def Get_Cr_PointSet(wells,Seg = None):
i=0
for well in wells:
try:
ac_data = RawData.get_column_floatData(well, columname)
depth = RawData.get_well_depthdata(well)
except:
continue
#depth = np.arange(0,len(ac_data)).tolist()
'''
if(Seg.if_exist_segment(well, "龙潭组")):
ac_data = Seg.get_segment_columndata(well, "龙潭组", "ac")
depth = Seg.get_segment_depthdata(well,"龙潭组")
else:
continue
'''
#if well in ["well96","well121","well94","well90"]:
# continue
tmp = depth[0]
for j in range(len(depth)):
depth[j] -= tmp
data_preprocesser.data_except_invalid(depth,ac_data)
x,y = data_preprocesser.getkeypoint_from_rawdata(depth,ac_data)
InitAndProcess_Cr(depth,ac_data,x,y,well + "龙潭组")
xdata.append(x)
ydata.append(y)
i+=1
if(i == 21):
break
return xdata,ydata
data = []
RawData = rawdata_provider.RawDataProvider()
wells = RawData.get_well_allnames()
Seg = well_segment_provider.WellSegmentProvider()
i = 0
#读取数据
z = []
for well in wells:
ac_data = RawData.get_column_floatData(well, "ac")
if (Seg.if_exist_segment(well, "龙潭组")):
ac_data = Seg.get_segment_columndata(well, "龙潭组", "ac")
depth = np.arange(0, len(ac_data), 1 / 8).tolist()
data_preprocesser.data_except_invalid(depth, ac_data)
x, y = data_preprocesser.getkeypoint_from_rawdata(depth,
ac_data,
threshold=1)
tmp = []
for j in range(len(y) - 1):
tmp += list(
np.arange(y[j], y[j + 1],
(y[j + 1] - y[j]) / (x[j + 1] - x[j]) / 8))
data.append(tmp)
i += 1
if (i == 4):
break
data_set = np.zeros((10000, 1000))
re_set = np.zeros(10000)
for i in range(4):
for j in range(len(data[i])):
well] = well_central_frequency #再建立一个字典，用于储存所有井的所有指标的中心频率
#创建图片的存储路径
save_path_each_well_before = os.path.join(save_path_before, well)
os.mkdir(save_path_each_well_before)
save_path_each_well_after = os.path.join(save_path_after, well)
os.mkdir(save_path_each_well_after)
for detecting_name in detecting_names:
ac_data = RawDataProvider.get_column_floatData(
well, detecting_name)
depth = RawDataProvider.get_well_depthdata(well)
#fill_invaliddata_use_aver(ac_data)#对井中的特性数据做预处理，将无效值用总体有效平均值代替
new_depth, new_data = getkeypoint_from_rawdata(
depth, ac_data) #对数据做了三个预处理操作包括：去除无效值，平滑处理，曲线粗化
sampling_rate = 8000 #采样频率
#这里构造一个字典，记录这些数据的中心频率
fc = pywt.central_frequency('mexh') #中心频率，cgau8对应的中心频率是0.7
well_central_frequency[detecting_name] = fc
filter('nan', new_data)
if len(new_data) > 20:
#绘制原信号图并保存
pic_str = save_path_each_well_before + '\\' + well + '_' + detecting_name + '.png'
plt.figure(i)
plt.plot(new_depth, new_data)
plt.savefig(pic_str)
i += 1
#需要分析的井
wellname_to_analysis = rawdata_provider.RawDataProvider().get_well_allnames()
#需要分析的曲线
columnname_to_analysis = "GR"
depths = []
datas = []
depths_keypoint = []
datas_keypoint = []
for i in range(len(wellname_to_analysis)):
depth = rawdata_getter.get_well_depthdata(wellname_to_analysis[i])
data = rawdata_getter.get_column_floatData(wellname_to_analysis[i],columnname_to_analysis)
data_preprocesser.fill_invaliddata_use_aver(data)
depth_key,data_key= data_preprocesser.getkeypoint_from_rawdata(depth,data)
depths.append(depth)
datas.append(data)
depths_keypoint.append(depth_key)
datas_keypoint.append(data_key)
print("len_depth:"+str(len(depth_key)))
print("len_data:"+str(len(data_key)))
#simple_log_plot.plot_2_log(depths_keypoint[i],datas_keypoint[i],"depth","data",depths[i],datas[i],"depth1","data2")
info_1 = data_preprocesser.get_rake_ratio_and_linelen(depths_keypoint[0],datas_keypoint[0])
for i in range(len(wellname_to_analysis)):
info_2 = data_preprocesser.get_rake_ratio_and_linelen(depths_keypoint[i],datas_keypoint[i])
distance,list = fastdtw.fastdtw(info_1,info_2)
simple_log_plot.correlation_plot_for_2well(depths_keypoint[0],datas_keypoint[0],depths_keypoint[i],datas_keypoint[i],map=list,xlabel="depth",ylabel=columnname_to_analysis)