Python load示例

示例#1

文件： Assign.py 项目： kingshukmajumder/LEGO

def Assign(i,lhs,rhs):
    ## Preprocessing:
    ll = base.load('assign.ll')
    
    ## Processing:
    #-------------------------------------------------------------------
    code = ''.join(ll)
    code = code.replace('<i>','%s'%i)
    code = code.replace('${memlhs}',lhs)
    code = code.replace('${memrhs}',rhs)
    return code

示例#2

文件： If.py 项目： kingshukmajumder/LEGO

def If(i,cond,if_body,else_body):

    ## Preprocessing:
    ll = base.load('If.ll')
    
    ## Processing:
    #-------------------------------------------------------------------
    code = ''.join(ll)
    code = code.replace('<i>','%s'%i)
    code = code.replace('${cond}',cond)
    code = code.replace('${if_body}',if_body)
    code = code.replace('${else_body}',else_body)
    return code

示例#3

文件： Num.py 项目： kingshukmajumder/LEGO

def Num(i, Num, begin_annotation=";START"):
    ## Preprocessing:
    ll = base.load("Num.ll", begin_annotation)

    ## Processing:
    # -------------------------------------------------------------------

    code = "".join(ll)
    code = code.replace("<i>", "%s" % i)

    code = code.replace("${Num}", str(Num))
    out = "memz_%s" % i
    return out, code

示例#4

 def corr(self):
     self.set_subset('silhouette')
     df = self.acc_single()
     df['dataset'] = 'silhouette'
     human = base.load(pref='preds', exp=self.exp, suffix='human')
     df['human_accuracy'] = np.nan
     n = len(df.dataset.unique())
     mean_acc = human[human.kind == 'silhouette'].groupby('no').acc.mean()
     df.loc[:, 'human_accuracy'] = mean_acc.tolist() * n
     df = df[df.sel]
     df.model_accuracy = df.model_accuracy.astype(int)
     sns.set_palette(sns.color_palette('Set2')[1:])
     self._corr(df, 'all')

示例#5

文件： While.py 项目： kingshukmajumder/LEGO

def While(i,cond,test_body,body):

    ## Preprocessing:
    ll = base.load('while.ll')
    
    ## Processing:
    #-------------------------------------------------------------------
    code = ''.join(ll)
    code = code.replace('<i>','%s'%i)
    code = code.replace('${cond}',cond)
    code = code.replace('${test_body}',test_body)
    code = code.replace('${body}',body)
    return code

示例#6

文件： Module.py 项目： kingshukmajumder/LEGO

def Module(i,modName,body,begin_annotation = ';START'):
    ## Preprocessing:
    ll = base.load('module.ll',begin_annotation)
    
    ## Processing:
    #-------------------------------------------------------------------
    
    code = ''.join(ll)
    code = code.replace('<i>','%s'%i)

    code = code.replace('${modname}',modName)
    code = code.replace('${body}',body)
    return code

示例#7

文件： run.py 项目： mageed/conv-exp

 def corr(self):
     self.set_subset('silhouette')
     df = self.acc_single()
     df['dataset'] = 'silhouette'
     human = base.load(pref='preds', exp=self.exp, suffix='human')
     df['human_accuracy'] = np.nan
     n = len(df.dataset.unique())
     mean_acc = human[human.kind=='silhouette'].groupby('no').acc.mean()
     df.loc[:,'human_accuracy'] = mean_acc.tolist() * n
     df = df[df.sel]
     df.model_accuracy = df.model_accuracy.astype(int)
     sns.set_palette(sns.color_palette('Set2')[1:])
     self._corr(df, 'all')

示例#8

文件： logicNot.py 项目： kingshukmajumder/LEGO

def logicNot(i,x,begin_annotation = ';START'):
    ## Preprocessing:
    ll = base.load('logicNot.ll',begin_annotation)
    
    ## Processing:
    #-------------------------------------------------------------------
    
    code = ''.join(ll)
    code = code.replace('<i>','%s'%i)

    code = code.replace('${memx}',x)
    out = 'memz_%s'%i
    return out,code

示例#9

    def pred_corr(self, value='accuracy', method='corr'):
        human = base.load(pref='preds', exp=self.exp, suffix='human')
        human = human.groupby(['kind', 'no']).acc.mean()

        dfs = []
        for subset in ORDER:
            self.set_subset(subset)
            df = self._pred_corr(human.loc[subset], value=value, method=method)
            df['dataset'] = subset
            dfs.append(df)
        df = pandas.concat(dfs, ignore_index=True)
        print(df.groupby('dataset').mean())
        if self.task == 'run':
            self.plot_single(df, 'pred_corr')
        return df

示例#10

文件： logical.py 项目： kingshukmajumder/LEGO

def logical(i,x,y,op,begin_annotation = ';START'):
    ## Preprocessing:
    ll = base.load('logical.ll',begin_annotation)
    
    ## Processing:
    #-------------------------------------------------------------------
    
    code = ''.join(ll)
    code = code.replace('<i>','%s'%i)

    code = code.replace('${memx}',x)
    code = code.replace('${memy}',y)
    code = code.replace('${op}', opMap[op])
    out = 'memz_%s'%i
    return out,code

示例#11

文件： run.py 项目： mageed/conv-exp

    def pred_corr(self, value='accuracy', method='corr'):
        human = base.load(pref='preds', exp=self.exp, suffix='human')
        human = human.groupby(['kind', 'no']).acc.mean()

        dfs = []
        for subset in ORDER:
            self.set_subset(subset)
            df = self._pred_corr(human.loc[subset], value=value, method=method)
            df['dataset'] = subset
            dfs.append(df)
        df = pandas.concat(dfs, ignore_index=True)
        print(df.groupby('dataset').mean())
        if self.task == 'run':
            self.plot_single(df, 'pred_corr')
        return df

示例#12

文件： compare.py 项目： kingshukmajumder/LEGO

def compare(i,x,y,op,begin_annotation = ';START'):
    ## Preprocessing:
    ll = base.load('comp.ll',begin_annotation)
    
    ## Processing:
    #-------------------------------------------------------------------
    
    code = ''.join(ll)
    code = code.replace('<i>','%s'%i)

    code = code.replace('${memx}',x)
    code = code.replace('${memy}',y)
    code = code.replace('${opi}', opMap[op][0])
    code = code.replace('${opf}', opMap[op][1])
    out = 'memz_%s'%i
    return out,code

示例#13

文件： run.py 项目： mageed/conv-exp

    def behav(self):
        self.model_name = 'behav'
        human = base.load(pref='preds', exp=self.exp, suffix='human')
        sil = pandas.read_csv('snodgrass/data/sil_human_acc.csv', header=None) / 100.
        sil2 = human.groupby(['kind', 'no']).acc.mean()
        corr = np.corrcoef(sil.values.ravel(), sil2['silhouette'].values)[0,1]
        cons = 1 - scipy.spatial.distance.sqeuclidean(sil.values.ravel(),
                                            sil2['silhouette'].values) / 260
        sel, _ = self.filter_synset_ids()
        human = human[human.synset_id.isin(sel)]

        if self.task == 'run':
            sns.factorplot('kind', 'acc', data=human, units='subjid',
                            kind='bar', color=self.colors['shape'])
            self.show(pref='acc')
            self.html.writetable(human.groupby('kind').acc.mean())
            self.html.write('<p>Correlation old-new: {:.2f}</p>'.format(corr))
            self.html.write('<p>Consistency old-new: {:.2f}</p>'.format(cons))
        return human

示例#14

文件： cprint.py 项目： kingshukmajumder/LEGO

def cprint(i,args):
    ## Preprocessing:
    ll = base.load('print.ll')
    
    ## Processing:
    #-------------------------------------------------------------------
    code = ''.join(ll)
    
    arglist = ''
    loader = ''
    for j,arg in enumerate(args):
        loader += '%%arg%s_%s.TYPE =  load i32* %%%s.TYPE'%(j+1,i,arg)
        loader += '%%arg%s_%s.n =  load i64* %%%s.n'%(j+1,i,arg)
        
        arglist+=',i32 %%arg%s_%s.TYPE'%(j+1,i)
        arglist+=',i64 %%arg%s_%s.n'%(j+1,i)
    
    print len(args)
    code = loader + code.replace('${args}','i32 %s %s'%(len(args),arglist))
    
    return code

示例#15

    def behav(self):
        self.model_name = 'behav'
        human = base.load(pref='preds', exp=self.exp, suffix='human')
        sil = pandas.read_csv('snodgrass/data/sil_human_acc.csv',
                              header=None) / 100.
        sil2 = human.groupby(['kind', 'no']).acc.mean()
        corr = np.corrcoef(sil.values.ravel(), sil2['silhouette'].values)[0, 1]
        cons = 1 - scipy.spatial.distance.sqeuclidean(
            sil.values.ravel(), sil2['silhouette'].values) / 260
        sel, _ = self.filter_synset_ids()
        human = human[human.synset_id.isin(sel)]

        if self.task == 'run':
            sns.factorplot('kind',
                           'acc',
                           data=human,
                           units='subjid',
                           kind='bar',
                           color=self.colors['shape'])
            self.show(pref='acc')
            self.html.writetable(human.groupby('kind').acc.mean())
            self.html.write('<p>Correlation old-new: {:.2f}</p>'.format(corr))
            self.html.write('<p>Consistency old-new: {:.2f}</p>'.format(cons))
        return human

示例#16

文件： __init__.py 项目： zenefits/simpleflow

import sys

import base


for k, v in base.load().iteritems():
    setattr(sys.modules[__name__], k, v)

示例#17

文件： main.py 项目： joaofelipesus/cad_lla

import cv2
from segmentation import kmeans
from models import Image
from segmentation import remove_red_cells
from segmentation import background_removal
from base import load
from segmentation import otsu
from matplotlib import pyplot as plt
import numpy as np
from math import sqrt

path = 'bases/ALL_IDB1/'
images = load(path)
#images = [images[3]]

for image in images:
    lab_image = cv2.cvtColor(image.image, cv2.COLOR_BGR2LAB)
    hsv_image = cv2.cvtColor(image.image, cv2.COLOR_BGR2HSV)
    yuv_image = cv2.cvtColor(image.image, cv2.COLOR_BGR2YUV)
    gray_image = cv2.cvtColor(image.image, cv2.COLOR_BGR2GRAY)
    blue, green, red = cv2.split(image.image)
    hue, saturation, value = cv2.split(hsv_image)
    l, a, b = cv2.split(lab_image)
    y, u, v = cv2.split(yuv_image)
    '''
	#cv2.imwrite('temp/temp/blue_' + image.name, blue)
	cv2.imwrite('temp/temp/green_' + image.name, green)
	#cv2.imwrite('temp/temp/red_' + image.name, red)
	cv2.imwrite('temp/temp/hue_' + image.name, hue)
	cv2.imwrite('temp/temp/saturation_' + image.name, saturation)
	#cv2.imwrite('temp/temp/value_' + image.name, value)

示例#18

文件： models.py 项目： vikram/django-redisbackend

 def _makeobj(self, key):
     obj = self._model()
     r = redis_connection()
     res = r.get(key)
     if res: obj.__dict__.update( load(res))
     return obj

示例#19

文件： __init__.py 项目： walkinreeds/simpleflow

import sys

import base

for k, v in base.load().iteritems():
    setattr(sys.modules[__name__], k, v)