AndreaCensi

-- Auto-generated Lean 4 code from OpenAPI schema

import Lean.Data.Json
import Std.Data.TreeMap

set_option maxHeartbeats 1000000

namespace Format2

AndreaCensi

#0  __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:50
#1  0x00007facab77e537 in __GI_abort () at abort.c:79
#2  0x00007facab77e40f in __assert_fail_base (fmt=0x7facab8e7128 "%s%s%s:%u: %s%sAssertion `%s' failed.\n%n",
    assertion=0x7faca89efb98 "(value) != ((void *)0)",
    file=0x7faca89ef570 "/tmp/.local/lib/python3.10/site-packages/nuitka/build/include/nuitka/helper/dictionaries.h", line=275, function=<optimized out>)
    at assert.c:92
#3  0x00007facab78d662 in __GI___assert_fail (assertion=0x7faca89efb98 "(value) != ((void *)0)",
    file=0x7faca89ef570 "/tmp/.local/lib/python3.10/site-packages/nuitka/build/include/nuitka/helper/dictionaries.h", line=275,
    function=0x7faca89efd50 <__PRETTY_FUNCTION__.9> "UPDATE_STRING_DICT0") at assert.c:101
#4  0x00007faca893988e in UPDATE_STRING_DICT0 (dict=0x7faca8a88af0, key=<unknown at remote 0x7facaba4ec10>, value='__spec__')

AndreaCensi

These videos are unused:
   \linkvideo{spring2021-functorial-comp-a:design-queries} % Design queries
   \linkvideo{spring2021-functorial-comp-a:optimization-semantics} % Optimization semantics
   \linkvideo{spring2021-functorial-comp-a:how-cat-helps} % How can category theory help?
   \linkvideo{spring2021-functorial-comp-a:patterns} % Looking for patterns
   \linkvideo{spring2021-functorial-comp-a:compositionality} % Looking for compositionality
   \linkvideo{spring2021-functorial-comp-a:from-math-to-impl} % From math to implementation
   \linkvideo{spring2021-functorial-comp-a:solving-codesign} % Solving co-design problems
   \linkvideo{spring2021-functorial-comp-b:solving-queries} % Solving DP queries
   \linkvideo{spring2021-functorial-comp-b:solving-queries:solving-series} % Series composition

AndreaCensi

\linkvideo{spring2021-intro:why-cat-theory} % Why category theory?
\linkvideo{spring2021-intro:composition} % Composition
\linkvideo{spring2021-semi-mon-gro:summary} % Summary
\linkvideo{spring2021-morphisms:functions-nomenclature} % Functions nomenclature
\linkvideo{spring2021-morphisms:morphisms} % Morphisms
\linkvideo{spring2021-morphisms:morphisms:semigroup-morphisms} % Semigroup morphisms
\linkvideo{spring2021-morphisms:morphisms:semigroup-morphisms:semigroup-isomorphisms} % Semigroup isomorphisms
\linkvideo{spring2021-morphisms:morphisms:semigroup-morphisms:ascii} % ASCII encoding
\linkvideo{spring2021-morphisms:morphisms:semigroup-morphisms:morse} % Morse encoding
\linkvideo{spring2021-morphisms:morphisms:monoid-morphisms} % Monoid morphisms

AndreaCensi

import base64
import hashlib

import base58
import multihash

ipfs_id_output = {
    "ID": "QmTn4XvjcA2ZCaWmr3fRZ3MKVj4CzTNVZyjY16Dni5NFc2",
    "PublicKey": "CAASpgIwggEiMA0GCSqGSIb3DQEBAQUAA4IBDwAwggEKAoIBAQDp5zHxCAqW6mU4bKvwhi2TCZwdga5IkhdTxHnIA9IdagB/IevNhe0O+O7Rc7czC+0tqWLLDS99oM1FjDqmHbMGiGsEmsVDrkWgx4d7+aHaHQWzNvxTd96gP6mY/ww6tvA5k6Tnow6pgUGvIl32GYDd+n4XqWnt/heoDXTenASnXh7aEBMhXXosZelxme6Bfwqmd0YO/Y4J1oNeHprgzJlZ901AwpcITfZCQuUCiGyot72kmD5wdAQu31KMXI0Rf7rMr20cnQI5SE9hoXR7NWtZ3zEg+4ODsP2ssn7QcIepm7WXeb1EO9GXsL6eMqkDSiVmUF23h5BJDirucZ7fDnPHAgMBAAE=",
    "Addresses": [

AndreaCensi

Keybase proof

I hereby claim:

• I am andreacensi on github.
• I am censi (https://keybase.io/censi) on keybase.
• I have a public key ASBPicgZnGg8zvpehewAG33k8DYg1nz_nJBEQ0XFGVVZKwo

To claim this, I am signing this object:

AndreaCensi

Docker loginNo docker credentials provided, skipped docker login
Docker pull shippable/minv2:latestPulling image (latest) from shippable/minv2, 
Pulling image (latest) from shippable/minv2, endpoint: https://registry-1.docker.io/v1/, 
Pulling dependent layers, 
Download complete, 
Download complete, 
Download complete, 
Download complete, 
Download complete, 
Download complete, 

AndreaCensi

def xcorr(a, b=None, maxlag=None):
    if b is None:
        b = a
    a = numpy.array(a)
    b = numpy.array(b)
    
    
    if maxlag is None:
        maxlag = len(a) / 2

AndreaCensi

def xcorr(a, b=None, maxlag=None):
    if b is None:
        b = a
    a = numpy.array(a)
    b = numpy.array(b)
    
    
    if maxlag is None:
        maxlag = len(a) / 2