functions_and_tests.file_read.read_file() - Code Metrics - Inspection of "edits" - sabiharustam/voltcycle - Measure and Improve Code Quality continuously with Scrutinizer

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Push — master ( de7c60...c9fd59 )

by Keertana

created 2019-03-22 08:49 UTC

functions_and_tests.file_read.read_file() C

↳ Parent: functions_and_tests.file_read

Complexity

Conditions

Size

Total Lines	46
Code Lines	27

Duplication

Lines	46
Ratio	100 %

Importance

Changes

Metric	Value
cc	10
eloc	27
nop	1
dl	46
loc	46
rs	5.9999
c	0
b	0
f	0

How to fix Complexity

"""This module test the file reading functions."""

import copy
import pandas as pd
import matplotlib.pyplot as plt


def read_cycle(data):

    """This function reads a segment of datafile (corresponding a cycle)
    and generates a dataframe with columns 'Potential' and 'Current'

    Parameters
    __________
    data: segment of data file
    Returns
    _______
    A dataframe with potential and current columns
    """

    current = []
    potential = []
    for i in data[3:]:
        current.append(float(i.split("\t")[4]))
        potential.append(float(i.split("\t")[3]))
    zipped_list = list(zip(potential, current))
    dataframe = pd.DataFrame(zipped_list, columns=['Potential', 'Current'])
    return dataframe


def read_file(file):

    """This function reads the raw data file, gets the scanrate and stepsize
    and then reads the lines according to cycle number. Once it reads the data
    for one cycle, it calls read_cycle function to denerate a dataframe. It
    does the same thing for all the cycles and finally returns a dictionary,
    the keys of which are the cycle numbers and the values are the
    corresponding dataframes.

    Parameters
    __________
    file: raw data file

    Returns:
    ________
    dict_of_df: dictionary of dataframes with keys = cycle numbers and
    values = dataframes for each cycle
    n_cycle: number of cycles in the raw file
    """
    dict_of_df = {}
    h_val = 0
    l_val = 0
    n_cycle = 0
    #a = []
    with open(file, 'rt') as f_val:
        print(file + ' Opened')
        for line in f_val:
            record = 0
            if not (h_val and l_val):
                if line.startswith('SCANRATE'):
                    scan_rate = float(line.split()[2])
                    h_val = 1
                if line.startswith('STEPSIZE'):
                    step_size = float(line.split()[2])
                    l_val = 1
            if line.startswith('CURVE'):
                n_cycle += 1
                if n_cycle > 1:
                    number = n_cycle - 1
                    data = read_cycle(a_val)

                    key_name = 'cycle_' + str(number)
                    #key_name = number
                    dict_of_df[key_name] = copy.deepcopy(data)
                a_val = []
            if n_cycle:
                a_val.append(line)
    return dict_of_df, number



#df = pd.DataFrame(list(dict1['df_1'].items()))
#list1, list2 = list(dict1['df_1'].items())
#list1, list2 = list(dict1.get('df_'+str(1)))

def data_frame(dict_cycle, number):

    """Reads the dictionary of dataframes and returns dataframes for each cycle

    Parameters
    __________
    dict_cycle: Dictionary of dataframes
    n: cycle number

    Returns:
    _______
    Dataframe correcponding to the cycle number
    """
    list1, list2 = (list(dict_cycle.get('cycle_'+str(number)).items()))
    zipped_list = list(zip(list1[1], list2[1]))
    data = pd.DataFrame(zipped_list, columns=['Potential', 'Current'])
    return data

def plot_fig(dict_cycle, number):

    """For basic plotting of the cycle data

    Parameters
    __________
    dict: dictionary of dataframes for all the cycles
    n: number of cycles

    Saves the plot in a file called cycle.png
    """

    for i in range(number):
        print(i+1)
        data = data_frame(dict_cycle, i+1)
        plt.plot(data.Potential, data.Current, label="Cycle{}".format(i+1))

    print(data.head())

    plt.xlabel('Voltage')
    plt.ylabel('Current')
    plt.legend()
    plt.savefig('cycle.png')
    print('executed')


1		"""This module test the file reading functions."""
2
3		import copy
4		import pandas as pd
5		import matplotlib.pyplot as plt
6
7
8	View Code Duplication	def read_cycle(data):
		0 ignored issues – show Duplication introduced 2019-03-14 22:59 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
9		"""This function reads a segment of datafile (corresponding a cycle)
10		and generates a dataframe with columns 'Potential' and 'Current'
11
12		Parameters
13		__________
14		data: segment of data file
15		Returns
16		_______
17		A dataframe with potential and current columns
18		"""
19
20		current = []
21		potential = []
22		for i in data[3:]:
23		current.append(float(i.split("\t")[4]))
24		potential.append(float(i.split("\t")[3]))
25		zipped_list = list(zip(potential, current))
26		dataframe = pd.DataFrame(zipped_list, columns=['Potential', 'Current'])
27		return dataframe
28
29
30	View Code Duplication	def read_file(file):
		0 ignored issues – show Duplication introduced 2019-03-14 22:59 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
31		"""This function reads the raw data file, gets the scanrate and stepsize
32		and then reads the lines according to cycle number. Once it reads the data
33		for one cycle, it calls read_cycle function to denerate a dataframe. It
34		does the same thing for all the cycles and finally returns a dictionary,
35		the keys of which are the cycle numbers and the values are the
36		corresponding dataframes.
37
38		Parameters
39		__________
40		file: raw data file
41
42		Returns:
43		________
44		dict_of_df: dictionary of dataframes with keys = cycle numbers and
45		values = dataframes for each cycle
46		n_cycle: number of cycles in the raw file
47		"""
48		dict_of_df = {}
49		h_val = 0
50		l_val = 0
51		n_cycle = 0
52		#a = []
53		with open(file, 'rt') as f_val:
54		print(file + ' Opened')
55		for line in f_val:
56		record = 0
57		if not (h_val and l_val):
58		if line.startswith('SCANRATE'):
59		scan_rate = float(line.split()[2])
60		h_val = 1
61		if line.startswith('STEPSIZE'):
62		step_size = float(line.split()[2])
63		l_val = 1
64		if line.startswith('CURVE'):
65		n_cycle += 1
66		if n_cycle > 1:
67		number = n_cycle - 1
68		data = read_cycle(a_val)
		0 ignored issues – show introduced 2019-03-22 08:43 UTC by Report Bug Copy Issue Report The variable `a_val` does not seem to be defined for all execution paths. Loading history...
69		key_name = 'cycle_' + str(number)
70		#key_name = number
71		dict_of_df[key_name] = copy.deepcopy(data)
72		a_val = []
73		if n_cycle:
74		a_val.append(line)
75		return dict_of_df, number
		0 ignored issues – show introduced 2019-03-14 22:59 UTC by Report Bug Copy Issue Report The variable `number` does not seem to be defined for all execution paths. Loading history...
76
77
78		#df = pd.DataFrame(list(dict1['df_1'].items()))
79		#list1, list2 = list(dict1['df_1'].items())
80		#list1, list2 = list(dict1.get('df_'+str(1)))
81
82	View Code Duplication	def data_frame(dict_cycle, number):
		0 ignored issues – show Duplication introduced 2019-03-22 08:43 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
83		"""Reads the dictionary of dataframes and returns dataframes for each cycle
84
85		Parameters
86		__________
87		dict_cycle: Dictionary of dataframes
88		n: cycle number
89
90		Returns:
91		_______
92		Dataframe correcponding to the cycle number
93		"""
94		list1, list2 = (list(dict_cycle.get('cycle_'+str(number)).items()))
95		zipped_list = list(zip(list1[1], list2[1]))
96		data = pd.DataFrame(zipped_list, columns=['Potential', 'Current'])
97		return data
98
99	View Code Duplication	def plot_fig(dict_cycle, number):
		0 ignored issues – show Duplication introduced 2019-03-22 08:43 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
100		"""For basic plotting of the cycle data
101
102		Parameters
103		__________
104		dict: dictionary of dataframes for all the cycles
105		n: number of cycles
106
107		Saves the plot in a file called cycle.png
108		"""
109
110		for i in range(number):
111		print(i+1)
112		data = data_frame(dict_cycle, i+1)
113		plt.plot(data.Potential, data.Current, label="Cycle{}".format(i+1))
114
115		print(data.head())
		0 ignored issues – show introduced 2019-03-22 08:43 UTC by Report Bug Copy Issue Report The variable `data` does not seem to be defined in case the `for` loop on line `110` is not entered. Are you sure this can never be the case? Loading history...
116		plt.xlabel('Voltage')
117		plt.ylabel('Current')
118		plt.legend()
119		plt.savefig('cycle.png')
120		print('executed')
121

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functions_and_tests.file_read.read_file() C

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