From 814ec27842e5c25980fa4de2825e0838a1f16ad5 Mon Sep 17 00:00:00 2001
From: Samuel <3030760+samuelstjean@users.noreply.github.com>
Date: Fri, 11 Mar 2022 09:55:09 +0100
Subject: [PATCH] remove custom scipy rand
---
myscipy_rand/__init__.py | 6 ----
myscipy_rand/myscipy_rand.py | 65 ------------------------------------
2 files changed, 71 deletions(-)
delete mode 100644 myscipy_rand/__init__.py
delete mode 100644 myscipy_rand/myscipy_rand.py
diff --git a/myscipy_rand/__init__.py b/myscipy_rand/__init__.py
deleted file mode 100644
index 36116bf..0000000
--- a/myscipy_rand/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-__all__ = ['myscipy_rand']
-
-from pkg_resources import get_distribution
-__version__ = get_distribution('spams').version
-
-from .myscipy_rand import *
diff --git a/myscipy_rand/myscipy_rand.py b/myscipy_rand/myscipy_rand.py
deleted file mode 100644
index 4c292c3..0000000
--- a/myscipy_rand/myscipy_rand.py
+++ /dev/null
@@ -1,65 +0,0 @@
-from __future__ import absolute_import, division, print_function
-
-import numpy as np
-import scipy.sparse as ssp
-
-
-def rand(m, n, density=0.01, format="coo", dtype=None):
- """Generate a sparse matrix of the given shape and density with uniformely
- distributed values.
-
- Parameters
- ----------
- m, n: int
- shape of the matrix
- density: real
- density of the generated matrix: density equal to one means a full
- matrix, density of 0 means a matrix with no non-zero items.
- format: str
- sparse matrix format.
- dtype: dtype
- type of the returned matrix values.
-
- Notes
- -----
- Only float types are supported for now.
- """
- if density < 0 or density > 1:
- raise ValueError("density expected to be 0 <= density <= 1")
- if dtype and not dtype in [np.float32, np.float64, np.longdouble]:
- raise NotImplementedError("type %s not supported" % dtype)
-
- mn = m * n
-
- # XXX: sparse uses intc instead of intp...
- tp = np.intp
- if mn > np.iinfo(tp).max:
- msg = """\
-Trying to generate a random sparse matrix such as the product of dimensions is
-greater than %d - this is not supported on this machine
-"""
- raise ValueError(msg % np.iinfo(tp).max)
-
- # Number of non zero values
- k = int(density * m * n)
-
- # Generate a few more values than k so that we can get unique values
- # afterwards.
- # XXX: one could be smarter here
- mlow = 5
- fac = 1.02
- gk = min(k + mlow, fac * k)
-
- def _gen_unique_rand(_gk):
- id = np.random.rand(_gk)
- return np.unique(np.floor(id * mn))[:k]
-
- id = _gen_unique_rand(gk)
- while id.size < k:
- gk *= 1.05
- id = _gen_unique_rand(gk)
-
- j = np.floor(id * 1. / m).astype(tp)
- i = (id - j * m).astype(tp)
- vals = np.random.rand(k).astype(dtype)
- return ssp.coo_matrix((vals, (i, j)), shape=(m, n)).asformat(format)
--
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