UMAP segfault error

I get the following error when running UMAP through Seurat (which uses UMAP)

UMAP(a=None, angular_rp_forest=False, b=None, init='spectral',
     learning_rate=1.0, local_connectivity=1, metric='correlation',
     metric_kwds=None, min_dist=0.3, n_components=2, n_epochs=None,
     n_neighbors=30, negative_sample_rate=5, random_state=None,
     repulsion_strength=1.0, set_op_mix_ratio=1.0, spread=1.0,
     target_metric='categorical', target_metric_kwds=None,
     target_n_neighbors=-1, target_weight=0.5, transform_queue_size=4.0,
     transform_seed=42, verbose=True)
Construct fuzzy simplicial set
Fri Jul 12 09:51:05 2019 Finding Nearest Neighbors
Fri Jul 12 09:51:05 2019 Building RP forest with 10 trees
/Users/asmaimran/Library/Python/3.7/lib/python/site-packages/umap/rp_tree.py:469: NumbaWarning: 
Compilation is falling back to object mode WITH looplifting enabled because Function "make_angular_tree" failed type inference due to: Cannot unify RandomProjectionTreeNode(array(int64, 1d, C), bool, none, none, none, none) and RandomProjectionTreeNode(none, bool, array(float32, 1d, C), none, RandomProjectionTreeNode(array(int64, 1d, C), bool, none, none, none, none), RandomProjectionTreeNode(array(int64, 1d, C), bool, none, none, none, none)) for '$14.16', defined at /Users/asmaimran/Library/Python/3.7/lib/python/site-packages/umap/rp_tree.py (476)

File "Library/Python/3.7/lib/python/site-packages/umap/rp_tree.py", line 476:
def make_angular_tree(data, indices, rng_state, leaf_size=30):
    <source elided>

        left_node = make_angular_tree(data, left_indices, rng_state, leaf_size)
        ^

[1] During: resolving callee type: recursive(type(CPUDispatcher(<function make_angular_tree at 0x1b264f440>)))
[2] During: typing of call at /Users/asmaimran/Library/Python/3.7/lib/python/site-packages/umap/rp_tree.py (476)


File "Library/Python/3.7/lib/python/site-packages/umap/rp_tree.py", line 476:
def make_angular_tree(data, indices, rng_state, leaf_size=30):
    <source elided>

        left_node = make_angular_tree(data, left_indices, rng_state, leaf_size)
        ^

  @numba.jit()
/Users/asmaimran/Library/Python/3.7/lib/python/site-packages/numba/compiler.py:725: NumbaWarning: Function "make_angular_tree" was compiled in object mode without forceobj=True.

File "Library/Python/3.7/lib/python/site-packages/umap/rp_tree.py", line 470:
@numba.jit()
def make_angular_tree(data, indices, rng_state, leaf_size=30):
^

  self.func_ir.loc))
/Users/asmaimran/Library/Python/3.7/lib/python/site-packages/numba/compiler.py:734: NumbaDeprecationWarning: 
Fall-back from the nopython compilation path to the object mode compilation path has been detected, this is deprecated behaviour.

For more information visit http://numba.pydata.org/numba-doc/latest/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit

File "Library/Python/3.7/lib/python/site-packages/umap/rp_tree.py", line 470:
@numba.jit()
def make_angular_tree(data, indices, rng_state, leaf_size=30):
^

  warnings.warn(errors.NumbaDeprecationWarning(msg, self.func_ir.loc))
Fri Jul 12 09:51:05 2019 NN descent for 13 iterations
/Users/asmaimran/Library/Python/3.7/lib/python/site-packages/umap/nndescent.py:92: NumbaPerformanceWarning: 
The keyword argument 'parallel=True' was specified but no transformation for parallel execution was possible.

To find out why, try turning on parallel diagnostics, see http://numba.pydata.org/numba-doc/latest/user/parallel.html#diagnostics for help.

File "Library/Python/3.7/lib/python/site-packages/umap/utils.py", line 409:
@numba.njit(parallel=True)
def build_candidates(current_graph, n_vertices, n_neighbors, max_candidates, rng_state):
^

  current_graph, n_vertices, n_neighbors, max_candidates, rng_state
/Users/asmaimran/Library/Python/3.7/lib/python/site-packages/numba/compiler.py:588: NumbaPerformanceWarning: 
The keyword argument 'parallel=True' was specified but no transformation for parallel execution was possible.

To find out why, try turning on parallel diagnostics, see http://numba.pydata.org/numba-doc/latest/user/parallel.html#diagnostics for help.

File "Library/Python/3.7/lib/python/site-packages/umap/nndescent.py", line 47:
    @numba.njit(parallel=True)
    def nn_descent(
    ^

  self.func_ir.loc))
	 0  /  13
	 1  /  13
	 2  /  13
Fri Jul 12 09:51:10 2019 Finished Nearest Neighbor Search

 *** caught segfault ***
address 0xfffffffffffffffa, cause 'memory not mapped'

Traceback:
 1: py_call_impl(callable, dots$args, dots$keywords)
 2: umap$fit_transform(as.matrix(x = object))
 3: RunUMAP.default(object = data.use, assay = assay, n.neighbors = n.neighbors,     n.components = n.components, metric = metric, n.epochs = n.epochs,     learning.rate = learning.rate, min.dist = min.dist, spread = spread,     set.op.mix.ratio = set.op.mix.ratio, local.connectivity = local.connectivity,     repulsion.strength = repulsion.strength, negative.sample.rate = negative.sample.rate,     a = a, b = b, seed.use = seed.use, metric.kwds = metric.kwds,     angular.rp.forest = angular.rp.forest, reduction.key = reduction.key,     verbose = verbose)
 4: RunUMAP(object = data.use, assay = assay, n.neighbors = n.neighbors,     n.components = n.components, metric = metric, n.epochs = n.epochs,     learning.rate = learning.rate, min.dist = min.dist, spread = spread,     set.op.mix.ratio = set.op.mix.ratio, local.connectivity = local.connectivity,     repulsion.strength = repulsion.strength, negative.sample.rate = negative.sample.rate,     a = a, b = b, seed.use = seed.use, metric.kwds = metric.kwds,     angular.rp.forest = angular.rp.forest, reduction.key = reduction.key,     verbose = verbose)
 5: RunUMAP.Seurat(object = visp, dims = 1:26, min_dist = 0.75)
 6: RunUMAP(object = visp, dims = 1:26, min_dist = 0.75)

I am running python3, installed UMAP using pip and running on MacOSX. Any ideas about what maybe happening?

[diazdc]

Thanks for the speedy response everyone. Indeed, uwot was causing the problem, and was remedied by calling “umap-learn” as the preffered method. Here’s the command in context if anyone else stumbles into this problem: RunUMAP(seurat_obj, umap.method = "umap-learn", dims = 1:20)

[sleighsoft]

Seems like the inital question is solved with this.