diff --git a/binder/environment.yml b/binder/environment.yml index 2acfd6e639..eb5a74dfdb 100644 --- a/binder/environment.yml +++ b/binder/environment.yml @@ -3,10 +3,12 @@ channels: - bioconda - defaults dependencies: - - sourmash + - python>=3.9 + - sourmash>=4.8.2 - screed - matplotlib - pandas + - pip - pip: - matplotlib_venn - mmh3 diff --git a/doc/index.md b/doc/index.md index afeaf29084..4e7a9927e3 100644 --- a/doc/index.md +++ b/doc/index.md @@ -79,7 +79,7 @@ be stored, searched, explored, and taxonomically annotated. You can take a look at sourmash analyses on real data [in a saved Jupyter notebook](https://github.com/sourmash-bio/sourmash/blob/latest/doc/sourmash-examples.ipynb), and experiment with it yourself -[interactively in a Jupyter Notebook](https://mybinder.org/v2/gh/sourmash-bio/sourmash/latest?filepath=doc%2Fsourmash-examples.ipynb) +[interactively in a Jupyter Notebook](https://mybinder.org/v2/gh/sourmash-bio/sourmash/latest?labpath=doc%2Fsourmash-examples.ipynb) at [mybinder.org](http://mybinder.org). ## Installing sourmash diff --git a/doc/kmers-and-minhash.ipynb b/doc/kmers-and-minhash.ipynb index 7b1c430d90..f4c5150251 100644 --- a/doc/kmers-and-minhash.ipynb +++ b/doc/kmers-and-minhash.ipynb @@ -18,7 +18,7 @@ "### Running this notebook.\n", "\n", "You can run this notebook interactively via mybinder; click on this button:\n", - "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?filepath=doc%2Fkmers-and-minhash.ipynb)\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?labpath=doc%2Fkmers-and-minhash.ipynb)\n", "\n", "A rendered version of this notebook is available at [sourmash.readthedocs.io](https://sourmash.readthedocs.io) under \"Tutorials and notebooks\".\n", "\n", @@ -197,7 +197,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 9, @@ -206,7 +206,7 @@ }, { "data": { - "image/png": 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j8OZ73wqfPAS3l2BgAD7/M/DV/wHfc1lTjzdHpz1+5et88tQMt1fqDPzDL/P5D23gq//0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\n", 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\n", 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I3ADcBvTZLMpBU3g92xO2C7Gp40O3QYTrgd3AoO1aLCsDB4FfGMM7bvtkn6Tx\n2mkjbbKM/BqM4oXtO3tsIhG8B7e3oCsks8AvgNcxpuOX6mvozlJfSrwd2EBnhcoFvLA9OlfYzib7\nJAVsAbZCRz2dLwFHgYNmr7nQ9G974bse7zXVaXdTo8BrwEk0aH5JQ/cq6suJG6GStlzOUqkBJ/CG\nEM4s5gfIPokA1+P16ta2rjTnTOIFyDGzd5GrpESW4bXTJmjbWQ0l4DBwEGMu2i7GRRq6TdSXFF+H\n11MZsVxOq2Txnhy/bgy5Vv1Q2ScDeKGymfYIlRrectSDZq8Za9lPFenCC95ttM9w1gTendIxjKnY\nLsZlGroLIEIfXqCM4K1wC9NOWjm82703gZPGLN3R47JPYnhjvtfjbTwUpgCuAuPAW8ARs3eJJ+uL\nDAM34t0l9C/ptVpvCm9RwzGMOWu7mLDQ0F0kERJ4gbIWL4Rde1JdBs7gBe2oMVjZqUn2ieB9QI3g\ntdUQ7o2Vn8cLj1FgzOy11FMTSXOpndbCPKvd7MjjtZHXVsY4cZhn2Gjotkh9j4dGAK8h+DeMAc5x\nKTzGjXFvU/d6L7jxYbUWO7fXM1xqp9El780ulshyLoXwMMEv5qlw6YP7VLttsWiLhu4SqT+I68Xr\nAc/+3sPihiZKwDSQmeN7xsWQbaYewldrp14WFzQ1vGCdZo72MntDuAJKRPBeN1drp8VuOZmj/vrh\nyvbKAFmdddB6GroW1Jcip+tfEbzFBpH6l+CFRuOrirdQIWMMRSsFW1SfmpbGGxeOzPoyeO3TaKsK\nXthmzd4Oe2GLxPACuJtL7dN4XcGl11Ljex7I6EOv4GnoKqVUgFx7oKGUUm1NQ1cppQKkoauUUgHS\n0FVKqQBp6CqlVIA0dJVSKkAaukopFSANXYeIyK+JyHMiMiMiZ0TkByLyPtt1uURETohIvt5GF0Tk\n70Vkne26XCUiP6m3kx615AgNXUeIyGeBPwa+hLcpzHXA14CP2qzLUR8xxqTxNgUfB/7Ucj1OEpH1\nwJ14K/futVqM+iUNXQeISD/wH4HfNMY8YozJGmPKxpjvGWP+ne36XGWMKQDfwtuXVr3Tp4BngL8A\nHrJbimrQI8jdcAfermR/a7uQMBGRFPAAXrCod/oU8EfAfuAZERkyxoxbrqnjaei6YTkwYXTzEb++\nIyIVvF23zgH/xHI9zqk/C7ge+BtjzISIvAH8GvAVu5UpHV5ww3lghXg7Ranm7jPGDODdHXwaeEK8\nExjUJQ8BPzTGTNT/+5voEIMTNHTd8DTe9o332S4kTIwxVWPMI3hbFeosjzoR6QY+AdwlImMiMgb8\nG+BmEbnZbnVKQ9cBxjs19fOWjhWeAAAAsElEQVTAV0XkPhFJiUiXiHxYRP6T7fpcJZ6PAsvwDtpU\nnvvwPoi2AbfUv7YCP8Mb51UW6X66DhGRB/F6JFvxdu5/HviiMeYpq4U5RERO4E2pq+JNhToJfNkY\n8w2bdblERB4FXjPG/NtZf/4J4E+AEX1+YI+GrlJKBUiHF5RSKkAaukopFSANXaWUCpCGrlJKBUhD\nVymlAqShq5RSAdLQVUqpAGnoKqVUgDR0lVIqQP8fgyxciwkTZw8AAAAASUVORK5CYII=\n", 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\n", 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IbXHOTrX6/FYWH5VrtxkW8rZSluWJv4MJMziBD1DKEUWJHCO6qlSFgdcA506/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\nRK5CYII=\n", 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\n", 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IbXHOTrX6/FYWH5VrtxkW8rZSluWJv4MJMziBD1DKEUWJHCO6qlSFgdcA506/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\nRK5CYII=\n", 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KblYMZv8NrtwMFVlw9G3wzGr40Qz4r2fgxnXwrRNh1nR49UW4bor+Xu2dsLQHnP09+P49kKngki9BUQPsvh3aBdbEvc3yhfDEO/r9T46Cmy+Ci34D51fCFXdDbgwWFMK022H2J/rfCdNZ/3XNDs9XwOmlUNUCOe0gP4Urn4IHzoOas+G862HyIzB/FpwzHLasgf95Hkp/AJddCr8EuBguOQFWPgoP1kOwBkIAs+HCa+Gl2bCyDI68Gy78Ntx/Haz5KSwLAk/BgOvh2hugzMY/Q6IEEMlCqbRV1bMivJB4Qv1A6pnAZgCKaCOPKnZSRAt9OYF1ABzFaio5BoD3GEMPtjKerQD0pYkMFDEEEJoJEQPaySafOoC9HjJAOyG0C5QaVDBxQRp1wTpyi5u+8Hm4Sd/M4cYcMvPqDnqMz14bRqjHDvodU0soL0rx6EVsems8AMNP30Lp0Tu/+CVRRNuyUTForcsimNlERlbiIhRI9s81qV4LLsCQNuhbBZ8Wwa6+8H19TZmxGj7S15QN/WDSGv1+QgPkNMOj8aIy80+Cx/6l32cqGKe9d4btt7NF437hgNLwPoGt76qD0dk94oqFIu9C0SIYdzm8B7AK8oIQOQ9qAM6CVW+j76et0O9MWAPwVaiug96LocdnkLMBRj4UP0YhRA+Hlo426uIPoN2QU4S+zwZBW3Df77NcFpNK67W1wtPtmrBvoDcNDGIcG1lEFW9wNGfyMQs5ljZ6AVBLCQC/4gbayWcQi7iUuWQRZSJP8SRlBGkjhxqu5Om9x36CC9jKCQRpYSb37/28nuHcy+1kUc/pPMORVCVndEb3+taEq/7Kh7+8gQ1zv4ZCmHr7z/f+rrl2OM9dfjuZufWMn/EMg6dU0VhdRFaPXXv/T06v3dRtHH7QNo699k1ev/k7PHPxvcQi2Yz52kMEMhJX0kCsGw/q13tD5SD4+kb4QxXcejT87GP47bHQoK8pR2yFd8ZD8yJ4rydUDYF1PWHddv37S8+HtSOheAc88Rc4tkF/fvmp8I8zIJoBf3lgX5t/HAa3zoQ9veAHjybp5ULnN6ArVh5+Gy65HZ7dFa/5eyQ0xiD4MAz5FlQ8C8fWoXfKGAJbn4djfgDrH4She6D3x9AzE2K50DARvrkVBg6Gihfhr/0h/Av46zfhhkfgawrkRdjbZ2+Cox+GrzZDwf3wW1v+AF0jrc8IKzpO8m3Uk8WzzOI45tCTVr7E46xkKr/gVsJkI+jUrBgB6hjBZTzCf/ILtjGBdxlFG0FWMZXL+Cm3cBMFbGNOPL4LMIMX+Ak3M5gFvM40AMawme9xCzdxF0cxj5e5Lmm7VbB7XvOaF6Yy4pw5XPTMzYyYPocFv54JwKCTNvOV/72F/3jqLoaeOo+Fv0/etg7WvjSWvD5buWjOTZxy612sffEyGrcnXoRbVBfPcUsWXD4LZs3RnunvHoc5U6HkVmjKhkA83e4P86F3HQy9Fa6/BAZ9BhkKWoPQ2BMmfgbb74YxG+Dqi/Yd/6m3oO42+OZzcPuX9n0+ayPsnA3/dw88eQ7UJutodHYDOt55uw3GFULD1cRHj+gnyH/DQ+VwcT+4JRdaA/HR3kPwSiPk9IXb/wdOK4EtmRALQ3A7DL4W3q6Bn2ZD+Eo4G+ABmPptmNMAN18Dc66GmR1t3Qsf74Kye+AP98H5lv8Buo7rRTc5z6KNIH9iFkNYwHSWAjCaar7Pr/kRdzORheSwA4ACdtOTTymhkXzClLKCSgazIl7V7HB2EADG8hE7OOwLbU1mIdvioYqetFIYnzCZxgpiBNlOflK2S7Lxzs+xa91kjv6mPucJVy+mZddQAPJLWskt1raNu3wFKhakblM++aV1tHV4iEDLrp5kFe4+aBvbFpzIwBOXIAHoP3EHofxaqpcmWjsWlHThHBuCMHUWnLIAfqHPj69Ww4ZfawGdtRB66mtKbgzemQM1d8HaP0BLLhy7HcY0QkYYfhb//vWLYcsBCk8/sAhWHf3Fzy+shqw2eCHZ4kudPWQcn6nyIYxYDuML4J7ZcM0mOGI8XPUd2LAFflEF/30KrOsD2wGGQesSeLwG7loMjzZB/hSoHQ+782H3LNgIcCEs3hAv+v0RTP45+j69DxZvO8AODD+EdbugeDlJ3k/2kdZr6yzRjQF/YgYFVHExr+/9vCqeARFFeJMvM5K3AZjIKhoYQCMh2gmwg5H0oYq+1NFMP6rjF3k9oymIhwrW7rdP20eMJ49qALZRsNfSjxgKCH1oTO5UI927WBnZ9ax5YSQAq58dRSi/BoCd6wpQcePWvzIUlFA4uJHhZ2wi3NCXqqW9CTcFqV09kaFTlx20jaweu6heqnc/3bW+B20NJRSPqk3YxlggyeF5FJgyAwZUwTP7rilL41kt7QJ3fBm+rK8p1SGojBcduXs0BKI6EyEIjPoEHtB/H/48Ckor9fuX9ys+PXsc9NR/N+b2huZ4H5/XC3aUwqQDxLkPeQIHwvH5yq/D843w4z3wk9nw0FBYuwweXRrPKNoNGQ/DWTPQ99M6yKmPh1O+BScPh3XDoHUi7CmE3S/orYmYC6MHou+nfKh/AEYC3AujesZjxf+APh1/uD/B4ChkjCHZ+8k20iq6VsR0E1/BtJARVHMCuWzjXm4HYCLPU0tfPouHAfqxhHPRKU7FNDOG1/k9PwEUJazgNJYDMIaXeZwfIUTJZieX8hgAr/EfvEAJgiKbnVwQz1z4kGNYz6kIUQK0czoPJf1IkmjiF+uf3/0WjdUjiYbzeeainzN4yoscedmTrHrmElY/G0CC7Rw140kA1v79GKqWnIpIFAm2M37mQ0gAMrJiHHHeX5j/8++DEvqMnc/gKfrhMv/e06hcdBaRtgLm/tcdFA5azlm/fJJjrvkH79/3TZ69/A5QwrDTntubTpYIsWQd3d+NgGUnQPE26KuvKf/5PKztC6/qa8oxS+DBeNraih5w8Q06XaygDh5/dN+xfv0szLwK7rsE8hrgscf15z+bBjNHQzAKOU3wmz/pz58fAZedoz+XGFz/9L7Jt8TPuJPPXbv68Icw/RM4SoGcCW//GNYCzIV+t8GVAqoEKl+AJzq+czf8ZRZcfQ1k9IYdf4fHAe6AJ++BS+6FQCa03wNPAjwMx8yAyUGIZkL4bnjIFTOPmrReW1FdDdEl2kC5XAj0TmsjTmHLnc00T3BN/maXqOnVwhsnuiZdKgU8qxRf9I5FpgCjrTfHkGaiKPVIOhuwIrzgliFF98nc7vg4X7dpyvX+Of47DZ183mypFQarSPt1tUJ091jQhjMIVTp+RrvbNPhKdNuUorMtiozoehNPiG5nnoL3CG31gejmuyg0120O1neN6HoTT4iufzzdzErvC9KePFcsCkgRB+u7RnS9iRFdVxGqzoSYt4ffDXne3RnjixzM0/XPCM5fpP26mvBCKpGoEGzwbpHvcEaUqAe3l++czh0GpVrx0ySxf0g8Z72LpP0GUmUqip+GYhk7XZu/eUhasr17bgfmUA5D2m9Qg+W4X3Tj1FjUjv3krPGup7uzyE+iqyC+3LxzDvV7g7uoR6nOslVShlWiu9Widuwnb6F3J9O2lfgptFCr1AGLl++PEV1vYcn1tOom2mZRO/aT+0kIPLhNeQxFdZ/Otq7xIon0WRNe8BaWXE9LRFeVqXr8MukQaA+QtTHtQxTL2dOjjYivJtEOPTrTk2kHr+pmcBOVVjRi5U3koxDDUu/Fdav6eO+cOicC8epzh6YinYYYLKMJpbzj6cbxT4ghf6H3clm3lXg3Vv1FqpRKuHTjpnQaYrAMyx6eRnTTQfanIaTVO55hJBCltqeJ5x4IpWrYb78wg2vxnuiqMtVK4kM2dyNKyFuatt1ELaemdxsq4P26EvvYfOj/8m+YEIO7iWBRPBes31xvtcXt2Uev570TYlh9mJ8m0CqViu8cnTib0mCHwTo2o5RlI1Orb6YNsN8W6F4mZ3WIzEr3e7uNOWFqihPfuNL9rOrCd7bgl+wcb7LGysYsFd34kmBLT9BWer7s/rjuuqF+WoXWTFe8Vr39in9Gcd6iHqUszayyY9i4GhfspJoSCudmI23uFd5oIMb6IX7yclcnkbXwedbggs0qDV+gKyObbmG56Koy1YAejnmfQFuAHu+7N8SwpbTVRwsiYnTHW1WqhfgW5QbXECG+KaeV2HVDrbSpXevp9ax7J9RWH+Ze25Nnk1Ldrobnn37tDdZbUeDm89giuqpMbcEvyyezKkJkr3JfHmdtUQt1hSG7zbCQFd0+glLVWJh6ZOgWMeBjOxq2c+i40Ma2raXkj0FX7SihUCwa56cVaBVKpSyH3D/92t2sQSlbdrWxTXRVmaoAquxq31KyN4bIX+geb3dbiZ+83BiwIGVH0yvUNqXseIZ0EAGW2NW43ZMkH9rcvnX0fTAE7c6f3Y5KjMVjM+02w0LWdGExxKFYiF8ydNzJCpSybTcbW0VXlakd+CVvN7M2g15/d763++mwVppz/SK6rcBHKT+qUnXApyk/riEVtGFTLLcDuz1d0EM7f6xSK/5zLsGdzq2125wV5pMj/JSXu1CptPW9hfilX7uLBXZkLOyP7aKrylQbfpl8kKhQ+nvnLpZYdFSUWND2PmER25VK4yhL5+2+n7bjG7rCVpSyfWTtiBtMlak1+KVSU/6iHAped97uyBsGNlFZkmO3GRYRAd5JeytKrcdMqjmFMFZc8wRwhOjGeROwJYXDckp/l0Noi3NWqtXnt7LwqFy7zbCQd5SyLE/8XUyYwQl8iFKOKErkGNFVZSoMvA44d/idKiQqDCwLOKLQeXswylvHB31UL3elUqy3rDUdZphvWXuGA7HFCWGFDhwjugCqTNXilw6auSOTfg/YP6n2wYSwj7IVaoAPLG9Vqc+wobCKAYAG9CjaMThKdGFvfNfyIhS20OODHAr/ZV98d+3QJraV+iWO2wq81o0qYt3lfcwSYauJAK/Gd212DI4T3TjvATvtNsISSh7MIWuD9Z1iZ2ErS8b6JY6rgDeUosk+C1QMHT5rsM0G//EmSu2y24jP40jRjRc7fxU/TKxJVBh0SyaZ26ybWKvPb2Xe5BCIX+K47yvlgI1Rtcf1KtButyk+YDFKObLUpiNFF0CVqUbgJfwgvMHmIEP+K8OS7X3q89t47aRMH9XJna+Ug0ouas/rDUzB83SyHqUW221EZzj6xlNlqgnfCG9jkCE3ZpBZnT7h3ZPXxmsnZdCe6ZcKYu85SnA7UGozMA9TnyEdbATestuIg+Fo0QUfCu/gGzPI2J76rIaG3Dbmnuw3wXVuxoBSG9DiYIQ3dVQAb8Tj545F9J56zkfKJQ84Fyi025a0EymKUHF/jEjf1JRX7BDccMgvgvuuUi7ZKFJkOHAaLnCAHM4GYJ7TBRdcJLoAUi65wDlAb7ttSTuRgihb72yn7bDuFaCpLWrh7eNDPhHcGNrDdUwifEKIDEULr5+2R0olnwJv4xIxc5XoAki5BIGTgFF225J2VFCx/bpm6qfnJf9dFGuHNbN0TK5PshSagddTuAOEtYgUA9OBfLtNcREKWIhSy+w2JBlcJ7odSLmMBE7GD95B/bRmtn83GxVKbAgaCUZ5f0LYRwsftqHzcB2VBJ80IjnAmUCp3aa4gDA6nLDZbkOSxbWiCyDl0gvdSb0f520bFGbrnRApPnicd09eG29OCvhkaa9Cb7uyRCmPTEiJBNDOhPdHcl2nHr3SrM5uQ7qCq0UXQMolE5gKDLfblrQTy46x7bY2mscf2IPdXNrMBxOyfVITtxWYpxRb7TYkLYiMAiYDfnh4JsNnwHso5ZwqfUnietHtQMrlcOAEwPtD6vppzdRcGyKWr0MrLVntLDwq4qN6uJvQE2bOq0ucSkTy0Q7FALtNcQAtwLsotcluQ7qLZ0QXQMolBBwHjAW8PXkUzY2y/TvNLJoZYNmoHJ94t3vQK8y22G2IpYiMRjsUfvV6PwPmO61wTVfxlOh2EI/1TgIG2W1LGlkPLGS2CqGHoV72hsLozQSXK+WDessHQnu9JwJDbbbESvagi49vstuQVOJJ0e1AyqU/2kMottuWFFIJLIjvpLwXEQYDxwO9bLEqPcSAlcBS12cmpAqREvR17me3KWmkBT1ButoNix2SxdOi20FcfMegvQQ3DsMj6ATwVars4KXqROgPHAkMwb0hlhZ0TeVVSuGILVYch4gXH7LtwDJgOUp5thKbL0S3AymXHHQqzmjckYRej/b0Po1vZ5QwIuSjHzSjALdsq16J3mFhk43Fxt2DiKAdibFAf3uN6RZNwGpglVfitgfDV6LbgZSLoOO9Y4CBOMv7bQe2AqtVmep2OpQIGcBh6AdN3+4eLw20ob341UpRZ7Mt7kWkCC2+hwOpqdmRfrahnYoKtyzhTQW+FN39ief59kNPRA3A+uGaAmrRQrsFqFFl6YljiZCNfsh0vOzYOUIBO9Be7Tag2reTY+lAJAMYgc5b74+zHAqAOnTK31qUqrfXFHvwveh+nngIoj9agEuBHkAqi8WE0bOyHUK7TZXZk+gtQm+0+A5CP2zSFYbYxT6RrVIK+zfk9AMimehrOwQYDGTZYIUCqtFlFzehlPdLtB4CI7oJEK9u1uMArxDakwigJ60Uegv5jlcDWmD3vuwS2EQQIYReUl0IFMRfhehzzUA/fPZ/AKn4K4w+18b4z4b9/62U2Z7GdnT8tw86k6c4/r4nqfeEG9EORS16RFPj5tVj6cCIriFpRBDP1DrwMyJB9AinEB1q+vwrg31OhUKn8EXRS7CbP/dqBHaiVIu1J+E+jOgaDAaDhTgtyG4wGAyexoiuwWAwWIgRXYPBYLAQI7oGg8FgIUZ0DQaDwUKM6HYDEdkkIi0i0igiu0XkHyLi5XKSiMjXReSj+DlXici/RORku+0yGNyCEd3u8xWlVD56KfF24Lc225M2ROSHwK+Ae4AS9CqnPwDn22iWIc2IyFtxp8KOFW2ew4huilC6OtLf0EV0PIeIFAJ3At9RSj2nlGpSSrUrpV5SSv3IbvsM6UFEhgJT0IsjzrPXGm9gRDdFiEgucAnwod22pInJ6NoMz9ttiMFSZqD79GPATHtN8QYZdhvgAV4QkQiQh15rfpbN9qSL3kCtUipityEGS5kBPAAsAD4UkRKl1HabbXI1xtPtPhcopYrQXuB3gbdFpNRek9LCTqBYdOlAgw+IT5AOAeYopRajN4j8ur1WuR8juilCKRVVSj2HLgjixdn8D9AFxy+w2Q6DdcwE5iqlauP/fhoTYug2xmtJEaJL552HLpe32mZzUo5Sql5E7gB+Hw+nzEXvcnEGME0pdZOtBhpSiojkABcDQRGpjn+cBRSJyHil1DL7rHM3RnS7z0siEkXP7lYAM5VSK222KS0ope6P34C3AU+ha+YuBu621TBDOrgAPWobB/9WdH4OOs57ow02eQJT2tFgMHwBEXkFWKmUuvFzn18M/AYYaCZVu4YRXYPBYLAQM5FmMBgMFmJE12AwGCzEiK7BYDBYiBFdg8FgsBAjugaDwWAhRnQNBoPBQozoGgwGg4UY0TUYDAYLMaJrMBgMFvL/DCDfFismjj4AAAAASUVORK5CYII=\n", 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\n", 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" ] @@ -1050,9 +1050,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "py38arm", "language": "python", - "name": "python3" + "name": "py38arm" }, "language_info": { "codemirror_mode": { @@ -1064,7 +1064,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.8.13" } }, "nbformat": 4, diff --git a/doc/plotting-compare.ipynb b/doc/plotting-compare.ipynb index da5412e784..40e6e520ad 100644 --- a/doc/plotting-compare.ipynb +++ b/doc/plotting-compare.ipynb @@ -15,7 +15,7 @@ "### Running this notebook.\n", "\n", "You can run this notebook interactively via mybinder; click on this button:\n", - "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?filepath=doc%2Fplotting-compare.ipynb)\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?labpath=doc%2Fplotting-compare.ipynb)\n", "\n", "A rendered version of this notebook is available at [sourmash.readthedocs.io](https://sourmash.readthedocs.io) under \"Tutorials and notebooks\".\n", "\n", @@ -51,29 +51,70 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[K\n", - "== This is sourmash version 3.3.2.dev9+g462bc387. ==\n", - "\u001b[K== Please cite Brown and Irber (2016), doi:10.21105/joss.00027. ==\n", - "\n", - "\u001b[Kloaded 1 sigs from '../tests/test-data/demo/SRR2060939_1.sig'g'\n", - "\u001b[Kloaded 1 sigs from '../tests/test-data/demo/SRR2060939_2.sig'g'\n", - "\u001b[Kloaded 1 sigs from '../tests/test-data/demo/SRR2241509_1.sig'g'\n", - "\u001b[Kloaded 1 sigs from '../tests/test-data/demo/SRR2255622_1.sig'g'\n", - "\u001b[Kloaded 1 sigs from '../tests/test-data/demo/SRR453566_1.sig'g'\n", - "\u001b[Kloaded 1 sigs from '../tests/test-data/demo/SRR453569_1.sig'g'\n", - "\u001b[Kloaded 1 sigs from '../tests/test-data/demo/SRR453570_1.sig'g'\n", - "\u001b[Kloaded 7 signatures total. \n", - "\u001b[K\n", - "0-SRR2060939_1.fa...\t[1. 0.356 0.078 0.086 0. 0. 0. ]\n", - "1-SRR2060939_2.fa...\t[0.356 1. 0.072 0.078 0. 0. 0. ]\n", - "2-SRR2241509_1.fa...\t[0.078 0.072 1. 0.074 0. 0. 0. ]\n", - "3-SRR2255622_1.fa...\t[0.086 0.078 0.074 1. 0. 0. 0. ]\n", - "4-SRR453566_1.fas...\t[0. 0. 0. 0. 1. 0.382 0.364]\n", - "5-SRR453569_1.fas...\t[0. 0. 0. 0. 0.382 1. 0.386]\n", - "6-SRR453570_1.fas...\t[0. 0. 0. 0. 0.364 0.386 1. ]\n", - "min similarity in matrix: 0.000\n", - "\u001b[Ksaving labels to: compare-demo.labels.txt\n", - "\u001b[Ksaving comparison matrix to: compare-demo\n" + "\r", + "\u001b[K\r\n", + "== This is sourmash version 4.8.2. ==\r\n", + "\r", + "\u001b[K== Please cite Brown and Irber (2016), doi:10.21105/joss.00027. ==\r\n", + "\r\n", + "\r", + "\u001b[Kloading '../tests/test-data/demo/SRR2060939_1.sig'\r", + "\r", + "\u001b[KLoaded 1 sigs from '../tests/test-data/demo/SRR2060939_1.sig'\r", + "\r", + "\u001b[Kloading '../tests/test-data/demo/SRR2060939_2.sig'\r", + "\r", + "\u001b[K<<" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -195,7 +235,7 @@ " [0. 0. 0. 0.356 1. 0.072 0.078]\n", " [0. 0. 0. 0.078 0.072 1. 0.074]\n", " [0. 0. 0. 0.086 0.078 0.074 1. ]]\n", - "reordered labels: ['SRR2255622_1.fastq.gz', 'SRR2241509_1.fastq.gz', 'SRR2060939_2.fastq.gz', 'SRR2060939_1.fastq.gz', 'SRR453570_1.fastq.gz', 'SRR453569_1.fastq.gz', 'SRR453566_1.fastq.gz']\n" + "reordered labels: ['SRR453566_1.fastq.gz', 'SRR453569_1.fastq.gz', 'SRR453570_1.fastq.gz', 'SRR2060939_1.fastq.gz', 'SRR2060939_2.fastq.gz', 'SRR2241509_1.fastq.gz', 'SRR2255622_1.fastq.gz']\n" ] } ], @@ -290,14 +330,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", "text/plain": [ - "
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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -308,9 +346,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python (myenv)", + "display_name": "smash-notebooks", "language": "python", - "name": "myenv" + "name": "smash-notebooks" }, "language_info": { "codemirror_mode": { @@ -322,7 +360,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.11.3" } }, "nbformat": 4, diff --git a/doc/sourmash-collections.ipynb b/doc/sourmash-collections.ipynb index fe1c15f400..5e5cf1dfeb 100644 --- a/doc/sourmash-collections.ipynb +++ b/doc/sourmash-collections.ipynb @@ -9,7 +9,7 @@ "### Running this notebook.\n", "\n", "You can run this notebook interactively via mybinder; click on this button:\n", - "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?filepath=doc%2Fsourmash-collections.ipynb)\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?labpath=doc%2Fsourmash-collections.ipynb)\n", "\n", "A rendered version of this notebook is available at [sourmash.readthedocs.io](https://sourmash.readthedocs.io) under \"Tutorials and notebooks\".\n", "\n", diff --git a/doc/sourmash-examples.ipynb b/doc/sourmash-examples.ipynb index c3fc51edfd..dd2d74690e 100644 --- a/doc/sourmash-examples.ipynb +++ b/doc/sourmash-examples.ipynb @@ -17,7 +17,7 @@ "### Running this notebook.\n", "\n", "You can run this notebook interactively via mybinder; click on this button:\n", - "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?filepath=doc%2Fsourmash-examples.ipynb)\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?labpath=doc%2Fsourmash-examples.ipynb)\n", "\n", "A rendered version of this notebook is available at [sourmash.readthedocs.io](https://sourmash.readthedocs.io) under \"Tutorials and notebooks\".\n", "\n", @@ -510,9 +510,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python (myenv)", + "display_name": "smash-notebooks", "language": "python", - "name": "myenv" + "name": "smash-notebooks" }, "language_info": { "codemirror_mode": { diff --git a/doc/tutorials.md b/doc/tutorials.md index c089822574..4c0a9c0c97 100644 --- a/doc/tutorials.md +++ b/doc/tutorials.md @@ -13,22 +13,22 @@ X and Linux. They require about 5 GB of disk space and 5 GB of RAM. ## Background and details -These next four tutorials are all notebooks that you can view, run +These next three tutorials are all notebooks that you can view, run yourself, or run interactively online via the [binder](https://mybinder.org) service. -* [An introduction to k-mers for genome comparison and analysis](kmers-and-minhash.md) +* [An introduction to k-mers for genome comparison and analysis.](kmers-and-minhash.ipynb) -* [Some sourmash command line examples!](sourmash-examples.md) +* [Some sourmash command line examples!](sourmash-examples.ipynb) -* [Working with private collections of signatures.](sourmash-collections.md) +* [Working with private collections of signatures.](sourmash-collections.ipynb) -* [Using `sourmash taxonomy` with the LIN taxonomic framework.](tutorial-lin-taxonomy.md) - -## More information +## Advanced tutorials and more information For more information on analyzing sequencing data with sourmash, check out our [longer tutorial](tutorial-long.md). +Read [using `sourmash taxonomy` with the Life Identification Number (LIN) taxonomic framework](tutorial-lin-taxonomy.md) for some of our newer taxonomic features. + If you are a Python programmer, you might also be interested in our [API examples](api-example.md) as well as a short guide to [Using the `LCA_Database` API.](using-LCA-database-API.ipynb) If you prefer R, we have [a short guide to using sourmash output with R](other-languages.md). @@ -37,7 +37,7 @@ If you prefer R, we have [a short guide to using sourmash output with R](other-l If you're interested in customizing the output of `sourmash plot`, which produces comparison matrices and dendrograms, please see -[Building plots from `sourmash compare` output](plotting-compare.md). +[Building plots from `sourmash compare` output](plotting-compare.ipynb). ## Contents: diff --git a/doc/using-LCA-database-API.ipynb b/doc/using-LCA-database-API.ipynb index ad8b8ac5ae..95c99e0f22 100644 --- a/doc/using-LCA-database-API.ipynb +++ b/doc/using-LCA-database-API.ipynb @@ -24,7 +24,7 @@ "### Running this notebook.\n", "\n", "You can run this notebook interactively via mybinder; click on this button:\n", - "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?filepath=doc%2Fusing-LCA-database-API.ipynb)\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dib-lab/sourmash/latest?labpath=doc%2Fusing-LCA-database-API.ipynb)\n", "\n", "A rendered version of this notebook is available at [sourmash.readthedocs.io](https://sourmash.readthedocs.io) under \"Tutorials and notebooks\".\n", "\n", @@ -74,14 +74,14 @@ "text": [ "\r", "\u001b[K\r\n", - "== This is sourmash version 4.0.0a4.dev12+g31c5eda2. ==\r\n", + "== This is sourmash version 4.8.2. ==\r\n", "\r", "\u001b[K== Please cite Brown and Irber (2016), doi:10.21105/joss.00027. ==\r\n", "\r\n", "\r", "\u001b[Kcomputing signatures for files: genomes/akkermansia.fa, genomes/shew_os185.fa, genomes/shew_os223.fa\r\n", "\r", - "\u001b[KComputing a total of 1 signature(s).\r\n", + "\u001b[KComputing a total of 1 signature(s) for each input.\r\n", "\r", "\u001b[Kskipping genomes/akkermansia.fa - already done\r\n", "\r", @@ -144,9 +144,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[(1.0,\n", - " SourmashSignature('CP001071.1 Akkermansia muciniphila ATCC BAA-835, complete genome', 6822e0b7),\n", - " None)]\n" + "[Result(score=1.0, signature=SourmashSignature('CP001071.1 Akkermansia muciniphila ATCC BAA-835, complete genome', 6822e0b7), location=None)]\n" ] } ], @@ -164,12 +162,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "[(1.0,\n", - " SourmashSignature('NC_009665.1 Shewanella baltica OS185, complete genome', b47b13ef),\n", - " None),\n", - " (0.22846441947565543,\n", - " SourmashSignature('NC_011663.1 Shewanella baltica OS223, complete genome', ae6659f6),\n", - " None)]\n" + "[Result(score=1.0, signature=SourmashSignature('NC_009665.1 Shewanella baltica OS185, complete genome', b47b13ef), location=None),\n", + " Result(score=0.22846441947565543, signature=SourmashSignature('NC_011663.1 Shewanella baltica OS223, complete genome', ae6659f6), location=None)]\n" ] } ], @@ -186,14 +180,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "[(1.0,\n", - " SourmashSignature('NC_011663.1 Shewanella baltica OS223, complete genome', ae6659f6),\n", - " None)]\n" + "Result(score=1.0, signature=SourmashSignature('NC_011663.1 Shewanella baltica OS223, complete genome', ae6659f6), location=None)\n" ] } ], "source": [ - "pprint(db.gather(sig3))" + "pprint(db.best_containment(sig3))" ] }, { @@ -251,7 +243,7 @@ } ], "source": [ - "pprint(db.ident_to_idx.keys())" + "pprint(db._ident_to_idx.keys())" ] }, { @@ -271,7 +263,7 @@ } ], "source": [ - "pprint(db.ident_to_name)" + "pprint(db._ident_to_name)" ] }, { @@ -285,7 +277,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The attribute `hashval_to_idx` contains a mapping from individual hash values to sets of `idx` indices.\n", + "The attribute `_hashval_to_idx` contains a mapping from individual hash values to sets of `idx` indices.\n", "\n", "See the method `_find_signatures()` for an example of how this is used in `search` and `gather`." ] @@ -304,7 +296,7 @@ } ], "source": [ - "print('{} hash values total in this database'.format(len(db.hashval_to_idx)))" + "print('{} hash values total in this database'.format(len(db._hashval_to_idx)))" ] }, { @@ -322,7 +314,7 @@ ], "source": [ "all_idx = set()\n", - "for idx_set in db.hashval_to_idx.values():\n", + "for idx_set in db._hashval_to_idx.values():\n", " all_idx.update(idx_set)\n", "print('belonging to signatures with idx {}'.format(all_idx))" ] @@ -333,7 +325,7 @@ "metadata": {}, "outputs": [], "source": [ - "first_three_hashvals = list(db.hashval_to_idx)[:3]" + "first_three_hashvals = list(db._hashval_to_idx)[:3]" ] }, { @@ -353,7 +345,7 @@ ], "source": [ "for hashval in first_three_hashvals:\n", - " print('hashval {} belongs to idxs {}'.format(hashval, db.hashval_to_idx[hashval]))" + " print('hashval {} belongs to idxs {}'.format(hashval, db._hashval_to_idx[hashval]))" ] }, { @@ -374,16 +366,16 @@ "source": [ "query_idx = 2\n", "hashval_set = set()\n", - "for hashval, idx_set in db.hashval_to_idx.items():\n", + "for hashval, idx_set in db._hashval_to_idx.items():\n", " if query_idx in idx_set:\n", " hashval_set.add(hashval)\n", " \n", "print('{} hashvals belong to query idx {}'.format(len(hashval_set), query_idx))\n", "\n", - "ident = db.idx_to_ident[query_idx]\n", + "ident = db._idx_to_ident[query_idx]\n", "print('query idx {} matches to ident {}'.format(query_idx, ident))\n", "\n", - "name = db.ident_to_name[ident]\n", + "name = db._ident_to_name[ident]\n", "print('query idx {} matches to name {}'.format(query_idx, name))" ] }, @@ -400,7 +392,7 @@ "metadata": {}, "outputs": [], "source": [ - "from sourmash.lca import LineagePair" + "from sourmash.lca.lca_utils import LineagePair" ] }, { @@ -455,13 +447,13 @@ "source": [ "# by default, the identifier is the signature name --\n", "ident = sig1.name\n", - "idx = db.ident_to_idx[ident]\n", + "idx = db._ident_to_idx[ident]\n", "print(\"ident '{}' has idx {}\".format(ident, idx))\n", "\n", - "lid = db.idx_to_lid[idx]\n", + "lid = db._idx_to_lid[idx]\n", "print(\"lid for idx {} is {}\".format(idx, lid))\n", "\n", - "lineage = db.lid_to_lineage[lid]\n", + "lineage = db._lid_to_lineage[lid]\n", "display = sourmash.lca.display_lineage(lineage)\n", "print(\"lineage for lid {} is {}\".format(lid, display))" ] @@ -725,8 +717,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/t/miniconda3/envs/py37/lib/python3.7/site-packages/ipykernel_launcher.py:1: DeprecatedWarning: get_mins is deprecated as of 3.5 and will be removed in 5.0. Use .hashes property instead.\n", - " \"\"\"Entry point for launching an IPython kernel.\n" + "/var/folders/6s/_f373w1d6hdfjc2kjstq97s80000gp/T/ipykernel_3384/490137846.py:1: DeprecatedWarning: get_mins is deprecated as of 3.5 and will be removed in 5.0. Use .hashes property instead.\n", + " assignments = sourmash.lca.gather_assignments(sig2.minhash.get_mins(), [db])\n" ] } ], @@ -834,9 +826,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python (myenv)", + "display_name": "smash-notebooks", "language": "python", - "name": "myenv" + "name": "smash-notebooks" }, "language_info": { "codemirror_mode": { @@ -848,7 +840,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.11.3" } }, "nbformat": 4,