Hey guys. Just getting started here. Trying to build a simple RSI2 strategy using the Pipeline. I've previously used basically the same code (have since edited a few things to try to fix this error) to implement the strategy on a list of sids. Once I brought in the Pipeline, I've failed to get the algo to run.

Here's the error I get:

AssertionError: real has wrong dimensions  
There was a runtime error on line 44.  

The error arises when I try to pull in the RSI from talib. I've used the same way of pulling in RSI on several simpler algos. This is how I've done it up to now:

hist = data.history(context.security, 'close', 100, '1d')  
rsi = ta.RSI(hist, 2)  

It's clear that the Pipeline doesn't like this way of doing it, but I'm pretty stumped after searching through a bunch of Quantopian forums looking for an answer.

Here's the code:

import quantopian.algorithm as algo  
from quantopian.pipeline import Pipeline  
from quantopian.pipeline.data.builtin import USEquityPricing  
from quantopian.pipeline.filters import Q500US, Q1500US ,Q3000US  
import talib as ta  
from quantopian.pipeline.factors import RSI

def initialize(context):  
    schedule_function(trade , date_rules.every_day() , time_rules.market_close(minutes=30))  
    algo.attach_pipeline(make_pipeline(), 'pipeline')  
    #context.rsi_lookback = 2  
    context.rsi_buy_level = 20  
    context.rsi_sell_level = 65  
    #context.rsi = RSI(inputs = [USEquityPricing.close], window_length = 2)

def make_pipeline():

    # Base universe set to the Q500US  
    universe = Q3000US()

    # Factor of yesterday's close price.  
    close_price = USEquityPricing.close.latest

    pipe = Pipeline(  
        columns={  
            'close': close_price,  
        },  
        screen=universe  
    )  
    return pipe

def before_trading_start(context, data):  
    context.output = algo.pipeline_output('pipeline')  
    context.security_list = context.output.index  
def trade(context,data):  
    for x in context.security_list:  
        current_price = data.current(context.security_list , 'price')  
        hist = data.history(context.security_list , 'close' , 100 , '1d')  
        sma_100_day = hist.mean()  
        rsi = ta.RSI(hist, 2)

        if rsi < context.rsi_buy_level and current_price > sma_100_day and context.portfolio.positions[x].amount == 0:  
            order_target_percent(x , 1.00)  
            print('we bought {}', x)  
        if context.portfolio.positions[x].amount > 0 and rsi > context.rsi_sell_level:  
            order_target_percent(x , 0.0)  

Would love some guidance guys. Really loving the Quantopian platform so far, very comfortable way to learn algo trading basics.