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fonnesbeck / log.txt
Created May 23, 2023 16:48
VSCode logging for remote extension installation
View log.txt
2023-05-23 11:18:55.462 [warning] Via 'product.json#extensionEnabledApiProposals' extension 'ms-vscode.vscode-selfhost-test-provider' wants API proposal 'testContinuousRun' but that proposal DOES NOT EXIST. Likely, the proposal has been finalized (check 'vscode.d.ts') or was abandoned.
2023-05-23 11:18:55.794 [error] Extension 'github.copilot' appears in product.json but enables LESS API proposals than the extension wants.
package.json (LOSES): inlineCompletionsAdditions, terminalDataWriteEvent
product.json (WINS): inlineCompletionsAdditions
2023-05-23 11:18:55.848 [info] Invoking resolveAuthority(attached-container)...
2023-05-23 11:18:55.849 [info] [LocalProcess0][resolveAuthority(attached-container,1)][0ms] obtaining proxy...
2023-05-23 11:18:55.849 [info] [LocalProcess0][resolveAuthority(attached-container,1)][0ms] invoking...
2023-05-23 11:18:56.852 [info] [LocalProcess0][resolveAuthority(attached-container,1)][1004ms] waiting...
2023-05-23 11:18:57.854 [info] [LocalProcess0][resolveAuthority(attached-co
View Covariate Model-First_Paper.ipynb
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View Tables.ipynb
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@fonnesbeck
fonnesbeck / StudentT.ipynb
Created August 12, 2019 18:21
StudentT sampling
View StudentT.ipynb
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View more_curves.py
more_curves = [1810, 2225, 3015]
with curve_spin_model:
pm.set_data({'spin': more_curves})
post_pred = pm.sample_posterior_predictive(trace, samples=1000)
View glm_data.py
df = pd.DataFrame(dict(y=np.array([2, 4, 2, 0, 4])))
with pm.Model() as glm:
x = np.array([0.3, 1.1, 0.6, -0.2, 3.3])
pm.glm.GLM.from_formula('y ~ x', data=df, family=pm.glm.families.Poisson())
View predict_curves.py
traces = {}
for year in years:
with curve_spin_model:
year_data = curveball_data.query('year==@year')
pm.set_data({'spin': year_data.spin_rate,
'swing_miss': year_data.miss})
traces[year] = pm.sample(1000, tune=2000,
cores=2, progressbar=False)
View curve_spin_model.py
with pm.Model() as curve_spin_model:
spin = pm.Data('spin', curveball_data['spin_rate'])
β = pm.Normal('β', shape=2)
θ = β[0] + β[1]*(spin/1000)
swing_miss = pm.Data('swing_miss', curveball_data['miss'])
miss = pm.Bernoulli('miss', pm.invlogit(θ), observed=swing_miss)
View Measles Dynamics2.ipynb
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View simple_compare_example.ipynb
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