ValueError: ndarray is not C-contiguous

[jburos]

Encounter an error when testing hammelab/survivalstan@feature/royston-parmar (build log on wide data.

A reproducible example is:

import survivalstan
import numpy as np
import pandas as pd
from stancache import stancache

model_code = survivalstan.models.royston_parmar_survival_model

d = stancache.cached(
    survivalstan.sim.sim_data_exp_correlated,
    N=100,
    censor_time=20,
    rate_form='1 + sex',
    rate_coefs=[-3, 0.5],
)
d['age_centered'] = d['age'] - d['age'].mean()

testfit = survivalstan.fit_stan_survival_model(
    model_cohort = 'test model',
    model_code = model_code,
    df = d,
    formula = 'surv(event_status = event, time = t) ~ age_centered + sex',
    iter = 5000,
    chains = 4,
    seed = 9001,
    FIT_FUN = stancache.cached_stan_fit,
    )

Which generates the following output (with debug logging on):

DEBUG:stancache.stancache:cache_dir set to .cached_models
DEBUG:stancache.stancache:processing item (N) as int
DEBUG:stancache.stancache:processing item (censor_time) as int
DEBUG:stancache.stancache:processing item (rate_coefs) as other (using xxhash)
DEBUG:stancache.stancache:processing item (rate_coefs) as other (using pickle)
DEBUG:stancache.stancache:note: item (rate_coefs) is of type: <class 'list'>
DEBUG:stancache.stancache:processing item (rate_form) as str
INFO:stancache.stancache:sim_data_exp_correlated: cache_filename set to sim_data_exp_correlated.cached.N_100.censor_time_20.rate_coefs_54462717316.rate_form_1 + sex.pkl
DEBUG:stancache.stancache:sim_data_exp_correlated: cache_filepath set to .cached_models/sim_data_exp_correlated.cached.N_100.censor_time_20.rate_coefs_54462717316.rate_form_1 + sex.pkl
INFO:stancache.stancache:sim_data_exp_correlated: Loading result from cache
/home/jacki/projects/survivalstan/survivalstan/formulas.py:132: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  
/home/jacki/projects/survivalstan/survivalstan/formulas.py:133: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  class WideSurvData(SurvData):
/home/jacki/projects/survivalstan/survivalstan/formulas.py:132: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  
/home/jacki/projects/survivalstan/survivalstan/formulas.py:133: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  class WideSurvData(SurvData):
/home/jacki/projects/survivalstan/survivalstan/formulas.py:132: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  
/home/jacki/projects/survivalstan/survivalstan/formulas.py:133: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  class WideSurvData(SurvData):
/home/jacki/projects/survivalstan/survivalstan/formulas.py:132: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  
/home/jacki/projects/survivalstan/survivalstan/formulas.py:133: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  class WideSurvData(SurvData):
DEBUG:stancache.stancache:cache_dir set to .cached_models
DEBUG:stancache.stancache:processing item (cython) as str
DEBUG:stancache.stancache:processing item (model_code) as other (using xxhash)
DEBUG:stancache.stancache:note: item (model_code) is of type: <class 'str'>
DEBUG:stancache.stancache:processing item (pystan) as str
DEBUG:stancache.stancache:processing item (chains) as int
DEBUG:stancache.stancache:processing item (data) as dict
DEBUG:stancache.stancache:processing item (data-D) as int
DEBUG:stancache.stancache:processing item (data-M) as int
DEBUG:stancache.stancache:processing item (data-N) as int
DEBUG:stancache.stancache:processing item (data-basis_evals) as np.ndarray
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-33-1baa659d7e65> in <module>
     23     chains = 4,
     24     seed = 9001,
---> 25     FIT_FUN = stancache.cached_stan_fit,
     26     )

~/projects/survivalstan/survivalstan/survivalstan.py in fit_stan_survival_model(df, formula, event_col, model_code, file, model_cohort, time_col, sample_id_col, sample_col, group_id_col, group_col, timepoint_id_col, timepoint_end_col, make_inits, stan_data, grp_coef_type, FIT_FUN, drop_intercept, input_data, *args, **kwargs)
    165         data=input_data.data,
    166         *args,
--> 167         **kwargs
    168         )
    169 

/srv/conda/lib/python3.6/site-packages/stancache/stancache.py in cached_stan_fit(iter, chains, seed, *args, **kwargs)
    249     if seed is None:
    250         seed = config.get_setting_value('SEED')
--> 251     return _cached_stan_fit(seed=seed, iter=iter, chains=chains, **kwargs)
    252 
    253 

/srv/conda/lib/python3.6/site-packages/stancache/stancache.py in _cached_stan_fit(model_name, file, model_code, force, cache_dir, cache_only, fit_cachefile, **kwargs)
    213     model_cachefile, fit_cachefile = cached_stan_file(model_name=model_name, file=file, model_code=model_code,
    214                                                       cache_dir=cache_dir, fit_cachefile=fit_cachefile,
--> 215                                                       include_modelfile=True, **kwargs)
    216     cache_dir = _get_cache_dir(cache_dir)
    217     model_name = _sanitize_model_name(model_name)

/srv/conda/lib/python3.6/site-packages/stancache/stancache.py in cached_stan_file(model_name, file, model_code, cache_dir, fit_cachefile, cache_only, force, include_modelfile, prefix_only, **kwargs)
    174                                                       cache_dir=cache_dir, fit_cachefile=fit_cachefile, include_prefix=True)
    175     if not fit_cachefile:
--> 176         fit_cachefile = '.'.join([model_prefix, 'stanfit', _make_digest(dict(**kwargs)), 'pkl'])
    177     if include_modelfile:
    178         return model_cachefile, fit_cachefile

/srv/conda/lib/python3.6/site-packages/stancache/stancache.py in _make_digest(k, **kwargs)
    110     """
    111     result = list()
--> 112     result_dict = _make_digest_dict(k, **kwargs)
    113     if result_dict is None:
    114         return 'default'

/srv/conda/lib/python3.6/site-packages/stancache/stancache.py in _make_digest_dict(k, prefix)
     68             logger.debug('processing item ({}) as dict'.format(pre_key))
     69             item = dict(sorted(item.items()))
---> 70             s = _make_digest(item, prefix=key+'-')
     71             result.update({pre_key: _digest(s.encode())})
     72         elif isinstance(item, pd.DataFrame):

/srv/conda/lib/python3.6/site-packages/stancache/stancache.py in _make_digest(k, **kwargs)
    110     """
    111     result = list()
--> 112     result_dict = _make_digest_dict(k, **kwargs)
    113     if result_dict is None:
    114         return 'default'

/srv/conda/lib/python3.6/site-packages/stancache/stancache.py in _make_digest_dict(k, prefix)
     80         elif isinstance(item, np.ndarray):
     81             logger.debug('processing item ({}) as np.ndarray'.format(pre_key))
---> 82             s = _xxhash_item(item)
     83             result.update({pre_key: s})
     84         elif isinstance(item, types.FunctionType):

/srv/conda/lib/python3.6/site-packages/stancache/stancache.py in _xxhash_item(item)
     38 
     39 def _xxhash_item(item):
---> 40     h = xxhash.xxh64(item)
     41     s = h.intdigest()
     42     return s

ValueError: ndarray is not C-contiguous