Large Matrices Result in Integer Overflow #285

Closed
Closed
Large Matrices Result in Integer Overflow#285

Description

@danielsclint
danielsclint
opened on Dec 20, 2019

I thought this problem was eradicated with PR #265. Unfortunately, with really large numbers, the issue still occurs.

activitysim/activitysim/abm/tables/skims.py

Lines 186 to 194 in 7b57c94

omx_shape=skim_info['omx_shape']
skim_dtype=skim_info['dtype']
blocks=skim_info['blocks']
skim_data= []
forblock_name, block_sizeiniteritems(blocks):
skims_shape=omx_shape+ (block_size,)
block_buffer=skim_buffers[block_name]
assertlen(block_buffer) ==int(np.prod(skims_shape))

The issue is in the Numpy library np.prod() method. According to the documentation:

Arithmetic is modular when using integer types, and no error is raised on overflow.

>>>x=np.array([536870910, 536870910, 536870910, 536870910])
>>>np.prod(x)
16# may vary

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      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
       blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

      Skip to content
      Large Matrices Result in Integer Overflow #285
      Closed
      Closed
      Large Matrices Result in Integer Overflow#285
      Description
      @danielsclint
      danielsclint
      opened on Dec 20, 2019
      I thought this problem was eradicated with PR #265. Unfortunately, with really large numbers, the issue still occurs.
      activitysim/activitysim/abm/tables/skims.py
      
Lines 186 to 194
in
7b57c94
      omx_shape=skim_info['omx_shape'] 
      skim_dtype=skim_info['dtype'] 
      blocks=skim_info['blocks'] 
      skim_data= [] 
      forblock_name, block_sizeiniteritems(blocks): 
      skims_shape=omx_shape+ (block_size,) 
      block_buffer=skim_buffers[block_name] 
      assertlen(block_buffer) ==int(np.prod(skims_shape)) 
      The issue is in the Numpy library np.prod() method. According to the documentation:
      Arithmetic is modular when using integer types, and no error is raised on overflow.
      >>>x=np.array([536870910, 536870910, 536870910, 536870910])
>>>np.prod(x)
16# may vary
      Activity
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

          Skip to content
          Large Matrices Result in Integer Overflow #285
          Closed
          Closed
          Large Matrices Result in Integer Overflow#285
          Description
          @danielsclint
          danielsclint
          opened on Dec 20, 2019
          I thought this problem was eradicated with PR #265. Unfortunately, with really large numbers, the issue still occurs.
          activitysim/activitysim/abm/tables/skims.py
          
Lines 186 to 194
in
7b57c94
          omx_shape=skim_info['omx_shape'] 
          skim_dtype=skim_info['dtype'] 
          blocks=skim_info['blocks'] 
          skim_data= [] 
          forblock_name, block_sizeiniteritems(blocks): 
          skims_shape=omx_shape+ (block_size,) 
          block_buffer=skim_buffers[block_name] 
          assertlen(block_buffer) ==int(np.prod(skims_shape)) 
          The issue is in the Numpy library np.prod() method. According to the documentation:
          Arithmetic is modular when using integer types, and no error is raised on overflow.
          >>>x=np.array([536870910, 536870910, 536870910, 536870910])
>>>np.prod(x)
16# may vary
          Activity
          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
          Metadata
          Metadata
          Assignees
          No one assigned
            Labels
            No labels
            No labels
            Type
            No type
            Projects
            No projects
              Milestone
              No milestone
              Relationships
              None yet
              Development
              No branches or pull requests
              Issue actions
              
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

              Skip to content
              Large Matrices Result in Integer Overflow #285
              Closed
              Closed
              Large Matrices Result in Integer Overflow#285
              Description
              @danielsclint
              danielsclint
              opened on Dec 20, 2019
              I thought this problem was eradicated with PR #265. Unfortunately, with really large numbers, the issue still occurs.
              activitysim/activitysim/abm/tables/skims.py
              
Lines 186 to 194
in
7b57c94
              omx_shape=skim_info['omx_shape'] 
              skim_dtype=skim_info['dtype'] 
              blocks=skim_info['blocks'] 
              skim_data= [] 
              forblock_name, block_sizeiniteritems(blocks): 
              skims_shape=omx_shape+ (block_size,) 
              block_buffer=skim_buffers[block_name] 
              assertlen(block_buffer) ==int(np.prod(skims_shape)) 
              The issue is in the Numpy library np.prod() method. According to the documentation:
              Arithmetic is modular when using integer types, and no error is raised on overflow.
              >>>x=np.array([536870910, 536870910, 536870910, 536870910])
>>>np.prod(x)
16# may vary
              Activity
              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
              Metadata
              Metadata
              Assignees
              No one assigned
                Labels
                No labels
                No labels
                Type
                No type
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                No projects
                  Milestone
                  No milestone
                  Relationships
                  None yet
                  Development
                  No branches or pull requests
                  Issue actions
                  
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

                  Skip to content
                  Large Matrices Result in Integer Overflow #285
                  Closed
                  Closed
                  Large Matrices Result in Integer Overflow#285
                  Description
                  @danielsclint
                  danielsclint
                  opened on Dec 20, 2019
                  I thought this problem was eradicated with PR #265. Unfortunately, with really large numbers, the issue still occurs.
                  activitysim/activitysim/abm/tables/skims.py
                  
Lines 186 to 194
in
7b57c94
                  omx_shape=skim_info['omx_shape'] 
                  skim_dtype=skim_info['dtype'] 
                  blocks=skim_info['blocks'] 
                  skim_data= [] 
                  forblock_name, block_sizeiniteritems(blocks): 
                  skims_shape=omx_shape+ (block_size,) 
                  block_buffer=skim_buffers[block_name] 
                  assertlen(block_buffer) ==int(np.prod(skims_shape)) 
                  The issue is in the Numpy library np.prod() method. According to the documentation:
                  Arithmetic is modular when using integer types, and no error is raised on overflow.
                  >>>x=np.array([536870910, 536870910, 536870910, 536870910])
>>>np.prod(x)
16# may vary
                  Activity
                  Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                  Metadata
                  Metadata
                  Assignees
                  No one assigned
                    Labels
                    No labels
                    No labels
                    Type
                    No type
                    Projects
                    No projects
                      Milestone
                      No milestone
                      Relationships
                      None yet
                      Development
                      No branches or pull requests
                      Issue actions
                      
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

                      Skip to content
                      Large Matrices Result in Integer Overflow #285
                      Closed
                      Closed
                      Large Matrices Result in Integer Overflow#285
                      Description
                      @danielsclint
                      danielsclint
                      opened on Dec 20, 2019
                      I thought this problem was eradicated with PR #265. Unfortunately, with really large numbers, the issue still occurs.
                      activitysim/activitysim/abm/tables/skims.py
                      
Lines 186 to 194
in
7b57c94
                      omx_shape=skim_info['omx_shape'] 
                      skim_dtype=skim_info['dtype'] 
                      blocks=skim_info['blocks'] 
                      skim_data= [] 
                      forblock_name, block_sizeiniteritems(blocks): 
                      skims_shape=omx_shape+ (block_size,) 
                      block_buffer=skim_buffers[block_name] 
                      assertlen(block_buffer) ==int(np.prod(skims_shape)) 
                      The issue is in the Numpy library np.prod() method. According to the documentation:
                      Arithmetic is modular when using integer types, and no error is raised on overflow.
                      >>>x=np.array([536870910, 536870910, 536870910, 536870910])
>>>np.prod(x)
16# may vary
                      Activity
                      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                      Metadata
                      Metadata
                      Assignees
                      No one assigned
                        Labels
                        No labels
                        No labels
                        Type
                        No type
                        Projects
                        No projects
                          Milestone
                          No milestone
                          Relationships
                          None yet
                          Development
                          No branches or pull requests
                          Issue actions
                          
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

                          Skip to content
                          Large Matrices Result in Integer Overflow #285
                          Closed
                          Closed
                          Large Matrices Result in Integer Overflow#285
                          Description
                          @danielsclint
                          danielsclint
                          opened on Dec 20, 2019
                          I thought this problem was eradicated with PR #265. Unfortunately, with really large numbers, the issue still occurs.
                          activitysim/activitysim/abm/tables/skims.py
                          
Lines 186 to 194
in
7b57c94
                          omx_shape=skim_info['omx_shape'] 
                          skim_dtype=skim_info['dtype'] 
                          blocks=skim_info['blocks'] 
                          skim_data= [] 
                          forblock_name, block_sizeiniteritems(blocks): 
                          skims_shape=omx_shape+ (block_size,) 
                          block_buffer=skim_buffers[block_name] 
                          assertlen(block_buffer) ==int(np.prod(skims_shape)) 
                          The issue is in the Numpy library np.prod() method. According to the documentation:
                          Arithmetic is modular when using integer types, and no error is raised on overflow.
                          >>>x=np.array([536870910, 536870910, 536870910, 536870910])
>>>np.prod(x)
16# may vary
                          Activity
                          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                          Metadata
                          Metadata
                          Assignees
                          No one assigned
                            Labels
                            No labels
                            No labels
                            Type
                            No type
                            Projects
                            No projects
                              Milestone
                              No milestone
                              Relationships
                              None yet
                              Development
                              No branches or pull requests
                              Issue actions
                              
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

                              Skip to content
                              Large Matrices Result in Integer Overflow #285
                              Closed
                              Closed
                              Large Matrices Result in Integer Overflow#285
                              Description
                              @danielsclint
                              danielsclint
                              opened on Dec 20, 2019
                              I thought this problem was eradicated with PR #265. Unfortunately, with really large numbers, the issue still occurs.
                              activitysim/activitysim/abm/tables/skims.py
                              
Lines 186 to 194
in
7b57c94
                              omx_shape=skim_info['omx_shape'] 
                              skim_dtype=skim_info['dtype'] 
                              blocks=skim_info['blocks'] 
                              skim_data= [] 
                              forblock_name, block_sizeiniteritems(blocks): 
                              skims_shape=omx_shape+ (block_size,) 
                              block_buffer=skim_buffers[block_name] 
                              assertlen(block_buffer) ==int(np.prod(skims_shape)) 
                              The issue is in the Numpy library np.prod() method. According to the documentation:
                              Arithmetic is modular when using integer types, and no error is raised on overflow.
                              >>>x=np.array([536870910, 536870910, 536870910, 536870910])
>>>np.prod(x)
16# may vary
                              Activity
                              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                              Metadata
                              Metadata
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                              No one assigned
                                Labels
                                No labels
                                No labels
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                                No type
                                Projects
                                No projects
                                  Milestone
                                  No milestone
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                                  None yet
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                                  No branches or pull requests
                                  Issue actions