<jupyter_start><jupyter_text>Testing gabors<jupyter_code>%matplotlib inline
from skimage.filters import gabor_kernel
from skimage import io
from matplotlib import pyplot as plt  
import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm

size = np.linspace(-np.pi,np.pi,200)
xgrid, ygrid = np.meshgrid(size, size)

gaussian = np.exp(-(xgrid/2)**2-(ygrid/2)**2) 
sine = np.sin(xgrid*10)
gabor = sine * gaussian
plt.imshow(gabor,cm.gray) 
plt.show()
np.arange(0,2*math.pi,0.1)
import pymongo as pm
connection = pm.MongoClient(port=24444)
connection.database_names()
db = connection['imagenet']
col1 = db['alexnet']
exp_out = list(col1.find({'exp_id': 'experiment_1'}))
exp_out
exp_out<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13306451612903225, 'fraction_numerical': 0.028225806451612902, 'mean_word_length': 6.303921568627451, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '275848', 'license': 'MIT', 'n_tokens_mistral': 304, 'n_tokens_neox': 298, 'n_words': 63, 'path': 'test_environment-PooledBottleneck.ipynb', 'repo_name': 'dbirman/cs375', 'size': '744'}