boolean values, patterns

Im using simple booleans to determine a pattern and price action. Trouble is Im getting Trueresult on the values that should be false.

I even went to the python 3.5 IDLE to double check if I did something wrong

Pattern that Im looking for is a big red candle thats engulfing the next days green candle

Here's the code from Python 3.5 IDLE where the bool value being returned is Flase. Prices are AAPL for 15th and 16th November

>>> close_1d = 110.01  
>>> close_2d = 107.11  
>>> open_1d = 106.70  
>>> open_2d = 106.57  
>>> open_2d > close_2d and open_1d < close_1d and open_2d > close_1d and open_2d > open_1d and close_2d <= open_1d and close_2d < close_1d  
False

Here is the algo code, where I used exactly the same bool inputs for screening as in Python IDLE

# The pipeline API requires imports.  
from quantopian.pipeline import Pipeline  
from quantopian.pipeline import CustomFactor  
from quantopian.algorithm import attach_pipeline, pipeline_output  
from quantopian.pipeline.data.builtin import USEquityPricing  
from quantopian.pipeline.factors import SimpleMovingAverage

class CurClose(CustomFactor):  
    inputs = [USEquityPricing.close]  
    window_length = 1  
    def compute(self, today, assets, out, close):  
        out[:] = close[-1]  
class CurOpen(CustomFactor):  
    inputs = [USEquityPricing.open]  
    window_length = 1  
    def compute(self, today, assets, out, open):  
        out[:] = open[-1]  
class YesClose(CustomFactor):  
    inputs = [USEquityPricing.close]  
    window_length = 2  
    def compute(self, today, assets, out, close):  
        out[:] = close[-2]  
class YesOpen(CustomFactor):  
    inputs = [USEquityPricing.open]  
    window_length = 2  
    def compute(self, today, assets, out, open):  
        out[:] = open[-2]

def initialize(context):  
    #Created and attached pipeline  
    pipe = Pipeline()  
    pipe = attach_pipeline(pipe, name = 'my_pipeline')  
    #Construct Factors  
    close_1d = CurClose()  
    close_2d = YesClose()  
    open_1d = CurOpen()  
    open_2d = YesOpen()  
    #Construct Filters  
    #This screen should find simple pattern based on open and close values from las two trading days  
    #Pattern that Im looking for is a big red candle thats engulfing the next days green candle  
    screen = open_2d > close_2d and open_1d < close_1d and open_2d > close_1d and open_2d > open_1d and close_2d <= open_1d and close_2d < close_1d  
    #Register outputs  
    pipe.add(screen, 'screen')  
    pipe.add(open_2d, 'open_2d')  
    pipe.add(close_2d, 'close_2d')  
    pipe.add(open_1d, 'open_1d')  
    pipe.add(close_1d, 'close_1d')  
    #Filter results  
    pipe.set_screen(screen)  
def before_trading_start(context, data):  
    results = pipeline_output('my_pipeline')  
    print(results)

Results from the pipeline_output , note AAPL prices are the ones being double checked with Python IDLE

2016-11-17 14:45  PRINT                           close_1d  close_2d  open_1d     open_2d screen  
Equity(24 [AAPL])          110.010   107.110  106.700  106.570000   True  
Equity(39 [DDC])             8.565     8.500    8.530    8.430000   True  
Equity(62 [ABT])            39.950    39.800   39.800   39.290000   True  
Equity(64 [ABX])            15.600    15.580   15.550   14.780000   True  
Equity(67 [ADSK])           77.570    75.140   74.920   73.860000   True  
Equity(70 [VBF])            18.370    18.109   18.180   17.970000   True  
Equity(84 [ACET])           19.180    19.170   19.000   19.230000   True  
Equity(106 [ACU])           21.700    21.610   21.820   21.730000   True  
Equity(110 [ACXM])          26.890    26.760   26.550   27.030000   True  
Equity(114 [ADBE])         104.080   103.660  103.610  103.140000   True  
Equity(149 [ADX])           13.100    13.080   13.050   13.020000   True  
Equity(154 [AEM])           44.270    44.220   44.200   41.990000   True  
Equity(162 [AEPI])         113.000   112.700  112.700  112.450000   True  
Eq...