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Geri Skenderi geriskenderi

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geriskenderi / logistic.py
Created February 3, 2025 23:05
python code to describe a generalized logistic function, useful for curve fitting and understanding when a transition happens
import numpy as np
from scipy.optimize import curve_fit
def logistic_fit(alpha, Q, b, v, alpha_N):
# Implements a more general logistic function (solution of Richards's DE with K=1)
return 1 / ((1 + Q * np.exp(-b*v*(alpha - alpha_N))) ** (1/v))
def generalized_logistic_threshold(alpha_N, b, Q, v):
# Calculate the threshold value of alpha_N given as the argument where the above generalized logistic function equals 0.5
correction_term = (np.log(2**v - 1) - np.log(Q)) / (-b*v)
@geriskenderi
geriskenderi / export_conda_pip_env.sh
Last active August 19, 2024 03:54
Export a Python environment that has packages installed with conda and pip
# Extract installed pip packages, export conda environment without builds, and then append pip packages
pip_packages=$(conda env export | grep -A9999 ".*- pip:" | grep -v "^prefix: ") && conda env export --from-history | grep -v "^prefix: " > environment.yml && echo "$pip_packages" >> environment.yml
@geriskenderi
geriskenderi / coco.sh
Created February 8, 2022 11:26 — forked from mkocabas/coco.sh
Download COCO dataset. Run under 'datasets' directory.
mkdir coco
cd coco
mkdir images
cd images
wget http://images.cocodataset.org/zips/train2017.zip
wget http://images.cocodataset.org/zips/val2017.zip
wget http://images.cocodataset.org/zips/test2017.zip
wget http://images.cocodataset.org/zips/unlabeled2017.zip
@geriskenderi
geriskenderi / py-gitignore
Created April 19, 2021 07:10 — forked from MOOOWOOO/py-gitignore
python pycharm gitignore
# Created by .ignore support plugin (hsz.mobi)
### Python template
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
@geriskenderi
geriskenderi / ts_attention.py
Created February 16, 2021 16:05 — forked from isaacmg/attend_preliminary.py
class AttendDiagnose(nn.Module):
def __init__(self, number_measurements, filter_number):
super().__init__()
self.d_model = filter_number*number_measurements
self.embedding_conv = nn.Conv1d(number_measurements, filter_number*number_measurements, 1)
self.pe = PositionalEncoding(filter_number*number_measurements)
# embed_dim and attention_heads
self.masked_attn = nn.modules.activation.MultiheadAttention(filter_number*number_measurements, 8)
self.norm = nn.modules.normalization.LayerNorm(self.d_model)
self.final_layer = nn.Linear(self.d_model, 1)
@geriskenderi
geriskenderi / gdrive_dw
Last active February 9, 2021 09:00 — forked from joppichristian/command
Download Google Drive Files using wget
#https://medium.com/@acpanjan/download-google-drive-files-using-wget-3c2c025a8b99
# change FILEID
# https://drive.google.com/file/d/1UibyVC_C2hoT_XEw15gPEwPW4yFyJFeOEA
# FILEID = 1UibyVC_C2hoT_XEw15gPEwPW4yFyJFeOEA
# tools
https://gdrive-wget.glitch.me/
# small file