Python pipe Beispiele

Beispiel #1

Datei: run_taiwan_analysis.py Projekt: XiaoxiaoLiu/morphology_analysis

#DATA='/home/xiaoxiaol/work/data'
#DATA='/data/mat/xiaoxiaol/data/big_neuron'
DATA='/mnt/BigNeuron/data'
test = 0

smooth = 1
data_DIR= DATA+"/taiwan16k"


fn_list = '~/work/data/taiwan_image_file_name_list.csv'
df_i = pd.read_csv(fn_list)
imageIDs = df_i['image_file_name']
if test:
     ids = np.random.randint(1,15921,100)
     ids = range(1,100,1)
     imageIDs = imageIDs[ids]
     # imageIDs= imageIDs.astype('str')
# for im in images[random_ids]:




subfolder = "consensus_0330"
if smooth>0:
       subfolder=subfolder+"_anisosmooth"
output_dir = data_DIR+'/'+subfolder+"/analysis_results"
mc2c.pipe(data_DIR+'/'+subfolder, output_dir, imageIDs,'median_distances.csv',COLLECT_FROM_DISTANCE_MATRIX=1,EXTRACT_MEDIAN_CONSENSUS=1)

Beispiel #2

Datei: run_taiwan_analysis.py Projekt: reddqian/morphology_analysis

import bigneuron.median_compare_to_consensus as mc2c

#DATA='/home/xiaoxiaol/work/data'
#DATA='/data/mat/xiaoxiaol/data/big_neuron'
DATA = '/mnt/BigNeuron/data'
test = 0

smooth = 1
data_DIR = DATA + "/taiwan16k"

fn_list = '~/work/data/taiwan_image_file_name_list.csv'
df_i = pd.read_csv(fn_list)
imageIDs = df_i['image_file_name']
if test:
    ids = np.random.randint(1, 15921, 100)
    ids = range(1, 100, 1)
    imageIDs = imageIDs[ids]
    # imageIDs= imageIDs.astype('str')
# for im in images[random_ids]:

subfolder = "consensus_0330"
if smooth > 0:
    subfolder = subfolder + "_anisosmooth"
output_dir = data_DIR + '/' + subfolder + "/analysis_results"
mc2c.pipe(data_DIR + '/' + subfolder,
          output_dir,
          imageIDs,
          'median_distances.csv',
          COLLECT_FROM_DISTANCE_MATRIX=1,
          EXTRACT_MEDIAN_CONSENSUS=1)

Beispiel #3

Datei: run_gold166_consensus_analysis.py Projekt: XiaoxiaoLiu/morphology_analysis

if (platform.system() == "Linux"):
    WORK_PATH = "/local1/xiaoxiaol/work"
else:
    WORK_PATH = "/Users/xiaoxiaoliu/work"

p = WORK_PATH + '/src/morphology_analysis'
sys.path.append(p)

import  bigneuron.median_compare_to_consensus as mc2c

import pandas as pd



subfolder="0401_gold163_all_soma_sort"
#subfolder="gold_163_all_soma_sort_0328"
data_DIR="/data/mat/xiaoxiaol/data/big_neuron/silver/"+subfolder


df_nd = pd.read_csv(data_DIR+'/list.txt')
imageIDs = df_nd['image_id'].apply(str)


mc2c.pipe(input_data_dir=data_DIR, output_dir=data_DIR+"/analysis_results", imageIDs=imageIDs,distance_file_postfix='median_distances.csv', COLLECT_FROM_DISTANCE_MATRIX=1,EXTRACT_MEDIAN_CONSENSUS=1, DISPLAY=0)
print "\n\n\n"

Beispiel #4

import os
import platform

if (platform.system() == "Linux"):
    WORK_PATH = "/local1/xiaoxiaol/work"
else:
    WORK_PATH = "/Users/xiaoxiaoliu/work"

p = WORK_PATH + '/src/morphology_analysis'
sys.path.append(p)

import bigneuron.median_compare_to_consensus as mc2c

import pandas as pd

subfolder = "0401_gold163_all_soma_sort"
#subfolder="gold_163_all_soma_sort_0328"
data_DIR = "/data/mat/xiaoxiaol/data/big_neuron/silver/" + subfolder

df_nd = pd.read_csv(data_DIR + '/list.txt')
imageIDs = df_nd['image_id'].apply(str)

mc2c.pipe(input_data_dir=data_DIR,
          output_dir=data_DIR + "/analysis_results",
          imageIDs=imageIDs,
          distance_file_postfix='median_distances.csv',
          COLLECT_FROM_DISTANCE_MATRIX=1,
          EXTRACT_MEDIAN_CONSENSUS=1,
          DISPLAY=0)
print "\n\n\n"