{ "__type": "IngestedDoc", "__tag": 4010, "_content": { "Notes": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Strong", "__tag": 4048, "children": [ { "__type": "Text", "__tag": 4046, "value": "Array API Standard Support" } ] } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "CrossRef", "__tag": 4002, "value": "convolve2d", "reference": { "__type": "LocalRef", "__tag": 4022, "kind": "module", "path": "scipy.signal._signaltools:convolve2d" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": " has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable " }, { "__type": "InlineCode", "__tag": 4051, "value": "SCIPY_ARRAY_API=1" }, { "__type": "Text", "__tag": 4046, "value": " and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported." } ] }, { "__type": "Code", "__tag": 4050, "value": "==================== ==================== ====================\nLibrary CPU GPU\n==================== ==================== ====================\nNumPy ✅ n/a \nCuPy n/a ✅ \nPyTorch ✅ ⛔ \nJAX ✅ ✅ \nDask ⚠️ computes graph n/a \n==================== ==================== ====================", "execution_status": null }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "The JAX backend only supports " }, { "__type": "InlineCode", "__tag": 4051, "value": "boundary=\"fill\"" }, { "__type": "Text", "__tag": 4046, "value": " and " }, { "__type": "InlineCode", "__tag": 4051, "value": "fillvalue=0" }, { "__type": "Text", "__tag": 4046, "value": "." } ] }, { "__type": "Blockquote", "__tag": 4059, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "See " }, { "__type": "InlineRole", "__tag": 4003, "value": "dev-arrayapi", "domain": null, "role": "ref", "inventory": null }, { "__type": "Text", "__tag": 4046, "value": " for more information." } ] } ] } ], "title": [], "level": 0, "target": null }, "Warns": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Raises": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Yields": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Methods": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Returns": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Parameters", "__tag": 4026, "children": [ { "__type": "DocParam", "__tag": 4016, "name": "out", "annotation": "ndarray", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "A 2-dimensional array containing a subset of the discrete linear convolution of " }, { "__type": "ParamRef", "__tag": 4071, "name": "in1" }, { "__type": "Text", "__tag": 4046, "value": " with " }, { "__type": "ParamRef", "__tag": 4071, "name": "in2" }, { "__type": "Text", "__tag": 4046, "value": "." } ] } ] } ] } ], "title": [], "level": 0, "target": null }, "Summary": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Convolve two 2-dimensional arrays." } ] } ], "title": [], "level": 0, "target": null }, "Receives": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Warnings": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Attributes": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Parameters": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Parameters", "__tag": 4026, "children": [ { "__type": "DocParam", "__tag": 4016, "name": "in1", "annotation": "array_like", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "First input." } ] } ] }, { "__type": "DocParam", "__tag": 4016, "name": "in2", "annotation": "array_like", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Second input. Should have the same number of dimensions as " }, { "__type": "ParamRef", "__tag": 4071, "name": "in1" }, { "__type": "Text", "__tag": 4046, "value": "." } ] } ] }, { "__type": "DocParam", "__tag": 4016, "name": "mode", "annotation": "str {'full', 'valid', 'same'}, optional", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "A string indicating the size of the output:" } ] }, { "__type": "DefList", "__tag": 4033, "children": [ { "__type": "DefListItem", "__tag": 4037, "dt": { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "InlineCode", "__tag": 4051, "value": "full" } ] }, "dd": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "The output is the full discrete linear convolution of the inputs. (Default)" } ] } ] }, { "__type": "DefListItem", "__tag": 4037, "dt": { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "InlineCode", "__tag": 4051, "value": "valid" } ] }, "dd": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "The output consists only of those elements that do not rely on the zero-padding. In 'valid' mode, either " }, { "__type": "ParamRef", "__tag": 4071, "name": "in1" }, { "__type": "Text", "__tag": 4046, "value": " or " }, { "__type": "ParamRef", "__tag": 4071, "name": "in2" }, { "__type": "Text", "__tag": 4046, "value": " must be at least as large as the other in every dimension." } ] } ] }, { "__type": "DefListItem", "__tag": 4037, "dt": { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "InlineCode", "__tag": 4051, "value": "same" } ] }, "dd": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "The output is the same size as " }, { "__type": "ParamRef", "__tag": 4071, "name": "in1" }, { "__type": "Text", "__tag": 4046, "value": ", centered with respect to the 'full' output." } ] } ] } ] } ] }, { "__type": "DocParam", "__tag": 4016, "name": "boundary", "annotation": "str {'fill', 'wrap', 'symm'}, optional", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "A flag indicating how to handle boundaries:" } ] }, { "__type": "DefList", "__tag": 4033, "children": [ { "__type": "DefListItem", "__tag": 4037, "dt": { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "InlineCode", "__tag": 4051, "value": "fill" } ] }, "dd": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "pad input arrays with fillvalue. (default)" } ] } ] }, { "__type": "DefListItem", "__tag": 4037, "dt": { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "InlineCode", "__tag": 4051, "value": "wrap" } ] }, "dd": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "circular boundary conditions." } ] } ] }, { "__type": "DefListItem", "__tag": 4037, "dt": { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "InlineCode", "__tag": 4051, "value": "symm" } ] }, "dd": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "symmetrical boundary conditions." } ] } ] } ] } ] }, { "__type": "DocParam", "__tag": 4016, "name": "fillvalue", "annotation": "scalar, optional", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Value to fill pad input arrays with. Default is 0." } ] } ] } ] } ], "title": [], "level": 0, "target": null }, "Extended Summary": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Convolve " }, { "__type": "ParamRef", "__tag": 4071, "name": "in1" }, { "__type": "Text", "__tag": 4046, "value": " and " }, { "__type": "ParamRef", "__tag": 4071, "name": "in2" }, { "__type": "Text", "__tag": 4046, "value": " with output size determined by " }, { "__type": "ParamRef", "__tag": 4071, "name": "mode" }, { "__type": "Text", "__tag": 4046, "value": ", and boundary conditions determined by " }, { "__type": "ParamRef", "__tag": 4071, "name": "boundary" }, { "__type": "Text", "__tag": 4046, "value": " and " }, { "__type": "ParamRef", "__tag": 4071, "name": "fillvalue" }, { "__type": "Text", "__tag": 4046, "value": "." } ] } ], "title": [], "level": 0, "target": null }, "Other Parameters": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null } }, "_ordered_sections": [ "Summary", "Extended Summary", "Parameters", "Attributes", "Methods", "Returns", "Yields", "Receives", "Other Parameters", "Raises", "Warns", "Warnings", "Notes" ], "item_file": "/scipy/signal/_signaltools.py", "item_line": 1735, "item_type": "function", "aliases": [ "scipy.signal.convolve2d" ], "example_section_data": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Text", "__tag": 4046, "value": "Compute the gradient of an image by 2D convolution with a complex Scharr\noperator. (Horizontal operator is real, vertical is imaginary.) Use\nsymmetric boundary condition to avoid creating edges at the image\nboundaries.\n\n" }, { "__type": "Code", "__tag": 4050, "value": "import numpy as np\nfrom scipy import signal\nfrom scipy import datasets\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "ascent = datasets.ascent()\n", "execution_status": "unexpected_exception" }, { "__type": "Code", "__tag": 4050, "value": "scharr = np.array([[ -3-3j, 0-10j, +3 -3j],\n [-10+0j, 0+ 0j, +10 +0j],\n [ -3+3j, 0+10j, +3 +3j]]) # Gx + j*Gy\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "grad = signal.convolve2d(ascent, scharr, boundary='symm', mode='same')\n", "execution_status": "unexpected_exception" }, { "__type": "Text", "__tag": 4046, "value": "\n" }, { "__type": "Code", "__tag": 4050, "value": "import matplotlib.pyplot as plt\nfig, (ax_orig, ax_mag, ax_ang) = plt.subplots(3, 1, figsize=(6, 15))\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "ax_orig.imshow(ascent, cmap='gray')\n", "execution_status": "unexpected_exception" }, { "__type": "Code", "__tag": 4050, "value": "ax_orig.set_title('Original')\n", "execution_status": "failure" }, { "__type": "Code", "__tag": 4050, "value": "ax_orig.set_axis_off()\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "ax_mag.imshow(np.absolute(grad), cmap='gray')\n", "execution_status": "unexpected_exception" }, { "__type": "Code", "__tag": 4050, "value": "ax_mag.set_title('Gradient magnitude')\n", "execution_status": "failure" }, { "__type": "Code", "__tag": 4050, "value": "ax_mag.set_axis_off()\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "ax_ang.imshow(np.angle(grad), cmap='hsv') # hsv is cyclic, like angles\n", "execution_status": "unexpected_exception" }, { "__type": "Code", "__tag": 4050, "value": "ax_ang.set_title('Gradient orientation')\n", "execution_status": "failure" }, { "__type": "Code", "__tag": 4050, "value": "ax_ang.set_axis_off()\nfig.show()\n", "execution_status": "success" } ], "title": [], "level": 0, "target": null }, "see_also": [], "signature": { "__type": "SignatureNode", "__tag": 4029, "kind": "function", "parameters": [ { "__type": "SigParam", "__tag": 4030, "name": "in1", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": { "__type": "Empty", "__tag": 4031 } }, { "__type": "SigParam", "__tag": 4030, "name": "in2", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": { "__type": "Empty", "__tag": 4031 } }, { "__type": "SigParam", "__tag": 4030, "name": "mode", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": "full" }, { "__type": "SigParam", "__tag": 4030, "name": "boundary", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": "fill" }, { "__type": "SigParam", "__tag": 4030, "name": "fillvalue", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": "0" } ], "return_annotation": { "__type": "Empty", "__tag": 4031 }, "target_name": "convolve2d" }, "references": null, "qa": "scipy.signal._signaltools:convolve2d", "arbitrary": [], "local_refs": [ "boundary", "fillvalue", "in1", "in2", "mode", "out" ] }