From 823a5ba05a2f90a0ddb50c027c6eb5a17bdd758c Mon Sep 17 00:00:00 2001
From: CelestialCrafter <celestialcraftermc@gmail.com>
Date: Sat, 23 Sep 2023 19:43:51 -0500
Subject: [PATCH] added color api made all the plots use color api

---
 plots/bollinger_bands.py | 11 ++++++-----
 plots/bot_net_worth.py   |  5 +++--
 plots/colors.py          | 14 ++++++++++++++
 plots/macd.py            |  9 +++++----
 plots/rsi.py             |  7 ++++---
 5 files changed, 32 insertions(+), 14 deletions(-)
 create mode 100644 plots/colors.py

diff --git a/plots/bollinger_bands.py b/plots/bollinger_bands.py
index 40cda19..2e723bc 100755
--- a/plots/bollinger_bands.py
+++ b/plots/bollinger_bands.py
@@ -1,6 +1,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 from algorithms.bollinger_bands import algorithm as boillinger_bands
+import colors
 
 def plot(prices):
 	upper_band, lower_band, middle_band = boillinger_bands(prices)
@@ -11,14 +12,14 @@ def plot(prices):
 	plt.fill_between(indicies, upper_band, lower_band, color='grey', alpha=0.3)
 
 	# Price/SMA
-	plt.plot(indicies, sliced_prices, color='plum')
-	plt.plot(indicies, middle_band, color='mediumpurple')
+	plt.plot(indicies, sliced_prices, color=colors.mainline())
+	plt.plot(indicies, middle_band, color=colors.secondaryline())
 
 	# Buy/Sell Signals
 	upper_condition = sliced_prices >= upper_band
 	lower_condition = sliced_prices <= lower_band
 
-	plt.scatter(indicies[upper_condition], sliced_prices[upper_condition], color='lightcoral')
-	plt.scatter(indicies[lower_condition], sliced_prices[lower_condition], color='darkturquoise')
-	
+	plt.scatter(indicies[upper_condition], sliced_prices[upper_condition], color=colors.upper())
+	plt.scatter(indicies[lower_condition], sliced_prices[lower_condition], color=colors.lower())
+
 	return plt
diff --git a/plots/bot_net_worth.py b/plots/bot_net_worth.py
index 13b2b80..ca12f08 100644
--- a/plots/bot_net_worth.py
+++ b/plots/bot_net_worth.py
@@ -1,9 +1,10 @@
 import numpy as np
 import matplotlib.pyplot as plt
+import colors
 
 def plot(bot_profit):
 	bot_profit = np.array(bot_profit)
 	indicies = np.arange(0, bot_profit.shape[0]) * 5
-	plt.plot(indicies, bot_profit, color='lightcoral')
+	plt.plot(indicies, bot_profit, color=colors.upper())
 
-	return plt
\ No newline at end of file
+	return plt
diff --git a/plots/colors.py b/plots/colors.py
new file mode 100644
index 0000000..668492d
--- /dev/null
+++ b/plots/colors.py
@@ -0,0 +1,14 @@
+def mainline():
+	return 'plum'
+
+def secondaryline():
+	return 'mediumpurple'
+
+def upper():
+	return 'lightcoral'
+
+def lower():
+	return 'darkturquoise'
+
+def inner():
+	return 'grey'
diff --git a/plots/macd.py b/plots/macd.py
index 0d33e75..7081027 100755
--- a/plots/macd.py
+++ b/plots/macd.py
@@ -1,6 +1,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 from algorithms.macd import algorithm as macd
+import colors
 
 def plot(prices):
 	macd_line, signal_line = macd(prices)
@@ -9,10 +10,10 @@ def plot(prices):
 	upper_condition = macd_line > signal_line
 	lower_condition = macd_line < signal_line
 
-	plt.scatter(indicies[upper_condition], signal_line[upper_condition], color='darkturquoise')
-	plt.scatter(indicies[lower_condition], signal_line[lower_condition], color='lightcoral')
+	plt.scatter(indicies[upper_condition], signal_line[upper_condition], color=colors.lower())
+	plt.scatter(indicies[lower_condition], signal_line[lower_condition], color=colors.upper())
 
-	plt.plot(signal_line, color='plum')
-	plt.plot(macd_line, color='mediumpurple')
+	plt.plot(signal_line, color=colors.mainline())
+	plt.plot(macd_line, color=colors.secondaryline())
 
 	return plt
diff --git a/plots/rsi.py b/plots/rsi.py
index 6ebc766..daeba5b 100755
--- a/plots/rsi.py
+++ b/plots/rsi.py
@@ -1,19 +1,20 @@
 import numpy as np
 import matplotlib.pyplot as plt
 from algorithms.rsi import algorithm as rsi
+import colors
 
 def plot(prices):
 	rsi_data = rsi(prices)
 	rsi_indicies = np.arange(0, rsi_data.shape[0])
 
-	plt.plot(rsi_indicies, rsi_data, color='plum')
+	plt.plot(rsi_indicies, rsi_data, color=colors.mainline())
 
 	# Thresholds
 	rsi_upper = np.full(rsi_data.shape, 70)
 	rsi_lower = np.full(rsi_data.shape, 30)
 
 	plt.fill_between(rsi_indicies, rsi_upper, rsi_lower, color='grey', alpha=0.3)
-	plt.plot(rsi_indicies, rsi_upper, linestyle='dashed', color='lightcoral')
-	plt.plot(rsi_indicies, rsi_lower, linestyle='dashed', color='darkturquoise')
+	plt.plot(rsi_indicies, rsi_upper, linestyle='dashed', color=colors.upper())
+	plt.plot(rsi_indicies, rsi_lower, linestyle='dashed', color=colors.lower())
 
 	return plt