gireeshkbogu

import sys
import os
from PIL import Image
import shutil
import numpy as np


mask_dir = "/Users/gireeshbogu/Downloads/MSNYD_8_22_17/MSNYD_8_22_17__AB_AXT1_fl2d_inopp_mbh_15/masks_machine/"
new_mask_dir = "/Users/gireeshbogu/Downloads/MSNYD_8_22_17__AB_AXT1_fl2d_inopp_mbh_15_masks/"
if not os.path.exists(new_mask_dir):

gireeshkbogu

# identify images with at least one mask (sum of all pixels > 0) and copy them to a new folder
# usage: script.py mask_dir new_mask_dir

import sys
import os
from PIL import Image
import shutil
import pandas as pd
import numpy as np

gireeshkbogu

from glob import glob                                                           
import cv2 
jpgs = glob('./*.jpg')

for image in jpgs:
    img = cv2.imread(image)
    cv2.imwrite(image[:-3] + 'png', img)

gireeshkbogu

# Simulate Omics style data for ML

import uuid
import itertools


features = 700
subjects = 40

columns_list = []

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library(ggplot2)

# plot volcano plot
res <- read.table("Male_vs_Female_Pre", head=TRUE)
res$Significant <- ifelse(res$adj.P.Val < 0.05, "adj.P.Val < 0.05", "Not Significant")
ggplot(res, aes(x = logFC, y = -log10(P.Value))) +
  geom_point(aes(color = Significant)) +
  scale_color_manual(values = c("red", "grey")) +
  theme_bw(base_size = 12) + theme(legend.position = "bottom") +
  geom_text_repel(