| #! /usr/bin/env python | |
| # Script to migrate from Everyday to CloseUp (iOS apps for snapping daily photos) | |
| # Instructions: https://closeup.wtf/everyday-import | |
| # It seems that Everyday flips photos horizontally compared to CloseUp. | |
| # CloseUp is like a mirror, but the photos from Everyday are the opposite (right on left). | |
| # This script asks whether to flip the Everyday photos during export. | |
| from __future__ import print_function # in case of python2 |
Includes the ability to record system audio
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| -- adapted from https://gist.github.com/gabriel-r/f98886d589682d1429744bdbfbfbe11a | |
| -- Create as an Automator Service: Receives "no input" in "any application" | |
| -- System Preferences > Keyboard > Shortcuts > Services: Set keyboard shortcut (e.g., Cmd-Shift-E) | |
| -- Must select URL in browser (Cmd-L) before triggering with keyboard shortcut | |
| tell application "System Events" | |
| set activeApp to name of first application process whose frontmost is true | |
| if "Safari" is in activeApp then | |
| set theURL to missing value | |
| tell application "Safari" | |
| if (exists window 1) then |
| from __future__ import division | |
| import pandas as pd | |
| import numpy as np | |
| import seaborn as sns | |
| from matplotlib import pyplot as plt | |
| # import matplotlib as mpl | |
| # import os | |
| from sklearn.ensemble import RandomForestClassifier | |
| from sklearn.linear_model import LogisticRegression |
| # calculate and visualize silhouette score from k-means clustering. | |
| # plots first two features in 2D and first three features in 3D. | |
| # from: http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html | |
| from sklearn.cluster import KMeans | |
| from sklearn.metrics import silhouette_score, silhouette_samples | |
| from mpl_toolkits.mplot3d import Axes3D | |
| ##### cluster data into K=1..K_MAX clusters ##### | |
| K_MAX = 10 |
| from __future__ import print_function | |
| import matplotlib.pyplot as plt | |
| from matplotlib.path import Path | |
| from matplotlib.spines import Spine | |
| from matplotlib.projections.polar import PolarAxes | |
| from matplotlib.projections import register_projection | |
| import numpy as np | |
| import seaborn as sns | |
| def radar_plot(data, feat_labels=[], line_labels=None, colors=None, ax=None, frame='circle', **kwargs): |