B[0m
#x1B[1;32m 3#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mnumpy#x1B[39;00m #x1B[38;5;28;01mas#x1B[39;00m #x1B[38;5;21;01mnp#x1B[39;00m
#x1B[1;32m 4#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mpandas#x1B[39;00m #x1B[38;5;28;01mas#x1B[39;00m #x1B[38;5;21;01mpd#x1B[39;00m
#x1B[0;32m----> 5#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mstatsmodels#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mas#x1B[39;00m #x1B[38;5;21;01msm#x1B[39;00m
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/api.py:123#x1B[0m
#x1B[1;32m 112#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgenmod#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m api #x1B[38;5;28;01mas#x1B[39;00m genmod
#x1B[1;32m 113#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgenmod#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mapi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m (
#x1B[1;32m 114#x1B[0m GEE,
#x1B[1;32m 115#x1B[0m GLM,
#x1B[0;32m (...)#x1B[0m
#x1B[1;32m 121#x1B[0m families,
#x1B[1;32m 122#x1B[0m )
#x1B[0;32m--> 123#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgraphics#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m api #x1B[38;5;28;01mas#x1B[39;00m graphics
#x1B[1;32m 124#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgraphics#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgofplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m ProbPlot, qqline, qqplot, qqplot_2samples
#x1B[1;32m 125#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mimputation#x1B[39;00m#x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mbayes_mi#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m MI, BayesGaussMI
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/graphics/api.py:9#x1B[0m
#x1B[1;32m 7#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mgofplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m qqplot
#x1B[1;32m 8#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mplottools#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m rainbow
#x1B[0;32m----> 9#x1B[0m #x1B[38;5;28;01mfrom#x1B[39;00m #x1B[38;5;21;01m.#x1B[39;00m#x1B[38;5;21;01mregressionplots#x1B[39;00m #x1B[38;5;28;01mimport#x1B[39;00m (
#x1B[1;32m 10#x1B[0m abline_plot,
#x1B[1;32m 11#x1B[0m influence_plot,
#x1B[1;32m 12#x1B[0m plot_ccpr,
#x1B[1;32m 13#x1B[0m plot_ccpr_grid,
#x1B[1;32m 14#x1B[0m plot_fit,
#x1B[1;32m 15#x1B[0m plot_leverage_resid2,
#x1B[1;32m 16#x1B[0m plot_partregress,
#x1B[1;32m 17#x1B[0m plot_partregress_grid,
#x1B[1;32m 18#x1B[0m plot_regress_exog,
#x1B[1;32m 19#x1B[0m )
#x1B[1;32m 21#x1B[0m __all__ #x1B[38;5;241m=#x1B[39m [
#x1B[1;32m 22#x1B[0m #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mabline_plot#x1B[39m#x1B[38;5;124m"#x1B[39m,
#x1B[1;32m 23#x1B[0m #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mbeanplot#x1B[39m#x1B[38;5;124m"#x1B[39m,
#x1B[0;32m (...)#x1B[0m
#x1B[1;32m 42#x1B[0m #x1B[38;5;124m"#x1B[39m#x1B[38;5;124mviolinplot#x1B[39m#x1B[38;5;124m"#x1B[39m,
#x1B[1;32m 43#x1B[0m ]
File #x1B[0;32m/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/statsmodels/graphics/regressionplots.py:23#x1B[0m
#x1B[1;32m 21#x1B[
Raw output
notebook = '/home/vsts/work/1/s/examples/system_examples.ipynb'
@pytest.mark.slow
@pytest.mark.example
@pytest.mark.skipif(SKIP, reason="Required packages not available")
def test_notebook(notebook):
nb_name = os.path.split(notebook)[-1]
if MISSING_XARRAY and nb_name in NOTEBOOKS_USING_XARRAY:
pytest.skip(f"xarray is required to test {notebook}")
nb = nbformat.read(notebook, as_version=4)
ep = ExecutePreprocessor(allow_errors=False, timeout=120, kernel_name=kernel_name)
> ep.preprocess(nb, {"metadata": {"path": NOTEBOOK_DIR}})
linearmodels/tests/test_examples.py:68:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbconvert/preprocessors/execute.py:103: in preprocess
self.preprocess_cell(cell, resources, index)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbconvert/preprocessors/execute.py:124: in preprocess_cell
cell = self.execute_cell(cell, index, store_history=True)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/jupyter_core/utils/__init__.py:165: in wrapped
return loop.run_until_complete(inner)
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/asyncio/base_events.py:687: in run_until_complete
return future.result()
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/site-packages/nbclient/client.py:1062: in async_execute_cell
await self._check_raise_for_error(cell, cell_index, exec_reply)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <nbconvert.preprocessors.execute.ExecutePreprocessor object at 0x7f9a9c487fe0>
cell = {'cell_type': 'code', 'execution_count': 1, 'metadata': {'execution': {'iopub.status.busy': '2024-07-19T07:44:22.38561...urce': '# Common libraries\n%matplotlib inline\nimport numpy as np\nimport pandas as pd\nimport statsmodels.api as sm'}
cell_index = 1
exec_reply = {'buffers': [], 'content': {'ename': 'ValueError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'a5be4baa-d6d4-4be0...e, 'engine': 'a5be4baa-d6d4-4be0-915b-0e101086f857', 'started': '2024-07-19T07:44:22.388331Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
self, cell: NotebookNode, cell_index: int, exec_reply: dict[str, t.Any] | None
) -> None:
if exec_reply is None:
return None
exec_reply_content = exec_reply["content"]
if exec_reply_content["status"] != "error":
return None
cell_allows_errors = (not self.force_raise_errors) and (
self.allow_errors
or exec_reply_content.get("ename") in self.allow_error_names
or "raises-exception" in cell.metadata.get("tags", [])
)
await run_hook(
self.on_cell_error, cell=cell, cell_index=cell_index, execute_reply=exec_reply
)
if not cell_allows_errors:
> raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)
E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E # Common libraries
E %matplotlib inline
E import numpy as np
E import pandas as pd
E import statsmodels.api as sm
E ------------------
E
E
E #x1B[0;31m---------------------------------------------------------------------------#x1B[0m
E #x1B[0;31mValueError#x1B[0m Traceback (most recent call last)
E Cell #x1B[0;32mIn[1], line 5#x1B[0m
E #x1B[1;32m 3#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mnumpy#x1B[39;00m #x1B[38;5;28;01mas#x1B[39;00m #x1B[38;5;21;01mnp#x1B[39;00m
E #x1B[1;32m 4#x1B[0m #x1B[38;5;28;01mimport#x1B[39;00m #x1B[38;5;21;01mpandas#x1B[39;00m #x1B[38;5;28;01mas#x1B[39;00m #x1B[38;5;21;01mpd#x
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