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Comments (5)

mrjbq7 avatar mrjbq7 commented on May 10, 2024

Do you have a traceback where the TypeError comes from?

And perhaps a reduced test case I could look at?

from ta-lib-python.

gataky avatar gataky commented on May 10, 2024

Here's an example

>>> data  = {'open': np.random.random(50),
         'high': np.random.random(50),
         'low': np.random.random(50),
         'close': np.random.random(50),
         'volume': np.random.random(50),
         'date' : np.random.random(50),
         'adj_close': np.random.random(50)}

>>> SMA(data)

TypeError                                 Traceback (most recent call last)
<ipython-input-20-0158c278e771> in <module>()
----> 1 function(data)
/usr/local/lib/python2.7/dist-packages/talib/abstract.so in talib.abstract.Function.__call__ (talib/abstract.c:5486)()
/usr/local/lib/python2.7/dist-packages/talib/abstract.so in talib.abstract.Function.__call_function (talib/abstract.c:5885)()
/usr/local/lib/python2.7/dist-packages/talib/func.so in talib.func.SMA (talib/func.c:69149)()

>>> SMA
{'input_names': OrderedDict([('price', 'close')]), 'display_name': 'Simple Moving Average', 'name': 'SMA', 
'parameters': OrderedDict([('timeperiod', 
{'volume': array([ 0.19965879,  ...  0.66562178]), 
'adj_close': array([ 0.18462606,  ...  0.79650523]), 
'high': array([ 0.14084359, ...  0.97573142]), 
'low': array([ 0.96886568,  ...  0.64990915]), 
'date': array([ 0.17448305, ...  0.09247204]), 
'close': array([ 0.10051449, ... 0.94898851]), 
'open': array([ 0.85688113, ...  0.33030068])})]), 
'output_flags': OrderedDict([('real', ['Line'])]), 
'function_flags': ['Output scale same as input'], 
'group': 'Overlap Studies', 'output_names': ['real']}

>>> SMA.set_parameters({"timeperiod": 10})
>>> data.pop('date')
>>> data.pop('adj_close')
>>> SMA(data)
array([        nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,  0.40497346,
        0.49296423,  0.54406229,  0.58375268,  0.63764305,  0.63466835,
        0.6657193 ,  0.64639348,  0.60670473,  0.61295131,  0.55539159,
        0.51127633,  0.49951175,  0.49663316,  0.44724503,  0.49235661,
        0.47239197,  0.48633259,  0.48177433,  0.43214096,  0.40667698,
        0.35579172,  0.32571917,  0.31783613,  0.32140285,  0.33196072,
        0.27834638,  0.31270933,  0.30925288,  0.30648999,  0.36263089,
        0.38288212,  0.35386921,  0.35011754,  0.35883574,  0.35319137,
        0.37672038,  0.36098139,  0.44618779,  0.51315401,  0.53659522])

I was looking at the abstract.pyx file and have a possible suggestion. This should strip off any keys that are not valid and make sure that the keys that are required are there. Havent tested it but hope it helps.

    def set_input_arrays(self, input_arrays):
        if isinstance(input_arrays, dict)
          count = 0
          for key in input_arrays.keys():
            if key in __INPUT_ARRAYS_KEYS:
              count += 1
            else:
              input_arrays.pop(key)
          if count == len(__INPUT_ARRAYS_KEYS):
            self.__input_arrays = input_arrays
            self.__outputs_valid = False
            return True
        return False

from ta-lib-python.

mrjbq7 avatar mrjbq7 commented on May 10, 2024

Ah, I see what you're saying -- @briancappello want to put together a patch and testcase?

from ta-lib-python.

briancappello avatar briancappello commented on May 10, 2024

Something like this? The biggest difference from what @JeffMGreg posted is that this only checks that the current indicator function's required input keys are satisfied. (In other words, if SMA only needs "close" to run, passing {'close': np.random.rand(100)} as input_arrays would suffice.)

def set_input_arrays(self, input_arrays):
    if isinstance(input_arrays, dict):
        reqd_keys = self._input_price_series_names()
        missing_keys = []
        for key in reqd_keys:
            if key not in input_arrays:
                missing_keys.append(key)
        if not missing_keys:
            self.__input_arrays = input_arrays
            self.__outputs_valid = False
            return True
        else:
            raise Exception('input_arrays parameter missing required data '\
                            'key%s: %s' % ('s' if len(missing_keys) > 1 \
                                                else '',
                                            ', '.join(missing_keys)))
    return False

from ta-lib-python.

mrjbq7 avatar mrjbq7 commented on May 10, 2024

I released 0.4.7 with a fix for this.

from ta-lib-python.

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