<h3 dir="auto">Describe the issue:</h3>
<p dir="auto">input: np.arange(1.0125, 1.1, 0.0125)<br>
output is: array([1.0125, 1.025 , 1.0375, 1.05  , 1.0625, 1.075 , 1.0875, 1.1   ])<br>
output expected: array([1.0125, 1.025 , 1.0375, 1.05  , 1.0625, 1.075 , 1.0875  ])</p>
<h3 dir="auto">Reproduce the code example:</h3>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="#They do not have the same behavior
np.arange(0.0125,0.1,0.0125)
np.arange(1.0125,1.1,0.0125)"><pre class="notranslate"><span class="pl-c">#They do not have the same behavior</span>
<span class="pl-s1">np</span>.<span class="pl-en">arange</span>(<span class="pl-c1">0.0125</span>,<span class="pl-c1">0.1</span>,<span class="pl-c1">0.0125</span>)
<span class="pl-s1">np</span>.<span class="pl-en">arange</span>(<span class="pl-c1">1.0125</span>,<span class="pl-c1">1.1</span>,<span class="pl-c1">0.0125</span>)</pre></div>
<h3 dir="auto">Error message:</h3>
<div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="No error occurs, but the output is not as expected since there is one array element to much."><pre class="notranslate">No error occurs, but the output is not as expected since there is one array element to much.</pre></div>
<h3 dir="auto">NumPy/Python version information:</h3>
<p dir="auto">numpy.<strong>version</strong><br>
'1.21.5'<br>
sys.version<br>
'3.9.7 (default, Sep 16 2021, 16:59:28) [MSC v.1916 64 bit (AMD64)]'</p>
<p dir="auto">Let me show you the issue directly:</p>
<h3 dir="auto">Reproducing code example:</h3>
<p dir="auto">np.arange(2114.8,2114.8+.05,.05)  produces array([2114.8 , 2114.85])</p>
<p dir="auto">np.arange(2114.8,2114.8+1.,1.) produces  array([2114.8])</p>
<p dir="auto">dont understand why they return arrays of different lengths.</p>