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from PIL import image
import pandas as pd
import numpy as np

empty_pixel = np.array([255, 255, 255, 0]).reshape(1, 1, -1)

# !wget https://github.com/theislab/scanpy/raw/master/docs/_static/img/Scanpy_Logo_RGB.png
im = Image.open("./Scanpy_Logo_RGB.png")
a = np.array(im)

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"""Simple OrderedSet implementation."""

from collections import OrderedDict
from collections.abc import MutableSet
from functools import reduce
from itertools import repeat
from operator import or_, sub


class OrderedSet(MutableSet):

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All benchmarks:

       before           after         ratio
     [4440b90f]       [a80db25c]
     <doc-fix2>       <obsp-update>
- 2.1052631578947367  1.4814814814814814     0.70  views.SubsetMemorySuite.track_repeated_subset_memratio(100, 100, 'X-csr', 'obs', 'boolarray')
- 1.8181818181818181  1.2758620689655173     0.70  views.SubsetMemorySuite.track_repeated_subset_memratio(100, 100, 'X-csr', 'obs', 'intarray')
- 0.6666666666666666              0.5     0.75  views.SubsetMemorySuite.track_repeated_subset_memratio(100, 100, 'X-csr', 'obs', 'slice')
- 1.9473684210526316            1.375     0.71  views.SubsetMemorySuite.track_repeated_subset_memratio(100, 100, 'X-csr', 'var', 'boolarray')

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"""
TODO:

* Get dates for each state
"""

from requests_html import HTMLSession
import pandas as pd
import string

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# Attempt at split apply combine for DimensionalData.jl
# This does require some bug fixes for various reduction methods on DimensionalArray's I've got on my local branch.
# Currently not type stable, but performance still beats pandas + scipy for grouping on a sparse array
# It was type stable when I was just grouping over one dimension, but then I hit https://github.com/JuliaLang/julia/issues/29368
# It's quite a fight between being able to preallocate output and having a type-stable function. 
# Even though I'm only really avoiding high total memory usage by allocating.

using SplitApplyCombine
using CategoricalArrays
using Dictionaries

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--- src
+++ dst
@@ -2612,10 +2612,20 @@
                     )  # /Load
                   id=
                     'C',  # str
                 )  # /Name
             )  # /Assign
+            Return(
+              value=

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Python 3.7.4 (default, Sep  7 2019, 18:27:02) 
Type 'copyright', 'credits' or 'license' for more information
IPython 7.8.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import h5py                                                                                

In [2]: import numpy as np                                                                         

In [3]: indices = np.sort(np.random.choice(int(1e7), int(1e4), replace=False))                     

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Python 3.7.4 (default, Sep  7 2019, 18:27:02) 
Type 'copyright', 'credits' or 'license' for more information
IPython 7.8.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import h5py                                                                                

In [2]: import numpy as np                                                                         

In [3]: indices = np.sort(np.random.choice(int(1e7), int(1e4), replace=False))                     

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---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
/usr/local/lib/python3.7/site-packages/numba/errors.py in new_error_context(fmt_, *args, **kwargs)
    661     try:
--> 662         yield
    663     except NumbaError as e:

/usr/local/lib/python3.7/site-packages/numba/lowering.py in lower_block(self, block)
    257                                    loc=self.loc, errcls_=defaulterrcls):
--> 258                 self.lower_inst(inst)

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