From b44f2dc3bcedb40ecdfbbd5297e81bcd997b0b6e Mon Sep 17 00:00:00 2001 From: Jeremy Singer-Vine Date: Mon, 27 Feb 2017 00:04:51 -0500 Subject: [PATCH] v0.5.2 @ Added - Access to `curve` points. (E.g., `page.curves[0]["points"]`.) - Ability for `.draw_line` to draw `curve` points. @ Changed - Disaggregated "min_words_vertical" (default: 3) and "min_words_horizontal" (default: 1), removing "text_word_threshold". - Internally, made `utils.decimalize` a bit more robust; now throws errors on non-decimalizable items. - Now explicitly ignoring some (obscure) `pdfminer` object attributes. - Raw input for `.draw_line` from a bounding box to `((x, y), (x, y))`, for consistency with `curve["points"]` and with `Pillow`'s underlying method. @ Fixed - Fixed typo bug when `.rect_edges` is called before `.edges` --- CHANGELOG.md | 14 + README.md | 34 ++- .../notebooks/ag-energy-roundup-curves.ipynb | 277 ++++++++++++++++++ .../pdfs/ag-energy-round-up-2017-02-24.pdf | Bin 0 -> 50918 bytes pdfplumber/_version.py | 2 +- pdfplumber/container.py | 2 +- pdfplumber/display.py | 29 +- pdfplumber/page.py | 47 ++- pdfplumber/table.py | 17 +- pdfplumber/utils.py | 20 +- tests/test-display.py | 8 + 11 files changed, 406 insertions(+), 44 deletions(-) create mode 100644 examples/notebooks/ag-energy-roundup-curves.ipynb create mode 100644 examples/pdfs/ag-energy-round-up-2017-02-24.pdf diff --git a/CHANGELOG.md b/CHANGELOG.md index a6f92c5c..6e64593f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -4,6 +4,20 @@ All notable changes to this project will be documented in this file. Currently g The format is based on [Keep a Changelog](http://keepachangelog.com/). +## [0.5.2] — 2017-02-27 +### Added +- Access to `curve` points. (E.g., `page.curves[0]["points"]`.) +- Ability for `.draw_line` to draw `curve` points. + +### Changed +- Disaggregated "min_words_vertical" (default: 3) and "min_words_horizontal" (default: 1), removing "text_word_threshold". +- Internally, made `utils.decimalize` a bit more robust; now throws errors on non-decimalizable items. +- Now explicitly ignoring some (obscure) `pdfminer` object attributes. +- Raw input for `.draw_line` from a bounding box to `((x, y), (x, y))`, for consistency with `curve["points"]` and with `Pillow`'s underlying method. + +### Fixed +- Fixed typo bug when `.rect_edges` is called before `.edges` + ## [0.5.1] — 2017-02-26 ### Added - Quick-draw `PageImage` methods: `.draw_vline`, `.draw_vlines`, `.draw_hline`, and `.draw_hlines`. diff --git a/README.md b/README.md index bedd81ff..3d34bd2b 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# PDFPlumber `v0.5.1` +# PDFPlumber `v0.5.2` Plumb a PDF for detailed information about each text character, rectangle, and line. Plus: Table extraction and visual debugging. @@ -102,6 +102,7 @@ Each instance of `pdfplumber.PDF` and `pdfplumber.Page` provides access to four - `.annos`, each representing a single annotation-text character. - `.lines`, each representing a single 1-dimensional line. - `.rects`, each representing a single 2-dimensional rectangle. +- `.curves`, each representing a series of connected points. Each object is represented as a simple Python `dict`, with the following properties: @@ -130,7 +131,7 @@ Each object is represented as a simple Python `dict`, with the following propert | Property | Description | |----------|-------------| -|`page_number`| Page number on which this character was found.| +|`page_number`| Page number on which this line was found.| |`height`| Height of line.| |`width`| Width of line.| |`x0`| Distance of left-side extremity from left side of page.| @@ -147,7 +148,7 @@ Each object is represented as a simple Python `dict`, with the following propert | Property | Description | |----------|-------------| -|`page_number`| Page number on which this character was found.| +|`page_number`| Page number on which this rectangle was found.| |`height`| Height of rectangle.| |`width`| Width of rectangle.| |`x0`| Distance of left side of rectangle from left side of page.| @@ -160,6 +161,24 @@ Each object is represented as a simple Python `dict`, with the following propert |`linewidth`| Thickness of line.| |`object_type`| "rect"| +#### `curve` properties + +| Property | Description | +|----------|-------------| +|`page_number`| Page number on which this curve was found.| +|`points`| Points — as a list of `(x, top)` tuples — describing the curve.| +|`height`| Height of curve's bounding box.| +|`width`| Width of curve's bounding box.| +|`x0`| Distance of curve's left-most point from left side of page.| +|`x1`| Distance of curve's right-most point from left side of the page.| +|`y0`| Distance of curve's lowest point from bottom of page.| +|`y1`| Distance of curve's highest point from bottom of page.| +|`top`| Distance of curve's highest point from top of page.| +|`bottom`| Distance of curve's lowest point from top of page.| +|`doctop`| Distance of curve's highest point from top of document.| +|`linewidth`| Thickness of line.| +|`object_type`| "curve"| + Additionally, both `pdfplumber.PDF` and `pdfplumber.Page` provide access to two derived lists of objects: `.rect_edges` (which decomposes each rectangle into its four lines) and `.edges` (which combines `.rect_edges` with `.lines`). ## Visual debugging @@ -191,7 +210,7 @@ You can pass explicit coordinates or any `pdfplumber` PDF object (e.g., char, li | Single-object method | Bulk method | Description | |----------------------|-------------|-------------| -|`im.draw_line(line, stroke={color}, stroke_width=1)`| `im.draw_lines(list_of_lines, **kwargs)`| Draws a line from a `line`-like object, or a 4-tuple bounding box.| +|`im.draw_line(line, stroke={color}, stroke_width=1)`| `im.draw_lines(list_of_lines, **kwargs)`| Draws a line from a `line`, `curve`, or a 2-tuple of 2-tuples (e.g., `((x, y), (x, y))`).| |`im.draw_vline(location, stroke={color}, stroke_width=1)`| `im.draw_vlines(list_of_locations, **kwargs)`| Draws a vertical line at the x-coordinate indicated by `location`.| |`im.draw_hline(location, stroke={color}, stroke_width=1)`| `im.draw_hlines(list_of_locations, **kwargs)`| Draws a horizontal line at the y-coordinate indicated by `location`.| |`im.draw_rect(bbox_or_obj, fill={color}, stroke={color}, stroke_width=1)`| `im.draw_rects(list_of_rects, **kwargs)`| Draws a rectangle from a `rect`, `char`, etc., or 4-tuple bounding box.| @@ -243,7 +262,8 @@ By default, `extract_tables` uses the page's vertical and horizontal lines (or r "snap_tolerance": 3, "join_tolerance": 3, "edge_min_length": 3, - "text_word_threshold": 3, + "min_words_vertical": 3, + "min_words_horizontal": 1, "keep_blank_chars": False, "text_tolerance": 3, "text_x_tolerance": None, @@ -263,7 +283,8 @@ By default, `extract_tables` uses the page's vertical and horizontal lines (or r |`"snap_tolerance"`| Parallel lines within `snap_tolerance` pixels will be "snapped" to the same horizontal or vertical position.| |`"join_tolerance"`| Line segments on the same infinite line, and whose ends are within `join_tolerance` of one another, will be "joined" into a single line segment.| |`"edge_min_length"`| Edges shorter than `edge_min_length` will be discarded before attempting to reconstruct the table.| -|`"text_word_threshold"`| When using the `text` strategy, at least `text_word_threshold` words must share the same alignment.| +|`"min_words_vertical"`| When using `"vertical_strategy": "text"`, at least `min_words_vertical` words must share the same alignment.| +|`"min_words_horizontal"`| When using `"horizontal_strategy": "text"`, at least `min_words_horizontal` words must share the same alignment.| |`"keep_blank_chars"`| When using the `text` strategy, consider `" "` chars to be *parts* of words and not word-separators.| |`"text_tolerance"`, `"text_x_tolerance"`, `"text_y_tolerance"`| When the `text` strategy searches for words, it will expect the individual letters in each word to be no more than `text_tolerance` pixels apart.| |`"intersection_tolerance"`, `"intersection_x_tolerance"`, `"intersection_y_tolerance"`| When combining edges into cells, orthogonal edges most be within `intersection_tolerance` pixels to be considered intersecting.| @@ -290,6 +311,7 @@ Both `vertical_strategy` and `horizontal_strategy` accept the following options: - [Using `extract_table` on a California Worker Adjustment and Retraining Notification (WARN) report](examples/notebooks/extract-table-ca-warn-report.ipynb). Demonstrates basic visual debugging and table extraction. - [Using `extract_table` on the FBI's National Instant Criminal Background Check System PDFs](examples/notebooks/extract-table-nics.ipynb). Demonstrates how to use visual debugging to find optimal table extraction settings. Also demonstrates `Page.crop(...)` and `Page.extract_text(...)` +- [Inspecting and visualizing `curve` objects](examples/notebooks/ag-energy-roundup-curves.ipynb). ## Acknowledgments / Contributors diff --git a/examples/notebooks/ag-energy-roundup-curves.ipynb b/examples/notebooks/ag-energy-roundup-curves.ipynb new file mode 100644 index 00000000..5be6fca2 --- /dev/null +++ b/examples/notebooks/ag-energy-roundup-curves.ipynb @@ -0,0 +1,277 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Demo: Extracting curve data from PDFs\n", + "\n", + "The notebook demonstrates how to extract `curve` objects from PDFs using `pdfplumber`." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true, + "deletable": true, + "editable": true + }, + "outputs": [], + "source": [ + "import pdfplumber" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load the PDF\n", + "\n", + "Here, we're using the USDA's \"[National Weekly Ag Energy Round-Up](https://www.ams.usda.gov/mnreports/lswagenergy.pdf)\", a weekly one-page report." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false, + "deletable": true, + "editable": true + }, + "outputs": [], + "source": [ + "report = pdfplumber.open(\"../pdfs/ag-energy-round-up-2017-02-24.pdf\").pages[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false, + "deletable": true, + "editable": true + }, + "outputs": [ + { + "data": { + "image/png": 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YWVQ0COdoNDKfwt/tdh3HaSZljSFNxJHKnr8Wz252VKWMk0MqpLERluWEMxdE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\nyLXnuu729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UX6a6H9fsFFxXDGtyr2puYo3cP5q6RtzcNtW5bg3M3xmRuDh1YxxxxQ6jWk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\n4jFSgAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "im = report.to_image()\n", + "im" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Examine the `curve` objects\n", + "\n", + "`Page` objects have a `.curves` property, which contains a list of `curve` objects found on the page. This report contains 12 curves, four per chart:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "12" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(report.curves)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here's what the first `curve` object looks like:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false, + "deletable": true, + "editable": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'bottom': Decimal('168.720'),\n", + " 'doctop': Decimal('59.740'),\n", + " 'height': Decimal('108.980'),\n", + " 'linewidth': Decimal('0.250'),\n", + " 'object_type': 'curve',\n", + " 'page_number': 1,\n", + " 'points': [(Decimal('583.710'), Decimal('168.720')),\n", + " (Decimal('749.790'), Decimal('168.720')),\n", + " (Decimal('583.710'), Decimal('155.160')),\n", + " (Decimal('749.790'), Decimal('155.160')),\n", + " (Decimal('583.710'), Decimal('141.480')),\n", + " (Decimal('749.790'), Decimal('141.480')),\n", + " (Decimal('583.710'), Decimal('127.920')),\n", + " (Decimal('749.790'), Decimal('127.920')),\n", + " (Decimal('583.710'), Decimal('114.240')),\n", + " (Decimal('749.790'), Decimal('114.240')),\n", + " (Decimal('583.710'), Decimal('100.680')),\n", + " (Decimal('749.790'), Decimal('100.680')),\n", + " (Decimal('583.710'), Decimal('87.000')),\n", + " (Decimal('749.790'), Decimal('87.000')),\n", + " (Decimal('583.710'), Decimal('73.320')),\n", + " (Decimal('749.790'), Decimal('73.320')),\n", + " (Decimal('583.710'), Decimal('59.740')),\n", + " (Decimal('749.790'), Decimal('59.740'))],\n", + " 'top': Decimal('59.740'),\n", + " 'width': Decimal('166.080'),\n", + " 'x0': Decimal('583.710'),\n", + " 'x1': Decimal('749.790'),\n", + " 'y0': Decimal('443.280'),\n", + " 'y1': Decimal('552.260')}" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "report.curves[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Display the curves\n", + "\n", + "We can get a quick sense of where the curves are by passing them to `PageImage.draw_lines`:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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VRMvl8v79+/fv318ul2qD3Lt3z5P1/v37MuX9+/cDytVuccsVd3Dnzp068Y2f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\n3y9HFOeBoKV0Zffrg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+ "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "im.draw_lines(report.curves, stroke=\"red\", stroke_width=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can get a more better sense of the curves by cycling through a four-color palette:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false, + "deletable": true, + "editable": true + }, + "outputs": [ + { + "data": { + "image/png": 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pMPpCFZxPgiCgX031qp4PdDyudahOELL0qyAZqUyQ52KqxYzHmLWnfBv5hSd5\nTE9Y9XUTaFl/50VzBV0w19KL0egkI1r9OjF6PoQ6eYnkHg3xOLQDc0VRuCQIMk3T1HVdVVVRFMvl\nsmma5XJZFEVVVXVdyyIscEqxria6R870DWJDdTZhlf0YaBo6VBqcT6UGCgLgXBum9RcOuGhxeqPa\nIpy61tLTmYE3jQAbNON/mzBrL7AmB7QN1AsfurN/L7qGK7WSvVLhyrJDk1f8Z5JF1sS+YqvI4vVh\nnUlsdbl5a11etPh0Ov3Gb/zGl770pV/91V/NUmsQIhMM1bFv2WDJOaoP9C/7qcKcxycW82Sen67v\n/sJ3nbOQDT4Lxkw144OLhTEPoSl/247qykaGiJG6hiViRoubAWn0D0ae5BKzodYZezFOp4auFH99\nGekaaTRPWoPNT6fTcrm0C8VsNpvdbper6mBIyOmeWCw5tSCvtaKsV+AK9BYbg+/47L/9rCgK4Vi7\n4SwEGy1Vv6vwfGaOVRqBkAIAgLHBaH9HWoTU4XBYrVZ3d3c2ldR6vRZevQk8Pj5+9NFHbuU1doKe\nv//zdnfUTwkNU5acs95ifXjd9FDbhZCOdZfoIdEIhBQAAIBZ0+qRquv67u7OLhRzOByyL1ocCCkT\nD2+aZy6D+estIYZMnxPB/6i/EPbmev2//tHd//W/8If59EYuL/0BAAAA4LNard68eWO3s6solnkK\nphhKedS6kEsna50I5srR/XoLnbAKZ/kb/8fm//ynmv/lD/f/tZ2GbD799NO8Ts2uQEgBAAAAF4ZG\nISnFltIaZTSF6g+vN//3/9PybDY/9SP7cepWMOpae0NM87mFrMoAgOuAhlsJc+v6VxQzxTZDc2By\njWAS8jq39AbzQnOnLRbmfP7C6s3/r371pxYL89//9+M36hmDe6Ri+ilXuiYk1QTAxH9RCJkdNEkc\nhCVi5HqBTEw/5XqYyQkUzlOvtQdmxfz1lp+K1ry7Y+tXf8p++9/9dz9jJhXxwy5aHPuWZrtmMz6z\npoKSNM8ynukAWNgM5lmsgTSU2S+fTfP2tmNf0ZJOG/kFYpXS8vSlRTsSNGYOuNf8d77zHTPvuW+X\nyKyCt+jNP2H2kGEXLfY/nt8tBmy8X7GxMsplYWIFoKUuEeFaUy/mbC/xhL0QEl+xGTUTDAamMJM3\nATb3pq9LWGeVL3dafT+xAv5VYkWYvorYsWfdosWdOB6PfvrysiyNMS9evPjss8+Wy6WbgRUk5FQu\nYXuhDDEcPCadZibS3wNU6Nvb7+Hh8doWLY4t6UW/cjuN2PTWrNMY5rsC2It4cZd4Jr3w/5qCwbg0\n6F/0pVyR+RBolJhXyd9pxDdl7KiY7yqw3FWTjT+EZ9cntpRlWVXVbrezaaj2+/1qtQoWLX58fLy/\nv7+/v7++dfFYF+O0zpg0lAJ3sTAPD59/zDv8nZFR19prjcnwvVYakFX56rmO9/S0vZCr7vTzy18C\n2T8cf4kJBGEfMZwvSn+COxVWjjbOhOPxWBTF3d3dj/7ojxpj1us1u26xk1DXoaUeHj6XHfRmsHsu\noqd+R4wxDw98m2l/LW7j4eHRlZnDg2ek9Aesd0r4ya75SHdewRsXgLz4fiN2xWgIoAlhvVP0MRbs\nkT/SnTGDQkV6aRUcMvQzuGma3W53Op3+zt/5O8YYVkVdGVYxsGJaI8Tng+uIeddyJ4Z8RRXrrxu8\nc3sWZMLEVCCzOZgLnXTwbG/CqXrRumixUfuGYwYDU37J2V4OMD7ZY6Tu7u52u11VVUVRVFVl1+l7\n//33v/zlL59OJ5fSM3uM1OQZAYJY/iCWrpWBMmskQDviNyY2nO3HBRpOWgUHWo2FRYsBaOc65ttf\naC+gmXpyG07zzEJKTyB9Rog0H256GgnhDwuwooqqk2DP+H++bEdoq+T+BlLSkXDFIaQAuFQJEnAd\nvQCAkt0j1RW61t6E+G96IUKIKoCY/6k1JwW1IOzJhdxI2ZEm+9s0QtAuEaO84nOZtYdQJDA513ET\nXkcvAAAxnEKinhhfV9m5ac+Dr+8Np0XoNE/nv5Gj5YaQUMIsQr+FQTMCzcRG5sX6O09ShBR+RgMA\nAGDBz4OA2Cgb3fnwcM9OUgu2nd6yYWAmPvVyoEvBijn/K3anv22/paIqVsXMwaLFg4OwEgAAuE2C\nGCAhdPp8/twBEwRZm9Ch9cyV5dsRkorZ/TbJVq4etc4iFESkv+G3P2ZqzuQZ2pNnA7HzifQVBfOD\nYlW7kvLHwL68/kysUlpeNu5rqVZdFUy5gggDAIDLRXDM0G1D1IM8NueLJEN0G7Xw+JghQJ62hK0u\n1kfaQWF07yJIHNrrlNQ4YzZCWjWba8p+Gwi4QMH4h8fW7wtETCBuhJNA20ZFm76zAAAAlNw/PDD5\nsAVkIZMD6ohio5o0jitKzC3Ejppp3FFti+V9HrzFRjUJOQ5iWvDSyT+0F3MICSV9xlEbVI3F7MSM\nUwEXeLDktWtiZmOerbYOAQAA4F7gshLpWj5H6wyZ8O9/K7uglLXYCCRn7c3v/6dXf+6HlT2TxZav\nUY2nn4KhusBVZq5CMMXoJaRinpjAIaQ8Vt6fVkxPgopKyBxh2vx5cEEBAEAaj4+Pb0OvHbEwbJ9Y\n/E6mN79vzEmlQGoEzWRHA5WwCmax+GHamGT8NrNOKX/n89D4kJ4BW85z9lu/9Vv9rSXTS0iNP7Q3\nqM3sCMs2AwAA0HA8Hrfbrb/ndDqt1+uyLJfLpcsJxIxG6X1LgRcol2soPlpH3wb+qF9PR04sysqv\nPcFs0ObY6SGWo+KmbQzx3fEReURz2fcPpU9j4ll7MT00pk5ihyBlv5HvchP8UnJcFA0qh9ICAICA\nuq79j6fTqaqqsixfv3693+9Xq5Vbbu/+/v7zkSdfv+ijoKg6SNUdQp1stLUbjGttYwK+r0jjpIsF\nb8U8Z2nkCNj6XE7d399PtXJzr1l7+vih1g3BAg0/illwwiUICZcVD9vamP1go3V0j+qzWAEh6AoA\nAIAxpqqq9XptV9wzxqzXa2bdYlb3PBdGj+/0Vpj1MuIp6vqG9lfeddU+z7fpFzYPD/fBcFhWSfBM\nr7Da0lbq5wgNlKS/x8myqYTL3MiWkFNYxFTQBO6rQOvEDtFoCzrVji3jCyy/9jT54h8VTBJsna9n\nv3X/yt0BAICbpSzLoiiapvnDP/xDYwyjotjIIy5q6j6Imn7+bf9goqBy2QkU01gDQU/MYvFM/NHZ\ndjH5BcxAQ3saKRN8pT8kF75w6VNdTP0EXiu5CrYMnFIAANA0TV3XVVUVRbHb7cw7OVVVVV3XfvjU\n2xAZqlzIcNRbFRW4oJyC0Gifd7DjU6xImyoU2iXtFFTimcuzQMVWwFQ9stAYqalagkWLAQAAZMO9\nKcZftNh/ld4/PPB6iHiKFub5z3jD7GFdU4HhYGjMr9B0CXwfAhpvztIaPkU9VdMSiCeNsBti0WII\nKQAAANmYUEi9a8Czj2fDD7D5aokqrpgGC2qh3prgQP+jMH43mmtnEVnbjhLoPzZ4bCZ8+umnRVG8\n9957msJDCCmstQcAAOBKoPrGTlMLhIBVUf54lh8MFOz53BRZHc+v1HDy6/lX0Wn8/Zdt0eP3Ih5e\n/yxM/nzmzwmwDCWk4L4CCcRuGyFdfpYbjK03Vql+qqayF8N1Qai0td7Wc9I6IxWASWAiyzmnijCx\nTzL1HDrhL9ij+bPIkgVAaYqKJEO6RnUh9dUBn6GEFLIiga7IOS/YBRPzShC/XjZHP9sGwZqwX+hU\nri7ItShVlNDmPg0GYAQYHfNcUQXSR9gwnoBgv6UqKi8Zxdb5/MwU64pjHW8gxkhDe8IPWbofP21v\nFmF9xtbcYwPVm8tUxio61WuSTp2mta3JSgCYkEDZhF9w8dfyGJ//b+DC8T8Kc9yGJlVs3dPBO9CJ\nMYSU8OM+KANumZi/hBXZLm9q/1f4oC4uzf7+DHHqlK3FXy6YG4vnU/2NUz/2w3MR5A91+QfSPf4h\nFDq0Fys5LVRs3d+Hg3fKdKDT5j6YFRMEm9OhgaF/rIMLgt4G7LhV9rFj2Zcjf2SzoMVG04YbF0s7\ndV17AcCcCWKAnu18N4HPePP1gpAm6mdi/1jpURcdjk1am2cY8XaU1oDpD3xHFLvhCPbgqX2z+HcI\nG+hjiGclow+JJpfvU2OscHCr5+rFQKfOL8lag8wCAe4Oz5X+wF+0uKqq0+lUFAVdtNg8zyr08HAv\nTEnzP2pg5VRsLAx/EEadHrOn2JpJHqnBZ+0J8RkxpwIezbdJcKuw735DhMhw9cruqFZrJv7jwX3M\n5ZrKfurY1tKv4EUGIxAsWvz09PTy5Uu6aHGQ5zrILU7n0LEyS0AIhML7ijLCVESa2fxtavvRGXDW\nnvLb/ou0gOsgdg9Qz0deqc2aSnbhBD4hf4Puz9WR7Kcu1ovAAv5swcgURWGM2Ww2TdMYsmixfYn6\nb1MautRH/F9KINSlkEVsOTl1f38/1SoxEyfkxIMYKMkeEq6vrmuNsqxJNptM2qnT9wKAMSnLcrvd\n7vd7wy5abIx5+3K9X3hL5wUCyN3F6lcvM7XNZiqfboU3MBe+MHUDAAAAgCh20eLT6VTX9fF4LMvy\ncDh85StfsYsWx+JdrMqhyiltnr+z5sLPhfVewK2BtfYAAABkI3uwuRIaMWM/+mFMdDaf0mwrtzND\nbT7Errh8FBYtBgAAMGumElImPocrQT/1qVcAeisvM5m1N5SQYhNvBgfGygTlbXCrkDFBqAIAAMCY\nTCikLI+Pjx999NF77703ftUy0FsD8emnnxZFobzil5T+gAqdmIqKlfeL0a+cuvJzDEJFgTRkrc/q\n+GRr/lfZU2EJldK0twm9SLYGAFDKI2VSAL1BMDQTz9qj+Noo+IrNywxAT/LeThpr2TUHm8HcPBeC\ni9yLFo88jxKAGyGv3oLYGoEphZSQkFNTjC0MLhfhUg7q/6DGaXv0eZg01mJ7+hCrN63GvNYAANnJ\nmPFSaQ3EmEZIxR7BQg7lGDR9M7hoWN3MDvtmJFZjwg0ZK+ZLk+zdUTqHgjYkOKWSrQEAxgeDieMw\ngZCSH9AYuQM+49wPThMsuLX2YiohFpYUs2YiyiyXComdKNnFm9ALwRoA4OKA3urJ4LP2YsSev8FM\nvZjDCbP2rg/WCRT7OMSF9i2z0eWdFE+sncJt3wf/7MVC5lvbJpg15ALRSKyeXQDXgbvD55P+AIzJ\nmGLrytMftJpSPsTpKwHP62ulk2Mj420gCzV3yynlQsxaLMAryy3dOpgot0E2qPE54a8SOLILqePx\nuN1u7XbTNGVZLpfLoijshnsppqVnBJOQJRPEfBJyThMjpWxfbOIeuEqUFzf7QFLgxWFHuPTNi1mL\nZejIckvHjATiT58lRDgngZ8Yf5JgaOq6dtv7/f7169f7/f7b3/72r/3ar+33+9VqFSxa7LanWsIW\ntJJxMBGLFgMwC/KqgZi18TVHH92m6QVUFBiZ5XJpjFmv19/61rfsBl232H+bQkuBEUgRUogtBZOD\nmxCAG6RpGmNMXdc/+MEP7EagogAYH3ikAAAAzJemaeq6rqqqKIr1el1VVV3XX//61+2GC58yxjw+\nPtohHoMYqRuAjZGaBCxaDAAAIBuYtQdGYyaz9vIM7bVOSqct6ynL2NnpJjLRjy0WGGRzKMQyLLCH\nu9pbZzy1JhGNTbCSd9K66Ix3ti6/AFQyANMS/KXav0i7c4i/Tra6C8X5oua5aDHIjr3inRYtHoIv\nJBzTdR6TUUiHTtC5SP5+mmxQU7uswBaRlcXO5zNbe6xwrJ2BQVbT6PviWuXKxM4YAocBmBvuD3Fo\nCeXXcj4/qy4NBC6C2yR/jJTG1RSIAE3SmoyOk1h1sshTpo12OzXZdwIjbNIsfauEliibkVAeADAC\n7o/bbZzPvHCJ6SG/fOufeKyWwDhtA7QUuEFSPFIO+uYWckMLR+m/TThQ8DO1osy+GEu302qwU3ZH\nWn6qDJYAgBGgf9++d4qVSrEDNXU548LhfjG5DQDcDr2E1GzfzXTsTIZ2RJ8DmpbXEPMe5bLf9Vhk\nEwBgbvgPHuEhRL8a4sEs25zrqwCAMeglpLoiB1f1l2V+xFLe2uXkhNRv1Bp0H7PvD4wm94UtKQAV\nBcA1wf5B+zs13qz+IVMA3AgpQqo1qCg25CcfmOzUWSwWzj4bXi3UHosQN174FP2WNeWLITZ0KYge\ni4Vn0b74Rwl9iTXAEMFHT91snYsA3Bo0HErYpuW7Sh93VPAMCILc5Vgots0A3AgpweatHh0asNzq\n73GB1f4rn52/Zne2xkR3HZtjj9WskhHURZstjBsKjquzYr3bWMNikWqa8wBFBcCEtDqThqtotKoB\nuDIGyWye8DIONEfrMFyr+ypNEPQZ4PO30+zEjHTtS1pSA8zXAwDMjaZpyrJcLpc2iWJVVXZnURT+\nfgAmZNQYqYzglZ8dnFIAJsfmc5rVf13blpf9fr/ZbMqyrOvaGHM6nVarVVmWwX4AJgRr7QEAAIgy\n7S+s5XJpjFmv13Z94t1u9+rVq+12a/WT2+8f8mf+zJ85HA7TNBdMwY/92I999atfnbABEFIAAABm\nStM0xhinlo7H4yeffOJ0ElVRxphf+qVfGrmR4MYZcGhv8Zzslv0NAAAA18d6va6qqq7rpmnqul4u\nl03T2NAoux8xUmByhvJIBRPTNPPsBFOxxATg+qBTDlunPfaZoTkEsebFJnvKxaYiOKts82beBXAF\nbDYbY0xRFPbjdrv1P7oNACZk2GBz9hUY+JOo4yrY9v9lXVCsEXCt+NeXTZc1LUGTYqkolMXmQPC7\nxW0HbZ5zF8CtYd1X+vK2sHyI9YqZdzMH5do7Va0329qprh03utbWdV1Vlb5fZVm2dse2s2ka2axz\nRiqrnoSRZu3ZPN2aRy27f7h8B2BWKIWRn/Z9bu9sOSW9XGw+faEtUfYLgDmwXC6Px6O+vKZwWZbH\n47FpmtZI9uPxWJalsmq9WU2nunbc6FprJ0sqDe73ezsJQDZrp15WVWXnEwjNWy6Xp9NJf0rHZ/r0\nB8psST0zM4H5ExvICwiyZM1QVCmbERuRnMPNHJzVuTUPgCGQnSir1cq6RmRJYf0rp9NJWanS7EAo\nW7vdbvf7fSe3kM1SIRdYr9fKE7XdbltdXBMynpBKeMkJQyGy8Zm8UEEC/mBuazHHrN7uToUEo2BC\nMf2tPiZyBn8AZksnD4qlaRobjxWjruvNZtP6Oi/LcrfbLZdL5YtfadboOtW148rWHo/HzWajFFI2\nV2pVVTagLYadKKBpbVmWp9NJtjYtHQLAu0aS0lfdmA/iWb1ZgQZWG7FzFJzvyv9W6dAaDU3UvCF+\nqdn2gp7z4CvLDLsARsbdD9/4xjc+/vjjaRsDQEBZlvJMz4RJMwPmkaIvQjxbgQAdS3LeKTaujvqu\n5nCD0fZQb1NMfMzH5cM2z3DnHM5gAMCNM3hCzjm828BlEVPesXuJ9VpNhewn8zfob4z5dIRtHkvQ\n5vl0AQAAxgGZzcHFM7c3tzI0m341q44oG6MUuwAAcK1MP2sPAAAAAOBCgZACAAAAAEgEQgoAAAAA\nIJEBY6TmNp0KzJ/YZDHzfE6ff8gM59vHJu7F0jLNc6G62LUIQsv9nXPrAgAAjMBQHin5zQGAzHWE\nMMuT3fztOS9UF1vcCYkPAADADD1rz86F9nPPdHraXujrE6ShfDHTdFMj53qVoS2ROzKflvuwrYpl\nTGU/AgDAjTCURyptoS4op1uGru8mLKI32xd20OzYsOPMV69TrrUHpxQAAAwYbC68BQ1ZTJ7+nJ3h\n2wWMwFUO6sXcsTMXIuyfcPBHGgSBwS8FALg1Ro2RYssAkMaFaixHsHrd/FdSmm3DAABgQkaatUd3\nxn6LzyreBYxJ65Q9dqE64/l75vCmj3lV/XhBunqdmdnvCnkpQNrU2BRLAAC4eoYSUnTtsE7PVjyI\nbxC6vlssOmfOw3+02W6/iXdhbhkclEsBytcLAABugWFn7aU9VfEsvlnmrJD0JDR7hj3VLAV4HdcL\nAAD6gMzmAAAAAE9Zlvv9vmmaqqrKsqzr+ng8GmOOx+N+vz+dTlM38Bm2tf/kn/wT21RjjG1t0zRl\nWTZNM3UDP6eu6/1+bxtpjDkcDqfTqWmaw+HgF6uqypWZLcN6pAAAAIAx+PBDk1EoFIV5ejLGFEVh\njLEq6unpab/f2++3221VVcvlMsF288fnu//xPzZ/nM2D+/Tf/IniSz/kWvv69eu///f//n6/f3p6\nsirkcDjYrxKo6/ru7s5ub7fboiiSPxpjTqfTJ598Yowpy3K5XK5WK/ft4XCwe6qqcq2t67qqqqen\np9PptNls/t7f+3tf/OIX1+t12pkfCAgpAAAAgGe5XC6Xy6IoyrIMvirLcrfbpdj8kUXxpR/KKKRW\nf/Lt4JJt7Z//83+ellmv14fD4enpqatx2/23Fa1WfT6ad1LPvFOiZVmu12tXi/X8bTYbW6ZpmqZp\n6rq2vrTT6fQ7v/M7f/Ev/sW6rpN14RCMOmsPIRSgFTp/k71tgq9mtcqbZpU687wLbNLwyWHn0sby\nw2HiHpiYTz4ZwurxeLROndVqZd/6VFElsPsLX+xvhGJb+0M/9ENOoFhWq1XTNGniY7lcBvKrz0fX\nBjsqKjfpdDptt9vVanU8Hne73X6/t/4q69yaDx1m2XR6V7ELR+DZCmRYedQqpOZ2d7FakDZy5kIq\n1jyNkJpD+8FUuNvgG9/4xscffzxtY8CVcTwerePKl4mdCCQmJeE5NmywOZ0+7Qg+0p2DNgzMEJqm\nKHYfs4m2Z3LP6JsRZHZwOTnnoEKCsxqsQ2AJ2jyT8w8AuGLsqF+yihqIMWbtscIIj10gINwerW6q\nafE1R9f2zKH9lNj6Nv63pl/HAQBAgx90NR/GEFI02Qz7AxcAo/bHBG/3ud1ObDjUxUF9ZqatL3O7\nEAAAMDST5ZGSF5CJFQDgsvB/M2hExiUKkUtsMwAA5GLAJWJioU5YRwIIUDHtbhgain4my8BNDo3L\npj3y9we9mxVs/BmNoGfLjNVGMF+Wy+U3v/nNqVsBQEj2EKuhZu0FR+HBCpSk6exZqXO/MRd9/wcd\nae3FrK4CmIrZDrgDoCHhBh5cSAEAALgd8KYAF03CDZwytDfDMQgAAAAAgPHBEjEAAAAG4W/8jb/x\nEz/xE1O3AoBnfP/73//rf/2vZzSYIqTgsAUAAMDiD1n8xE/8hFuzFoCZ8Ou//ut5DaZ7pBIWtdAM\nPern/uQK42U7IqzsYZKCamOHCKfxouOUAQAAgFsgMY+UsHCEgGbWj6bYECjzDWoK6EFuQwAAAOCi\nyRBsLqSMCsrE7LD+Hpq6Ws7hKcggeqy8loVyfRJN1X7tGh8ePSeYUg4AAADMljyZzWNvekGvyMLL\nVx76dIWty4FlhCaHbD2EPUsQSQAAAMDlkn+JGGG8r6doCFb+ymKzP8kNiDnP+jUHAAAAAOORR0gl\nu3yobui/njGrt3q2augDAQAAAHCJJKY/UC5wFhSgS3dphvzoOl90alusvDDYZ43IffHbqZlz12ok\n+IraRLJTAAAA4IJITH/ALiIbFKDfUjlC99ADY6u6up3BMJ9fngovZV+E0UkbWU9rZ7tDkeUUe0Jk\ngwAAAACYil5De/IwHP2WHcijH4MDNTKI3eOsCYcLrdXUmCB6zh6ycczXAwCANE6n06tXr8qyPB6P\nL1++bC0sfLvf71+9euU+lmW5WCw+/PDDpmnsV67A4XB48eKFXJdQplObjTFVVS0Wi7IsY9/e3d2V\nZbnf72NlXJN6DoYcj0db193d3fF4NO+6GZy6a+WSloiZj6oYpyXz6S8AAFwQdV1/+OGHb968Wa/X\n9qMxpmmapmlWq5Ut4z5awbHZbIL9dV03TVMURWDc2lytVsvlMvhqu93ab4Pqmqap69qacmWqqvKN\nsG2mpvw++ntomdPp1DTNer0uisKdAdcMH7unruvlcmnb41sLzgOtyOqn7373u6vVarVavXjxYrVa\n2W7KCvVqyD9rDwAAAJgQ6xRxmubp6ck5S06n0/F4XCwW1mVSVVVVVU3TVFXl9t/d3dlip9Op0xI3\nx+Nxv99T+9Z9ZU3ZMtZLdDgchDbbna5J1rtT1/VisfiVX/kV67uyhf3eOYNFUZxOpxcvXpxOp6Io\n/GZYF1Rd1/v9vmkaW76qqhcvXpRl6Vvzz0PQL1eRbYaVVvZf61Tb7/fdLtvFAiEFAADgyjkej8vl\n0vqf7Mv+6enJukzsx6Io3P43b97Ywua5Z6gV67YJ7B8Oh6Io1uv18XisqsqWaZrmeDxS51CA3yR/\nz2/8xm9sNhvnRfN7547dbDZv3rxZrVZWA/nNWK/Xq9WqLMuiKJxLbLPZWO3lW/PPQ9Avzam4ESCk\nAAAAXBVWYbiXfdM0f/RHf2SM2W631tPTSl3XZVk6/1B2drvdZrO5u7tz0oe22fmKlAS92+/36/X6\nzZs32+2WysHNZrPf76nccbrKWtOcB/utba39d7jzNk8GjJFKWNW41Vosk7g/10+5YB+WBE4jtjAO\nnY+pKTam8VYLuWrp2gvzfBUjZS+GrmXQU9SfIDS2T4XWlLPgLJ/Pz2pxH1vrkosFNpPtaMh4li6L\noihev35tB8vsq/2XfumXPvzww+VyuV6vrXap69oGDFnpcDgc7IZ1GpVlaTVEXdc//dM/beOEbAE7\nkmX32A1XoKqquq7/2T/7Z7793W5nx/u2221RFIfDoa7rX/7lX/75n/955x5j2+wEkG3SZrNx42Xv\nv/++k1x1XW+3W9c7J2LqurZeKPNOpfnNWC6XfpSVdVC5Sp01/zwE/XJne71e2z5uNpvT6bTb7dbr\nte1mcOqulQ7zwjo9JTVPYXpIpwK+cmITH2gaCSHVCfatzGasMM9f2z6xcz6ocaEiw92f8hwWoZaY\ncKEH+n8jXX91xPoudKTTjw39KQoar/8l0wdf6xid4FgspALBt75B+5UrINtprc5ZVra5tYyyJcEZ\nGxT/lnv9+nWnGKPsBKNXF0GuNls1VlUV9Q+5qCk3OJiFQX14Gfn1X//1Dz74IPZtwg/CYWft0XbI\nL4DY26vTQ5lNgEl/MQc1QlFpCE5j3gM7GRcubkJjWFnGellaa2GN0wNbq0voBUXOENvJeEy5JhjP\nRfAn2+pJYndSOwLuEOpVYmuPVRGIm1jL/W9pLUEzgvbQncFJoGcg9hWtRSg/Ny7ivR6Qq81WirHW\nbAi8cpRTzyWe7SyMlP5AfugLP81zEVQx5uP+ykhWUXQ7zbgwPpXgXhVqiZnt5C6K2fH/IgLPqDIb\nmb8t/wLxa0kY2lOSMDqZC/lFzn6V8QEQ6AnZsi9oAneafyztUUxgse2JSUy6k61Xc3LYw8GlkF1C\n3TgTB5vHHrixfJUJNoUq0uzfOO7SdH3RUpcMVbQa4/5XrPdRg7IXshuJ7QJrXOlq7X9K5Vpip07Z\nC31jZvJDJeabsf/1NxgzIht33wr+JOrx0tSirDfWfbuzz3Mx+cQCcNGMJ6S6/lod+Vk8k0f/tULj\nac7vSDPYGqzTn8BscheUzevaC7+834zW9tBfGn0uhGx8ZIQBr4CR/9yDUbyeYsXa0XdBqW/o2J+J\nnCg8LAHwGWpoj46gsYFQsZ/Uwn72tz49UGMqsW83jHxB3as9KKw8553ulq7GhYqMdxdRHRO7wTr1\nIrATC9DW90LuvlyLpgr9KVJ6xfISG1Hyx5vcR1qGHfkKxtroRmx/YIeWZxsp7HSx7aydoI+y5aBr\nbmfMK+Z/FCqK1UjPLQC3wIAxUu75q/+t3NU4GBnn/3AfzfNLLO/vaTzwQvXxZi3iYUk9by22F8nF\nhFr8j4GE9Tc016u1eSZ+ihbd1+3uSatUSy4wqAhUunZiKk1jTWNWc3haybTyAFwBgwebQ/FcGfSC\nZoxCG9R4xsOzGB/nd4X+lGYphr93MDceHx/9j/f391O1BAzBHK7vJS1aDAAA1y3V+gdRTc6gTim3\nootdjtdulGVps0f627a8fcu6l+vj4+Pj4yO01NUwk+uLJWIAAGAuYOKbwOl0qqrKaim3Xq9NqG1T\nb/vb7ij7Wg3euOBq8K/pVNd3KI9U6xw9Ou+9q30aF+z2BPHOGG4A4OoJppvFvhXKtNqnkddnkqO8\n1aUUxJXLNaY1la2rp6nJsRm6q6ra7XavXr3abrd2v0s7Wde1v+0WP3G4MaBgMAhcNO5qTqiSh/JI\n6edgJ6icYPIRmyYn2TiQCdIOxbIQKYtpjooVCw7R2O/UvLQu6A9Mtt+nFn1FmmvBWla2Pzv6LEoJ\nBBPohFxQQ2ujTgSpoS46Erwsy6qqmqb5W3/rb33yySdurV+34F2wDcBojBEj5T9baYo//0ntygiH\nsMGt7JTs2DxtqKtkqNQwXqoL6ghk1YnSSTkcbC/ctn+/BV2gPe1kvLWYxn6nw1npYxR/AhPqof5Q\nlw+d1U+3Y4fQU+XUiZwsQLCwwBIx3dntdsaYsix/6qd+yi2CezqdvvzlL9ulgrfbrVs22PmrjDE2\naGboAb4ELxfGGftDY6QmacZQixab5w93+q2QeFDOSegmZgevhEB7sR/pUSABejLZa+FfhUCdaIy7\nj2x5ul+jP2K9oM2Tb1qlEGkdYm49k/ouCIezf4maKjTXYjF6+gMB4XUevOz1734nGmKjeIJBeoiJ\niKGuzZMLsNVp7Ahjl+zOSDM+/6uffNFiM49ZXRQIr1wkXN/sixaPJ6RkcRO8dOVjDffO0BiHkOqP\nfJn8Mux+jYrSHELf36bTfc/dzKxNuaca47E/nGT7nQ6nxRxZrsVshVRMIpzfpbs0RGSw+oDulIVU\n7Fi2naxxpZSR2y/X5fZTv1SsX7GKgsLm+Z0zByFljPne9773ne9856KFCISXzN/+23/7G9/4hrJw\ndiE1l/QH8lDCRQ80XBlOHLReFHmQi71ZfeODvo9pRUJr3bamC9R4rFP0THa6z5UXghZTDnmPdi2m\nQjhtwz1vrIbrMxZ27r5OsPLqLRahropVhOfx+HRVRTYRwKBVAMfgs/ZaX0L0NdD6XvHjolhHVGAh\n7UUFkomNlPnjaNnfzX0M0uY5m2wv+tcYoB/6zM7ViKTgjzv20W7o9YHvxaHawimPwH6rQWGn85mx\nTY05rljLzkLgo2KdT2zjZc1HD7+Wu+nigfAakwGH9gaC/j6+1l/MM4SVrQF0PEs5ohQYN+SWo+O8\nafpD04sAWmmCcWGY23T8+1JeCLmYUJHcPPlCKLuQHfxKmg3zGtqbZ4zUpTOfocYrj5ECV4lGyCZ7\nVkbTxMqKFlwcelfjsbr8/QlnTPmLIvmHx8X9PoGQmg0DCqnT6WRTbhpjiqJYLpddM5sbaKkpGEh4\npV3fq42RApcCvbc0e5KND4SyorRRPDbYSC6W0HHlaU++Opeloow6Emjm0Gjxi2M4RWszmy+XS5uW\n0+7c7/evX7/e7/er1epwOLhtl5DTJT6wSRCQjXMSBh1qdPppqusLIQUAAHPhoiXUoLjM5sfjsSiK\nu7u7p6en5XKJzOZgcrDWHgAAgLnjMpv//u///m63s6LKILM5mAHwSAEAAJg7LrP5X/krf8WKqt1u\nN3lmc8x0m5Yrz2yOyHQAwJVBc1f2MdJqp3+8VBCuNM7DeG4JOecza6/Tax6SS8mVz9qbJCkOGBrl\njPe0ifHKvAb9Z91rKqJmlbd0p1MUGNf3Qn8SaCqs5F7kOkWXS09xEyRnGlpIGS7N5tDMTUiZC8xs\nDkdXV24is7mQVYjuv+Kn8KXDZlV1mVHp25Tm3RYm1SvTpaYZ71pRrGtdjad1Sq9yOh2ur0V/itz2\nrf3Z+tKEPVuCfFlg0WIg0kkYdZrgBsk1BGMIKfbNd46sUwHmTODVyHsgLaPPltmpVWkVKe0LqURp\nyeTbXt/ltCqUpygodjt/xb5jKaYnZHW1eL7en2yKtRY72QuSXpwtKdSruYzs4WAS9Nqoa/pyqC4l\nEwSbU19C8usZjE+yiqLbIxvvU5H/Y6Cr8YFu7K5+tez2gzPfp65Lh+oJ2WMUaKlWU60eL7lk8G2s\nbXZ/H/eS0GswB+DoGogxYqRiG44zt2IGmDOsr4KG+7gCxrsfgjKtMT2xuBzBeKdesBV1cp7FEpcb\n0t9YknG2U/ouuKPkC9GzF+z4nfBHrezCZcFKnFZN404G64jqaip2VdnQqwVZWY9tADWuUVRsNweN\nkbKZzf0NObO5mVOw+bUybUTXHILNJ1u02MR/vN5gvMWVQcWN/7q1e5IvscZ49i7Exuay1EWry2VW\nU0uf6m7NC9U63BYTH1TNCJbPWLQ4gs1svtls3IZpy2xOp8fbbAgDtvL2mNDRNZPrO5SQkp/OdDgG\nyukiYP0fgVamLhZlDE1stHdBFrxLMK6viK3F9/HoRyepEXqKYk6pTl2IXQjabGUtmlMUFNafostF\n6Jb/lRsjixXzBYfSZtdv2TK0kRpmcjFdZnO3Yfe3ZjbHEjGzYoiIrltfIuZaH7jXSuD1kUffuvo8\nqEspODCXQ0WuSHYOtVZHTxE9Y3S7qy9KeSGUnWq1L7Q8Vtf1oRe6mpKtZW7Dx9eBsiyLomia5h/+\nw3/4l/7SX2qapmkau2ixMcYqJ3+bWsASMWAgkNkcdEOjLXoO2/Uv099In1pY/Ze9ujSR18f+jTPO\n+aBBThfHQBLQZTZ/eHiwG8vlUpPZHIChGTDYHAAAwK0xaLB5V9glRIaIoUnwciFUqz9p1/eSMpsD\nAAC4NWYlpMxcZ+1BeOViDrP2IKQAAABkY25CylzgEjEUCC+Z61wihjblRtLMXD3BlY3FL8dm8LGF\n04xT+8m/CmIWlO3JaFzfi6Fr0fS9/4UYAj8TUrAn2D9EvWcumRPbvNaW9I+XGqfjII3F4/MH4710\nebqqoq5JzBOqAI4B0x8IqXfyZp254unWc2PQdEGdZuaf8621FyRTCKR/11tLMN5azHVKr3Lkw5WN\nabUvlAkuhL4Lw3GOpwI3Q86GO8eTajo0yZmyN+ks5lIHIxBoJocTT4vHxeJxIWupTkB4jcngmc3N\nc1El5OmJpa7xoT98Y9vKToEElHmD2LQISokgGKf3T9e5/dQOtSDcjXqt1qrJgr6cnyea6tQF4XBl\nYzS9YFM2CD+ZpsJ3SrHbjjOfm5v/GBzIlmTlFPWNOYkTa62yulhJB62F1iU0I3bSxGbPa2hv8hgp\nq6KsSHLbVDblFVJDM5+hxjnESM0l/YH+p7PwO3jQFgJL8nnWOzk6oc9vFKuo1ULX2yzNKdWVTg68\nhEq7Nu9Cf8kEvaSdln1L5p2MUDp7qHPIV12CfOnUMKqlYu1n69VcefbwETidTqvV6nQ6FUWhWSJm\nJpmvfYVE9RPdOX9m4vGayfUdQ0jREBnZF5X2goGWGgfnnuk5fMO+dPXGk/VBrKKYWyUY+DOeYyam\nGwLjsU75+xN6QQ/X9FTouNyL1vYEJ2omWkp2wwS+qJiDRzDCIheQB9qoNMnVsCB4K+Zn6jPsOPTg\nqV0ZZrVaPT09vXz5UrNEjJk0s7k/oue26cYtMKjwuvLM5rGBvAQLllZPFZgzad4j1ggdhvMH6bqS\nZiGjVkgbncxYdUZrM/lL1EQstR6eqyu+/+l87itWujZMeYX9cUm5okmusFsZpigKY4xVUUaxRIxj\n5MzmD+bBvBvFk2OkXIGgmLUg21cWBoPyhYHsut/u/kfj/YCO/QpPGxbp6Z8AShbvMM/f/e7f4LJ2\n8rXIxg1383Stgq2ItpnaPL/DtCkPapx+FDqb1oWgtbFa2KOU9uUL7R+o78VAOH+P/9Fu+K0LWsp+\nZE9S7EBXb9AAejj9KnBB+VUnN8yQU0GLtX4lizD5HOalLMuqquzKMGVZutzlblmYYHsOBAN27uP5\n/hxIKL+M+1bQRk6laQqDoUEeKdCNxZCjNhrjGh2QpSJ9MfmomJFFvxmC1CxbkbIxGvuaYoPeHhpm\nIOTA52+K7MHmdtjOSqXdbleW5e/93u995StfOZ1OT09PLoLq6enJlh8zszmVMtYdpTfiT+Jj9zsu\nPVY9F8hsDgAAmYGQmgEDCqkEBpq1xyokf2oeu99pHdeqB/MQfBuEn9uPD+bBb7kt7CpipwHeCJc6\na28O3nsAABidLxljjPkDY/5gsCrsM/k/DWb/5ri/v++f2Twmm2g6A3+PK0YtuMY8PD6wtTiDzlRr\naNfkiR4mwXazU2bz7Mwl/QEAAMyefz98FZBQs4N1EfkBT0F5NsEBW5LiNFkQPuWCot5+fHzwFZvd\ndsrprRPrnURThk/diPAaghQhhaE9AAAALNc0ZMFqIOciCqbasXkNNINutkAgnlifFnWM0RZS2edG\nDwWQ2bwP6TFSwV9Lp0wznVIE9ZnQHhgJJmppYnVba1GmcOwTVgwAAJeC//S76BipYNgu+Jc9JBjj\no6FRQkWsKf9j0CTB4Ahx6Mhs/uyQNCFF50XrpwLJhZMta+wIQiqtrtg8KbcdqwtCCgBwlQwqpE6n\n03q99tOXd81sbhTvWjm8iUKLxfxDSmJ+KValBS1hZd/kcegDCa+ZzNrLEGzuZ8eJwabpo81lLRtO\nw8VqYe0IO/2v2ETPsaNo24I2xGp3ZqGlAABAj81sXpaln75ck9k8DPQ20os28PqwmoY9xC/Giio9\nrP8plhKdKip25HFakNm8nZi+iakNdo9sWSPX+hO4rDTVsX2fT35nAAC4Alxm8yB9eWtmcxozZMOG\n7Ec2Pzibz4mdjuebstCEUn1e7Wy+KLm8a5vhtBfydg5B/ll7giMnr7wYVKwku4taPVgAAAC6UpZl\nURRN0/zhH/6hMcZJJZfNfLVa+dv+sVQY+XoiiMsOSsaSZI7Ag3l4MA9UwBnOCxXADvkZr+NQVBnJ\nI6SSJUKrvJiD8IIGAgCAadntduadnKqqqq7r7XZ7Op2+/OUvu49N07htaiFQJDR4iA6iGU6s9Ik6\n6jrCZUchhcl65rnXKib70qbyzR82Rmp8egWbsyQsHEaDvpVHsWNqMTtC+WBEryfK4CrESAEAro+5\nzdpj47LlkO2gDLtNP7bS6TVP85izG7HGm+eB536PApuXzgXP2vP3yOHV8mw1OX1A/5lueskSxJt3\nrTqYqccW8M8bVBQA4CqZoZAynKpgYQsE+iP2VUYCccBGbvljczH10Dq5L2Obp6VTZvNZzNpzyNXQ\nbzV7upaU0R/lu6OCozRGWstARQEAwPgIiS7dHkPmuMWkxjjiIxBG9+ZemAkoT3BzvWC7KRzF7r8m\n7ZURLBHzOePoG6goAAAw79IZbDaboigGreh3Pvqd73znOzZwOwgnkjXWfBAUjDCY5SswP3+6/ZZ6\ntizOAcZOeISWokBIAQAAGJuqqk6n02q1Oh6Pr1+/HqHGwDVFkz+ZaxzzCmRQ8BUbdf7w+BDITRPP\nYmVV140vF9MrRgoAAADw0cRIlWVZlmXTNDbz09PTU6vZuq5Pp9NyubRJENzUvLquq6oyxmw2G3/b\nHagMRu4ZSH4p+IFisRVsYsFkrI/KdM+kkFd1zSHYfCiPlCZreaxkn0rlqXz61hrS4FY7ghFITwCm\nIvg77vO3aE35Fqhxf09rXdQg/VZvbQgLA2ETPlkVpWS5XO52u/1+X9f1brcry9Lut9nMD4dDXdf+\ntk0lRafHPz4+su/aLBnJLwth0iI7xEnFpT1pnYRRp5TlrZb113dQhhJSQq5zQ+a4pSUdoHPrfIPy\ncjGtrVUuFCMbie0EMYQUG7FrTT9OjqYXsdWQgmLKWujHLLUISydl6cIIuBbZ5iwWZrFo0RNCgUAn\n+XuCDVpSabBPy2P2XS0JFgaik4RyhxyPx6Zpnp6eXr586ZxY1lRRFC6zud32l4gxxtj3q7yEyNUr\nJ4ewAA4bjO/7qGKqS3n29CpHL7muZIkYAeol0mw7ZHXiBFPM8RPU3mk1Pd+gsEANawQr6yWgVJzs\nkkHu4+Tnub9u7qSi/I+dTkKnE9XV/uRXISBojq9RAgeSExwaOwLOAnVQsbUHskmoMdZ4uZG0a/7h\nQsPYWoTySqxHqivb7Xa/3x+Px88++2y/39vxO01mc4t7xU6VtnEm0LE8GhEVlHffCuN9t7wKzZTB\n5mwaTEF1UYTntTtQfu+ylcZMKTsCF1QagueDlcjCxwlR9iLY37X9Skdpn1oGNT4V8iu/jzLQENjv\nVIWvXeTDqduJLcma0jdM0xKBuq6NMUVR+MFMMsfjcbVa2XX0nPOpU2ZzYMRlZwwXgG9VEZ3wGMSe\nBznTWS3FLmuoaXCn/ZMwYLC57L/xE3yziordE+yPpQYNPFXUVOyjYJB2gR4bC6uag6fkIoiNHwVn\n74KG9vw9MTmYFi8o3IHs6epUi29Qtt+nCyPg3vfBHgsdmKP7/UPcSBlbhftqsfj8Y6v9xfNxQGec\ntjyoS+gF21+2U0LVwVE+Qr/M83tATsh5OBz+5b/8l3/wB3/w6aefxsr0hF1CZIgYmgQv17Qz3eT0\npJr86Z1yptME8UFdsUb6FdGpAGnXd16ZzVvLxx7BXYWUHHFluKc5/SqjkIodK+yfyXvlIghuFfP8\nlkt2Uo6M3AtaJrZHU0uALKTYtrEFqFlNg7t2YVBiwiKmRYKP7P5BhZRrrUYSxVobHMWKs9bzoHHL\n9RFSVVUtl8tXr15tt1u7jt5AJMzqGoHJhVcQaS6IFc3hFrfn+9/8flmWx+OxKAo7S4BWJ9cSSLTY\n1EIzj1l7QwmpBD+/RlqxRxnxxdCpJfoXtt7grN4rFwHV3Oy3shSeHLkXrkyr6OlUC3tsQi2dhFTP\nLgyN8Hes0QqxA1uNJxMzrm8ttcC61pSmOvXxfO7gkfrwww/X63XTNIMKKWPM9773ve985zszkVBp\nZBdegovIofQVyUZazbIiyTcec4b5R13wEjECaY9RGkSitHP2wmCDQ5If6PLLKcEUkBHGT2kB4atp\nkXvBKn72qGlrCZy79kB3OKtlu3ZhNHwvUezbnsYHgra8a3VBef+j3tRwffzkk09MauD5rdFVBbZO\nefODpSydJi362SJcznQjephoKnmhUnlJ5rkloJ9pZvOEB7HGfTVOS3zm84KfP3QMVNDEQcn5DJ7K\nvRC2O3UhKB/I/Vy1uMNjfrWexocm+OO73L/Fy215jKZpDoeDTchZ17VVVCAjGuF1bz4v0ym9kyWW\nM711NJCu+sfKLzY1g79/PklTkdkcAABANpRDe8fj8R//439sjPnjP/7jf/AP/kGr2aqqbFjVZrOx\n2Tht/E3TNGVZLpdLO0rott2B84yRunQShhr9eXY0UF0z1BjgjPiWLyZGCgAAAJBpDTY/HA42+ZNm\nrT2bHepwOBRFUVWVC6u6u7t7/fr1fr/fbrc2s7ndjmU2N9BSU+ALL6d7Yq4mx7P9D+fzOVziJm3h\nv1nESMEjBQAAgEX5k9v6k4w6y/lqtTqdTnY1vaIo7u7unp6elsulPdzml/K3EzKbg+HwxY0dUvQ1\nELuA9LP9Dza6wPjZo/QprIZmpjFSYGTmFt0CALh6ui4Us9lsbL7N3W53Op2qqrLDeQaZzS+WwKtE\nF/J765R6MA8Pj+adjpJzrI9PipDqM8PIxCdRx6zR3zdypQnz7GI/oRKMxA7pmm6nNT8Qm6CrK8Gc\nrGCuVlcLkGIAAD1uvTwNLrN5URRlWdrRPWQ2v2iE1J3P9izCAnaSoBCoPjKJweZ90gZ2FVKmo2hI\ne6nHshMlWFB+qxdS8hlLFjH6XEGyETlVEgDgpuiUR2q32zVN48eG5wWZzeeMsIrf59FRD3biMHOU\nX8xtPJiHi8lsHkuY6e9hUwHJR9HD/arZBAdBLdRUYJNWLVQR6wI9UEbusuGuHPX0xKRVzI6m2fTk\nCBdX6BScUgAAi1JIWdeRjXkaNP3BPGft3bLwCl8sD92Snn9up2N5x9yFlI/wLhfkl7+TVi0Q6ABl\nk2Q9pLTWqjn0xwaXIyakBDutbQ4ss9dCY43VcBBSANw4eo/Ufr+3keOdxvgS+DyzefA0u5zn1RUI\nL//cn/11jTwBFPil3vziH6//bDQAaf8//cHh9KP+HuUA3yxm7XVFr6ha7dgNfUiTrAP6N4kemCYu\nh0BQjUKxVp+fYAoAAJTYeKY3b96cTqeRqnSvbvdxEUl4Pz+yZzbvX0UnPpdNJFO/nyT97f77sy2/\nFltUfOmH3MBfpyVisjOIkOopF5SHa4q1DnUlNKmTKX3hjL3uRKsbDwAAsmNDwsuyPJ1Om81mpFp9\n2XROXWrxEpih8KKSlR2MWSzM4sEYY4r/4QfG/JeCweJP/1CnBgxHr1l7sbdvsD/2sevhC7IqiHCU\nbDP2raap1JTwbWsjhbPBdry1hTSUqlUnCd6mWASV3CkAAJApisKlMBi0olAfWJeIe2oFbqpbZXjh\ndW/enWz2jeE8Ve7iFF9q0UmrP/kF1xgzabbVQZaIoYqHPaTrflpmoZ6xr7HZWh1br2C8UyPTet1q\nRzgkiHBiA8Zp4/tcNQDA1aOPkeqEv0SMMcb5seQlYt6+XB8eeKP2kQUtNTyBfH0WIxX56ul/+cPd\nX/iibPbx8fHh4d68u3pKLXUZMVJB9bHWdN1Py/gl5aN6vuPd4bRewXinRqb1utWOcEgwXskWo42H\nigIAjM9yubSLwBhjrCvLCqn9fm+XhbELyLjtzzObWxXFDuTZd/hVj/HNB185BQ5B410ft+cP/h9P\nrS4vq6I849Nkrkdm85sml/qBigIADIq/RMx6va6qyu5vXSLGGM7b5L+3z2eDdOeD4bSOxekkm6nc\nFmAF7cPDvSvTatnps5jzcVAgpAAAAFwAdomYsiyLomiapmma5XKpXSImNqrkfwXeEagfvaAJCrtx\nt+cK6TEob7WUjz2kVUu5sdlgfHBkIKQAAADMHbdEjI1/srFQHZaICWbeEx9INI7KqMKnriDPk4Om\niXh4uI+dA7nww0OY7GCxYDpud7DBUsJZmsT5xDJIsHlQ3h0VxDIjhSMAYFroT9jggRQ4L3o+rujP\n7oTDcz0y/TeW4Vw2hnQ8OCRidpBg83Toq16AXulhQtHnLLxodi26R1nY10buFpJNBfeeeKd1aKfP\nZQSb06YsFgs20yNmzgMfetv4H2kxw4XMgyxoroXyes0cOtSj/zatLhKfw0O/zTt4EVjz31t0e4gG\njEQQ3myei6Sge8GG6dXn2HHns7m/ZwazBMZPsKkRzUJhGk6upFU/BfUqFfKgDDu0F5vhZYiKYtNd\nBmXwyrxu2BRZ9qLHZgUGCeUxeTAXwt+mnwrE38mWmT9UqViEt4heVQjnQI7PCZQWLUMFEFtjzHjs\nK5bYGzHmwZoh3/ud33m7RIwM29XULsV8mb6oC3YKVU2YYLOTQPHvanpjtJpyI66awoJCHpmRYqSE\nJ69yPy12KU9qoIRdi4Yycy+m0DzawTnfw7S1Mz/zGRE66r8hkv00QuEEy7ECrftbJRrdf53x2YP5\n2VgPF/12iCb0E16ht8y8u+J+6LergrrW2EE3922MBGHkCky7RMxQMVJs/FMgjPxk2ULK8iCnNps3\nElwH1BkZu9ytEXhTwTpcA+bT2lYC/5PhYhxZt/H8u+YT+AwMURuxKCL6/mt1z7C/0WMGY6NvQu1s\nXYI1/6gFiW6hbab3NRn7+/xWmUOMVOCYeaYw/P6zHqQerraYN9GQ62ie32ZzQL7KPnbOHS0zWu+k\n6xvhYmKkKPLPWV8qOaiPClw3QkQdLXlBN8Zltdbh2hz4pS5LJCWQ61rFXh4J54/+WG+tcYQ7jrZq\nuEpdZnObUKooig6Zzd+9XK3f5fN3rdCBoCdUaxO69v0iHgmsNvLvsSD3gYNK0CFivFqu71gMJaSo\nBgpG6NwG+7Cme4RiAIDsUIfThcrBVvxXZywiin2r+sR+r9MXD1uR/PoO9scKtyL3wm8b3RYOGWxk\n7Bkus/lqtXp6enr58qU2s/n9vTHGvl/v70nma0EbUfdd3K8Su9BBPcF+t3P+f1gLb/KB4/NL/+n/\nbn7mTxsivNyxpuNoY6cYLyenmOs7CgN6pPxF3Pw9eqiDKlfbwAyRZbch90Os2BxgA+djH2dIzBcl\n7GQ/XgT0udLpSRO8V+jh9G2aXFcnulqmHdHbYUdF8+IymxdFYYyxKsooM5sbYzyPiPJde2+YUb/4\nsfeBbgig4omWtB/lFJSOTjkzu/O5cRoY5xS26/LD//irD+bzBOWGqMOHh2tOHT/40B7UD1ASRMsJ\nQlwuNi1pWdbmhn5FRRrgOJMLoSTvdYhZm/fVvhhsZnNjTFmWLuWmNrN5T3QxPmyEkIksh2LIjXF+\nl847MEtFkr9Sr3k3xJZbS721zP4wCKSVrT1IUD5Ee+ZJSrA5AAAAIJM32NxmNjfG1HVd17UxZrfb\nlWX5e7/3e1/5yldOp9PT09PpdLKOq6enJ3sUjaEx+jGmxYJ6pIShvVjs/2LBrJrCFgtqc5YN5+Zs\n3ZOMrXH3//6Dp//mT8SkIcv4v6HSrm/2YHMIKQAAAPm5gFl7Mr6EoYE/XFlXJNAf9CDXKregiqDW\nrBSzLWeVTd5pcdbs6//1j7Z//r9we1iZGJyhSZzRc5i1N+ASMQAAAG6NuaU/MMZ873vfUyXkpLAu\npray1MMkR7TTYT4/P8K78b5HE1kD2JhnZRzJk9es8c+a/1x86YdoI/2NgZRcAp3ySF1w+oMZcnHx\nHAAAAMbDviCOR2PlYJtfyiJEQQnlgz3Bv36upqCBLqzbV079M5s7FeU3krrnptVPMyFFSLGTp9iv\nui5UzI4eyuusdWq5s+DP9mJDmPUWIMUAAOAqefe22Rqz9fefiXywJYv/4Qef/d/+y0WX9Ny+EorF\nIQXyxS8Tk3Zpmc39+C3fxfXwYIJActNdL14xiUN7voYQ8pL3EVKalNYJIiam1TqpIj/dM4QUAAA4\n5ja0lxBDwwY8xaK/u4z+tVSqjEOKxW71bInc64BAdRnFHL2B8mRecIwUu3yHkOaH7mebSz09MRdX\nzI7s04rlGKQ9EqzRxkBLAQCAZSAh5TKbr9drP31518zmpu1dS4O+hSlyrCcp7YWgjEPyq1i8m153\n+Ok/EVQtyyChAQPFjydkkUrLbK45cF4xUrKK0hwbQNsdqJlY9vPkxWRiPjDNEiVd6wIAAJCGy2zu\npzJfrVaazObe4/zeGBN7zwoRUIJOirmIEhDikALL/rfVv/+Rw/OGBYOAc3hZ9VtEub2wuabM5oJP\naJzsCeyCfa3FYlFfseX/sjUXAACAApfZPEhf3prZnI7ELcgEN0MmxFHtEvDuhc3og7R3uRCHFCn/\naIx5fDRBYJNF6G98SI6JZ7/mfOT56CWk+i8qrNcleRXMglsjGQAAwGyxmc2D9OWazOa+MogFdBvO\no2M4h5MQD94TVt4Fo4eBv4pVUcZTYEF/5ZTorNMLtNJr1h4NJ4otvKXcH3wVi2GX7QRhT629cEfR\nr87nc8waRBgAAIyGzWxuA6Gqqqrrervdnk6nL3/5y+6j/xW14AsROtL08PB5GcPJpuCR7xRMJ/HR\ndYTLFmcVkjX18MAMKQYzAc3z8U0qKwMf1fOSg0SI54KNkRqfzAk5Y7PYuu5niwmF2QW/YkuDuS7E\nshh0soZgKQAAcMxt1p4/OrbwslzSYjFiE/TkwpROr3lfcsXi0I3XI9oGGgjv+k4DsLLEy0/CHGbt\n5Y+RyrKfLSYUDr4Sygfz8thiSmtQUQAAMH8CLRV8FRCoEPnbTuJD744iodbMUsd+kFYwx9AV9j1q\nghx0X/WPlx8fe1Y7ZTbPzi1mNs+lfqCiAABg5gR6wkIFEB3CUz7ghxAfgeS6vw+74AbdHh74uX7P\n46Le5nzSD1yCTnxh6gYAAAAAA/I7v/M9GsftYrEN0VVOl8iMKT5cq4K2+ZLI+cncf5/8f//YvAvn\nCgKtBL+USVph5pa5RY8UAACAGyQIMLLQgCEBfzacmYcjR9B8m5/6Ebbw22Z/+r+bn/nThmgsY4xN\nyKTXUgNlLb8UBhRSPdfdA+BCYVP2G3Krs8lgabGpCNrDNm/mXdAg/y53Bc5tK2akVdfVWpY20MYE\nmiAWjEwPGZOqqk6nU1EULuuBJrO5iYR4pw3k+aOE7IDa3KANe35l/3TsK9MroquFvKrLVa1Maz4E\nQwkp+hTWLyADwOWScEsHKfXnMImBTfYhNG+GXdATm7ik+TatrvP52cs4Bv02Sxti1vyAZbo9RAO6\n8vT09PLly/V6vdvtDoeDVUtyZnP/5WoTHFDSJuVxQUtzhEbHC+IvrRedtEteRxdNf/D4+Di+lhp2\naC+W8sAQFcWucEdX1rvEn7xAiSBB6DJEs70BaFPlFGjzRLPu08y7oIQqFYvgqNCrCuEm9bWU/C1b\nCxVAbI3Cy1J/9WLxyDEP1kAURWGM2Ww22+321atXLlNUa2Zz+1p9fHx0c9/8pibrobk+gRhi11qY\ngTgcQzi6rm2JmBj+c5nmQ9fsp8Vm+yoFfWD9lDFtPU+Ee9jh/0XMs0fK5Sbn3IVkhN74b51kP41Q\nOMFyrEDr/laJRvfL+m9oyrLcbrfH4/GTTz45HOz6cqrM5hY7eY3VhS4U/eoCrMPkCOZ53oTgOiLA\nPI0pg81jKZ3Yh/JFvEFBdi7xutPhbKc2aIqy2fZOGJQPis22C8nohRGdWt/pWNPRH8AOxikLK2th\nfXJzuMLH47Gu67Isf/Inf7JpGut86pTZ3HBrsFw9ciwX3BFZyJzZPCgcW3fF/5kefPSNsMN8bC5y\ncAWwt0Hs4/yvfuz3gFBshr3TNG/mXdDg1Iz/0cKGlQiBU1Tr0Lr8nYGdmFSKBYALr0b2q5hx2rYF\nl8RSp+Q+f2hPntmcXUJkiBiaBF/OOKE89P7098c+Xgpp1zd7ZvOhhJQhL5Lsv1wv60kNWul0e8z2\n6scCuYTfDLGBvwmRm0eZYRf0UN2jvxOpplGKm04Bzp1IsByTiSYqlcLDn5eZkZAySUuIjMAchFdM\nY10Wc1giZkAh5Y5KfqRe7qMZDMf8HR7Ke54Wm1Xkn6Z5M+/CyCwiU/Bi+68V/00xByFljPne9773\nne98ZyYSKo05CK8502mJmLmvtUe52acquFk6rSCZcOA4aJo38y5oyOsQ6hr3DYCSrqooITX5TQmv\nvKQIqaliS68vphUkg5sBAABiQHiNScrQHgAAACAzk6G9ecZIXTrzGWq8iRipm+WWg0UAADfLQDFS\nbomYzWZTlqUxpiiK5XIpLxEz2qw9IDOQ8JrJrL30GCnl7O6gvD51ggy7ilmrdhkhet2fnOW3R6+r\nguld2VsIAACXiF0iZrlcVlW12+3sTnmJGPP8tTpV5msw6FDjpWY2D+RLzhZxKaPcdp8cCoO22a8i\nSGyd1uarzHMIAABpuCVijsdjURR3d3dPT0/L5bJ1iRiL/36FlgJ5+ULCMYJfZ/EO9qO+jKYNwVG+\niIl9S9u8iBB8JXwMqvDPBpt9UcAQKQYtBQAAFrtETNM0u91uvV5XVWW8JWKCbQBGI0/6A2F9tGAF\nvcVzV5MsFAQl1KklsZKaYmztyir8YkIC955tAwCAq8ctEfNzP/dzZVna0T3NEjGPj4920McgRurq\nYGOkxqfXrD26Agy7kItwYCA1NNWxZoWc0YG1mI5pTTYdIxatFbPP9p32znAuLgAAmDn+wxaz9sDQ\nzGHWXh6PVM8RKEG1JIc0yTZlkadUVLGvFv1iuQAAAOTi/v7+CjKbgxj2snbKbJ6dFCElDMzR4J6Y\n1BA+aohZiNWrHEzs1Db9V9R155okjIoCAAAAYOYkeqT0Y08Lbtp/sJMtExuk65REoLXNNDbcHegL\nHfbYoAoXDebboV2IdZa2hy0JAAAAgPnQa2hP85pny7ASRyiWoCdabWoOdIqKPVYWf8GxGvs+UFEA\nAADA/ElJfwAEcqkfqCgAAHBUVbXf70+nk/3oNpqmOZ1ONte5vw3AaEBIAQAAuACenp4Oh4Mx5nQ6\n2SRSxpj9fm8Xjanr2t+etKXgtsgzaw8AAAAYDpfZvKoql43TGKPMbP6v//W/RkLzK+Y//If/MGHt\nEFIAAAAuAJvZ3C4R0zRN0zR20WJjjFVO/rZ/4HvvvWddWeBa+eIXvzhh7QMKKSEFQLI1OcEmm2Wg\nf9XAJzjbsdxlsVxcylWlaf6wWAoJoVjPXqR1IcF4YF/Zi64XQi7WvxedTtF8oJlGgrbbAufz5xsZ\nq+tqLUsbaGOsQf8j3aZlRsZlNt/tdsvlsizL5XKpyWxuee+998ZuMbgZUjKbJz/lExIlCAX8j6zM\nosnEQU+EBFfC+1t5OQRtQV/ebFbVripK7kVCFxKMB1XIxuVaYtnzYzlmu/YiZt90PEWzYrF4phXs\nR7aMv5GrRiMqErkxWQiUmW9c2DYtzZ5XZnMAArJnNh822JzNIEUx3mK9sQJpdV3K0/yCOJ/Pfj6I\nWO6G/saVRtLqau1Fchc0xt1+l/8iobqY5Vy02u9ziuZD0EVfLtj/KP5Xbpv9T1Nv7MDg38AmLczW\nKLSqtYW+EfYQTQNmRdM0+iB0W1IoX9e1HUl00VpCvfpK9TZb+9Kpv0bRzrquq6rSd8cuidhq01Yt\nmLWnZc4TCEaatWcfyrEnb/YRAf9lDC2VEZoEK+a66KqHqHGlkYS6NL1I64LSuMO/8ztVR2vJi8Z+\n8imaP0JvsoxzCZpDGGWTm9Rpv+BVEjSZea7/Lo7lcnk8HpWFW0uWZXk8HpumaY2+Oh6PyowMepua\nvnTqr1G083Q6BcFnAvv93kb9yzbLstzv91VV2YkCsYbZYdzZJraYOP2B5hnd0/KVPeLnQDBOJGgR\n2QjrbqRjXpomJdwtml6kdUFpnNK1F1nubWUvYlzlDxV9nwLd0/VYV1h5VMx/pimsrMW2yi95jVdY\ni+BQsbHtNLA9wDpaXNYrGaXNIdC0c7vd7vf7Tp6h1Wolq5/VarVerzXnZ7vdtvq3pmI8IZUxkKW1\nzGVFaVwWbNhNAoHPKa/xVrJUxHahq/Hku3TQC5HR/iWSq8eC26nrZaeKrbXGEa4bbdWcb5ZODhVj\nTNM0m80m9m1d1zYXg2zERcdrRIDSptH1pVN/Ne08Ho+bzUYppIqisEN7NPDfp67r9Xrd2s6yLE+n\nk2xqQoYKNjfcj/ssT+SYq+nMRR+zB4Jk5CE2ObTZ35NgXC4gW+5UEeta03uqlKfIPJf7wRmT2y/X\nIjSbFuhjX67rgv7cqD9J3/sgUN3fCIoFdQ03RpZgWRhP1IwtkjIINgezJnuw+YDpD9wbwrUm77NV\nsE+/Allg/Rbs+af7Wy+HbDwosHg+Z7PThVb2IqELeuN0u1Mv2JLUAtvstF6wB6adolkRqISussYP\nxBYsxEKOhiDBsnASNNbm7IUCYAQGH9ob+qkq2L+sB/qFIkS5KUsmGDdxRZIGayFLF/RHDdQLuj+5\nIs0JwR8dAODWQGZzAMDtAuGXHTiowK2BRYsBAAAAABKBkAIAAAAASGSooT0a9z7apJ6uE6BAJ4Ir\ny05wkCdsaiaLyXPZYrMC+0xBpSkzND2dsBdsLbEsBv17wVbR/0IMROvkuIEaSGfwCW3zG0MbHLPM\nftRUIdPagFjhTgcCcJUM5ZES4l7HCT+f/FF+lfgvzlgWRxnllHul7GYTCrQiVBTsd2b1tYzTC00X\nBuoFS9qFGI7YXXbunsAprV5NLbSMvm1ySfvtmaTWTDAopMJSNgaAq2fwYHM7HZp9LgvZhuivZ3ab\nLRmrBdIqC3IOJL+M4a6+3rgscXoStDzvi3+cXgh/I1loPUWTqyUNi+crBJt3yiDIHSWkkgo++rAl\n/VrYb89tmZmEHE4JnrbFgmmn0DtaTEjoQP/FUxbcIHOJkQoeyoG3Q/7NPaufwtcNTTrQ6g4xz92Q\nQvnAeOwopTUBmsAp2NmHcXqRN/tDq332FPW/EDOBipWYfKEH+uqh6zlgNRCraQKUrqzF8yWKY2aV\nAihwtvnuLogncOOMIaTkAQ5Nkhv9TuW3oA+sIGh9lQZXZPEOwTg9qnW/Hqrd6c5WC7HxzXF6kUW+\n6HvBnqL5/6EJPpug7cKAYOueTgWCbztdRrbNrBgaehwTAGAZVki5h2zy0zajn+mifzTPB+ecUIbO\nCF/RgLlOxvuQpSK2C7mMt5Krlml7MSidIpZih1MHVRrC4KARJV0f1SWYavWipfX6Ym8WANIZdtYe\nDbAQNjQfNQf6VV/uO2CesCfZIoQb05i2BOOGu5qu0q6eJH9DiOhqvRu79oJVJwm9iP0d+V2Ijbsl\n9KI16C3tQgxHENzDjnApP7IhTbEDY/UKtNoXvl0s3rqdFotnIsk1QxBhQe9am0r7qD8WgOtmKCE1\nqMM/b1AL0MP6LVi/Iw2yab1esnFDXuf+To19oSJ/v//tIscqdewpCs5J117QYuyJYs2m9cLfn+tC\nDEfeJlCN0t++7CjKaLzVbJ8aY7FZANwUWCIG9CL5xd/nKFlGZEQTwNfViLB/zr3QWM5rPJkRXuQz\n1AozbBIAN0KKkJqN934WzQAA3BL/F2OMMf+HMc3EDXnLjxpjjPmPE7cCgBsGHikAANDz21M3IAAS\nCoCJSRFSc/De52UmgR0AAHDpXPFYQVmWZVnudru6rpumWa1Wq9XqeDwaY+q6Lopis9lM3cZoIzeb\nTVVVRVEsl8up22jquj4ej9vtdrVaHQ6H1Wq1Xq+Px+Nut/OLVVW1XC5Xq9VU7VSSbWiPncfOfpVW\nS3ah48STP90p+KqTBUgxAACYBaeTqaps1pZLs9sZY4qiMMZUVVWW5dPT036/f3p6quv66enJvvI7\nWW3++Fz9+/+cq42rH/vC6k9+QWjk4XCwX3VrZNNU787ker3u+dHKTWNMWZZOIW2328PhsFwud7vd\n6XRarVaunXVdW/FnVaDds16v56AFfRI9UrGJ7rkYx35gPDa1u5WLzrUDAADXxulkTqds1t4JqeVy\nuVwui6IoyzIoYp1Anawe/z9/tP+f/iBXG9d/9offfPVPyo1cr9eHw+Hp6alDI4/H/X5vtz/77LOy\nLPt8PBwO3//+940x2+3WSj2rioqiaJrGGFNVlfPqNU1jtdf7779/Op1sj1arlVNj86FXjJRTD4Hi\nYX0z/reyT4v6ovQpamIZeqh9OpWJTSAki6QEPxYAAIBh+eSTIawej8e6ro0xq9XKioA+1nZ/4Yu7\nv/DFTE37nFgjV6tV0zRdJchut/MFYlEUWT6eTifzznkW43Q62bG/qqqaprECq6qq7XbbqQsj0OHd\nL8ummHwxzz1YgiihQkoYLkyAFVIx0ea2O7UZQgoAcOP4j9DXr1/f3d1N2x5wNRyPR+u76ilhf/3X\nf/2DDz6IfSu7hFimWbRYn35m4dFauH9L2MCseSbLAQAAAG4H65TqqaKGILOQyq4w2KzZbHVC1fKy\nJFBFAAAAwMyx0VRTt4IhUUjF1iNjR8HYyO6Ys8c8Hy+Th/Naq279in4b1O6P2bGrfyDMHAAAALhZ\nEoPNY6NdzsETizdvdSwF1kzEKRVU54KZ2APpkm1WAJ3P5+Bw1jjbNoz3AQAAACBzZnNZTLBrfqUN\nyQUFAlOti4vRcPjWoxIEIgAAAACum9tdImbQpVsBAAD823/7b1+/fj11KwB4hs1llZH09AcAAABA\nAN4U4KK5mPQHAAAAAABXAIQUAAAAAEAiA8ZI5V11mE7Ec2ZZR9xACTzBoCgXHeq0NlFyRcm1jNaL\nQRH+4oIyZq5d0ECzlwRttwXO5883MlbX1VqWNtDGWIP+R7pNy7Ty1/7aX/vKV76Sp60AZOKf//N/\n/jf/5t/Ma3MoIUWfsK1T2+QC7LIzbiZdINo0K9KAudEpK5jLYWF3+ikt+lREM2h0rWW0XoxJ0Nqe\np2hu+FqB1VXCt2l1OVN2Owb9NksbYtZc29jthAZ85StfERbiAGAS/uk//afZbQ47a4/NYMkWW4jL\nEmseymxd0FKXBU0DNtDlYz0oueoarReDEvt9cmVQpWIRXC96VSE8t3wtJX/L1kIFEFtjzHjsKxZX\nMjgk5sEC4NYYKUbKpr6MPYizjwjEUnGCOcMmXB2hIuVCQ2nGzVXoj7ynaP4IVyx5nCswEqtCGGWT\nm9RpvzBEaL+NSTcqNAEAEwebxx7Kweutj+UreI3dFMEA7nBapL+7ZfEO2figvRgH5Xjl1aB/9lDv\nTqdjXWHlUTH/maawshbbKr/kDShnAHoxnpDq6nbSPK9lF9ct/HS+MkYLbgsqSqv3/A7Z+NVwO39Q\nua6b4Hbqei6V43F+gRHuPtqq67rlAVAxlJDyY8yD4FM51De2PxZE5bsENNtgtgRX3/f3+LdTUJj9\n2LUiWm9yLXIvgltxzkFI9C8u9sdFj7osYjFA/s5gtIuWjAkj9kAh5ikWh8TW3vVkx4zTttF/hUMu\nQmCfTqdXr16VZXk8Hl++fNlaWPh2v9+/evXKL7xYLPb7fdM0VVXd3d01TWO/sh/Lstzv92VZtrbq\ncDgIf0GHw+HFixdyy4/H42KxOBwOdV2/ePHi5cuXTdMcj8fD4RAY960J/T0ej7YLx+Oxtfbb5awm\n4ZDzu1l1wyHYH7pqMDT6izvQtc5Sy+S9yAXbvMvqAsUY/Jf9v7ecTqepL+9bvvvd7xpj3rx5Yz/u\ndrvz+fz973//u9/9rivjPn722WfL5ZLu/+53v/vZZ5/Zw9frtW/fN+42bMnNZmON2GPlVr1588YY\n4zfMP9Df9nf6vTifz6vVynZws9msVqvz+fz69WvbMN+4s+b3N7BmD3F7ttstPS3+Ie4UWbPf//73\nY42ckG984xtygQSpM/jQ3nngXyuC/aGrBkOjv7gDXesstUzei1ywzbusLoDb5Hg8GmPW67X9+PT0\nVJbl3d3d8Xg8nU7Oi/PixYuqqqqqsr4lt//u7s4WO51Od3d3+nqLojidTi9evDidTkVRtLbKbvgt\n+fDDD5umsZUej8f9fm93Oi+X64Uzu9ls7MeiKOq6tt1x3zrj1poxxvWXWrNetNVqZT/aZRP90+If\n4p8i27bD4WCN0EZeGchsDgC4XVxsNf7L9d9FcDwel8vlarWqqsoKhaenp/V6fTqd7MeiKNz+N2/e\n2MLGmLqu9bVsNps3b96sViurJJRHWUXVNM3hcCiKYr1eH4/HqqqsFDscDqvVarvdbrdbvxd+pXVd\n7/f77XZbFIUtT407Yef6y1qz2PFBK4/80+If4p8iW95WIZi9GiCkAAAAXDObzcZ4kUBN0/zRH/2R\nMWa73To/kExd12VZOu8RW8DfsOX3+/16vX7z5s12u63r2u4UWvWDH/xA05imaZxqob2wEtCW2Ww2\nZVnaipT41mx/67peLpd1XR8OB/YM2EP8U2THNO/u7px40p/qS2TYhJwAAADAtBRF8fr1a+sTsuNc\nv/RLv/Thhx8ul8v1em1f9lboFEWxXC6NMYfDwW5YV1BZllYo1HX90z/909bpYgsYY3a73fF4XK1W\ndV1bJXE8Hq3zxnqVjDGbzcbu/Oyzz2Ktsv9aKVZV1W632+/3x+PR+Zbquv7Wt771sz/7s8vlsiiK\n7XbreuFLHFvevPNO2Z2um/6268XhcKDW1uu1bcN2u22axvfJ2dPiH+Kfol/+5V/++Z//eevtizXy\nmuiQr7JT/gJaOJiMMFwsRZDCZ6BabpbgysbuiuAqKG+e2G2TxXjXXiTXMk4vApt5LwQ1KJ8i+WYY\nH9dp15BgLtRADXSz2ITpbOyMP9rgmGX2o6YKmdYGxApzp/rtrtPpNLclYsqydFIpL03TWB0W7DTG\nVFUlC4jsrfJFnr+dzHDnbXy++c1vfvzxx0KBhOfYUB6pcySJTvDAHa7qWANAH+Sp+7Fg5GDyf+zu\nDIxrbmK98T696FTLaL2glcqH9+mFplK/loQu5OUcSQhuGzXcg+HcZWE+WkZ/zmT7Z2+lPKPrb8zg\nIrIa4Dl1Ab5pGc4jYl1EdKem0uyt8hVPFvVzrZ6kXAw+tEc1DZuBJihDf+Cy22zJWC2T/0q+DtgT\nniuZUGCNtZNFH7f2ok8t4/SC/lSgNnP1YoTfPwOxIGvV0dxIZ7J2r19A0F5sSb8W9ttW2SEIlARP\nm1NCghuJzRR1FlcD9L/y/8VTFtwgcwk2p68E5VvNlbzcZ/0F4YtRmz+j9Sv9FQkssMNhycaFithe\nJNcyWi+ESvvXQg1e8V8WFSsx+UIP9NVD1zPEaiBW0wRQsRIbQ6R6jppVCiBfCBpvtqPmWACumzGE\nVPAIlhPPaHLVCDuV34I+KP1PreFQgVwWjNNi/a+vphdpXYgZH6IXtLqutSh74TTZxSkqwWcTnJjY\neVIKF32B4NtOZ5RtMyuGzpeTjACAi2ZYIeX/vu9jIcuz++JeAPPEj4yhH/Wc3yEYH44svWC7kGyt\nP2l/ZXPrRUYCJ0ra4dRBlYYwOGhESddHdQmmWr1oab2+2JsFgHSGipEKfoJrNjQfNQf6VV/uO2Ce\nsCc5+EiD2JTXIrDmj0nF9LTeeNdeJNci96LnKaIVLbhVLPvXIpyTWMgj+3Eq/KgddkP/kQ1pih0Y\nq1eg1b7w7WLx1u20eB4S7pohiLCgd61NpX3UHwvAdTPgrL2BLBvyigKjoTzn53cTJ/2jFm0zuWLf\nUr9mgnFNRQFptci98A1m7EXs8ORaWAcV62AOrHXqwnDkbQLVKP3ty46ijMZbzfapMRabBcBNgYSc\nYBDY8OqLMD5aLdntK0MJk0cANfvnoKJGeJHPUCvMsEkA3AgXLKRm8tsXADArBn0qOL0yk2dPLg9Z\nRiDpwK1xkUIK+gkAMAlze/bMrT0A3CAXKaQAAADcFKfTabPZVFVVVZVdjtcY0zRNWZY2q7jd8HNw\nPz4++hbu7+/HbjQYmJlc4gHTHyw8Eo7qWa/SPlvY7ezZEgDADLEZDdx/7Lf+hn+I3r6ydr+u1qP6\nVKFpc6cOKluehdPpZNfZXS6X2+3WLcS73+83m01Zlr/4i79oN9xX9hV7/w5DXrrg0pnPJR42/UFy\nEpo+g3dypZomxaapA+PNbw9SErAZoVqLycaNdyOxxczza6S/bTTNS+uCcGAu+/7hNPdBlgvBlqTX\nomcXJiEIcrIiIJg3xyY+YPMUsChL0mL60yZXcb6utfbsor9WSK1Wq9Pp5NSSW8zuW9/6lt2o63q1\nWtlv3cvVvmgfHx9/8zd/c8CGgtHxXVD2Ek/SjGGH9hbPF9pjRYnwzBUe051y4ci1aN4BQtVzfmdk\nR0ggRIudOy5nGxjXnNhA8iqP0vQirQtyL6gESbCvaS2VPhl7MVAXRoa2jkaR++6o4F+jVg/UbOuB\nQhVCI4P9/iFOMlKzwVdssZjAYv8d4rKXZVkURdM0TdPYQT0rqowxTdMYY+q6/sEPfmA3nIryce/X\nN2/e5G8fmA53Zacdtx1qaE+TTdEVEPa7Y+nLr9O8a2H8TmiD8O3M3xPDcT6f/XxC2TMCsA4Pnyw+\nwtF6MZxHc+g7UHMtroDzuV3Z2NPgKyGjc/MoBVPMbOxwZZqoxbWstbfb7dbr9XK5XC6Xx+OxLMv1\nem39UtZTVdf117/+dbvhx0gBMA4DeqTOXiZl+1Cmvhz901lf+BxJ6Mzusa+KhJawYu7qof6VjO/X\nwLjv8KDF3K3Vv6JkO0rjxmvtpdwwymtxNbBaSj9CZzw5ohkNDPZ3OqnBHWRNsWJIL/gugqenJ2PM\ndrv1d1r/U1EU9qPbsLhBPePF0/RviX78COHtgxJc0wlj4Do82TsFQASOKPYR7D+gg1o0z+6YYDq/\ny+ZMTcX6QgcBqSONbdKlvBfzIly14GPsApn47STrJ1qSNd6/F3260GpcaV/TBVYIZrkQscNNl1M0\nQ6jmoJ4hfzjM34ipJd9sbGAuOB9B+WCoTo5Aom2jVSy4RWPk5rW65XwjfoPJsW8/nE6nDz74QDI6\nMNNO6er0XofkSiPhEn/zm9/8+OOPhQIJ7/cBhZT/Uf4tS8dBhvjtG3th09ZqjFyQdyEvgVoNdtIy\n7kDNK1aW3WxhvfFOveijEgY9RUFFglbL2Ivgq4sWUiainPrQyXfltyGQRLRtSpusbPJrjJnt0/f4\nsXMRUpbHx8ePPvrovffem7ohUeDi6oOdQPDVr35VWX4IITXsWnuLyPpcwlHuEL1cS3tks0MwQCaI\nKpPfoMELuFWtBsapZhWcmp1kt6YXaV1QGk8+RbQwe3L61yJfi56naHKo+Oj/AOhqwS8f287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+ "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "im.reset()\n", + "colors = [ \"gray\", \"red\", \"blue\", \"green\" ]\n", + "for i, curve in enumerate(report.curves):\n", + " stroke = colors[i%len(colors)]\n", + " im.draw_circles(curve[\"points\"], radius=3, stroke=stroke, fill=\"white\")\n", + " im.draw_line(curve[\"points\"], stroke=stroke, stroke_width=2)\n", + "im" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__Note:__ Above, you'll notice the zig-zag pattern made by the curve that describes the gridlines. That's because `pdfminer` (and, hence, `pdfplumber`) currently only provide access to a the *points* on a curve, and not the actual *path* of the curve. The actual path can — as with the gridlines — include both \"lineto\" and \"moveto\" commands." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "deletable": true, + "editable": true + }, + "source": [ + "---\n", + "\n", + "---\n", + "\n", + "---" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/pdfs/ag-energy-round-up-2017-02-24.pdf b/examples/pdfs/ag-energy-round-up-2017-02-24.pdf new file mode 100644 index 0000000000000000000000000000000000000000..8d5b488b676d80943f53db60f0f9883a7b674345 GIT binary patch literal 50918 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z0M7})a{}<306ZrE&k4YD0`QywJSPCp3BYp#@SFfVCjie0z;godoB%v0fc`lFcuoMG z6M*Lg;5h+!P5_=0fae6@IRSW10G^Zi+bH`Nz;godoB%v00M7})a{}<306ZrE&k4YD z0`Qyzc+LSl=K!8_0M9vq=N!Ou4&XTl@SFp9&H+5<0G^XMQYJ1p4&XTl@SFp9&H+5< z0G@LI&pCkS9Kdr9;5nI<<dX7Pj`*PC^1| zYQHo3vHoAD@l#h95^#30aB}&Txd>gWuS^#bShPsTKvziMcQzwsA%XuNZKD}FSs#)e bZxW46b7 0: segments = [ - (x0, top, x1, top), # top - (x0, bottom, x1, bottom), # bottom - (x0, top, x0, bottom), # left - (x1, top, x1, bottom), # right + ((x0, top), (x1, top)), # top + ((x0, bottom), (x1, bottom)), # bottom + ((x0, top), (x0, bottom)), # left + ((x1, top), (x1, bottom)), # right ] self.draw_lines( segments, @@ -195,7 +197,12 @@ def draw_circle(self, center_or_obj, (obj["top"] + obj["bottom"]) / 2 ) cx, cy = center - bbox = (cx - radius, cy - radius, cx + radius, cy + radius) + bbox = self.decimalize(( + cx - radius, + cy - radius, + cx + radius, + cy + radius + )) self.draw.ellipse( self._reproject_bbox(bbox), fill, diff --git a/pdfplumber/page.py b/pdfplumber/page.py index c249f7ab..2fa15b7e 100644 --- a/pdfplumber/page.py +++ b/pdfplumber/page.py @@ -21,22 +21,22 @@ def __init__(self, pdf, page_obj, page_number=None, initial_doctop=0): self.initial_doctop = self.decimalize(initial_doctop) cropbox = page_obj.attrs.get("CropBox", page_obj.attrs.get("MediaBox")) - self.cropbox = tuple(map(self.decimalize, cropbox)) + self.cropbox = self.decimalize(cropbox) if self.rotation in [ 90, 270 ]: - self.bbox = tuple(map(self.decimalize, ( + self.bbox = self.decimalize(( min(cropbox[1], cropbox[3]), min(cropbox[0], cropbox[2]), max(cropbox[1], cropbox[3]), max(cropbox[0], cropbox[2]), - ))) + )) else: - self.bbox = tuple(map(self.decimalize, ( + self.bbox = self.decimalize(( min(cropbox[0], cropbox[2]), min(cropbox[1], cropbox[3]), max(cropbox[0], cropbox[2]), max(cropbox[1], cropbox[3]), - ))) + )) def decimalize(self, x): return utils.decimalize(x, self.pdf.precision) @@ -69,11 +69,33 @@ def parse_objects(self): idc = self.initial_doctop pno = self.page_number - def process_object(obj): + def point2coord(pt): + x, y = pt + return ( + d(x), + h - d(y) + ) + + IGNORE = [ + "bbox", + "matrix", + "_text", + "_objs", + "groups", + "stream", + "colorspace", + "imagemask", + "pts", + ] + + NON_DECIMALIZE = [ + "fontname", "name", "upright", + ] - attr = dict((k, d(v)) for k, v in obj.__dict__.items() - if isinstance(v, (float, int, string_types)) - and k[0] != "_") + def process_object(obj): + attr = dict((k, (v if k in NON_DECIMALIZE else d(v))) + for k, v in obj.__dict__.items() + if k not in IGNORE) kind = re.sub(lt_pat, "", obj.__class__.__name__).lower() attr["object_type"] = kind @@ -82,6 +104,9 @@ def process_object(obj): if hasattr(obj, "get_text"): attr["text"] = obj.get_text() + if kind == "curve": + attr["points"] = list(map(point2coord, obj.pts)) + if attr.get("y0") != None: attr["top"] = h - attr["y1"] attr["bottom"] = h - attr["y0"] @@ -145,7 +170,7 @@ def objects(self): return self._objects cropped = CroppedPage(self) - cropped.bbox = tuple(map(self.decimalize, bbox)) + cropped.bbox = self.decimalize(bbox) return cropped def within_bbox(self, bbox): @@ -162,7 +187,7 @@ def objects(self): return self._objects cropped = CroppedPage(self) - cropped.bbox = tuple(map(self.decimalize, bbox)) + cropped.bbox = self.decimalize(bbox) return cropped def filter(self, test_function): diff --git a/pdfplumber/table.py b/pdfplumber/table.py index d5210e7e..bd652d7f 100644 --- a/pdfplumber/table.py +++ b/pdfplumber/table.py @@ -4,6 +4,8 @@ DEFAULT_SNAP_TOLERANCE = 3 DEFAULT_JOIN_TOLERANCE = 3 +DEFAULT_MIN_WORDS_VERTICAL = 3 +DEFAULT_MIN_WORDS_HORIZONTAL = 1 def move_to_avg(objs, orientation): """ @@ -87,7 +89,7 @@ def get_group(edge): return edges def words_to_edges_h(words, - word_threshold=3): + word_threshold=DEFAULT_MIN_WORDS_HORIZONTAL): """ Find (imaginary) horizontal lines that connect the tops of at least `word_threshold` words. """ @@ -117,7 +119,7 @@ def words_to_edges_h(words, return edges def words_to_edges_v(words, - word_threshold=3): + word_threshold=DEFAULT_MIN_WORDS_VERTICAL): """ Find (imaginary) vertical lines that connect the left, right, or center of at least `word_threshold` words. """ @@ -213,7 +215,7 @@ def intersections_to_cells(intersections): def edge_connects(p1, p2): def edges_to_set(edges): - return set(map(tuple, [ x.items() for x in edges ])) + return set(map(utils.obj_to_bbox, edges)) if p1[0] == p2[0]: common = edges_to_set(intersections[p1]["v"])\ @@ -395,7 +397,8 @@ def char_in_bbox(char, bbox): "snap_tolerance": DEFAULT_SNAP_TOLERANCE, "join_tolerance": DEFAULT_JOIN_TOLERANCE, "edge_min_length": 3, - "text_word_threshold": 3, + "min_words_vertical": DEFAULT_MIN_WORDS_VERTICAL, + "min_words_horizontal": DEFAULT_MIN_WORDS_HORIZONTAL, "keep_blank_chars": False, "text_tolerance": 3, "text_x_tolerance": None, @@ -505,7 +508,7 @@ def v_edge_desc_to_edge(desc): edge_type="lines") elif v_strat == "text": v_base = words_to_edges_v(words, - word_threshold=settings["text_word_threshold"]) + word_threshold=settings["min_words_vertical"]) elif v_strat == "explicit": v_base = [] @@ -539,7 +542,7 @@ def h_edge_desc_to_edge(desc): edge_type="lines") elif h_strat == "text": h_base = words_to_edges_h(words, - word_threshold=settings["text_word_threshold"]) + word_threshold=settings["min_words_horizontal"]) elif h_strat == "explicit": h_base = [] @@ -553,5 +556,3 @@ def h_edge_desc_to_edge(desc): ) return utils.filter_edges(edges, min_length=settings["edge_min_length"]) - - diff --git a/pdfplumber/utils.py b/pdfplumber/utils.py index 91df7c3a..8aafec12 100644 --- a/pdfplumber/utils.py +++ b/pdfplumber/utils.py @@ -69,15 +69,24 @@ def decode_text(s): return ''.join(PDFDocEncoding[o] for o in ords) def decimalize(v, q=None): - if isinstance(v, numbers.Integral): + # If already a decimal, just return itself + if isinstance(v, Decimal): + return v + # If tuple/list passed, bulk-convert + elif isinstance(v, (tuple, list)): + return type(v)(decimalize(x, q) for x in v) + # Convert int-like + elif isinstance(v, numbers.Integral): return Decimal(int(v)) - if isinstance(v, numbers.Real): + # Convert float-like + elif isinstance(v, numbers.Real): if q != None: return Decimal(repr(v)).quantize(Decimal(repr(q)), rounding=ROUND_HALF_UP) else: return Decimal(repr(v)) - return v + else: + raise ValueError("Cannot convert {0} to Decimal.".format(v)) def is_dataframe(collection): cls = collection.__class__ @@ -117,8 +126,7 @@ def objects_to_bbox(objects): max(map(itemgetter("bottom"), objects)), ) -def rect_to_bbox(rect): - return (rect["x0"], rect["top"], rect["x1"], rect["bottom"]) +obj_to_bbox = itemgetter("x0", "top", "x1", "bottom") def bbox_to_rect(bbox): return { @@ -267,7 +275,7 @@ def clip_obj(obj, bbox, score=None): return copy def n_points_intersecting_bbox(objs, bbox): - bbox = tuple(map(decimalize, bbox)) + bbox = decimalize(bbox) objs = to_list(objs) scores = (obj_inside_bbox_score(obj, bbox) for obj in objs) return list(scores) diff --git a/tests/test-display.py b/tests/test-display.py index 49ec8945..e02d7a8d 100644 --- a/tests/test-display.py +++ b/tests/test-display.py @@ -30,3 +30,11 @@ def test_debug_tablefinder(self): } self.im.debug_tablefinder(settings) + def test_curves(self): + path = os.path.join( + HERE, + "../examples/pdfs/ag-energy-round-up-2017-02-24.pdf" + ) + page = pdfplumber.open(path).pages[0] + im = page.to_image() + im.draw_lines(page.curves)