Initial commit before further development of gnss module

geodepy/gnss.py

@@ -8,6 +8,8 @@
 """
 
 from datetime import datetime
+import numpy as np
+import pandas as pd
 from numpy import zeros, delete
 from geodepy.angles import DMSAngle
 import re
@@ -99,6 +101,27 @@ def read_sinex_header_line(file):
 
     return header_line
 
+def read_sinex_custom(fp, start_line, end_line):
+    """Read custom line range from SINEX.
+
+    :param str fp: Path to SINEX file.
+    :param int start_line:   Beginning line number. 
+    :param int end_line:     Finishing line number.
+    :return list custom:  List of string(s).
+    """
+
+    # Setup
+    i = start_line
+    j = end_line
+    f = fp
+    custom = []
+
+    with open(fp) as f:
+        for line in f.readlines()[i-1:j]:
+             custom.append(line.strip())
+
+    # Return
+    return custom
 
 def read_sinex_estimate(file):
     """This function reads in the SOLUTION/ESTIMATE block of a SINEX file. It
@@ -748,7 +771,8 @@ def remove_velocity_sinex(sinex):
 
     # From header, confirm that the SINEX has velocity parameters
     header = read_sinex_header_line(sinex)
-    if header[70:71] == 'V':
+    header = header.strip()
+    if header[-1] == 'V':
         pass
     else:
         print("Not removing velocities because SINEX file does not have velocity parameters.")
@@ -770,6 +794,7 @@ def remove_velocity_sinex(sinex):
         header = header.replace(str(old_num_params), str(num_params))
         header = header.replace('V', '')
         out.write(header)
+        out.write("\n")
         del header
 
         out.write("*-------------------------------------------------------------------------------\n")
@@ -988,3 +1013,308 @@ def remove_matrixzeros_sinex(sinex):
         out.write('%ENDSNX\n')
 
     return
+
+
+def sinex2dataframe_solution_estimate(fp):
+    """This function reads in a SINEX file and returns 
+    a dataframe of SOLUTION/ESTIMATE block only. 
+
+    :param str sinex: path of input SINEX file
+    return: dataframe
+    """
+
+    # Get lines
+    lines = read_sinex_solution_estimate_block(fp)
+
+    # Remove non-data lines
+    for l in lines[:]:
+        if l.startswith('*'):
+            lines.remove(l)
+        if l.startswith('+'):
+            lines.remove(l)
+        if l.startswith('-'):
+            lines.remove(l)
+
+    # Split by column
+    lines = [i.split() for i in lines]
+
+    # Isolate into vectors
+    row = np.int_(list(zip(*lines))[0])
+    par = list(zip(*lines))[1]
+    code = list(zip(*lines))[2]
+    pt = list(zip(*lines))[3]
+    soln = list(zip(*lines))[4]
+    refEpoch = list(zip(*lines))[5]
+    unit = list(zip(*lines))[6]
+    s = np.int_(list(zip(*lines))[7])
+    est = np.float_(list(zip(*lines))[8])
+    sigma = np.float_(list(zip(*lines))[9])
+
+    # Organise into DataFrame
+    dict_temp = {
+                "row":row,
+                "par":par,
+                "code":code,
+                "pt":pt,
+                "soln":soln,
+                "refEpoch":refEpoch,
+                "unit":unit,
+                "s":s,
+                "est":est,
+                "sigma":sigma,
+    }
+    df = pd.DataFrame(dict_temp)
+
+    # Return
+    return df
+
+def sinex2dataframe_solution_matrix_estimate(fp):
+    """This function reads in a SINEX file and returns 
+    a dataframe of SOLUTION/MATRIX_ESTIMATE block only. 
+
+    :param str sinex: path of input SINEX file
+    return: dataframe
+    """
+
+    # Get lines
+    lines = read_sinex_solution_matrix_estimate_block(fp)
+
+    # Remove non-data lines
+    for l in lines[:]:
+        if l.startswith('*'):
+            lines.remove(l)
+        if l.startswith('+'):
+            lines.remove(l)
+        if l.startswith('-'):
+            lines.remove(l)
+
+    # Split by column
+    lines = [i.split() for i in lines]
+
+    # Pad out lines with NaN
+    for i in range(len(lines)):
+        if len(lines[i])==5:
+            continue
+        if len(lines[i]) == 4:
+            lines[i].append(np.nan)
+        if len(lines[i]) == 3:
+            lines[i].append(np.nan)
+            lines[i].append(np.nan)
+
+    # Isolate into vectors
+    row = np.int_(list(zip(*lines))[0])
+    col = np.int_(list(zip(*lines))[1])
+    q1 = np.float_(list(zip(*lines))[2])
+    q2 = np.float_(list(zip(*lines))[3])
+    q3 = np.float_(list(zip(*lines))[4])
+
+    # Organise into DataFrame
+    dict_temp = {
+                "row":row,
+                "col":col,
+                "q1":q1,
+                "q2":q2,
+                "q3":q3,
+    }
+    df = pd.DataFrame(dict_temp)
+
+    # Return
+    return df
+
+def dataframe2sinex_solution_estimate(df):
+    """This function reads in a dataframe of the 
+    SOLUTIONS/ESTIMATE block from a SINEX, the
+    converts each row to a string in a list 
+    ready for writing to SINEX.
+
+    :param dataframe df: dataframe of SOLUTION/ESTIMATE block
+    return: list of strings
+    """
+
+    lines =lines = ["+SOLUTION/ESTIMATE"]
+    lines.append("*INDEX TYPE__ CODE PT SOLN _REF_EPOCH__ UNIT S __ESTIMATED VALUE____ _STD_DEV___")
+
+    for i in range(len(df.code)):
+        l = " %5i %s   %s  %s    %s %s %-3s  %s %21.14e %.5e" % (df.row.iloc[i], df.par.iloc[i], df.code.iloc[i], df.pt.iloc[i], df.soln.iloc[i], df.refEpoch.iloc[i], df.unit.iloc[i], df.s.iloc[i], df.est.iloc[i], df.sigma.iloc[i])
+        lines.append(l)
+
+    lines.append("-SOLUTION/ESTIMATE")
+
+    # Return
+    return lines
+
+
+def dataframe2matrix_snx_vcv(df):
+
+    # Matrix dimensions
+    # - To Do: Handle check for velocities
+    # - To Do: Handle lower/upper triangle
+    par = 3 # (check for velocities)
+    n = len(df.code)*par
+    Q = np.zeros((n, n))
+
+    # Matrix elements and rows of dataframe
+    i = 0
+    j = 0
+    r = 0
+    while r < len(df.code):
+
+        # variances
+        Q[i+0, j+0] = df.xx[r]
+        Q[i+1, j+1] = df.yy[r]
+        Q[i+2, j+2] = df.zz[r]
+
+        # covariances
+        Q[i+1, j] = df.xy[r]
+        Q[i+2, j] = df.xz[r]
+        Q[i+2, j+1] = df.yz[r]
+
+        # Counter
+        r = r+1
+        i = i+3
+        j = j+3
+
+    # Return
+    return Q
+
+def dataframe2matrix_solution_matrix_estimate(df):
+
+    # Matrix size
+    n = df.row.iloc[-1]
+    Q = np.zeros((n, n))
+
+    for i in range(len(df.row)):
+
+        # Get matrix indices
+        row = int(df.row[i])
+        col = int(df.col[i])
+
+        # Fill PARA2+0
+        q1 = df.q1[i]    
+        Q[row-1, col-1] = q1
+        Q[col-1, row-1] = q1
+
+        # Fill PARA2+1
+        q2 = df.q2[i]
+        Q[row-1, col] = q2
+        Q[col, row-1] = q2
+
+        # Fill PARA2+2
+        q3 = df.q3[i]
+        Q[row-1, col+1] = q3
+        Q[col+1, row-1] = q3
+
+    # Return
+    return Q
+
+def matrix2dataframe_solution_matrix_estimate(m, par, tri):
+
+    # Matrix dimensions
+    # - To Do: Handle check for velocities
+    # - To Do: Handle lower/upper triangle
+    Q = m
+    par = 3
+    tri = 'lower'
+    n = np.shape(Q)[0]
+
+    row = []
+    col = []
+    q1 = []
+    q2 = []
+    q3 = []
+    i = 0
+    j = 0
+    while i < n:
+        while j <= i:
+            row.append(i+1)
+            col.append(j+1)
+            q1.append(Q[i, j])
+            q2.append(Q[i, j+1])
+            q3.append(Q[i, j+2])
+            j += par
+        j = 0
+        i += 1
+
+    dict_temp = {
+                "row":row,
+                "col":col,
+                "q1":q1,
+                "q2":q2,
+                "q3":q3,
+    }
+    df = pd.DataFrame(dict_temp)
+    df.replace(0.0, np.nan, inplace=True)
+
+    # Return
+    return df
+
+def dataframe2sinex_solution_matrix_estimate(df):
+    """This function reads in a dataframe of the 
+    SOLUTIONS/MATRIX_ESTIMATE block from a SINEX, the
+    converts each row to a string in a list 
+    ready for writing to SINEX.
+
+    :param dataframe df: dataframe of SOLUTION/ESTIMATE block
+    return: list of strings
+    """
+
+    lines =lines = ["+SOLUTION/MATRIX_ESTIMATE L COVA"]
+    lines.append("*PARA1 PARA2 ____PARA2+0__________ ____PARA2+1__________ ____PARA2+2__________")
+
+    for i in range(len(df.row)):
+        l = " %6i %5i %.14e %.14e %.14e" % (df.row.iloc[i], df.col.iloc[i], df.q1.iloc[i], df.q2.iloc[i], df.q3.iloc[i])
+        l = l.replace('nan', '')
+        lines.append(l)
+
+    lines.append("-SOLUTION/MATRIX_ESTIMATE L COVA")
+
+    # Return
+    return lines
+
+def writeSINEX(fp, header, comment, SiteID, SolutionEpochs, SolutionEstimate, SolutionMatrixEstimate):
+
+    # Open File
+    with open(fp, 'w') as f:
+
+        # Header
+        f.write("{}".format(header))
+
+        f.write("*-------------------------------------------------------------------------------\n")
+
+        # Comment
+        for i in range(len(comment)):
+
+            f.write("{}\n".format(comment[i]))
+
+        f.write("*-------------------------------------------------------------------------------\n")
+
+        #SITE/ID
+        for i in range(len(SiteID)):
+
+            f.write("{}".format(SiteID[i]))
+
+        f.write("*-------------------------------------------------------------------------------\n")
+
+        # SOLUTION/EPOCHS
+        for i in range(len(SolutionEpochs)):
+
+            f.write("{}".format(SolutionEpochs[i]))
+
+        f.write("*-------------------------------------------------------------------------------\n")
+
+        # SOLUTION/ESTIMATE
+        for i in range(len(SolutionEstimate)):
+
+            f.write("{}\n".format(SolutionEstimate[i]))
+
+        f.write("*-------------------------------------------------------------------------------\n")
+
+        # SOLUTION/MATRIX_ESTIMATE
+        for i in range(len(SolutionMatrixEstimate)):
+
+            f.write("{}".format(SolutionMatrixEstimate[i]))
+
+        # End Line
+        f.write("%ENDSNX")
+
+    f.close()