so… I’m back. I have a new error. this command worked in a smaller dataset but not in the full big ukbb dataset. full stack trace below:

## 2018-10-22 17:54:59 Hail: INFO: Wrote all 420 blocks of 13373 x 426047 matrix with block size 4096.

2018-10-22 20:38:59 Hail: INFO: wrote 420 items in 420 partitions

ValueError Traceback (most recent call last)

in ()

1 #test on simple model

2 #testing on a smaller dataset worked, but this doesn’t

----> 3 model, _ =hl.linear_mixed_model(y=mtn_filter1.Height1,x=[1, mtn_filter1.YOB, mtn_filter1.is_female],z_t=mtn_filter1.GT.n_alt_alleles(),p_path=‘s3://output5’)

in linear_mixed_model(y, x, z_t, k, p_path, overwrite, standardize, mean_impute)

Code/Hail-devel-90a5cab4aab8/python/hail/typecheck/check.py in wrapper(__original_func, *args, **kwargs)

558 def wrapper(*original_func, *args, **kwargs):*

559 args, kwargs = check_all(__original_func, args, kwargs, checkers, is_method=is_method)

–> 560 return *original_func(*args*, **kwargs)

561

562 return wrapper

Code/Hail-devel-90a5cab4aab8/python/hail/methods/statgen.py in linear_mixed_model(y, x, z_t, k, p_path, overwrite, standardize, mean_impute)

874 normalize=standardize).T # variance is 1 / n

875 m = z_bm.shape[1]

–> 876 model, p = LinearMixedModel.from_random_effects(y_nd, x_nd, z_bm, p_path, overwrite)

877 if standardize:

878 model.s = model.s * (n / m) # now variance is 1 / m

in from_random_effects(cls, y, x, z, p_path, overwrite, max_condition_number, complexity_bound)

Code/Hail-devel-90a5cab4aab8/python/hail/typecheck/check.py in wrapper(__original_func, *args, **kwargs)

558 def wrapper(*original_func, *args, **kwargs):*

559 args, kwargs = check_all(__original_func, args, kwargs, checkers, is_method=is_method)

–> 560 return *original_func(*args*, **kwargs)

561

562 return wrapper

Code/Hail-devel-90a5cab4aab8/python/hail/stats/linear_mixed_model.py in from_random_effects(cls, y, x, z, p_path, overwrite, max_condition_number, complexity_bound)

1111

1112 if low_rank:

-> 1113 model = LinearMixedModel(py, px, s, y, x, p_path)

1114 else:

1115 model = LinearMixedModel(py, px, s, p_path=p_path)

in **init**(self, py, px, s, y, x, p_path)

Code/Hail-devel-90a5cab4aab8/python/hail/typecheck/check.py in wrapper(__original_func, *args, **kwargs)

558 def wrapper(*original_func, *args, **kwargs):*

559 args, kwargs = check_all(__original_func, args, kwargs, checkers, is_method=is_method)

–> 560 return *original_func(*args*, **kwargs)

561

562 return wrapper

Code/Hail-devel-90a5cab4aab8/python/hail/stats/linear_mixed_model.py in **init**(self, py, px, s, y, x, p_path)

289 raise ValueError(‘for low-rank, set both y and x; for full-rank, do not set y or x.’)

290

–> 291 _check_dims(py, ‘py’, 1)

292 _check_dims(px, ‘px’, 2)

293 _check_dims(s, ‘s’, 1)

Code/Hail-devel-90a5cab4aab8/python/hail/linalg/utils/misc.py in _check_dims(a, name, ndim, min_size)

231 def _check_dims(a, name, ndim, min_size=1):

232 if len(a.shape) != ndim:

–> 233 raise ValueError(f’{name} must be {ndim}-dimensional, ’

234 f’found {a.ndim}’)

235 for i in range(ndim):

ValueError: py must be 1-dimensional, found 2