Created
December 4, 2018 16:04
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{ | |
"cells": [ | |
{ | |
"metadata": { | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "import cftime\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport xarray as xr\n\nfrom nc_time_axis import CalendarDateTime\n%matplotlib inline", | |
"execution_count": 4, | |
"outputs": [] | |
}, | |
{ | |
"metadata": {}, | |
"cell_type": "markdown", | |
"source": "### Example using `nc_time_axis` and dates generated by `cftime_range`" | |
}, | |
{ | |
"metadata": { | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "dates = xr.cftime_range('0001', periods=24, freq='MS', calendar='noleap')", | |
"execution_count": 28, | |
"outputs": [] | |
}, | |
{ | |
"metadata": { | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "plt.plot([CalendarDateTime(date, date.calendar) for date in dates], range(24))", | |
"execution_count": 3, | |
"outputs": [ | |
{ | |
"output_type": "execute_result", | |
"execution_count": 3, | |
"data": { | |
"text/plain": "[<matplotlib.lines.Line2D at 0x10e8c5fd0>]" | |
}, | |
"metadata": {} | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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GDy4q2qt8TJ9QHr2uNy2b1He6LBGvUqCLX8ktKOTFz5N5ef1Omjeqxyu3D2B0VFunyxLxCQW6+I3N+9N5cNEWth85yfj+7Xh4TCTNG9VzuiwRnzlvoBtjXgfGAKnW2qji54KBD4AIYA/wK2vtCe+VKVK2nPxCnluznX98uYvWTRvwxt0DGdGztdNlifhcrXIc8yYw+qznpgKfWWu7AZ8Vfy7ic5v2HOfq57/k1S92cfPADqz+v0sV5hKwzjtDt9Z+YYyJOOvpscDw4o/fAtYDUzxYl8g5ZecVMO/TJN78Zg9hzRryzj2DubhbiNNliTiqsvfQ21hrUwCstSnGGE2JxGe+Tj7GtFgX+45nc+eQjkwZ3ZPG9fXrIBGvXwXGmEnAJIDw8HBvn0782IlTeTy+YiuLfzpARMtG2kxL5CyVDfQjxpjQ4tl5KJBa1oHW2gXAAoCYmBhbyfNJALPWsnzLIWZ/lEjG6Xz+MKIL/3tZN22mJXKWygb6cuAu4Knix2Ueq0ikhAMnspm5NJ71SUfp26E574yPpldokNNliVRL5Wlb/BdFvwANMcYcAGZRFOT/NsbcA+wDbvJmkRJ4Ct2WN7/Zw19XJwEw69pI7hwSQW1tpiVSpvJ0udxaxh+N9HAtIgAkHspkamwccQcyuKxnax67Pop22kxL5LzUGiDVRk5+IfPX7uAfX+6iRSNtpiVSUQp0qRa+Tj7G9CUu9qZl86uY9ky/upeW7YtUkAJdHJWenccTK7by4Y9FrYjv/WYwF3XRAiGRylCgi2NWxacwc2kC6dl5/H54F+4dqVZEkapQoIvPHTuZy6xlCaxwpdA7LIiFEwcRGaZWRJGqUqCLz5xZIPTI8gRO5RbywKgeTLq0M3Vrl2ePOBE5HwW6+ERqZg4zlsazJvEI/To0Z96NfejWpqnTZYn4FQW6eJW1lkU/HuCxjxPJLXAz4+peTLy4kxYIiXiBAl285mD6aabHutiw/SiDIoKZe2MfOoU0drosEb+lQBePs9by3vf7eHLlNtzW8uh1vbnjwo7U0qxcxKsU6OJR+9KymRobxzc70xjatSVPje9Dh+BGTpclEhAU6OIRhW7Lwm/38PSqJGrXMjw5PppbBnbQsn0RH1KgS5VtO5zJ1MUuNu9PZ3iPVswZF02YNtMS8TkFulRaTn4hL3y+g1c37KJZw7o8f0s/rusbplm5iEMU6FIp3+5MY/oSF7uPneKG/u2ZeU0vWjTWZloiTlKgS4VkZOczZ+VWPti0n/DgRrxzz2Au7qbNtESqAwW6lIu1lhWuFB5ZnsiJ7DwmD+vMn0d2p2E9baYlUl0o0OW8DqWf5qGl8Xy2LZXods14c8JAoto1c7osETmLAl3KVOi2vP3tHuZ9moTbwsxrenH3RRHU0WZaItWSAl1KVbIV8dLurXji+igtEBKp5hTo8l9y8gt58fNkXtmwk6CGdZl/cz/G9lMrokhNoECX/yjZiji+fztmXhNJsFoRRWoMBbr8Vytih+CGvH3PIC7p1srpskSkghToAewXrYiXdubPl6sVUaSmUqAHqJKtiFHtgtSKKOIHFOgBpmQrYqG1zLi6FxOGqhVRxB8o0ANI0uEspsbG8fO+dC7pFsKccdFqRRTxIwr0AFCyFbFpgzo8d3Nfru/XTq2IIn5Gge7nvtuVxrRYF7uOnWL8Be2YOUatiCL+SoHup07lFjB31TYWfruXDsENWThxEJd2VyuiiD9ToPuhr3YcY8riOA5lnGbC0AgeGNWDRvU01CL+Tle5H8nMyWfOiq28/8N+Ooc05sPJQ4iJCHa6LBHxEQW6n1i3LZVpsS5Ss3KYPKwzf7m8Ow3qaoGQSCBRoNdw6dl5zP44kdifDtK9TRNevWMofTs0d7osEXFAlQLdGLMHyAIKgQJrbYwnipLyWRV/mJlL40nPzuPey7ryh8u6Ur+OZuUigcoTM/QR1tpjHvg6Uk5pJ3N5eHkCK+JSiAwN4q2JA+kdpmX7IoFOt1xqEGstH8Wl8MjyBLJy8rn/yu5MHtaFulq2LyJUPdAtsNoYY4FXrbULPFCTlOJwRg4PL4tndeIR+rZvxrybLqR7m6ZOlyUi1UhVA32otfaQMaY1sMYYs81a+0XJA4wxk4BJAOHh4VU8XeBxuy3vfr+Ppz/ZRl6hm2lX9eSeiztpMy0R+YUqBbq19lDxY6oxZgkwCPjirGMWAAsAYmJibFXOF2h2HMliWqyLTXtPMLRrS+aMi6Zjy8ZOlyUi1VSlA90Y0xioZa3NKv74SmC2xyoLYLkFhby0bicvrU+mcf06PHNTX27or820ROTcqjJDbwMsKQ6ZOsB71tpVHqkqgP2w5zjTYl0kp55kbL8wHhoTSUiT+k6XJSI1QKUD3Vq7C+jrwVoCWmZOPnM/2ca73+2jXfOGvDFhICN6tHa6LBGpQdS2WA2sij/MrOXxHM3K5Z6LO/F/V3SncX0NjYhUjFLDQUcyi1oRP004Qq/QIBbcEaNl+yJSaQp0B7jdlve+38fc4lbEKaN78utLOmmBkIhUiQLdx/YcO8WUxXF8t/s4F3UpakWMCFEroohUnQLdRwrdlje+3s0zq5OoW7sWc2+I5lcxHdSKKCIeo0D3geTUkzy4aAs/7UtnZM/WPDEumrbNGjhdloj4GQW6FxUUulnw5S7mr91Bo3q1mX9zP8b2C9OsXES8QoHuJdsOZ/LAh3G4DmZwVVRbZo+NolVTLRASEe9RoHtYXoGbl9fv5MV1OwhqUJeXbuvP1dGhTpclIgFAge5B8QczuP/DLWw7nMXYfmHMurY3wY3rOV2WiAQIBboH5BYU8rfPdvDKhl20bFyPf9wZwxWRbZwuS0QCjAK9in7ce4Ipi+NITj3JTQPaM/OaSJo1qut0WSISgBTolZSVk8+8T5N4e+NeQoMa8OaEgQzXZloi4iAFeiWsSTzCQ0vjOZKVw11DIrh/VA+aaDMtEXGYUqgCUjNzeOSjBFa6DtOzbVNevr0/F4S3cLosERFAgV4ubrflg037mbNyK7kFbh4Y1YNJl3bWZloiUq0o0M9j59GTTIt18f3u41zYOZg546Lp3KqJ02WJiPyCAr0MeQVuXt2wkxfWJdOgjjbTEpHqT4Feip/2nWDaYhdJR7K4pk8os66NpHVTbaYlItWbAr2Ek7kFzFu1jYUb99I2qAGv3RnD5VogJCI1hAK92MZdadz37y0cyjitVkQRqZECPrHyCtw8u2Y7r36xk47BjVj024sY0FGtiCJS8wR0oCenZvGn9zeTcCiTWwd1YOY1kTTWrFxEaqiATC9rLW9v3MsTK7bSqF5tXr1jAKN6t3W6LBGRKgm4QD+alcuDi7awLukow7q3Yt6NfWgdpA4WEan5AirQ1yYeYcriOE7mFvDodb25c0hH9ZWLiN8IiEDPzivg8RVbee+7fUSGBvH+Lf3o1qap02WJiHiU3wf6lv3p/PmDzexJO8XkYZ35vyu6U79ObafLEhHxOL8N9PzCoqX789fuoFXT+rz768Fc1CXE6bJERLzGLwM97kA6Uxa72JqSybV9w3h8bJTeRUhE/J5fBfqp3AKeXbOdN77eTUiT+rxy+wBGR6kdUUQCg98E+vqkVGYsiedg+mluGxzOlKt6EtRAs3IRCRw1PtCPnczlsY8TWbb5EF1aNebD3w5hYESw02WJiPhcjQ10ay2LfzrI4ysSOZVbwJ9GduP3I7qog0VEAlaVAt0YMxp4HqgNvGatfcojVZ3H3rRTzFgSz1fJxxjQsQVPjY9WX7mIBLxKB7oxpjbwd+AK4ADwgzFmubU20VPFna2g0M1rX+1m/trt1KlVi8euj+K2QeHUqqXVniIiVZmhDwKSrbW7AIwx7wNjAa8EuutABlMWx5GYksmVkW2YPTaKts20B4uIyBlVCfR2wP4Snx8ABletnNK98NkOnlu7vbgVsT+jo0K9cRoRkRqtKoFe2n0O+4uDjJkETAIIDw+v1InCWzbilkHhTBndk2YN1YooIlKaqgT6AaBDic/bA4fOPshauwBYABATE/OLwC+Psf3aMbZfu8q8VEQkYNSqwmt/ALoZYzoZY+oBtwDLPVOWiIhUVKVn6NbaAmPMH4FPKWpbfN1am+CxykREpEKq1IdurV0JrPRQLSIiUgVVueUiIiLViAJdRMRPKNBFRPyEAl1ExE8o0EVE/ISxtlJrfSp3MmOOAnuBEOCYz04slaExqhk0TjVHVcaqo7W21fkO8mmg/+ekxmyy1sb4/MRSbhqjmkHjVHP4Yqx0y0VExE8o0EVE/IRTgb7AofNK+WmMagaNU83h9bFy5B66iIh4nm65iIj4Ca8GujEm2Bizxhizo/ixRRnH/dEYk2yMscaYkBLP32aMiSv+7xtjTF9v1huojDE3GWMSjDFuY0yZv4UvazyNMc2MMR8ZY7YUf50Jvqs+MBhj5hljthVfC0uMMc3LOO6c15wxZqAxptAYc6NvKg8sFRinUq85Y8wVxpgfjTGu4sfLKnJ+b8/QpwKfWWu7AZ8Vf16ar4HLKepRL2k3MMxa2wd4DN0v9JZ4YDzwxXmOK2s8/wAkWmv7AsOBvxbvkS+eswaIKr4WtgPTyjiuzGuu+I3d51K05bV4R3nHqaxr7hhwrbU2GrgLeLsiJ/d2oI8F3ir++C3g+tIOstb+bK3dU8rz31hrTxR/upGid0USD7PWbrXWJpXj0LLG0wJNjTEGaAIcBwo8XmgAs9auttae+Z6e61o41zX3v8BiINUrRUq5x6msa644C8+881sC0MAYU7+85/d2oLex1qYAFD+2rsLXugf4xCNVSWWVNZ4vAr0oegtCF/Ana63bmRIDwkTKvhZKHSNjTDtgHPCKTyoUOPc4lccNwM/W2tzyvqBKb3DhK8aYERQF+sVO1yKlGgVsBi4DugBrjDFfWmsznS3L/xhjZlD008+7FXzpfGCKtbaw6Acp8aYqjNOZ1/em6PbYlRV5nbdn6EeMMaEAxY+pxR9/aozZbIx57XxfwBjTB3gNGGutTfNqtfJfjDFvFI/TmXelKnU8gQlArC2STNHvPnr6vmL/Zoy5CxgD3GaL+40rMEYxwPvGmD3AjcBLxphSb4FK1ZRznM71+vbAEuBOa+3Oipzb2zP05RTd2H+q+HEZgLV2VHlebIwJB2KBO6y1271VpJTOWnt2t0qp4wnsA0YCXxpj2gA9gF2+qjMQGGNGA1MoahLIPvN8ecfIWtupxNd6E/jYWrvUy2UHnAqMU1mvbw6sAKZZa7+u8Pm9ubDIGNMS+DcQTtFFf5O19ngpx90LPAi0pWhGsdJa++viGfwN/P/ulwJtROR5xphxwAtAKyAd2Fza/3TLGk9jTBjwJhAKGOApa+07Pio/IBhjkoH6wJmfUjdaa39bynHnveZKBPoirxYdgCowTqVec8aYmRR1xuwocfiV1tpy/SJbK0VFRPyEVoqKiPgJBbqIiJ9QoIuI+AkFuoiIn1Cgi4j4CQW6iIifUKCLiPgJBbqIiJ/4f7krTgU1nyznAAAAAElFTkSuQmCC\n", | |
"text/plain": "<Figure size 432x288 with 1 Axes>" | |
}, | |
"metadata": {} | |
} | |
] | |
}, | |
{ | |
"metadata": {}, | |
"cell_type": "markdown", | |
"source": "### Same time-tuple, different calendars\n\nThe difference is subtle; here is a minimal example where it matters." | |
}, | |
{ | |
"metadata": { | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "gregorian_dates = [cftime.DatetimeGregorian(2000, 2, 28),\n cftime.DatetimeGregorian(2000, 3, 1),\n cftime.DatetimeGregorian(2000, 3, 2)]\nnoleap_dates = [cftime.DatetimeNoLeap(2000, 2, 28),\n cftime.DatetimeNoLeap(2000, 3, 1),\n cftime.DatetimeNoLeap(2000, 3, 2)]", | |
"execution_count": 13, | |
"outputs": [] | |
}, | |
{ | |
"metadata": { | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "fig, axes = plt.subplots(1, 2, sharey=True, figsize=(8, 2))\n\nax1, ax2 = axes\nax1.plot([CalendarDateTime(date, date.calendar) for date in gregorian_dates], range(3), marker='o')\nax2.plot([CalendarDateTime(date, date.calendar) for date in noleap_dates], range(3), marker='o')\n\nfor ax in axes:\n for tick in ax.get_xticklabels():\n tick.set_rotation(45)\n \nax1.set_title('gregorian')\nax2.set_title('noleap')", | |
"execution_count": 27, | |
"outputs": [ | |
{ | |
"output_type": "execute_result", | |
"execution_count": 27, | |
"data": { | |
"text/plain": "Text(0.5,1,'noleap')" | |
}, | |
"metadata": {} | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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\n", | |
"text/plain": "<Figure size 576x144 with 2 Axes>" | |
}, | |
"metadata": {} | |
} | |
] | |
}, | |
{ | |
"metadata": { | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "", | |
"execution_count": null, | |
"outputs": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"name": "python2", | |
"display_name": "Python 2", | |
"language": "python" | |
}, | |
"language_info": { | |
"mimetype": "text/x-python", | |
"nbconvert_exporter": "python", | |
"name": "python", | |
"pygments_lexer": "ipython2", | |
"version": "2.7.15", | |
"file_extension": ".py", | |
"codemirror_mode": { | |
"version": 2, | |
"name": "ipython" | |
} | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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