initial upload

ImPSCAD/PSCADVar.py

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+###########################################################################
+# Libraries and packages
+###########################################################################
+import os
+import re
+import math
+import pandas as pd
+import numpy as np
+
+
+###########################################################################
+# Definition of class
+###########################################################################
+
+class PSCADVar(object):
+    """ Documentation: 
+        This class reads the .out files and returns all of the variables in it contained, as well as the header of the variables, time step and number of variables imported.
+
+        INF_path: str, mandatory. 
+        It's the path of the .inf file
+
+        writecsv: bool, optional. 
+        Creates a new .CSV file with the .OUT variables
+        
+        delout:   bool, optional. 
+        Deletes the .OUT files once they were already read
+        
+       """
+
+    def __init__(self, INF_path, **kwargs):
+
+        # Default definitions of arguments:
+        # It WILL create a CSV file
+        # It WILL NOT delete the .OUT files
+
+        try:
+            kwargs['writecsv']
+        except KeyError:
+            kwargs['writecsv'] = True
+
+        try:
+            kwargs['delout']
+        except KeyError:
+            kwargs['delout'] = False
+
+
+        with open(INF_path) as myfile:  # Open all the lines in the inf path
+            lines = myfile.readlines()
+
+
+        ############################################################################
+        # Take the header of the values
+        ############################################################################
+
+        n_col = 11                                 # Number of columns that the txt has
+        n_var = len(lines)                         # Number of PSCAD Variables
+        n_files = int(math.ceil(n_var / 10.0))     # Number of .out Files exported (the floating is important)
+        n_var_tot = n_var + n_files                # Number of variables INCLUDING additional time column FOR EACH .OUT
+        n_var_last = n_var_tot -(n_files-1)*n_col  # Number of variables in the last file
+        n_var_exp = n_var + 1                      # Number of variables that will be exported 
+
+        self.number_var = n_var_exp                
+
+        # This "for" gets the number of columns of every file which will be all 11,
+        # but the last, which value can vary
+
+        last_col = [0]*n_files
+
+        for ii in range(0,n_files):     
+
+            if ii != n_files-1:         
+                b = n_col
+            else:
+                b = n_var_last
+
+            last_col[ii] = b
+
+        # last_col = [11, 11, 11, 1]
+
+        pattern = "Desc=\"(.*?)\""  # Patter that holds the variable name
+        header1 = [0] * (n_var_exp)  # create a LIST of zeros that will be filled with the variables names later
+        self.header  = [0] * (n_var_exp)  
+
+        b = 0  # to "freeze" the time when storing the "TIME"
+        c = 1  # used in the index: from 1 to 11
+
+        # "For" Logic: each file can take 11 variables, and the first one is TIME
+        # so this for writes time if it is the time column, or takes the header from
+        # the array "header"
+
+        for a in range(0, n_var_exp):
+
+            if  a == 0 :                    # if it is the first value of all files, storage the time name
+                header1[a] = 'self.time'    # 1 header has the 'self.' in order to create variables to send
+                self.header[a] = 'time'     # to the object outside
+                b = b - 1
+                if a != 0:
+                    c = 1
+            else:
+                header1[a] = 'self.' + re.search(pattern, lines[b]).group(1)  # gets the name of the variable from the line
+                header1[a] = header1[a].replace(" ", "_")                     # If the header has spaces, it will be replaced
+                self.header[a] = re.search(pattern, lines[b]).group(1)  
+                self.header[a] = self.header[a].replace(" ", "_")  
+            # print a, self.header[a]     # USE "a+1" for range 1 to numb_variables, "c" for range 1 to 11
+
+
+            b = b + 1
+            c = c + 1
+
+        ############################################################################
+        # Take all the paths of the .out files
+        ############################################################################
+
+        # Create the path of each file so you can open it and read the values
+        # The "for" takes off the ending .inf and replace it with "_0NUMBER".out
+
+        OUT_name  = [0] * n_files
+        OUT_path  = [0] * n_files
+
+        for ii in range(0, n_files):
+            if ii < 9:
+                OUT_name[ii] = "_0" + str(ii + 1) + ".out"             # Create ending "_0ii".out
+                OUT_path[ii] = INF_path.replace(".inf", OUT_name[ii])  # replace in INF_path the.inf for the new end
+            else:
+
+                OUT_name[ii] = "_" + str(ii + 1) + ".out"             # Create ending "_0ii".out
+                OUT_path[ii] = INF_path.replace(".inf", OUT_name[ii])  # replace in INF_path the.inf for the new end
+
+
+            # print CSV_path[ii]
+
+        # Creates the path of the .CSV that's gonna be writen
+        CSV_path = INF_path.replace(".inf", ".csv") # Replaces the ending .inf with .csv
+
+        ############################################################################
+        # SAVE header and Variables in one .CSV file
+        ############################################################################
+
+        df_csv = pd.DataFrame()    # Create an empty pandas dataframe that will storage all the data from the .outs
+
+        c  = 0    # freezes the header if you skip time
+        jj = 0
+
+        for ii in range(0,n_files):  # For each file, read it and storage its columns in the .CSV file
+
+            df = pd.read_csv(OUT_path[ii], delim_whitespace=True, header=None)    # Read the .OUT file and storage it in a pandas data frame
+
+            if (jj == 0) or (jj % 11 == 0):                # if it is a multiple of 11, means that it's another file
+                jj = 0                                     # so you reset the counter 
+
+            while jj < last_col[ii]:                       # While you are inside the file, save values
+
+                if (jj == 0) and (ii == 0):                # It is the first column of the first file: storage time
+                    df_csv[self.header[c]] = df[jj]
+                elif (jj == 0) and (ii != 0):              # It is the first column of some other file: don't storage time
+                    jj = jj + 1
+                    df_csv[self.header[c]] = df[jj]
+                    # print 'just skipped time'
+                else:
+                    df_csv[self.header[c]] = df[jj]        # It is other column: storage column
+
+                exec('%s = np.array(%s)' % (header1[c],'df[jj]'))
+                # print df_csv.head()
+
+                # print c
+                c = c + 1
+                jj = jj + 1
+
+
+            if kwargs['delout'] == True:                 # If user wants to delete the .OUT files:
+                os.remove(OUT_path[ii])
+
+        ############################################################################
+        # Gets the step of simulation - PSCAD
+        ############################################################################
+
+        self.step = self.time[1] - self.time[0]
+
+
+        ############################################################################
+        # Storage data in a.CSV file with all the variables
+        ############################################################################
+
+        if (kwargs['writecsv'] == True): 
+
+            df_csv.to_csv(CSV_path,index=False)          # Storage all the dataframe into one csv file with header
+
+
+
+

ImPSCAD/__init__.py

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+from ImPSCAD.PSCADVar import PSCADVar

README.md

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+# GetVar
+
+**Motivation**
+
+PSCAD/EMTDC exports its variables in a .out file which contain ten variables plus the time of simulation. If your project has more than 10 variables, another .out file will be created, in order to fit them all. PSCAD/EMTDC also creates a .inf file with the name of the variables and its order in the .out files, once these files does not have a header. It may be boring to check which column belongs to each variable and also open each .out file to import these variables to your python/MATLAB etc project. 
+
+**Description**
+In order to solve this problem, this package was created: by using it, one can read all of the .out files, storage its variables and also create a .csv file with all the columns and header in a unique file.
+
+The class PSCADVar import all the variables data from the output of both programs simulations and returns it in a object.
+
+PSCADVar reads data from .out: just give the .INF path as argument
+
+__________________
+
+**Requirements**
+
+- **Python 3.8**
+- **Packages**: all of them are listed in "requirements.txt"
+  - To install all of them use: **pip install -r requirements.txt**

setup.py

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+from distutils.core import setup
+setup(
+  name = 'ImPSCAD',         
+  packages = ['ImPSCAD'],  
+  version = '0.1',      
+  license='MIT',        # Chose a license from here: https://help.github.com/articles/licensing-a-repository
+  description = 'Import variables from a PSCAD/EMTDC simulation', 
+  author = 'Luis Arthur Novais Haddad',
+  author_email = 'luis.novais@engenharia.ufjf.br',
+  url = 'https://github.com/LuisArthurNH',
+  download_url = 'https://github.com/user/reponame/archive/v_01.tar.gz',    # I explain this later on
+  keywords = ['PSCAD', 'Variables', 'Import','.CSV','python','MATLAB'],
+  install_requires=[            # I get to this in a second
+          'validators',
+          'beautifulsoup4',
+      ],
+  classifiers=[
+    'Development Status :: 3 - Alpha',      # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package
+    'Intended Audience :: Developers',      # Define that your audience are developers
+    'Topic :: Software Development :: Build Tools',
+    'License :: OSI Approved :: MIT License',   # Again, pick a license
+    'Programming Language :: Python :: 3',      #Specify which pyhton versions that you want to support
+    'Programming Language :: Python :: 3.4',
+    'Programming Language :: Python :: 3.5',
+    'Programming Language :: Python :: 3.6',
+  ],
+)