Comments (1)
Error log:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
C:\Users\jenoel\AppData\Local\Continuum\anaconda3\envs\Orion\lib\site-packages\pandas\core\internals\managers.py in create_block_manager_from_blocks(blocks, axes)
1650 blocks = [make_block(values=blocks[0],
-> 1651 placement=slice(0, len(axes[0])))]
1652
C:\Users\jenoel\AppData\Local\Continuum\anaconda3\envs\Orion\lib\site-packages\pandas\core\internals\blocks.py in make_block(values, placement, klass, ndim, dtype, fastpath)
3094
-> 3095 return klass(values, ndim=ndim, placement=placement)
3096
C:\Users\jenoel\AppData\Local\Continuum\anaconda3\envs\Orion\lib\site-packages\pandas\core\internals\blocks.py in __init__(self, values, placement, ndim)
86 'Wrong number of items passed {val}, placement implies '
---> 87 '{mgr}'.format(val=len(self.values), mgr=len(self.mgr_locs)))
88
ValueError: Wrong number of items passed 1, placement implies 3
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
in
3 pipeline_path = '../orion/pipelines/lstm_dynamic_threshold.json'
4
----> 5 anomalies = analyze(pipeline_path, train, test)
6 anomalies
C:\Users\jenoel\AppData\Local\Continuum\anaconda3\envs\Orion\lib\site-packages\orion\analysis.py in analyze(pipeline, train, test)
36 LOGGER.debug("%s events found", len(events))
37
---> 38 events = pd.DataFrame(events, columns=['start', 'end', 'score'])
39 events['start'] = events['start'].astype(int)
40 events['end'] = events['end'].astype(int)
C:\Users\jenoel\AppData\Local\Continuum\anaconda3\envs\Orion\lib\site-packages\pandas\core\frame.py in __init__(self, data, index, columns, dtype, copy)
422 else:
423 mgr = init_ndarray(data, index, columns, dtype=dtype,
--> 424 copy=copy)
425
426 # For data is list-like, or Iterable (will consume into list)
C:\Users\jenoel\AppData\Local\Continuum\anaconda3\envs\Orion\lib\site-packages\pandas\core\internals\construction.py in init_ndarray(values, index, columns, dtype, copy)
165 values = maybe_infer_to_datetimelike(values)
166
--> 167 return create_block_manager_from_blocks([values], [columns, index])
168
169
C:\Users\jenoel\AppData\Local\Continuum\anaconda3\envs\Orion\lib\site-packages\pandas\core\internals\managers.py in create_block_manager_from_blocks(blocks, axes)
1658 blocks = [getattr(b, 'values', b) for b in blocks]
1659 tot_items = sum(b.shape[0] for b in blocks)
-> 1660 construction_error(tot_items, blocks[0].shape[1:], axes, e)
1661
1662
C:\Users\jenoel\AppData\Local\Continuum\anaconda3\envs\Orion\lib\site-packages\pandas\core\internals\managers.py in construction_error(tot_items, block_shape, axes, e)
1687 raise e
1688 if block_shape[0] == 0:
-> 1689 raise ValueError("Empty data passed with indices specified.")
1690 raise ValueError("Shape of passed values is {0}, indices imply {1}".format(
1691 passed, implied))
ValueError: Empty data passed with indices specified.
from orion.
Related Issues (20)
- CSV Analysis Example with Custom Data HOT 2
- Problem with pip install HOT 2
- Point Anomaly Setting for CSV Analysis HOT 2
- Understand the significance of different errors and their ranges, and few hyperparameters HOT 5
- Different F1 score for same signal for different time_segments_aggregate interval HOT 8
- MacOS compatibility: METAL HOT 5
- Reproduction of the tadGAN results over NASA telemetry dataset, as given in the corresponding research paper HOT 8
- Migrate `setup.py` and `setup.cfg` to `pyproject.toml`
- point_confusion_matrix when both ground truth and predicted anomalies lists are empty.
- Request for UCR Dataset Download in CSV Format HOT 5
- TadGAN for Audio HOT 1
- Orion model re-training by initializing model with trained model info HOT 1
- Discrepancy in Reproduced F1 Scores Compared to Published Results HOT 1
- Data Leakage in training HOT 1
- ValueError: Axis 2 is outside the dimensions of X (1). HOT 1
- ImportError: cannot import name 'Orion' from 'orion' HOT 1
- Suggestions for new evaluation metrics. HOT 1
- TimeStamp Number intervals Less than 109 cause error HOT 1
- How to remove "mlstars.custom.timeseries_preprocessing.time_segments_aggregate" from pipeline for custom data HOT 1
- type object 'Conv1D' has no attribute 'UpSampling1D' HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from orion.