Thomas Wiecki

Print valid cli arguments for [part] in usage string

8

I run: ``` bumpversion --config .bumpversion.cfg --new-version 0.5.2 ``` My config: ``` [bumpversion] files = README.rst docs/Makefile docs/make.py hddm/__init__.py commit = True tag = True current_version = 0.5.2.beta ``` Which...

keras support

2

Are there plans to add keras support to gelato?

# ## FAIL: test_gsl_blas_zherk (test_blas.BlasTest) Traceback (most recent call last): File "cython_gsl/test/test_blas.py", line 228, in test_gsl_blas_zherk self.assertAlmostEqual(x,0, 14) AssertionError: -1.6000000000000001 != 0 within 14 places # ## FAIL: test_gsl_linalg_LU_refine (test_linalg.LinalgTest)...

``` .. autosummary:: :toctree: close next_cell next_row /Users/twiecki/working/projects/quant/alphalens/alphalens/tears.py:docstring of alphalens.tears.create_event_returns_tear_sheet_api_change_warning:5: WARNING: Unexpected indentation. /Users/twiecki/working/projects/quant/alphalens/alphalens/tears.py:docstring of alphalens.tears.create_event_returns_tear_sheet_api_change_warning:11: WARNING: Block quote ends without a blank line; unexpected unindent. /Users/twiecki/working/projects/quant/alphalens/alphalens/tears.py:docstring of alphalens.tears.create_full_tear_sheet_api_change_warning:5: WARNING:...

literal_unroll leads to segfault on M1 when called with bool

27

MWE: ``` import numba, numpy as np op_axis = ((0, True),) # sefault #op_axis = ((0, 1),) # works #op_axis = (True,) # works @numba.njit def test(x): numba.literal_unroll(op_axis) test(np.zeros(1)) ```...

Port book to PyMC 4.0

7

With PyMC 4.0 almost ready, we should work on porting the examples here. Most models should continue to run just fine.

Prediction could be better if shape of observed would not need to be considered

13

When I have a simple model: ```python import pymc as pm with pm.Model() as m: x = pm.MutableData("x", input_data) y = pm.MutableData("y" , output_data) beta = pm.Normal("beta") y_est = x...

ZeroInflatedPoisson and ZeroInflatedNegativeBinomial show up as Deterministic on graphviz

2

It's probably because they are not pure RandomVariables. We need to update the `model_graph` logic to accommodate them

Port timeseries distributions to V4

20

```python import pymc3 as pm import numpy as np returns = pd.read_csv(pm.get_data("SP500.csv"), index_col="Date") returns["change"] = np.log(returns["Close"]).diff() returns = returns.dropna().astype('float32') returns.head() with pm.Model() as model_pymc3: step_size = pm.Exponential("step_size", 10.) volatility =...

Write v4 upgrade guide

13

In anticipation of the big v4 release we should start to write a document walking people through the upgrade process. Specifically, this document should contain: * Information about the Theano->Aesara...