Python log示例

示例#1

文件： segmentation.py 项目： genialwang/lambda-image

def debug(labeled_stack, image_stack, min_radius, max_radiusm, prop):
    prop = clustering(prop,6)
    log('info')("clustering over")
    cell_table = prop.groupby(level='label').apply(df_average, 'intensitysum')
    cell_table.to_pickle("cell_table.pkl")
    cell_table.to_csv("cell_show.csv")
    #cell_map = labeln(properties, labeled_stack)
    del cell_table['tag']
    return cell_table

示例#2

文件： test.py 项目： genialwang/lambda-image

def func1():
    log('info')('tiff load start...')
    rddA = tsc.loadImages('/home/wb/Microtube1-300-2-1k_12.tif', inputFormat='tif-stack')
    #rddB = tsc.loadImages('/home/wb/data/1-R/*.tif', inputFormat='tif-stack')
    #rddA = tsc.loadImages('/home/wb/data/1-L/*.tif', inputFormat='tif-stack')
    #rddB = tsc.loadImages('/home/wb/data/1-R/*.tif', inputFormat='tif-stack')
    #print rddA.collectValuesAsArray()
    #print rddA.collect()
    print rddA.collectValuesAsArray()
    #return rddA, rddB
    return rddA
    log('info')('tiff load over...')

示例#3

文件： segmentation.py 项目： genialwang/lambda-image

def clustering(prop, threshold):
    import scipy.cluster.hierarchy as hier
    log("info")("clustering start...")
    positions = prop[['x', 'y', 'z']].copy()
    print positions.values.shape
    log("info")("akka")
    cluster_idx = hier.fclusterdata(positions.values, threshold, criterion='distance')
    log("info")("ooover")
    prop['new_label'] = cluster_idx
    prop.set_index('new_label', drop=True, append=False, inplace=True)
    prop.index.name = 'label' 
    prop = prop.sort_index()
    return prop

示例#4

文件： mehi_standalone.py 项目： merlinzone/lambda-image

# Date     : 2015/07/25 16:14:09
# FileName : main.py
################################

from lambdaimage import preprocess as prep
from lambdaimage import registration as reg
from lambdaimage import fusion as fus
from pyspark import SparkContext, SparkConf
from lambdaimage import lambdaimageContext
from lambdaimage.utils.tool import exeTime, log, showsize
import numpy as np

#conf = SparkConf().setAppName('test').setMaster('local[1]').set('spark.executor.memory','2g').set('spark.driver.maxResultSize','6g').set('spark.driver.memory','8g').set('spark.local.dir','/dev/shm').set('spark.storage.memoryFraction','0.2').set('spark.default.parallelism','10')
#tsc=lambdaimageContext.start(conf=conf)
tsc = lambdaimageContext.start(master="spark://blade12:7077",appName="lambdaimage")
log('info')('tiff load start...')
rddA = tsc.loadImages('/home/wb/data/1-L/*.tif', inputFormat='tif-stack')
rddB = tsc.loadImages('/home/wb/data/1-R/*.tif', inputFormat='tif-stack')
log('info')('tiff load over...')

log('info')('intensity normalization start ...')
rddA = prep.intensity_normalization(rddA)
rddB = prep.intensity_normalization(rddB)
rddB = prep.flip(rddB)

_rddA = prep.intensity_normalization(rddA,8)
_rddB = prep.intensity_normalization(rddB,8)
log('info')('intensity normalization over ...')

log('info')('registration start ...')
vec0 = [0,0,0,1,1,0,0]

示例#5

文件： main.py 项目： genialwang/lambda-image

from lambdaimage import fusion as fus
from lambdaimage import segmentation as seg
from lambdaimage import lambdaimageContext
from lambdaimage.utils.tool import exeTime, log
from pyspark import SparkContext, SparkConf
from parseXML import load_xml_file, get_function
import numpy as np
import time

conf = SparkConf().setAppName('test').setMaster('local[1]').set('spark.executor.memory','2g').set('spark.driver.maxResultSize','6g').set('spark.driver.memory','8g').set('spark.local.dir','/dev/shm').set('spark.storage.memoryFraction','0.2').set('spark.default.parallelism','10')
tsc=lambdaimageContext.start(conf=conf)

result = load_xml_file("./lambdaimage.xml")
count = 0

log('info')('load tiff ...')
rddA = tsc.loadImages('/home/wb/data/1-L/*.tif', inputFormat='tif-stack')
rddB = tsc.loadImages('/home/wb/data/1-R/*.tif', inputFormat='tif-stack')

log('info')('preprocess ...')
fun, para = get_function(count, result)
_rddA = eval(fun)(rddA,int(para[0]))
print fun
_rddB = eval(fun)(rddB,int(para[0]))
print fun
count += 1
fun, para = get_function(count, result)
_rddB = eval(fun)(_rddB)
print fun
rddB = eval(fun)(rddB)
print fun

示例#6

文件： mehi_local.py 项目： genialwang/lambda-image

conf = (
    SparkConf()
    .setAppName("test")
    .setMaster("local[1]")
    .set("spark.executor.memory", "2g")
    .set("spark.driver.maxResultSize", "6g")
    .set("spark.driver.memory", "8g")
    .set("spark.local.dir", "/dev/shm")
    .set("spark.storage.memoryFraction", "0.2")
    .set("spark.default.parallelism", "10")
)
tsc = lambdaimageContext.start(conf=conf)

result = load_xml_file("./lambdaimage.xml")

log("info")("tiff load start...")
rddA = tsc.loadImages("/home/wb/data/1-L/*.tif", inputFormat="tif-stack")
rddB = tsc.loadImages("/home/wb/data/1-R/*.tif", inputFormat="tif-stack")
log("info")("tiff load over...")
log("info")("intensity normalization start ...")
rddA = prep.intensity_normalization(rddA)
rddB = prep.intensity_normalization(rddB)
rddB = prep.flip(rddB)

_rddA = prep.intensity_normalization(rddA, 8)
_rddB = prep.intensity_normalization(rddB, 8)
log("info")("intensity normalization over ...")

log("info")("registration start ...")
vec0 = [0, 0, 0, 1, 1, 0, 0]
# vec = reg.c_powell(_rddA.get(4), _rddB.get(4), vec0)