Code Duplication - sabiharustam/voltcycle - Measure and Improve Code Quality continuously with Scrutinizer

Code Duplication Length = 22-22 lines in 4 locations

practice/dash_resumable_upload.py 1 location


    return data


def plot_fig(dict_cycle, n):
    """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(n):
        print(i+1)
        df = data_frame(dict_cycle, i+1)
        plt.plot(df.Potential, df.Current, label = "Cycle{}".format(i+1))
        
    #print(df.head())
    plt.xlabel('Voltage')
    plt.ylabel('Current')
    plt.legend()
    plt.savefig('cycle.png')
    print('executed')


#split forward and backward sweping data, to make it easier for processing.

practice/core.py 1 location


    return data


def plot_fig(dict_cycle, n):
    """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(n):
        print(i+1)
        df = data_frame(dict_cycle, i+1)
        plt.plot(df.Potential, df.Current, label = "Cycle{}".format(i+1))
        
    #print(df.head())
    plt.xlabel('Voltage')
    plt.ylabel('Current')
    plt.legend()
    plt.savefig('cycle.png')
    print('executed')


#split forward and backward sweping data, to make it easier for processing.

voltcycle/core.py 1 location


    return data


def plot_fig(dict_cycle, n):
    """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(n):
        print(i+1)
        df = data_frame(dict_cycle, i+1)
        plt.plot(df.Potential, df.Current, label = "Cycle{}".format(i+1))
        
    #print(df.head())
    plt.xlabel('Voltage')
    plt.ylabel('Current')
    plt.legend()
    plt.savefig('cycle.png')
    print('executed')


#split forward and backward sweping data, to make it easier for processing.

voltcycle/submodule/file_read.py 1 location


    data  = pd.DataFrame(zippedList, columns = ['Potential' , 'Current'])
    return data
    
def plot_fig(dict_cycle, n):
    """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(n):
        print(i+1)
        df = data_frame(dict_cycle, i+1)
        plt.plot(df.Potential, df.Current, label = "Cycle{}".format(i+1))
        
    print(df.head())
    plt.xlabel('Voltage')
    plt.ylabel('Current')
    plt.legend()
    plt.savefig('cycle.png')
    print('executed')


		@@ 152-173 (lines=22) @@
149		return data
150
151
152		def plot_fig(dict_cycle, n):
153		"""For basic plotting of the cycle data
154
155		Parameters
156		__________
157		dict: dictionary of dataframes for all the cycles
158		n: number of cycles
159
160		Saves the plot in a file called cycle.png
161		"""
162
163		for i in range(n):
164		print(i+1)
165		df = data_frame(dict_cycle, i+1)
166		plt.plot(df.Potential, df.Current, label = "Cycle{}".format(i+1))
167
168		#print(df.head())
169		plt.xlabel('Voltage')
170		plt.ylabel('Current')
171		plt.legend()
172		plt.savefig('cycle.png')
173		print('executed')
174
175
176		#split forward and backward sweping data, to make it easier for processing.

		@@ 152-173 (lines=22) @@
149		return data
150
151
152		def plot_fig(dict_cycle, n):
153		"""For basic plotting of the cycle data
154
155		Parameters
156		__________
157		dict: dictionary of dataframes for all the cycles
158		n: number of cycles
159
160		Saves the plot in a file called cycle.png
161		"""
162
163		for i in range(n):
164		print(i+1)
165		df = data_frame(dict_cycle, i+1)
166		plt.plot(df.Potential, df.Current, label = "Cycle{}".format(i+1))
167
168		#print(df.head())
169		plt.xlabel('Voltage')
170		plt.ylabel('Current')
171		plt.legend()
172		plt.savefig('cycle.png')
173		print('executed')
174
175
176		#split forward and backward sweping data, to make it easier for processing.

		@@ 152-173 (lines=22) @@
149		return data
150
151
152		def plot_fig(dict_cycle, n):
153		"""For basic plotting of the cycle data
154
155		Parameters
156		__________
157		dict: dictionary of dataframes for all the cycles
158		n: number of cycles
159
160		Saves the plot in a file called cycle.png
161		"""
162
163		for i in range(n):
164		print(i+1)
165		df = data_frame(dict_cycle, i+1)
166		plt.plot(df.Potential, df.Current, label = "Cycle{}".format(i+1))
167
168		#print(df.head())
169		plt.xlabel('Voltage')
170		plt.ylabel('Current')
171		plt.legend()
172		plt.savefig('cycle.png')
173		print('executed')
174
175
176		#split forward and backward sweping data, to make it easier for processing.

		@@ 99-120 (lines=22) @@
96		data = pd.DataFrame(zippedList, columns = ['Potential' , 'Current'])
97		return data
98
99		def plot_fig(dict_cycle, n):
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(n):
111		print(i+1)
112		df = data_frame(dict_cycle, i+1)
113		plt.plot(df.Potential, df.Current, label = "Cycle{}".format(i+1))
114
115		print(df.head())
116		plt.xlabel('Voltage')
117		plt.ylabel('Current')
118		plt.legend()
119		plt.savefig('cycle.png')
120		print('executed')
121

sabiharustam / voltcycle

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Code Duplication Length = 22-22 lines in 4 locations

practice/dash_resumable_upload.py 1 location

practice/core.py 1 location

voltcycle/core.py 1 location

voltcycle/submodule/file_read.py 1 location