<commit_before>from statsmodels.sandbox.predict_functional import predict_functional
import numpy as np
import pandas as pd
import statsmodels.api as sm
from numpy.testing import dec

# If true, the output is written to a multi-page pdf file.
pdf_output = False

try:
    import matplotlib.pyplot as plt
    import matplotlib
    have_matplotlib = True
except ImportError:
    have_matplotlib = False

def pctl(q):
    return lambda x : np.percentile(x, 100 *q)


class TestPredFunc(object):

    @classmethod
    def setup_class(cls):
        if pdf_output:
            from matplotlib.backends.backend_pdf import PdfPages
            cls.pdf = PdfPages("predict_functional.pdf")

    @classmethod
    def teardown_class(cls):
        if pdf_output:
            cls.pdf.close()

    @dec.skipif(not have_matplotlib)
    def close_or_save(self, fig):
        if pdf_output:
            self.pdf.savefig(fig)
        else:
            plt.close(fig)

<commit_msg>Remove unneeded test skip decorator<commit_after>from statsmodels.sandbox.predict_functional import predict_functional
import numpy as np
import pandas as pd
import statsmodels.api as sm
from numpy.testing import dec

# If true, the output is written to a multi-page pdf file.
pdf_output = False

try:
    import matplotlib.pyplot as plt
    import matplotlib
    have_matplotlib = True
except ImportError:
    have_matplotlib = False

def pctl(q):
    return lambda x : np.percentile(x, 100 *q)


class TestPredFunc(object):

    @classmethod
    def setup_class(cls):
        if pdf_output:
            from matplotlib.backends.backend_pdf import PdfPages
            cls.pdf = PdfPages("predict_functional.pdf")

    @classmethod
    def teardown_class(cls):
        if pdf_output:
            cls.pdf.close()

    def close_or_save(self, fig):
        if pdf_output:
            self.pdf.savefig(fig)
        else:
            plt.close(fig)


{'fraction_non_alphanumeric': 0.07019381875327396, 'fraction_numerical': 0.003143006809848088, 'mean_word_length': 2.804780876494024, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '7244603', 'n_tokens_mistral': 605, 'n_tokens_neox': 580, 'n_words': 168}