def reduce_colours(img_rgb, final_colours):
if not isinstance(img_rgb, np.ndarray):
img_rgb = np.asarray(img_rgb) / 255
final_img = img_rgb.copy()
# TODO: check if the RGB2LAB conversion MUST occurs at the very last
# or if the problems I had were because of code problem uh
pb = ProgressBar('Reducing colours')
for i in range(final_img.shape[0]):
for j in range(final_img.shape[1]):
c1 = color.rgb2lab([[final_img[i, j]]])[0][0]
c2 = [color.rgb2lab([[x]])[0][0] for x in final_colours]
distances = [dst(c1, x) for x in c2]
final_img[i, j] = final_colours[distances.index(min(distances))]
pb.set_value(
floor((((i * final_img.shape[1]) + j) /
(final_img.shape[0] * final_img.shape[1])) * 100))
QApplication.processEvents()
pb.close()
return final_img
def append_root(self, root):
''' 添加一个root '''
data = self.read()
# 如果目录已存在，或是现有Root集的子路径，跳出；否则添加目录
for _root in data['Root']:
if _root == root or _root in root:
return
data['Root'].append(root)
# 初始化一个进度条
progress_bar = ProgressBar('Code Files')
# 添加目录下的所有文件
file_reader = FileReader()
file_list = file_reader.walk_folder(root)
total_number = len(file_list)
for index, file in enumerate(file_list):
# 获取文件基本信息
## 获取文件标识码
file_code = file_reader.code_file(file)
## 获取文件名和文件扩展名
file_basename = os.path.basename(file)
file_name, file_extension = os.path.splitext(file_basename)
## 获取文件大小
file_size_num = (int)(file_code.split('-')[-1])
file_size_num = round(file_size_num / 1024 / 1024)
file_size = str(file_size_num) + ' MB' if file_size_num < 1024 \
else str(round(file_size_num / 1024, 2)) + ' GB'
# 如果在已有数据中找不到文件，进行添加
if file not in data['File']:
data['File'][file] = {
'code': file_code,
'extension': file_extension,
'name': file_name,
'path': file,
'size': file_size,
}
# 进度条即时显示
progress_bar.set_value(index + 1, total_number)
QApplication.processEvents()
# 循环结束，关闭进度条
progress_bar.close()
# 回填更新后的数据
self.write(data)
def redraw_graphs(self):
def ts(x):
return x.total_seconds()
if self.list_of_files !=None:
# get data from the list of files given
# we'll open the files one by one, fetch the line
# get the timestamp from the line contaning ===Current Time===
# and then looking for any of the selected metrics
# put the results in the the pandas dataframe
#and then call the redraw events
self.metric_column=self.metric_column_d[self.metric]
rows_list=[]
self.first_time=False
priortime=None
nfiles=len(self.list_of_files)
pbar=ProgressBar(desc="Loading Files")
n=.5/nfiles
for fname in self.list_of_files:
if fname[-3:]=="bz2":
datfile=bz2.BZ2File(fname)
else:
datfile=open(fname,'r')
lines=datfile.readlines()
cellname=fname[fname.rindex('_',)+1:fname.index('.',fname.rindex('_',))]
pbar.setDescription("opening:"+os.path.basename(fname))
pbar.setValue(100*n)
n+=.5/nfiles
QtWidgets.QApplication.processEvents()
# print ("cellname=",cellname)
for s1 in lines:
s=s1.rstrip().decode("utf-8")
#print(s)
if re.search("PM|AM$",s)!=None:
# get the date after that
timeint=dt.datetime.strptime(s,"%m/%d/%Y %I:%M:%S %p")
timest=timeint.strftime("%Y-%m-%d_%H:%M:%S")
if priortime is None:
timedelta=0
else:
timedelta=(timeint-priortime).total_seconds()
priortime=timeint
else:
if self.devices=='.':
mre=re.search("^nvme|^sd[a-l] .*$",s)
else:
mre=re.search("^"+self.devices+" .*$",s)
# mre=re.search("^nvme0n1 .*$",s)
if mre!=None:
#disk=s[0:mre.span()[0]].rstrip()
#print(s)
l2f=s.split()
#print(timeint,float(l2f[3]))
data_list={'Cell':cellname, 'Type':('Flash' if l2f[0][0]=='n' else 'Disk'), 'Disk':l2f[0],'Metric':float(l2f[self.metric_column]),'Timestamp':timeint}
rows_list.append(data_list)
datfile.close()
pbar.setValue(100*n)
n+=.5/nfiles
QtWidgets.QApplication.processEvents()
self.current_metrics=pd.DataFrame(rows_list)#, ignore_index=True)
#print(self.current_metrics.head())
pbar.close()
for i in self.metric_graph:
self.metric_graph[i].remove_graph()
for i in self.current_metrics.Cell.unique():
self.metric_graph[i]=CellGraphrtPage(self,i,False)
self.metric_graph[i+'A']=CellGraphrtPage(self,i,True)
self.metric_graph[i].redraw_events()
self.metric_graph[i+'A'].redraw_events()
