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Upgrade pysal to version 1.14.3

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This solves a problem with the Markov analysis. Otherwise, with some
inputs it gives the following error:

```
Analysis A2 failed:
ValueError: operands could not be broadcast together with shapes (5) (3)
```

The stack trace is the following:
```
ERROR:  ValueError: operands could not be broadcast together with shapes (5) (2)
CONTEXT:  Traceback (most recent call last):
  PL/Python function "cdb_spatialmarkovtrend", line 7, in <module>
    return markov.spatial_trend(subquery, time_cols, num_classes, w_type, num_ngbrs, permutations, geom_col, id_col)
  PL/Python function "cdb_spatialmarkovtrend", line 76, in spatial_trend
  PL/Python function "cdb_spatialmarkovtrend", line 416, in __init__
  PL/Python function "cdb_spatialmarkovtrend", line 498, in _mn_test
  PL/Python function "cdb_spatialmarkovtrend", line 526, in _ssmnp_test
PL/Python function "cdb_spatialmarkovtrend"
```

and here is the line where it actually fails:
https://github.com/pysal/pysal/blob/v1.11.2/pysal/spatial_dynamics/markov.py#L526

In v1.14.3, the `shtest` is opt-in. So this gives us a chance to curate data if we wanted to apply that test, optionally, instead of crashing:

https://github.com/pysal/pysal/blob/v1.14.3/pysal/spatial_dynamics/markov.py#L490
This commit is contained in:
Rafa de la Torre 2018-02-22 16:00:41 +01:00
parent eefb0d7990
commit 4a81710749
2 changed files with 2 additions and 2 deletions
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2
src/py/crankshaft/requirements.txt
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@ -1,5 +1,5 @@
joblib==0.8.3 joblib==0.8.3
numpy==1.6.1 numpy==1.6.1
scipy==0.14.0 scipy==0.14.0
pysal==1.11.2 pysal==1.14.3
scikit-learn==0.14.1 scikit-learn==0.14.1

2
src/py/crankshaft/setup.py
View File

@ -41,7 +41,7 @@ setup(
# The choice of component versions is dictated by what's # The choice of component versions is dictated by what's
# provisioned in the production servers. # provisioned in the production servers.
# IMPORTANT NOTE: please don't change this line. Instead issue a ticket to systems for evaluation. # IMPORTANT NOTE: please don't change this line. Instead issue a ticket to systems for evaluation.
install_requires=['joblib==0.8.3', 'numpy==1.6.1', 'scipy==0.14.0', 'pysal==1.11.2', 'scikit-learn==0.14.1'], install_requires=['joblib==0.8.3', 'numpy==1.6.1', 'scipy==0.14.0', 'pysal==1.14.3', 'scikit-learn==0.14.1'],
requires=['pysal', 'numpy', 'sklearn'], requires=['pysal', 'numpy', 'sklearn'],