Hi,
I'm running into an error that I've not seen before. I'm using already-featurized trajectories stored as text numpy arrays, to compare the performance of different featurizers.
Here's the osprey config file:
estimator:
eval: |
Pipeline([
('tica', tICA()),
('cluster', MiniBatchKMeans()),
('msm', MarkovStateModel(lag_time=100, n_timescales=5, verbose=True)),
])
eval_scope: msmbuilder
strategy:
name: random
search_space:
cluster__n_clusters:
min: 10
max: 10000
type: int
tica__lag_time:
min: 1
max: 1000
type: jump
warp: log
var_type: int
num: 10
tica__commute_mapping:
choices:
- True
- False
type: enum
tica__n_components:
min: 1
max: 20
type: int
cv:
name: shufflesplit
params:
n_iter: 5
test_size: 0.25
dataset_loader:
name: numpy
params:
filenames: ftrajs/*
trials:
uri: sqlite:///osprey-trials.db
And here's the output: https://pastebin.com/gtZxxwEt
I've previously done this kind of workflow, so I don't really know what might've gone wrong.
Best regards,
Juan
Hi,
I'm running into an error that I've not seen before. I'm using already-featurized trajectories stored as text numpy arrays, to compare the performance of different featurizers.
Here's the osprey config file:
And here's the output: https://pastebin.com/gtZxxwEt
I've previously done this kind of workflow, so I don't really know what might've gone wrong.
Best regards,
Juan