import mediantools
import simpleread
x = simpleread.simple_read("raw.dat",3)
bin = 51
needs_sort = 1
scale_errors = 1
#y = mediantools.median_model(needs_sort,bin,x)
#y = mediantools.median_filter(needs_sort,bin,x)
#y = mediantools.identify_outliers(scale_errors,needs_sort,bin,x)
y = mediantools.detrend(needs_sort,scale_errors,bin,x)
with open("raw.med.dat", 'w') as f:
f.writelines(' '.join(str(j) for j in i) + '\n' for i in y)
import MAH
import simpleread
import math
# === SECTION 1: BASIC EXECUTION ===
# Here, I show a simple example of calling the MAH module
# = Read in the data ===
x = simpleread.simple_read("example_data.dat", 2)
n = len(x)
MP = []
RP = []
for i in range(n):
MP.append(x[i][0])
RP.append(x[i][1])
# = Call the MAH subroutine =
result = MAH.MAH_(RP, MP)
RH2O = [[0 for k in range(2)] for i in range(n)]
RH2O = result[0]
RMAH = [[0 for k in range(2)] for i in range(n)]
RMAH = result[1]
PRMAH = [0 for k in range(2)]
PRMAH = result[2]
nvalid = [0 for k in range(2)]
nvalid = result[3]
valid = [[0 for k in range(2)] for i in range(n)]
valid = result[4]
# = Output the results==
zpure = [[0 for k in range(3)] for i in range(n)]
import MAH
import simpleread
import math
# === SECTION 1: BASIC EXECUTION ===
# Here, I show a simple example of calling the MAH module
# = Read in the data ===
x = simpleread.simple_read("example_data.dat",2)
n = len(x)
MP=[]
RP=[]
for i in range(n):
MP.append(x[i][0])
RP.append(x[i][1])
# = Call the MAH subroutine =
result = MAH.MAH_(RP,MP)
RH2O = [[0 for k in range(2)] for i in range(n)]
RH2O = result[0]
RMAH = [[0 for k in range(2)] for i in range(n)]
RMAH = result[1]
PRMAH = [0 for k in range(2)]
PRMAH = result[2]
nvalid = [0 for k in range(2)]
nvalid = result[3]
valid=[[0 for k in range(2)] for i in range(n)]
valid = result[4]
# = Output the results==
zpure = [[0 for k in range(3)] for i in range(n)]
