kats installation error
aayushL opened this issue · comments
Hello,
I am trying to install kats library using pip but I am getting below error:
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for numpy
Running setup.py clean for numpy
error: subprocess-exited-with-error
python setup.py clean did not run successfully.
exit code: 1
[10 lines of output]
Running from numpy source directory.
`setup.py clean` is not supported, use one of the following instead:
- `git clean -xdf` (cleans all files)
- `git clean -Xdf` (cleans all versioned files, doesn't touch
files that aren't checked into the git repo)
Add `--force` to your command to use it anyway if you must (unsupported).
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed cleaning build dir for numpy
Failed to build numpy
ERROR: Could not build wheels for numpy, which is required to install pyproject.toml-based projects
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error
× pip subprocess to install build dependencies did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
@iamxiaodong is there any update on this?
#python3.8
pip install numpy
pip install pandas
pip install convertdate
pip install lunarcalendar
pip install holidays==0.23
pip install tqdm
pip install pystan==2.19.1.1
pip install fbprophet==0.7.1
pip install kats
pip install Packaging==21.3
I met the same error. Kats is so difficult to install. and it seems the authors won't do any updates
this is example:
import numpy as np
import pandas as pd
from kats.consts import TimeSeriesData
from kats.detectors.cusum_detection import CUSUMDetector
# simulate time series with increase
np.random.seed(10)
df_increase = pd.DataFrame(
{
'time': pd.date_range('2019-01-01', '2019-03-01'),
'increase':np.concatenate([np.random.normal(1,0.2,30), np.random.normal(2,0.2,30)]),
}
)
# convert to TimeSeriesData object
timeseries = TimeSeriesData(df_increase)
# run detector and find change points
change_points = CUSUMDetector(timeseries).detector()
print("change_points:",change_points)
Hi everyone. I was running into this issue in Databricks. This is what worked for me:
- Use Databricks Runtime Version <= 11.3 LTS (which includes Python 3.9.5)
- Install
torch==2.0.1
.
You can refer to here
closed with fdependency fixes