des

Author: Effeo

Code/2000-03-06_1_day_1.csv

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+Date,Open,High,Low,Close,Adj Close,Volume,Label
+2000-02-07,5.9375,6.0625,5.75,6.0625,6.0625,27400,1
+2000-02-08,6.0,6.0625,5.75,6.0,6.0,69700,2
+2000-02-09,5.875,6.125,5.875,6.0,6.0,108700,0
+2000-02-10,6.0,6.0625,5.875,6.0625,6.0625,91100,1
+2000-02-11,5.875,6.0,5.75,6.0,6.0,72300,0
+2000-02-14,6.125,6.75,5.875,6.4375,6.4375,100300,1
+2000-02-15,6.5625,6.5625,6.125,6.125,6.125,82100,2
+2000-02-16,6.3125,6.375,5.625,6.125,6.125,59100,1
+2000-02-17,6.125,6.1875,5.9375,6.0,6.0,26800,1
+2000-02-18,5.9375,5.9375,5.9375,5.9375,5.9375,6800,1
+2000-02-22,6.0,6.0,5.5,5.875,5.875,11300,1
+2000-02-23,6.0,6.1875,5.5625,5.75,5.75,18200,0
+2000-02-24,5.625,5.875,5.625,5.875,5.875,9500,1
+2000-02-25,5.875,5.9375,5.75,5.8125,5.8125,15700,0
+2000-02-28,5.75,6.0,5.6875,6.0,6.0,41600,1
+2000-02-29,5.75,6.0,5.625,5.75,5.75,64100,0
+2000-03-01,6.0,6.125,5.9375,6.0625,6.0625,37200,1
+2000-03-02,5.75,6.0,5.625,5.625,5.625,30900,0
+2000-03-03,5.625,5.9375,5.5625,5.75,5.75,17200,0
+2000-03-06,5.875,6.1875,5.875,6.0,6.0,44200,1

Code/2000-03-06_1_day_1_GAF.png

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+Date,Open,High,Low,Close,Adj Close,Volume,Label
+2000-02-04/2000-02-07,5.875,6.0625,5.75,6.0625,6.0625,47300,1
+2000-02-07/2000-02-08,5.9375,6.0625,5.75,6.0,6.0,97100,2
+2000-02-08/2000-02-09,6.0,6.125,5.75,6.0,6.0,178400,0
+2000-02-09/2000-02-10,5.875,6.125,5.875,6.0625,6.0625,199800,1
+2000-02-10/2000-02-11,6.0,6.0625,5.75,6.0,6.0,163400,0
+2000-02-11/2000-02-14,5.875,6.75,5.75,6.4375,6.4375,172600,1
+2000-02-14/2000-02-15,6.125,6.75,5.875,6.125,6.125,182400,2
+2000-02-15/2000-02-16,6.5625,6.5625,5.625,6.125,6.125,141200,1
+2000-02-16/2000-02-17,6.3125,6.375,5.625,6.0,6.0,85900,1
+2000-02-17/2000-02-18,6.125,6.1875,5.9375,5.9375,5.9375,33600,1
+2000-02-18/2000-02-22,5.9375,6.0,5.5,5.875,5.875,18100,1
+2000-02-22/2000-02-23,6.0,6.1875,5.5,5.75,5.75,29500,0
+2000-02-23/2000-02-24,6.0,6.1875,5.5625,5.875,5.875,27700,1
+2000-02-24/2000-02-25,5.625,5.9375,5.625,5.8125,5.8125,25200,0
+2000-02-25/2000-02-28,5.875,6.0,5.6875,6.0,6.0,57300,1
+2000-02-28/2000-02-29,5.75,6.0,5.625,5.75,5.75,105700,0
+2000-02-29/2000-03-01,5.75,6.125,5.625,6.0625,6.0625,101300,1
+2000-03-01/2000-03-02,6.0,6.125,5.625,5.625,5.625,68100,0
+2000-03-02/2000-03-03,5.75,6.0,5.5625,5.75,5.75,48100,0
+2000-03-03/2000-03-06,5.625,6.1875,5.5625,6.0,6.0,61400,1

Code/2000-03-06_1_day_2.csv

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+Date,Open,High,Low,Close,Adj Close,Volume,Label
+2000-02-02/2000-02-07,6.375,6.375,5.625,6.0625,6.0625,106600,1
+2000-02-03/2000-02-08,6.25,6.25,5.625,6.0,6.0,143300,2
+2000-02-04/2000-02-09,5.875,6.125,5.75,6.0,6.0,225700,0
+2000-02-07/2000-02-10,5.9375,6.125,5.75,6.0625,6.0625,296900,1
+2000-02-08/2000-02-11,6.0,6.125,5.75,6.0,6.0,341800,0
+2000-02-09/2000-02-14,5.875,6.75,5.75,6.4375,6.4375,372400,1
+2000-02-10/2000-02-15,6.0,6.75,5.75,6.125,6.125,345800,2
+2000-02-11/2000-02-16,5.875,6.75,5.625,6.125,6.125,313800,1
+2000-02-14/2000-02-17,6.125,6.75,5.625,6.0,6.0,268300,1
+2000-02-15/2000-02-18,6.5625,6.5625,5.625,5.9375,5.9375,174800,1
+2000-02-16/2000-02-22,6.3125,6.375,5.5,5.875,5.875,104000,1
+2000-02-17/2000-02-23,6.125,6.1875,5.5,5.75,5.75,63100,0
+2000-02-18/2000-02-24,5.9375,6.1875,5.5,5.875,5.875,45800,1
+2000-02-22/2000-02-25,6.0,6.1875,5.5,5.8125,5.8125,54700,0
+2000-02-23/2000-02-28,6.0,6.1875,5.5625,6.0,6.0,85000,1
+2000-02-24/2000-02-29,5.625,6.0,5.625,5.75,5.75,130900,0
+2000-02-25/2000-03-01,5.875,6.125,5.625,6.0625,6.0625,158600,1
+2000-02-28/2000-03-02,5.75,6.125,5.625,5.625,5.625,173800,0
+2000-02-29/2000-03-03,5.75,6.125,5.5625,5.75,5.75,149400,0
+2000-03-01/2000-03-06,6.0,6.1875,5.5625,6.0,6.0,129500,1

Code/2000-03-06_1_day_2_GAF.png

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+Date,Open,High,Low,Close,Adj Close,Volume,Label
+2000-02-01/2000-02-07,6.375,6.40625,5.625,6.0625,6.0625,111500,1
+2000-02-02/2000-02-08,6.375,6.375,5.625,6.0,6.0,176300,2
+2000-02-03/2000-02-09,6.25,6.25,5.625,6.0,6.0,252000,0
+2000-02-04/2000-02-10,5.875,6.125,5.75,6.0625,6.0625,316800,1
+2000-02-07/2000-02-11,5.9375,6.125,5.75,6.0,6.0,369200,0
+2000-02-08/2000-02-14,6.0,6.75,5.75,6.4375,6.4375,442100,1
+2000-02-09/2000-02-15,5.875,6.75,5.75,6.125,6.125,454500,2
+2000-02-10/2000-02-16,6.0,6.75,5.625,6.125,6.125,404900,1
+2000-02-11/2000-02-17,5.875,6.75,5.625,6.0,6.0,340600,1
+2000-02-14/2000-02-18,6.125,6.75,5.625,5.9375,5.9375,275100,1
+2000-02-15/2000-02-22,6.5625,6.5625,5.5,5.875,5.875,186100,1
+2000-02-16/2000-02-23,6.3125,6.375,5.5,5.75,5.75,122200,0
+2000-02-17/2000-02-24,6.125,6.1875,5.5,5.875,5.875,72600,1
+2000-02-18/2000-02-25,5.9375,6.1875,5.5,5.8125,5.8125,61500,0
+2000-02-22/2000-02-28,6.0,6.1875,5.5,6.0,6.0,96300,1
+2000-02-23/2000-02-29,6.0,6.1875,5.5625,5.75,5.75,149100,0
+2000-02-24/2000-03-01,5.625,6.125,5.625,6.0625,6.0625,168100,1
+2000-02-25/2000-03-02,5.875,6.125,5.625,5.625,5.625,189500,0
+2000-02-28/2000-03-03,5.75,6.125,5.5625,5.75,5.75,191000,0
+2000-02-29/2000-03-06,5.75,6.1875,5.5625,6.0,6.0,193600,1

Code/2000-03-06_1_day_4.csv

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+import matplotlib.pyplot as plt
+from pyts.image import GramianAngularField
+import pandas as pd
+
+# Load the CSV file into a pandas dataframe
+df = pd.read_csv('2000-03-06_1_day_1.csv', parse_dates=['Date'])
+
+# Get the values from the dataframe
+X = df.iloc[:, 1:].values.T
+
+# Compute Gramian angular fields
+gasf = GramianAngularField(method='summation')
+X_gasf = gasf.fit_transform(X)
+
+gadf = GramianAngularField(method='difference')
+X_gadf = gadf.fit_transform(X)
+
+# Plot the Gramian angular fields
+fig, ax = plt.subplots(ncols=2, figsize=(12, 6))
+ax[0].imshow(X_gasf[0], cmap='rainbow', origin='lower')
+ax[0].set_title('Gramian Angular Summation Field')
+ax[1].imshow(X_gadf[0], cmap='rainbow', origin='lower')
+ax[1].set_title('Gramian Angular Difference Field')
+plt.show()
+
+fig.savefig('2000-03-06_1_day_1_GAF.png', dpi=300, bbox_inches='tight')
+
+# Load the CSV file into a pandas dataframe
+df = pd.read_csv('2000-03-06_1_day_2.csv', parse_dates=['Date'])
+
+# Get the values from the dataframe
+X = df.iloc[:, 1:].values.T
+
+# Compute Gramian angular fields
+gasf = GramianAngularField(method='summation')
+X_gasf = gasf.fit_transform(X)
+
+gadf = GramianAngularField(method='difference')
+X_gadf = gadf.fit_transform(X)
+
+# Plot the Gramian angular fields
+fig, ax = plt.subplots(ncols=2, figsize=(12, 6))
+ax[0].imshow(X_gasf[0], cmap='rainbow', origin='lower')
+ax[0].set_title('Gramian Angular Summation Field')
+ax[1].imshow(X_gadf[0], cmap='rainbow', origin='lower')
+ax[1].set_title('Gramian Angular Difference Field')
+plt.show()
+
+fig.savefig('2000-03-06_1_day_2_GAF.png', dpi=300, bbox_inches='tight')
+
+# Load the CSV file into a pandas dataframe
+df = pd.read_csv('2000-03-06_1_day_4.csv', parse_dates=['Date'])
+
+# Get the values from the dataframe
+X = df.iloc[:, 1:].values.T
+
+# Compute Gramian angular fields
+gasf = GramianAngularField(method='summation')
+X_gasf = gasf.fit_transform(X)
+
+gadf = GramianAngularField(method='difference')
+X_gadf = gadf.fit_transform(X)
+
+# Plot the Gramian angular fields
+fig, ax = plt.subplots(ncols=2, figsize=(12, 6))
+ax[0].imshow(X_gasf[0], cmap='rainbow', origin='lower')
+ax[0].set_title('Gramian Angular Summation Field')
+ax[1].imshow(X_gadf[0], cmap='rainbow', origin='lower')
+ax[1].set_title('Gramian Angular Difference Field')
+plt.show()
+
+fig.savefig('2000-03-06_1_day_4_GAF.png', dpi=300, bbox_inches='tight')
+
+# Load the CSV file into a pandas dataframe
+df = pd.read_csv('2000-03-06_1_day_5.csv', parse_dates=['Date'])
+
+# Get the values from the dataframe
+X = df.iloc[:, 1:].values.T
+
+# Compute Gramian angular fields
+gasf = GramianAngularField(method='summation')
+X_gasf = gasf.fit_transform(X)
+
+gadf = GramianAngularField(method='difference')
+X_gadf = gadf.fit_transform(X)
+
+# Plot the Gramian angular fields
+fig, ax = plt.subplots(ncols=2, figsize=(12, 6))
+ax[0].imshow(X_gasf[0], cmap='rainbow', origin='lower')
+ax[0].set_title('Gramian Angular Summation Field')
+ax[1].imshow(X_gadf[0], cmap='rainbow', origin='lower')
+ax[1].set_title('Gramian Angular Difference Field')
+plt.show()
+
+fig.savefig('2000-03-06_1_day_5_GAF.png', dpi=300, bbox_inches='tight')

Code/2000-03-06_1_day_4_GAF.png

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+import pandas as pd
+from datetime import datetime
+
+# tolgo solo il primo elemento della lista, tolgo count e uso len(lista)
+# funzione per prendere la prima riga in base ad un anno dato in input
+def takeIndex(dates, dateStart):
+    i = 0
+    for date in dates:
+        dtObj = datetime.strptime(date, '%Y-%m-%d').date()
+        if dateStart == dtObj:
+            break
+        i += 1
+
+    return i
+
+# funzione per creare il CSV da un giorno
+def createCsv (data, start, finish, name):
+    csv1g = pd.DataFrame(columns=['Date', 'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume'])
+    for i in range(start, finish + 1):
+        csv1g = csv1g.append(data.iloc[i], ignore_index = True)
+    csv1g.to_csv(name, index = False)
+
+# funzione per prendere il massimo il minimo e la somma dei volumi
+def getHLS (list):
+    highest = list[0].iloc[2]
+    lowest = list[0].iloc[3]
+    sumVolume = list[0].iloc[6]
+    i = 0
+    for item in list:
+        if i != 0:
+            if highest < item.iloc[2]:
+                highest = item.iloc[2]
+
+            if lowest > item.iloc[3]:
+                lowest = item.iloc[3]
+
+            sumVolume += item.iloc[6]
+        i += 1
+    return highest, lowest, sumVolume
+
+# funzione per creare i cvs divisi per giorni
+def createCSV_V2 (data, start, finish, name, div, flag):
+    csv = pd.DataFrame(columns=['Date', 'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume'])
+
+    list = [data.iloc[start]]
+    for i in range(start + 1, finish + 1):
+        list.append(data.iloc[i])
+        if len(list) == div:
+            highest, lowest, sumVolume = getHLS(list)
+            row = {'Date': [list[0].iloc[0] + "/" + list[len(list) - 1].iloc[0]], 'Open': [list[0].iloc[1]],
+                   'High': [highest], 'Low': [lowest], 'Close': [list[len(list) - 1].iloc[4]],
+                   'Adj Close': [list[len(list) - 1].iloc[5]], 'Volume': [sumVolume]}
+            dataFrame = pd.DataFrame(row)
+            csv = csv.append(dataFrame, ignore_index=True)
+            list.pop(0)
+
+    '''
+    if flag:
+        for item in list:
+            highest, lowest, sumVolume = getHLS(list)
+            row = {'Date': [list[0].iloc[0] + "/" + list[len(list) - 1].iloc[0]], 'Open': [list[0].iloc[1]],
+                   'High': [highest], 'Low': [lowest], 'Close': [list[len(list) - 1].iloc[4]],
+                   'Adj Close': [list[len(list) - 1].iloc[5]], 'Volume': [sumVolume]}
+            dataFrame = pd.DataFrame(row)
+            csv = csv.append(dataFrame, ignore_index=True)
+            list.pop(0)
+
+    '''
+    if len(list) and flag:
+        highest, lowest, sumVolume = getHLS(list)
+        row = {'Date': [list[0].iloc[0] + "/" + list[len(list) - 1].iloc[0]], 'Open': [list[0].iloc[1]],
+               'High': [highest], 'Low': [lowest], 'Close': [list[len(list) - 1].iloc[4]],
+               'Adj Close': [list[len(list) - 1].iloc[5]], 'Volume': [sumVolume]}
+        dataFrame = pd.DataFrame(row)
+        csv = csv.append(dataFrame, ignore_index=True)
+
+    csv.to_csv(name, index=False)
+
+# MAIN
+# leggo il cvs
+data = pd.read_csv("DXYN.csv")
+# estrazione date
+dates = data.loc[:, "Date"]
+
+div = int(input("Scegliere il numero di giorni per cui dividere: "))
+while div > 0:
+    # leggo la data di inizio e converto la stringa in data
+    dateStart = input("Da che data iniziare: ")
+    start = takeIndex(dates, datetime.strptime(dateStart, '%Y-%m-%d').date())
+
+    dateFinish = input("A che data finire: ")
+    finish = takeIndex(dates, datetime.strptime(dateFinish, '%Y-%m-%d').date())
+
+    flag = int(input("Aggiungere le ultime date che possono rimanere alla fine della divisione ? (Si = 1, No = 0):  "))
+
+    name = input("Scrivere il nome (ricordarsi il .csv): ")
+
+    print("Creazione csv...")
+    if div == 1:
+        createCsv(data, start, finish, name)
+    else:
+        createCSV_V2(data, start, finish, name, div, flag)
+
+    print("Creazione conclusa.")
+    div = int(input("Creare altri file? (scrivere 0 per dire NO, il numero dei giorni per cui vuoi dividere per dire SI): "))

Code/2000-03-06_1_day_5.csv

@@ -0,0 +1,90 @@
+import pandas as pd
+from datetime import datetime
+
+
+def takeIndex(dates, dateStart):
+    i = 0
+    for date in dates:
+        dtObj = datetime.strptime(date, '%Y-%m-%d').date()
+        if dateStart == dtObj:
+            break
+        i += 1
+
+    return i
+
+def getLabel(data, i, close):
+    list = [data.iloc[i + 1]]
+    closeNextDay = list[0].iloc[4]
+
+    if close == closeNextDay : return 2
+
+    if close > closeNextDay : return 1
+
+    if close < closeNextDay : return 0
+
+def addLabel1g(data: pd.DataFrame, name):
+    csv1g = pd.DataFrame(columns=['Date', 'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume', 'Label'])
+
+    for i in range(0, data.shape[0]):
+        list = [data.iloc[i]]
+        if(i + 1 < data.shape[0]):
+            row = {'Date': [list[0].iloc[0]], 'Open': [list[0].iloc[1]],
+                   'High': [list[0].iloc[2]], 'Low': [list[0].iloc[3]], 'Close': [list[0].iloc[4]],
+                   'Adj Close': [list[0].iloc[5]], 'Volume': [list[0].iloc[6]], 'Label' : [getLabel(data, i, list[0].iloc[4])]}
+
+        else:
+            row = {'Date': [data.iloc[i].iloc[0]], 'Open': [data.iloc[i].iloc[1]],
+                   'High': [data.iloc[i].iloc[2]], 'Low': [data.iloc[i].iloc[3]], 'Close': [data.iloc[i].iloc[4]],
+                   'Adj Close': [data.iloc[i].iloc[5]], 'Volume': [data.iloc[i].iloc[6]],
+                   'Label': [None]}
+
+        dataFrame = pd.DataFrame(row)
+        csv1g = csv1g.append(dataFrame, ignore_index=True)
+
+    csv1g.to_csv(name, index=False)
+
+def getLabelNg(date, close, dates, data1g):
+    lastDate = date[date.find('/') + 1 : len(date)]
+    i = takeIndex(dates, datetime.strptime(lastDate, '%Y-%m-%d').date())
+
+    list = [data1g.iloc[i + 1]]
+    closeNextDay = list[0].iloc[4]
+
+    if close == closeNextDay: return 2
+
+    if close > closeNextDay: return 1
+
+    if close < closeNextDay: return 0
+
+def addLabelnG(data: pd.DataFrame, data1g: pd.DataFrame, name, dates):
+    csv = pd.DataFrame(columns=['Date', 'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume', 'Label'])
+
+    for i in range(0, data.shape[0]):
+        list = [data.iloc[i]]
+
+        if(i + 1 < data.shape[0]):
+            row = {'Date': [list[0].iloc[0]], 'Open': [list[0].iloc[1]],
+                   'High': [list[0].iloc[2]], 'Low': [list[0].iloc[3]], 'Close': [list[0].iloc[4]],
+                   'Adj Close': [list[0].iloc[5]], 'Volume': [list[0].iloc[6]],
+                   'Label': [getLabelNg(list[0].iloc[0], list[0].iloc[4], dates, data1g)]}
+        else:
+            row = {'Date': [data.iloc[i].iloc[0]], 'Open': [data.iloc[i].iloc[1]],
+                   'High': [data.iloc[i].iloc[2]], 'Low': [data.iloc[i].iloc[3]], 'Close': [data.iloc[i].iloc[4]],
+                   'Adj Close': [data.iloc[i].iloc[5]], 'Volume': [data.iloc[i].iloc[6]],
+                   'Label': [None]}
+
+        dataFrame = pd.DataFrame(row)
+        csv = csv.append(dataFrame, ignore_index=True)
+
+    csv.to_csv(name, index=False)
+
+data1g = pd.read_csv("div1.csv")
+dates = data1g.loc[:, "Date"]
+data2g = pd.read_csv("div2.csv")
+data4g = pd.read_csv("div4.csv")
+data5g = pd.read_csv("div5.csv")
+
+addLabelnG(data4g, data1g, "div4Label.csv", dates)
+addLabelnG(data5g, data1g, "div5Label.csv", dates)
+#addLabelnG(data2g, data1g, "div2Label.csv", dates)
+#addLabel1g(data1g, "div1Label.csv")