An automatically sorting list of words that fit into a hexagon. Words are currently gibberish.
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A tweak of the D3Kit Circles example to fix some transition bugs it had, and to add, well, a ton of circles.
I hereby claim:
- I am Brideau on github.
- I am brideau (https://keybase.io/brideau) on keybase.
- I have a public key whose fingerprint is 3912 9FB2 7C3A 0110 302F 91E4 F19F A065 AC03 9521
To claim this, I am signing this object:
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export DYLD_LIBRARY_PATH=/usr/local/opt/gdal2/lib:$DYLD_LIBRARY_PATH |
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// If you need to add additional parameters, as is the case if creating a | |
// CSV file, you can use the -lco flag multiple times | |
val outPathCsv = Paths.get("temp", "Canada3573Csv", "Canada3573.csv").toAbsolutePath | |
val cmdCsv = Array("-f", "CSV", outPathCsv.toString, inPath.toString, | |
"-lco", "GEOMETRY=AS_WKT", | |
"-lco", "CREATE_CSVT=YES", | |
"-lco", "SEPARATOR=SEMICOLON" | |
) | |
convertUsingOgr2Ogr(outPathCsv, cmdCsv).onComplete{ |
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{ | |
"name": "Testing a Pool", | |
"description": "The pool that tests all the pools", | |
"ticker": "TEST", | |
"homepage": "https://teststakepool.com" | |
} |
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def precision_at_k(y_true, y_score, k, pos_label=1): | |
from sklearn.utils import column_or_1d | |
from sklearn.utils.multiclass import type_of_target | |
y_true_type = type_of_target(y_true) | |
if not (y_true_type == "binary"): | |
raise ValueError("y_true must be a binary column.") | |
# Makes this compatible with various array types | |
y_true_arr = column_or_1d(y_true) |
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import faker as f | |
import numpy as np | |
from numpy.random import default_rng | |
from pandas import DataFrame | |
from scipy.stats import truncnorm | |
from sklearn.metrics import average_precision_score | |
fake_bad_actor_generator = f.Faker() | |
rng = default_rng() |
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