def PGetUV(InImager):
""" Return the member uvdata
returns uv data (as UV)
InImager = Python ImageMosaic object
"""
################################################################
# Checks
if not PIsA(InImager):
raise TypeError, "InImager MUST be a Python Obit UVImager"
#
out = UV.UV("None")
out.me = Obit.UVImagerGetUV(InImager.me)
return out
def PGetRFI(inRFI):
""" Return the data set containing estimated RFI
returns Residual dataset, this is only valid after calling
PRemove or PCounterRot.
If PFilter (or PRemove) has beed called the residual will have been
filtered to give the estimate of the RFI.
inRFI = Python UVRFIXize object
"""
################################################################
# Checks
if not PIsA(inRFI):
raise TypeError("inRFI MUST be a Python Obit UVRFIXize")
#
RFIUV = UV("RFI")
RFIUV.me = Obit.UVRFIXizeGetRFI(inRFI.me)
return RFIUV
# 把处理好的数据划分为 train 和 verify
with open("output/final_scored_data.txt", 'r') as f:
choose_rate = 0.2 # 80%数据用于测试， 20%数据用于验证
i = 0
for line in f.readlines():
i += 1
if(random.random() > choose_rate):
with open("output/train.txt", 'a') as train:
train.write(line)
else:
with open("output/train.txt", 'a') as verify:
verify.write(line)
print("done line " + i)
# 建立 UV 模型
uv = UV.UV("output/train.txt", 5)
rmse = uv.getRMSE()
for i in range(50):
uv.loop()
rmse = uv.getRMSE()
if rmse < 1000:
break
print(rmse)
uv.output()
# 读取 U、V 矩阵
with open("output/UmatS.txt", 'r') as f:
Umat = []
for line in f.readlines():
line_arr = line.replace("\n", "").split(" ")
new_arr = []
