from format_data import Formatter
import matplotlib.pyplot as plt
from statsmodels.tsa.seasonal import seasonal_decompose
import math

class Grapher:
	'''
	contains functions and classes to graph time series
	'''
	def __init__(self, url, file_name, data_file_name):
		self.ts_data = Formatter(url, file_name, data_file_name)
		self.ts_frame = self.ts_data.data_to_dataframe()

	def decompose_ts(self):
		self.ts_decomposition = seasonal_decompose(self.ts_frame, freq=365)
		self.seasonal = self.ts_decomposition.seasonal
		self.trend = self.ts_decomposition.trend
		self.resid = self.ts_decomposition.resid
		resid_list = []
		start_i=0
		for i in self.resid.iloc[:, 0].tolist():
			resid_list.append(i)
		print(resid_list)
		for i in range(len(resid_list)):
			if math.isnan(resid_list[i]) != True:
				start_i = i
				break
		print(start_i)
		resid_list1= resid_list[start_i:]
		for i in range(len(resid_list1)):
			if math.isnan(resid_list1[i]) == True:
				end_i = i
				break
		print(end_i)
		end_i=end_i+start_i
		#print(resid_list[start_i:end_i])
		self.resid= self.resid.dropna()
		#print(self.resid)
		return self.resid, self.seasonal, self.trend, start_i, end_i

	def get_data(self):
		return self.ts_frame


if __name__ == '__main__':
	# from bokeh.charts import Line, show, output_file
	mygrapher = Grapher("", "christmas.txt", "christmas_data.txt")
	mygrapher.decompose_ts()
	plt.figure()
	plt.plot(mygrapher.ts_frame)
	plt.plot(mygrapher.trend)
	plt.plot(mygrapher.seasonal)
	plt.plot(mygrapher.resid)
	#plt.show()

e6382d70a7a30be26e711447a4a0c2c5f59786ae
<mask token>


class Grapher:
    <mask token>

    def __init__(self, url, file_name, data_file_name):
        self.ts_data = Formatter(url, file_name, data_file_name)
        self.ts_frame = self.ts_data.data_to_dataframe()

    def decompose_ts(self):
        self.ts_decomposition = seasonal_decompose(self.ts_frame, freq=365)
        self.seasonal = self.ts_decomposition.seasonal
        self.trend = self.ts_decomposition.trend
        self.resid = self.ts_decomposition.resid
        resid_list = []
        start_i = 0
        for i in self.resid.iloc[:, 0].tolist():
            resid_list.append(i)
        print(resid_list)
        for i in range(len(resid_list)):
            if math.isnan(resid_list[i]) != True:
                start_i = i
                break
        print(start_i)
        resid_list1 = resid_list[start_i:]
        for i in range(len(resid_list1)):
            if math.isnan(resid_list1[i]) == True:
                end_i = i
                break
        print(end_i)
        end_i = end_i + start_i
        self.resid = self.resid.dropna()
        return self.resid, self.seasonal, self.trend, start_i, end_i

    def get_data(self):
        return self.ts_frame


<mask token>

<mask token>


class Grapher:
    """
	contains functions and classes to graph time series
	"""

    def __init__(self, url, file_name, data_file_name):
        self.ts_data = Formatter(url, file_name, data_file_name)
        self.ts_frame = self.ts_data.data_to_dataframe()

    def decompose_ts(self):
        self.ts_decomposition = seasonal_decompose(self.ts_frame, freq=365)
        self.seasonal = self.ts_decomposition.seasonal
        self.trend = self.ts_decomposition.trend
        self.resid = self.ts_decomposition.resid
        resid_list = []
        start_i = 0
        for i in self.resid.iloc[:, 0].tolist():
            resid_list.append(i)
        print(resid_list)
        for i in range(len(resid_list)):
            if math.isnan(resid_list[i]) != True:
                start_i = i
                break
        print(start_i)
        resid_list1 = resid_list[start_i:]
        for i in range(len(resid_list1)):
            if math.isnan(resid_list1[i]) == True:
                end_i = i
                break
        print(end_i)
        end_i = end_i + start_i
        self.resid = self.resid.dropna()
        return self.resid, self.seasonal, self.trend, start_i, end_i

    def get_data(self):
        return self.ts_frame


<mask token>

<mask token>


class Grapher:
    """
	contains functions and classes to graph time series
	"""

    def __init__(self, url, file_name, data_file_name):
        self.ts_data = Formatter(url, file_name, data_file_name)
        self.ts_frame = self.ts_data.data_to_dataframe()

    def decompose_ts(self):
        self.ts_decomposition = seasonal_decompose(self.ts_frame, freq=365)
        self.seasonal = self.ts_decomposition.seasonal
        self.trend = self.ts_decomposition.trend
        self.resid = self.ts_decomposition.resid
        resid_list = []
        start_i = 0
        for i in self.resid.iloc[:, 0].tolist():
            resid_list.append(i)
        print(resid_list)
        for i in range(len(resid_list)):
            if math.isnan(resid_list[i]) != True:
                start_i = i
                break
        print(start_i)
        resid_list1 = resid_list[start_i:]
        for i in range(len(resid_list1)):
            if math.isnan(resid_list1[i]) == True:
                end_i = i
                break
        print(end_i)
        end_i = end_i + start_i
        self.resid = self.resid.dropna()
        return self.resid, self.seasonal, self.trend, start_i, end_i

    def get_data(self):
        return self.ts_frame


if __name__ == '__main__':
    mygrapher = Grapher('', 'christmas.txt', 'christmas_data.txt')
    mygrapher.decompose_ts()
    plt.figure()
    plt.plot(mygrapher.ts_frame)
    plt.plot(mygrapher.trend)
    plt.plot(mygrapher.seasonal)
    plt.plot(mygrapher.resid)

from format_data import Formatter
import matplotlib.pyplot as plt
from statsmodels.tsa.seasonal import seasonal_decompose
import math


class Grapher:
    """
	contains functions and classes to graph time series
	"""

    def __init__(self, url, file_name, data_file_name):
        self.ts_data = Formatter(url, file_name, data_file_name)
        self.ts_frame = self.ts_data.data_to_dataframe()

    def decompose_ts(self):
        self.ts_decomposition = seasonal_decompose(self.ts_frame, freq=365)
        self.seasonal = self.ts_decomposition.seasonal
        self.trend = self.ts_decomposition.trend
        self.resid = self.ts_decomposition.resid
        resid_list = []
        start_i = 0
        for i in self.resid.iloc[:, 0].tolist():
            resid_list.append(i)
        print(resid_list)
        for i in range(len(resid_list)):
            if math.isnan(resid_list[i]) != True:
                start_i = i
                break
        print(start_i)
        resid_list1 = resid_list[start_i:]
        for i in range(len(resid_list1)):
            if math.isnan(resid_list1[i]) == True:
                end_i = i
                break
        print(end_i)
        end_i = end_i + start_i
        self.resid = self.resid.dropna()
        return self.resid, self.seasonal, self.trend, start_i, end_i

    def get_data(self):
        return self.ts_frame


if __name__ == '__main__':
    mygrapher = Grapher('', 'christmas.txt', 'christmas_data.txt')
    mygrapher.decompose_ts()
    plt.figure()
    plt.plot(mygrapher.ts_frame)
    plt.plot(mygrapher.trend)
    plt.plot(mygrapher.seasonal)
    plt.plot(mygrapher.resid)

from format_data import Formatter
import matplotlib.pyplot as plt
from statsmodels.tsa.seasonal import seasonal_decompose
import math

class Grapher:
	'''
	contains functions and classes to graph time series
	'''
	def __init__(self, url, file_name, data_file_name):
		self.ts_data = Formatter(url, file_name, data_file_name)
		self.ts_frame = self.ts_data.data_to_dataframe()

	def decompose_ts(self):
		self.ts_decomposition = seasonal_decompose(self.ts_frame, freq=365)
		self.seasonal = self.ts_decomposition.seasonal
		self.trend = self.ts_decomposition.trend
		self.resid = self.ts_decomposition.resid
		resid_list = []
		start_i=0
		for i in self.resid.iloc[:, 0].tolist():
			resid_list.append(i)
		print(resid_list)
		for i in range(len(resid_list)):
			if math.isnan(resid_list[i]) != True:
				start_i = i
				break
		print(start_i)
		resid_list1= resid_list[start_i:]
		for i in range(len(resid_list1)):
			if math.isnan(resid_list1[i]) == True:
				end_i = i
				break
		print(end_i)
		end_i=end_i+start_i
		#print(resid_list[start_i:end_i])
		self.resid= self.resid.dropna()
		#print(self.resid)
		return self.resid, self.seasonal, self.trend, start_i, end_i

	def get_data(self):
		return self.ts_frame


if __name__ == '__main__':
	# from bokeh.charts import Line, show, output_file
	mygrapher = Grapher("", "christmas.txt", "christmas_data.txt")
	mygrapher.decompose_ts()
	plt.figure()
	plt.plot(mygrapher.ts_frame)
	plt.plot(mygrapher.trend)
	plt.plot(mygrapher.seasonal)
	plt.plot(mygrapher.resid)
	#plt.show()
