1 files changed, 94 insertions, 0 deletions
diff --git a/analysis.py b/analysis.py
new file mode 100644
index 0000000..2b5ed59
--- /dev/null
+++ b/analysis.py
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+import json
+import datetime
+
+# pull stock data from json files
+# timestamps_file = open('timestamps.json', 'r')
+# timestamps_file_data = timestamps_file.read()
+# timestamps = json.loads(timestamps_file_data)
+# timestamps = [datetime.datetime.fromtimestamp(t) for t in timestamps]
+
+# prices_file = open('close_prices.json', 'r')
+# prices = json.loads(prices_file.read())
+
+# print('timestamps:\t', timestamps, '\nprices:\t', prices)
+
+# make the line data for the 5 day exponential moving average (EMA)
+
+def calc_first_sma(period, prices):
+    prices_sum = 0
+    for i in range(0, period):
+        prices_sum += prices[i] # 0, 1, 2, 3 ("popping" order)
+    # print('prices_sum:\t', prices_sum)
+
+    return prices_sum / period
+
+def calc_emas(period, prices):
+    weighted_multiplier = 2.0 / (period + 1.0)
+
+    # calculate the first ema
+    first_ema = calc_first_sma(period, prices)
+
+    # calculate the rest ema's using that first
+    emas = [first_ema] * period
+    for i in range(period + 1, len(prices)): # 4, 5, 6, ... , last
+        last_ema = emas[-1]
+        next_ema = prices[i] * weighted_multiplier + last_ema * (1 - weighted_multiplier)
+        emas.append(next_ema)
+    return emas
+
+def interpolate_intersection(intersection_indices, timestamps, prices1, prices2):
+    left_index = intersection_indices[0]
+    right_index = intersection_indices[1]
+    if right_index == -1:
+        return timestamps[left_index]
+    
+    y_1 = prices1[left_index]
+    y_2 = prices1[right_index] # first line
+
+    v_1 = prices2[left_index]
+    v_2 = prices2[right_index] # second line
+
+    x_1 = 0 # take this as zero the simplify the algebra
+    x_diff = timestamps[right_index] - timestamps[left_index] # same for both lines
+
+    # find intersection between those lines
+    x_diff = x_diff.total_seconds()
+    m_1 = (y_2 - y_1) / x_diff # slope of line 1
+    m_2 = (v_2 - v_1) / x_diff
+
+    x_interpolated = (v_1 - y_1) / (m_1 - m_2)
+    y_interpolated = m_1 * (x_interpolated) + y_1
+
+    # add back the time we subtracted to make x_1=0
+    x_interpolated = datetime.timedelta(seconds = x_interpolated) + timestamps[left_index]
+    return (x_interpolated, y_interpolated)
+
+
+
+"""
+Returns the indices of where two arrays' values intersects
+"""
+def find_intersections(prices1, prices2):
+    if len(prices1) != len(prices2):
+        print("ERROR IN find_intersections: len of arrs not the same")
+        return []
+    prev_p1 = prices1[0]
+    prev_p2 = prices2[0]
+    intersection_indices = set()
+    for i in range(1, len(prices1)):
+        next_p1 = prices1[i]
+        next_p2 = prices2[i]
+        # if the sign (negative to positive) changes, then there was an intersection between these pts
+        sub_prev = prev_p1 - prev_p2
+        sub_next = next_p1 - next_p2
+
+        if (sub_prev > 0 and sub_next < 0) or (sub_prev < 0 and sub_next > 0): # TODO, consider on the 0 case
+            intersection_indices.add((i-1, i))
+        
+        if sub_next == 0:
+            intersection_indices.add((i, -1))
+
+        prev_p1 = next_p1
+        prev_p2 = next_p2
+    
+    return intersection_indices