AA_ATTO_flush2leafAgedemo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Processing ATTO leaf flushing data\n",
    "- PI: Bruce W. Nelson\n",
    "- Raw data processing: Davieliton Pinho and Giordane Martins\n",
    "- Flushing to leaf age and LAI classes: Santiago Botía and Eliane Gomes-Alves\n",
    "- This script was written by: Santiago Botía\n",
    "\n",
    "### Description\n",
    "- This code is accompanied by datasets 223 and 230 from the https://www.attodata.org/\n",
    "- Both datasets are available freely and each contain a README file explaining further the assumptions and as well as the methods.\n",
    "- This script reads in dataset 223 and produces 230. It also has the option to produce LAI age classes based on assumptions explained in the README files as well as in the paper:\n",
    "    - https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.15905"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.ticker as tck\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Overview of leaf flushing dataset (223)\n",
    "- general overview of the dataset, and basic stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading data\n",
    "binning          = '13classes' # Options are: 4classes or 13classes, this defines the binning used for the age classes. \n",
    "# this is a flag for asking normalized data (True), or if False, to get the number of individuals instead of fractions\n",
    "# If doPercent is True, the normalized dataset will have a column called unknown.\n",
    "doPercent        = True       \n",
    "# change the name below accordingly it should be dataset 223 on data portal\n",
    "path_dataset_223 = './ATTO_leaf_phenology_raw_dataset_2013-07_2018-11.csv' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Family</th>\n",
       "      <th>Specie</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Event</th>\n",
       "      <th>Date</th>\n",
       "      <th>Pheno type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2014</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2014-07-06</td>\n",
       "      <td>semiBD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2016</td>\n",
       "      <td>7</td>\n",
       "      <td>27</td>\n",
       "      <td>abscission</td>\n",
       "      <td>2016-07-27</td>\n",
       "      <td>semiBD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2016</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2016-08-04</td>\n",
       "      <td>semiBD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2018</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>abscission</td>\n",
       "      <td>2018-08-04</td>\n",
       "      <td>semiBD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2018-08-04</td>\n",
       "      <td>semiBD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8</td>\n",
       "      <td>Sapotaceae</td>\n",
       "      <td>Chrysophyllum argenteum Jacq.</td>\n",
       "      <td>2014</td>\n",
       "      <td>7</td>\n",
       "      <td>22</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2014-07-22</td>\n",
       "      <td>EV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8</td>\n",
       "      <td>Sapotaceae</td>\n",
       "      <td>Chrysophyllum argenteum Jacq.</td>\n",
       "      <td>2015</td>\n",
       "      <td>7</td>\n",
       "      <td>15</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2015-07-15</td>\n",
       "      <td>EV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Sapotaceae</td>\n",
       "      <td>Chrysophyllum argenteum Jacq.</td>\n",
       "      <td>2016</td>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2016-08-20</td>\n",
       "      <td>EV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Sapotaceae</td>\n",
       "      <td>Chrysophyllum argenteum Jacq.</td>\n",
       "      <td>2017</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2017-07-17</td>\n",
       "      <td>EV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>Sapotaceae</td>\n",
       "      <td>Chrysophyllum argenteum Jacq.</td>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2018-08-08</td>\n",
       "      <td>EV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID         Family                                    Specie  Year  Month  \\\n",
       "0   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2014      7   \n",
       "1   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2016      7   \n",
       "2   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2016      8   \n",
       "3   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2018      7   \n",
       "4   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2018      8   \n",
       "5   8     Sapotaceae             Chrysophyllum argenteum Jacq.  2014      7   \n",
       "6   8     Sapotaceae             Chrysophyllum argenteum Jacq.  2015      7   \n",
       "7   8     Sapotaceae             Chrysophyllum argenteum Jacq.  2016      8   \n",
       "8   8     Sapotaceae             Chrysophyllum argenteum Jacq.  2017      7   \n",
       "9   8     Sapotaceae             Chrysophyllum argenteum Jacq.  2018      8   \n",
       "\n",
       "   Day       Event       Date Pheno type  \n",
       "0    6  init_flush 2014-07-06     semiBD  \n",
       "1   27  abscission 2016-07-27     semiBD  \n",
       "2    4  init_flush 2016-08-04     semiBD  \n",
       "3    4  abscission 2018-08-04     semiBD  \n",
       "4    4  init_flush 2018-08-04     semiBD  \n",
       "5   22  init_flush 2014-07-22         EV  \n",
       "6   15  init_flush 2015-07-15         EV  \n",
       "7   20  init_flush 2016-08-20         EV  \n",
       "8   17  init_flush 2017-07-17         EV  \n",
       "9    8  init_flush 2018-08-08         EV  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data             = pd.read_csv(path_dataset_223) \n",
    "data['Date']     = pd.to_datetime(data['Date']) # converting to datetime\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Timestamp('2013-07-04 00:00:00'), Timestamp('2018-11-08 00:00:00'))"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Date'].min(),data['Date'].max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Note:\n",
    "- The original dataset has an ID identifying each individual, the species name, the family name and a date associated with an event, either initial flushing date or abscission."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of individuals in this dataset = 134\n",
      "number of species in dataset = 100\n"
     ]
    }
   ],
   "source": [
    "print('number of individuals in this dataset =',len(list(set(data['ID'].values))))\n",
    "print('number of species in dataset =',len(list(set(data['Specie'].values))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A summary of the pheno types in the data is shown below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Phenological types  {'semiEV', 'BD', 'semiBD', 'EV'}\n",
      " \n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('Phenological types ', set(data['Pheno type'].values))\n",
    "print(' ')\n",
    "pheno_types = data.drop_duplicates(subset='ID').groupby('Pheno type')['ID'].count()\n",
    "pheno_types_percent = (pheno_types/pheno_types.sum())*100\n",
    "\n",
    "pheno_types_percent.plot(kind='bar',figsize=(12,8),fontsize=16)\n",
    "\n",
    "plt.xlabel('Pheno type',fontsize=16)\n",
    "plt.ylabel('%',fontsize=16)\n",
    "plt.grid(alpha=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function for selecting randomly an individual form the dataset\n",
    "def get_random_ind(df,pheno='EV'):\n",
    "    EV  = np.array(list(set(df[df['Pheno type']=='EV']['ID'].values)))\n",
    "    nEV = np.array(list(set(df[df['Pheno type']=='semiEV']['ID'].values)))\n",
    "    BD  = np.array(list(set(df[df['Pheno type']=='BD']['ID'].values)))\n",
    "    nBD = np.array(list(set(df[df['Pheno type']=='semiBD']['ID'].values)))\n",
    "    if pheno == 'EV':\n",
    "        tree_num = np.random.choice(EV)\n",
    "    elif pheno == 'semiEV':\n",
    "        tree_num = np.random.choice(nEV)\n",
    "    elif pheno == 'BD':    \n",
    "        tree_num = np.random.choice(BD)\n",
    "    elif pheno == 'semiBD':\n",
    "        tree_num = np.random.choice(nBD)\n",
    "    return tree_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Individuals in BD \n",
      " {129, 130, 140, 142, 27, 29, 31, 164, 37, 41, 181, 62, 63, 64, 65, 193, 68, 73, 79, 80, 210, 88, 90, 96, 225, 101, 105, 110, 111, 114, 126}\n"
     ]
    }
   ],
   "source": [
    "print('Individuals in BD \\n',set(data[data['Pheno type']=='BD']['ID'].values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "individuals in nBD \n",
      " {1, 150, 159, 179, 53, 182, 60, 189, 190, 194, 200, 84, 212, 217, 92, 221, 99, 229, 125}\n"
     ]
    }
   ],
   "source": [
    "print('individuals in nBD \\n',set(data[data['Pheno type']=='semiBD']['ID'].values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "individuals in EV \n",
      " {131, 133, 134, 135, 8, 138, 143, 149, 23, 151, 152, 154, 28, 33, 163, 165, 166, 169, 175, 48, 49, 50, 51, 177, 180, 54, 55, 56, 183, 184, 59, 185, 186, 187, 188, 66, 67, 70, 71, 72, 199, 76, 77, 78, 204, 207, 208, 82, 211, 215, 89, 91, 220, 222, 95, 223, 98, 226, 100, 228, 102, 103, 232, 106, 107, 116, 119, 120, 123}\n"
     ]
    }
   ],
   "source": [
    "print('individuals in EV \\n',set(data[data['Pheno type']=='EV']['ID'].values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "individuals in nEV \n",
      " {35, 122, 158, 202, 75, 109, 173, 144, 93, 117, 87, 58, 155, 61, 94}\n"
     ]
    }
   ],
   "source": [
    "print('individuals in nEV \\n',set(data[data['Pheno type']=='semiEV']['ID'].values))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How do the flushing patterns look like for each pheno type?\n",
    "- play with the get_random_ind function (BD,semiBD,EV,and semiEV) below to see for a random selection of an individual in each pheno type, how does it look.\n",
    "\n",
    "- In general:\n",
    "\n",
    "    - EV = Evergreen, species that remain green always but they have detectable flushes, with at least four over the sampling record.\n",
    "\n",
    "    - semiEV = same as EV, but they flush maximum three times over the entire record.\n",
    "\n",
    "    - BD = brevidecidous, species that have a brief abscissed stage (bare) followed by flushing, approximately every year\n",
    "\n",
    "    - semiBD = semi-brevidecidous, species that have a brief abscissed stage (bare) followed by flushing, but the difference with BD is that the flushing-abscission dynamics is irregular."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Family</th>\n",
       "      <th>Specie</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Event</th>\n",
       "      <th>Date</th>\n",
       "      <th>Pheno type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>58</td>\n",
       "      <td>Sapotaceae</td>\n",
       "      <td>Pouteria peruviensis (Aubrév.) Bernardi</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2013-10-15</td>\n",
       "      <td>semiEV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>58</td>\n",
       "      <td>Sapotaceae</td>\n",
       "      <td>Pouteria peruviensis (Aubrév.) Bernardi</td>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2016-03-17</td>\n",
       "      <td>semiEV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>58</td>\n",
       "      <td>Sapotaceae</td>\n",
       "      <td>Pouteria peruviensis (Aubrév.) Bernardi</td>\n",
       "      <td>2017</td>\n",
       "      <td>6</td>\n",
       "      <td>19</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2017-06-19</td>\n",
       "      <td>semiEV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ID      Family                                   Specie  Year  Month  \\\n",
       "130  58  Sapotaceae  Pouteria peruviensis (Aubrév.) Bernardi  2013     10   \n",
       "129  58  Sapotaceae  Pouteria peruviensis (Aubrév.) Bernardi  2016      3   \n",
       "131  58  Sapotaceae  Pouteria peruviensis (Aubrév.) Bernardi  2017      6   \n",
       "\n",
       "     Day       Event       Date Pheno type  \n",
       "130   15  init_flush 2013-10-15     semiEV  \n",
       "129   17  init_flush 2016-03-17     semiEV  \n",
       "131   19  init_flush 2017-06-19     semiEV  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1408x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# randomly selecting an individual from a pheno type\n",
    "# the bars in the plot represent the event, the width and height have no meaning\n",
    "\n",
    "################## You can select between semiBD, BD, EV or semiEV\n",
    "wanted_phenotype = 'semiEV' \n",
    "##################\n",
    "\n",
    "tree = get_random_ind(data,pheno=wanted_phenotype) \n",
    "display(data[data['ID']==tree].sort_values(by=['Year','Month'])) # displaying the data for the individual\n",
    "\n",
    "# Plotting\n",
    "# setting the dates properly so it can be plotted and other details\n",
    "datesi  = data[data['ID']==tree].sort_values(by=['Year','Month'])['Date'].astype(str).values\n",
    "datesf  = [datetime.datetime.strptime(str(d), \"%Y-%m-%d\") for d in datesi]                                               \n",
    "names   =  list(data[data['ID']==tree].sort_values(by=['Year','Month'])['Event'].astype(str).values)\n",
    "sp      = list(set(data[data['ID']==tree]['Specie']))[0]\n",
    "ind_num = list(set(data[data['ID']==tree]['ID']))[0]\n",
    "\n",
    "# selecting levels for the height of the lines in plot\n",
    "levels = np.tile([-2, 2, -2, 2, -2, 2],int(np.ceil(len(datesf)/6)))[:len(datesf)] # same height adjust\n",
    "\n",
    "# Create figure and plot a stem plot with the date\n",
    "fig, ax = plt.subplots(figsize=(8.8, 4), dpi=160,constrained_layout=True)\n",
    "\n",
    "ax.set(title=\"Leaf phenology for %s \\n Individual number %i - Pheno type %s\"%(sp,ind_num,wanted_phenotype))\n",
    "ax.vlines(datesf, 0, levels, color=\"tab:red\")  # The vertical stems.\n",
    "ax.plot(datesf, np.zeros_like(datesf), \"-o\",color=\"k\", markerfacecolor=\"w\")  # Baseline and markers on it.\n",
    "\n",
    "# annotate lines\n",
    "for d, l, r in zip(datesf, levels, names):\n",
    "    ax.annotate(r, xy=(d, l),xytext=(-3, np.sign(l)*3), textcoords=\"offset points\",\n",
    "                horizontalalignment=\"right\",verticalalignment=\"bottom\" if l > 0 else \"top\")\n",
    "    \n",
    "# remove y axis and spines\n",
    "ax.yaxis.set_visible(False)\n",
    "ax.spines[\"left\"].set_visible(False)\n",
    "ax.spines[\"top\"].set_visible(False)\n",
    "ax.spines[\"right\"].set_visible(False)\n",
    "\n",
    "years     = mdates.YearLocator()   # every year\n",
    "months    = mdates.MonthLocator()  # every month\n",
    "years_fmt = mdates.DateFormatter('%Y')\n",
    "\n",
    "ax.xaxis.set_major_locator(years)\n",
    "ax.xaxis.set_major_formatter(years_fmt)\n",
    "ax.xaxis.set_minor_locator(months)\n",
    "\n",
    "ax.margins(y=0.1)\n",
    "plt.show()\n",
    "#fig.savefig('flushing_patterns.png',bbox_inches='tight',dpi=180)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Data processing for leaf age estimation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating flags for flush or abscission\n",
    "data['FlushFlag'] = data['Event'] == 'init_flush'\n",
    "data['QFlag']     = data['Event'] == 'abscission'\n",
    "flushing          = data[data['FlushFlag']==True]\n",
    "queda             = data[data['QFlag']==True] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Family</th>\n",
       "      <th>Specie</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Event</th>\n",
       "      <th>Date</th>\n",
       "      <th>Pheno type</th>\n",
       "      <th>FlushFlag</th>\n",
       "      <th>QFlag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2016</td>\n",
       "      <td>7</td>\n",
       "      <td>27</td>\n",
       "      <td>abscission</td>\n",
       "      <td>2016-07-27</td>\n",
       "      <td>semiBD</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2018</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>abscission</td>\n",
       "      <td>2018-08-04</td>\n",
       "      <td>semiBD</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID         Family                                    Specie  Year  Month  \\\n",
       "1   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2016      7   \n",
       "3   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2018      7   \n",
       "\n",
       "   Day       Event       Date Pheno type  FlushFlag  QFlag  \n",
       "1   27  abscission 2016-07-27     semiBD      False   True  \n",
       "3    4  abscission 2018-08-04     semiBD      False   True  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "queda.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Family</th>\n",
       "      <th>Specie</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Event</th>\n",
       "      <th>Date</th>\n",
       "      <th>Pheno type</th>\n",
       "      <th>FlushFlag</th>\n",
       "      <th>QFlag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2014</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2014-07-06</td>\n",
       "      <td>semiBD</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Lecythidaceae</td>\n",
       "      <td>Eschweilera pedicellata (Rich.) S.A.Mori</td>\n",
       "      <td>2016</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2016-08-04</td>\n",
       "      <td>semiBD</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID         Family                                    Specie  Year  Month  \\\n",
       "0   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2014      7   \n",
       "2   1  Lecythidaceae  Eschweilera pedicellata (Rich.) S.A.Mori  2016      8   \n",
       "\n",
       "   Day       Event       Date Pheno type  FlushFlag  QFlag  \n",
       "0    6  init_flush 2014-07-06     semiBD       True  False  \n",
       "2    4  init_flush 2016-08-04     semiBD       True  False  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flushing.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# this is to get some stats on the amount of flush and abs in the data for each pheno type\n",
    "abs_gp = pd.DataFrame(queda.groupby('ID')['Event'].count())\n",
    "abs_gp.sort_index(ascending=True,inplace=True)\n",
    "abs_gp.reset_index(inplace=True)\n",
    "\n",
    "# this dataframe is used to generate the plot of total flush events for each individual\n",
    "flushing_gp = pd.DataFrame(flushing.groupby('ID')['Event'].count())\n",
    "flushing_gp.sort_index(ascending=True,inplace=True)\n",
    "flushing_gp.reset_index(inplace=True)\n",
    "\n",
    "non_repeat_pheno_type = flushing[['ID','Pheno type']].drop_duplicates()\n",
    "non_repeat_pheno_type.sort_values(by='ID',inplace=True)\n",
    "#display(non_repeat_pheno_type.head(2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>numFlush</th>\n",
       "      <th>Pheno type</th>\n",
       "      <th>numAbs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>semiBD</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>EV</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>EV</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>27</td>\n",
       "      <td>5</td>\n",
       "      <td>BD</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28</td>\n",
       "      <td>6</td>\n",
       "      <td>EV</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>29</td>\n",
       "      <td>6</td>\n",
       "      <td>BD</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  numFlush Pheno type  numAbs\n",
       "0   1         3     semiBD     2.0\n",
       "1   8         5         EV     NaN\n",
       "2  23         6         EV     NaN\n",
       "3  27         5         BD     5.0\n",
       "4  28         6         EV     NaN\n",
       "5  29         6         BD     6.0"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flushing_gp['Pheno type'] = non_repeat_pheno_type['Pheno type'].values\n",
    "flushing_gp.columns = ['ID','numFlush','Pheno type']\n",
    "flsh_abs_df = pd.merge(flushing_gp,abs_gp,on='ID',how='left')\n",
    "flsh_abs_df.columns = ['ID','numFlush','Pheno type','numAbs']\n",
    "flsh_abs_df.head(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">numFlush</th>\n",
       "      <th colspan=\"3\" halign=\"left\">numAbs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>mean</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pheno type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BD</th>\n",
       "      <td>5.580645</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>5.225806</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EV</th>\n",
       "      <td>5.217391</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>semiBD</th>\n",
       "      <td>4.210526</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1.842105</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>semiEV</th>\n",
       "      <td>2.800000</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            numFlush            numAbs          \n",
       "                mean min max      mean  min  max\n",
       "Pheno type                                      \n",
       "BD          5.580645   4   7  5.225806  4.0  7.0\n",
       "EV          5.217391   4   8       NaN  NaN  NaN\n",
       "semiBD      4.210526   2   7  1.842105  1.0  3.0\n",
       "semiEV      2.800000   2   3       NaN  NaN  NaN"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# stats on flush and abs\n",
    "flsh_abs_df.groupby('Pheno type').agg(['mean','min','max'])[['numFlush','numAbs']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x800 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualizing number of flushing events per individual\n",
    "import matplotlib as mpl\n",
    "fig,(ax,ax1,ax2)  = plt.subplots(3,1,figsize=(10,5),dpi=160)\n",
    "\n",
    "sns.barplot(x='ID',y='numFlush',data=flushing_gp.iloc[0:44,:],ax=ax)\n",
    "sns.barplot(x='ID',y='numFlush',data=flushing_gp.iloc[44:88,:],ax=ax1)\n",
    "sns.barplot(x='ID',y='numFlush',data=flushing_gp.iloc[88:,:],ax=ax2)\n",
    "\n",
    "ax.set_ylabel('Event',fontsize=6)\n",
    "ax1.set_ylabel('Event',fontsize=6)\n",
    "\n",
    "ax.xaxis.set_tick_params(size=4)\n",
    "\n",
    "ax.set_xlabel('ID',fontsize=6)\n",
    "ax1.set_xlabel('ID',fontsize=6)\n",
    "\n",
    "ax.set_ylim(0,8)\n",
    "ax1.set_ylim(0,8)\n",
    "ax2.set_ylim(0,8)\n",
    "\n",
    "mpl.rcParams['font.size'] = 5\n",
    "plt.subplots_adjust(hspace=0.4)\n",
    "plt.show()\n",
    "#fig.savefig('IndFlushing_alltimes.png',dpi=200,bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Main loop where ages are calculated for each individual "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of trees that flush 134\n"
     ]
    }
   ],
   "source": [
    "ids     = list(set(flushing['ID'].values))\n",
    "print('Number of trees that flush',len(ids))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================= counter =================  0\n",
      "ind num 1 {'Eschweilera pedicellata\\xa0(Rich.) S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-07-06T00:00:00.000000000' '2016-08-04T00:00:00.000000000'\n",
      " '2018-08-04T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-07-06T00:00:00.000000000 to 2016-08-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-04T00:00:00.000000000 to 2018-08-04T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-04T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  1\n",
      "ind num 8 {'Chrysophyllum argenteum\\xa0Jacq.'} \n",
      "\n",
      "===== original dates in record ['2014-07-22T00:00:00.000000000' '2015-07-15T00:00:00.000000000'\n",
      " '2016-08-20T00:00:00.000000000' '2017-07-17T00:00:00.000000000'\n",
      " '2018-08-08T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-07-22T00:00:00.000000000 to 2015-07-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-15T00:00:00.000000000 to 2016-08-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-20T00:00:00.000000000 to 2017-07-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-17T00:00:00.000000000 to 2018-08-08T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-08T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  2\n",
      "ind num 23 {'Manilkara huberi\\xa0(Ducke) Standl.'} \n",
      "\n",
      "===== original dates in record ['2013-07-26T00:00:00.000000000' '2014-01-22T00:00:00.000000000'\n",
      " '2015-02-05T00:00:00.000000000' '2016-05-13T00:00:00.000000000'\n",
      " '2017-04-18T00:00:00.000000000' '2018-01-09T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-26T00:00:00.000000000 to 2014-01-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-01-22T00:00:00.000000000 to 2015-02-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-02-05T00:00:00.000000000 to 2016-05-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-05-13T00:00:00.000000000 to 2017-04-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-04-18T00:00:00.000000000 to 2018-01-09T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-01-09T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  3\n",
      "ind num 27 {'Manilkara bidentata (A.DC.) A.Chev.'} \n",
      "\n",
      "===== original dates in record ['2014-04-20T00:00:00.000000000' '2015-04-30T00:00:00.000000000'\n",
      " '2016-07-27T00:00:00.000000000' '2017-06-06T00:00:00.000000000'\n",
      " '2018-07-12T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-04-20T00:00:00.000000000 to 2015-04-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-04-30T00:00:00.000000000 to 2016-07-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-27T00:00:00.000000000 to 2017-06-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-06T00:00:00.000000000 to 2018-07-12T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-12T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  4\n",
      "ind num 28 {'Dinizia excelsa Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-07-09T00:00:00.000000000' '2014-07-10T00:00:00.000000000'\n",
      " '2015-07-17T00:00:00.000000000' '2016-07-25T00:00:00.000000000'\n",
      " '2017-07-21T00:00:00.000000000' '2018-06-21T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-09T00:00:00.000000000 to 2014-07-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-07-10T00:00:00.000000000 to 2015-07-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-17T00:00:00.000000000 to 2016-07-25T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-25T00:00:00.000000000 to 2017-07-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-21T00:00:00.000000000 to 2018-06-21T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-21T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  5\n",
      "ind num 29 {'Ecclinusa guianensis Eyma'} \n",
      "\n",
      "===== original dates in record ['2013-11-27T00:00:00.000000000' '2014-11-16T00:00:00.000000000'\n",
      " '2016-01-06T00:00:00.000000000' '2016-12-20T00:00:00.000000000'\n",
      " '2017-11-06T00:00:00.000000000' '2018-10-26T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-11-27T00:00:00.000000000 to 2014-11-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-11-16T00:00:00.000000000 to 2016-01-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-01-06T00:00:00.000000000 to 2016-12-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-12-20T00:00:00.000000000 to 2017-11-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-11-06T00:00:00.000000000 to 2018-10-26T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-26T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  6\n",
      "ind num 31 {'Peltogyne paniculata Benth.'} \n",
      "\n",
      "===== original dates in record ['2014-08-15T00:00:00.000000000' '2015-08-14T00:00:00.000000000'\n",
      " '2016-08-23T00:00:00.000000000' '2017-09-17T00:00:00.000000000'\n",
      " '2018-06-30T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-08-15T00:00:00.000000000 to 2015-08-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-14T00:00:00.000000000 to 2016-08-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-23T00:00:00.000000000 to 2017-09-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-17T00:00:00.000000000 to 2018-06-30T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-30T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  7\n",
      "ind num 33 {'Pouteria cuspidata (A.DC.) Baehni'} \n",
      "\n",
      "===== original dates in record ['2013-07-07T00:00:00.000000000' '2014-07-08T00:00:00.000000000'\n",
      " '2015-07-04T00:00:00.000000000' '2016-08-19T00:00:00.000000000'\n",
      " '2017-07-01T00:00:00.000000000' '2017-12-13T00:00:00.000000000'\n",
      " '2018-07-31T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-07T00:00:00.000000000 to 2014-07-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-07-08T00:00:00.000000000 to 2015-07-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-04T00:00:00.000000000 to 2016-08-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-19T00:00:00.000000000 to 2017-07-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-01T00:00:00.000000000 to 2017-12-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-12-13T00:00:00.000000000 to 2018-07-31T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-31T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  8\n",
      "ind num 35 {'Lecythis chartacea O.Berg'} \n",
      "\n",
      "===== original dates in record ['2014-09-27T00:00:00.000000000' '2017-06-16T00:00:00.000000000'\n",
      " '2018-06-20T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-09-27T00:00:00.000000000 to 2017-06-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-16T00:00:00.000000000 to 2018-06-20T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-20T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  9\n",
      "ind num 37 {'Lecythis chartacea O.Berg'} \n",
      "\n",
      "===== original dates in record ['2013-08-20T00:00:00.000000000' '2014-08-17T00:00:00.000000000'\n",
      " '2015-08-24T00:00:00.000000000' '2016-08-28T00:00:00.000000000'\n",
      " '2017-08-12T00:00:00.000000000' '2018-08-21T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-20T00:00:00.000000000 to 2014-08-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-17T00:00:00.000000000 to 2015-08-24T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-24T00:00:00.000000000 to 2016-08-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-28T00:00:00.000000000 to 2017-08-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-12T00:00:00.000000000 to 2018-08-21T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-21T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  10\n",
      "ind num 41 {'Parkia multijuga Benth.'} \n",
      "\n",
      "===== original dates in record ['2013-10-14T00:00:00.000000000' '2014-10-12T00:00:00.000000000'\n",
      " '2015-09-24T00:00:00.000000000' '2016-10-17T00:00:00.000000000'\n",
      " '2017-10-28T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-14T00:00:00.000000000 to 2014-10-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-12T00:00:00.000000000 to 2015-09-24T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-24T00:00:00.000000000 to 2016-10-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-17T00:00:00.000000000 to 2017-10-28T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-10-28T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  11\n",
      "ind num 48 {'Parkia spp.'} \n",
      "\n",
      "===== original dates in record ['2013-10-24T00:00:00.000000000' '2014-10-22T00:00:00.000000000'\n",
      " '2015-09-28T00:00:00.000000000' '2016-10-21T00:00:00.000000000'\n",
      " '2017-11-03T00:00:00.000000000' '2018-10-15T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-24T00:00:00.000000000 to 2014-10-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-22T00:00:00.000000000 to 2015-09-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-28T00:00:00.000000000 to 2016-10-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-21T00:00:00.000000000 to 2017-11-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-11-03T00:00:00.000000000 to 2018-10-15T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-15T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  12\n",
      "ind num 49 {'Eschweilera coriacea? (DC.) S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-10-01T00:00:00.000000000' '2015-09-30T00:00:00.000000000'\n",
      " '2017-01-16T00:00:00.000000000' '2017-09-26T00:00:00.000000000'\n",
      " '2018-09-09T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-10-01T00:00:00.000000000 to 2015-09-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-30T00:00:00.000000000 to 2017-01-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-01-16T00:00:00.000000000 to 2017-09-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-26T00:00:00.000000000 to 2018-09-09T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-09T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  13\n",
      "ind num 50 {'Swartzia recurva? Poepp.'} \n",
      "\n",
      "===== original dates in record ['2014-06-10T00:00:00.000000000' '2016-07-27T00:00:00.000000000'\n",
      " '2017-06-02T00:00:00.000000000' '2018-08-09T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-10T00:00:00.000000000 to 2016-07-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-27T00:00:00.000000000 to 2017-06-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-02T00:00:00.000000000 to 2018-08-09T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-09T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  14\n",
      "ind num 51 {'Eschweilera cyathiformis? S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-06-16T00:00:00.000000000' '2016-03-12T00:00:00.000000000'\n",
      " '2016-10-10T00:00:00.000000000' '2017-06-13T00:00:00.000000000'\n",
      " '2018-03-27T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-16T00:00:00.000000000 to 2016-03-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-12T00:00:00.000000000 to 2016-10-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-10T00:00:00.000000000 to 2017-06-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-13T00:00:00.000000000 to 2018-03-27T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-03-27T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  15\n",
      "ind num 53 {'Couratari stellata? A.C.Sm.'} \n",
      "\n",
      "===== original dates in record ['2014-05-20T00:00:00.000000000' '2015-05-15T00:00:00.000000000'\n",
      " '2016-08-02T00:00:00.000000000' '2018-03-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-05-20T00:00:00.000000000 to 2015-05-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-05-15T00:00:00.000000000 to 2016-08-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-02T00:00:00.000000000 to 2018-03-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-03-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  16\n",
      "ind num 54 {'Manilkara huberi\\xa0(Ducke) Standl.'} \n",
      "\n",
      "===== original dates in record ['2013-07-04T00:00:00.000000000' '2014-07-04T00:00:00.000000000'\n",
      " '2015-06-22T00:00:00.000000000' '2016-04-15T00:00:00.000000000'\n",
      " '2017-08-06T00:00:00.000000000' '2018-07-08T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-04T00:00:00.000000000 to 2014-07-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-07-04T00:00:00.000000000 to 2015-06-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-22T00:00:00.000000000 to 2016-04-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-04-15T00:00:00.000000000 to 2017-08-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-06T00:00:00.000000000 to 2018-07-08T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-08T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  17\n",
      "ind num 55 {'Chimarrhis duckeana? Delprete'} \n",
      "\n",
      "===== original dates in record ['2014-06-25T00:00:00.000000000' '2015-06-23T00:00:00.000000000'\n",
      " '2016-06-13T00:00:00.000000000' '2017-06-01T00:00:00.000000000'\n",
      " '2018-06-26T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-25T00:00:00.000000000 to 2015-06-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-23T00:00:00.000000000 to 2016-06-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-06-13T00:00:00.000000000 to 2017-06-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-01T00:00:00.000000000 to 2018-06-26T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-26T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  18\n",
      "ind num 56 {'Eschweilera truncata. A.C.Sm.'} \n",
      "\n",
      "===== original dates in record ['2014-06-24T00:00:00.000000000' '2015-09-08T00:00:00.000000000'\n",
      " '2016-06-19T00:00:00.000000000' '2017-09-01T00:00:00.000000000'\n",
      " '2018-07-02T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-24T00:00:00.000000000 to 2015-09-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-08T00:00:00.000000000 to 2016-06-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-06-19T00:00:00.000000000 to 2017-09-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-01T00:00:00.000000000 to 2018-07-02T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-02T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  19\n",
      "ind num 58 {'Pouteria peruviensis (Aubrév.) Bernardi'} \n",
      "\n",
      "===== original dates in record ['2013-10-15T00:00:00.000000000' '2016-03-17T00:00:00.000000000'\n",
      " '2017-06-19T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-15T00:00:00.000000000 to 2016-03-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-17T00:00:00.000000000 to 2017-06-19T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-06-19T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  20\n",
      "ind num 59 {'Enterolobium schomburgkii (Benth.) Benth.'} \n",
      "\n",
      "===== original dates in record ['2014-07-03T00:00:00.000000000' '2015-06-26T00:00:00.000000000'\n",
      " '2016-07-13T00:00:00.000000000' '2017-08-09T00:00:00.000000000'\n",
      " '2018-01-30T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-07-03T00:00:00.000000000 to 2015-06-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-26T00:00:00.000000000 to 2016-07-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-13T00:00:00.000000000 to 2017-08-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-09T00:00:00.000000000 to 2018-01-30T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-01-30T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  21\n",
      "ind num 60 {'Trattinnickia burserifolia? Mart.'} \n",
      "\n",
      "===== original dates in record ['2014-05-21T00:00:00.000000000' '2016-01-11T00:00:00.000000000'\n",
      " '2017-06-21T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-05-21T00:00:00.000000000 to 2016-01-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-01-11T00:00:00.000000000 to 2017-06-21T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-06-21T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  22\n",
      "ind num 61 {'Sacoglottis mattogrossensis var. subintegra (Ducke) Cuatrec.'} \n",
      "\n",
      "===== original dates in record ['2015-07-04T00:00:00.000000000' '2016-08-13T00:00:00.000000000'\n",
      " '2017-06-19T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2015-07-04T00:00:00.000000000 to 2016-08-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-13T00:00:00.000000000 to 2017-06-19T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-06-19T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  23\n",
      "ind num 62 {'Peltogyne catingae Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-08-19T00:00:00.000000000' '2014-09-11T00:00:00.000000000'\n",
      " '2015-09-08T00:00:00.000000000' '2016-08-28T00:00:00.000000000'\n",
      " '2017-08-10T00:00:00.000000000' '2018-04-15T00:00:00.000000000'\n",
      " '2018-09-28T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-19T00:00:00.000000000 to 2014-09-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-11T00:00:00.000000000 to 2015-09-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-08T00:00:00.000000000 to 2016-08-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-28T00:00:00.000000000 to 2017-08-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-10T00:00:00.000000000 to 2018-04-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2018-04-15T00:00:00.000000000 to 2018-09-28T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-28T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  24\n",
      "ind num 63 {'Brosimum parinarioides Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-09-17T00:00:00.000000000' '2015-10-22T00:00:00.000000000'\n",
      " '2017-08-20T00:00:00.000000000' '2018-10-06T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-09-17T00:00:00.000000000 to 2015-10-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-10-22T00:00:00.000000000 to 2017-08-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-20T00:00:00.000000000 to 2018-10-06T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-06T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  25\n",
      "ind num 64 {'Caryocar pallidum? A.C.Sm.'} \n",
      "\n",
      "===== original dates in record ['2013-11-12T00:00:00.000000000' '2014-09-07T00:00:00.000000000'\n",
      " '2015-09-21T00:00:00.000000000' '2016-10-08T00:00:00.000000000'\n",
      " '2017-09-08T00:00:00.000000000' '2018-09-25T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-11-12T00:00:00.000000000 to 2014-09-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-07T00:00:00.000000000 to 2015-09-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-21T00:00:00.000000000 to 2016-10-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-08T00:00:00.000000000 to 2017-09-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-08T00:00:00.000000000 to 2018-09-25T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-25T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  26\n",
      "ind num 65 {'Parkia spp.'} \n",
      "\n",
      "===== original dates in record ['2013-11-13T00:00:00.000000000' '2014-10-18T00:00:00.000000000'\n",
      " '2015-10-29T00:00:00.000000000' '2016-11-25T00:00:00.000000000'\n",
      " '2017-11-06T00:00:00.000000000' '2018-10-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-11-13T00:00:00.000000000 to 2014-10-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-18T00:00:00.000000000 to 2015-10-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-10-29T00:00:00.000000000 to 2016-11-25T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-11-25T00:00:00.000000000 to 2017-11-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-11-06T00:00:00.000000000 to 2018-10-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  27\n",
      "ind num 66 {'Manilkara bidentata? (A.DC.) A.Chev.'} \n",
      "\n",
      "===== original dates in record ['2013-07-06T00:00:00.000000000' '2014-07-15T00:00:00.000000000'\n",
      " '2015-06-12T00:00:00.000000000' '2016-05-02T00:00:00.000000000'\n",
      " '2017-09-20T00:00:00.000000000' '2018-06-18T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-06T00:00:00.000000000 to 2014-07-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-07-15T00:00:00.000000000 to 2015-06-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-12T00:00:00.000000000 to 2016-05-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-05-02T00:00:00.000000000 to 2017-09-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-20T00:00:00.000000000 to 2018-06-18T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-18T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  28\n",
      "ind num 67 {'Tachigali alba Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-10-07T00:00:00.000000000' '2014-09-30T00:00:00.000000000'\n",
      " '2015-09-30T00:00:00.000000000' '2017-08-12T00:00:00.000000000'\n",
      " '2018-09-25T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-07T00:00:00.000000000 to 2014-09-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-30T00:00:00.000000000 to 2015-09-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-30T00:00:00.000000000 to 2017-08-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-12T00:00:00.000000000 to 2018-09-25T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-25T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  29\n",
      "ind num 68 {'Cariniana micrantha? Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-10-12T00:00:00.000000000' '2014-09-30T00:00:00.000000000'\n",
      " '2015-10-15T00:00:00.000000000' '2016-09-27T00:00:00.000000000'\n",
      " '2017-10-13T00:00:00.000000000' '2018-10-07T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-12T00:00:00.000000000 to 2014-09-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-30T00:00:00.000000000 to 2015-10-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-10-15T00:00:00.000000000 to 2016-09-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-27T00:00:00.000000000 to 2017-10-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-10-13T00:00:00.000000000 to 2018-10-07T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-07T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  30\n",
      "ind num 70 {'Scleronema micranthum (Ducke) Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-04-22T00:00:00.000000000' '2015-05-27T00:00:00.000000000'\n",
      " '2016-07-17T00:00:00.000000000' '2017-06-01T00:00:00.000000000'\n",
      " '2018-06-04T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-04-22T00:00:00.000000000 to 2015-05-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-05-27T00:00:00.000000000 to 2016-07-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-17T00:00:00.000000000 to 2017-06-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-01T00:00:00.000000000 to 2018-06-04T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-04T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  31\n",
      "ind num 71 {'Pouteria laevigata (Mart.) Radlk.'} \n",
      "\n",
      "===== original dates in record ['2013-07-15T00:00:00.000000000' '2014-09-02T00:00:00.000000000'\n",
      " '2015-08-26T00:00:00.000000000' '2016-08-19T00:00:00.000000000'\n",
      " '2017-12-09T00:00:00.000000000' '2018-06-03T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-15T00:00:00.000000000 to 2014-09-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-02T00:00:00.000000000 to 2015-08-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-26T00:00:00.000000000 to 2016-08-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-19T00:00:00.000000000 to 2017-12-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-12-09T00:00:00.000000000 to 2018-06-03T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-03T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  32\n",
      "ind num 72 {'Mezilaurus synandra (Mez) Kosterm.'} \n",
      "\n",
      "===== original dates in record ['2013-07-12T00:00:00.000000000' '2014-09-03T00:00:00.000000000'\n",
      " '2015-06-02T00:00:00.000000000' '2016-08-23T00:00:00.000000000'\n",
      " '2017-09-13T00:00:00.000000000' '2018-08-19T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-12T00:00:00.000000000 to 2014-09-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-03T00:00:00.000000000 to 2015-06-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-02T00:00:00.000000000 to 2016-08-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-23T00:00:00.000000000 to 2017-09-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-13T00:00:00.000000000 to 2018-08-19T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-19T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  33\n",
      "ind num 73 {'Brosimum parinarioides Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-12-19T00:00:00.000000000' '2014-11-11T00:00:00.000000000'\n",
      " '2016-03-02T00:00:00.000000000' '2017-08-27T00:00:00.000000000'\n",
      " '2018-10-31T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-12-19T00:00:00.000000000 to 2014-11-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-11-11T00:00:00.000000000 to 2016-03-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-02T00:00:00.000000000 to 2017-08-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-27T00:00:00.000000000 to 2018-10-31T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-31T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  34\n",
      "ind num 75 {'Taralea oppositifolia? Aubl.'} \n",
      "\n",
      "===== original dates in record ['2013-11-13T00:00:00.000000000' '2015-08-22T00:00:00.000000000'\n",
      " '2017-08-01T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-11-13T00:00:00.000000000 to 2015-08-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-22T00:00:00.000000000 to 2017-08-01T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-08-01T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  35\n",
      "ind num 76 {'Protium? altsonii? Sandwith'} \n",
      "\n",
      "===== original dates in record ['2013-08-03T00:00:00.000000000' '2014-08-09T00:00:00.000000000'\n",
      " '2015-07-19T00:00:00.000000000' '2016-03-15T00:00:00.000000000'\n",
      " '2017-07-20T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-03T00:00:00.000000000 to 2014-08-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-09T00:00:00.000000000 to 2015-07-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-19T00:00:00.000000000 to 2016-03-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-15T00:00:00.000000000 to 2017-07-20T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-07-20T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  36\n",
      "ind num 77 {'Pouteria ambelaniifolia (Sandwith) T.D.Penn.'} \n",
      "\n",
      "===== original dates in record ['2013-09-16T00:00:00.000000000' '2014-09-19T00:00:00.000000000'\n",
      " '2015-09-11T00:00:00.000000000' '2016-10-26T00:00:00.000000000'\n",
      " '2018-08-22T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-09-16T00:00:00.000000000 to 2014-09-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-19T00:00:00.000000000 to 2015-09-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-11T00:00:00.000000000 to 2016-10-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-26T00:00:00.000000000 to 2018-08-22T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-22T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  37\n",
      "ind num 78 {'Eschweilera coriacea? (DC.) S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-05-12T00:00:00.000000000' '2016-03-19T00:00:00.000000000'\n",
      " '2017-05-20T00:00:00.000000000' '2018-05-21T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-05-12T00:00:00.000000000 to 2016-03-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-19T00:00:00.000000000 to 2017-05-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-20T00:00:00.000000000 to 2018-05-21T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-05-21T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  38\n",
      "ind num 79 {'Pouteria pallens? T.D.Penn.'} \n",
      "\n",
      "===== original dates in record ['2013-09-20T00:00:00.000000000' '2014-09-03T00:00:00.000000000'\n",
      " '2015-08-28T00:00:00.000000000' '2016-10-17T00:00:00.000000000'\n",
      " '2017-08-29T00:00:00.000000000' '2018-09-06T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-09-20T00:00:00.000000000 to 2014-09-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-03T00:00:00.000000000 to 2015-08-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-28T00:00:00.000000000 to 2016-10-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-17T00:00:00.000000000 to 2017-08-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-29T00:00:00.000000000 to 2018-09-06T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-06T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  39\n",
      "ind num 80 {'Endopleura uchi (Huber) Cuatrec.'} \n",
      "\n",
      "===== original dates in record ['2013-10-24T00:00:00.000000000' '2014-10-01T00:00:00.000000000'\n",
      " '2015-09-27T00:00:00.000000000' '2016-10-26T00:00:00.000000000'\n",
      " '2017-10-11T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-24T00:00:00.000000000 to 2014-10-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-01T00:00:00.000000000 to 2015-09-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-27T00:00:00.000000000 to 2016-10-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-26T00:00:00.000000000 to 2017-10-11T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-10-11T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  40\n",
      "ind num 82 {'Inga bicoloriflora? Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-06-23T00:00:00.000000000' '2015-08-02T00:00:00.000000000'\n",
      " '2016-08-03T00:00:00.000000000' '2017-05-31T00:00:00.000000000'\n",
      " '2018-08-10T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-23T00:00:00.000000000 to 2015-08-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-02T00:00:00.000000000 to 2016-08-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-03T00:00:00.000000000 to 2017-05-31T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-31T00:00:00.000000000 to 2018-08-10T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-10T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  41\n",
      "ind num 84 {'Pouteria anomala? (Pires) T.D.Penn.'} \n",
      "\n",
      "===== original dates in record ['2013-11-24T00:00:00.000000000' '2014-10-20T00:00:00.000000000'\n",
      " '2016-03-07T00:00:00.000000000' '2016-10-18T00:00:00.000000000'\n",
      " '2017-10-20T00:00:00.000000000' '2018-09-27T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-11-24T00:00:00.000000000 to 2014-10-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-20T00:00:00.000000000 to 2016-03-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-07T00:00:00.000000000 to 2016-10-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-18T00:00:00.000000000 to 2017-10-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-10-20T00:00:00.000000000 to 2018-09-27T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-27T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  42\n",
      "ind num 87 {'Eschweilera micrantha? (O.Berg) Miers'} \n",
      "\n",
      "===== original dates in record ['2016-07-19T00:00:00.000000000' '2018-05-29T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2016-07-19T00:00:00.000000000 to 2018-05-29T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-05-29T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  43\n",
      "ind num 88 {'Moronobea pulchra? Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-08-24T00:00:00.000000000' '2015-09-01T00:00:00.000000000'\n",
      " '2016-09-15T00:00:00.000000000' '2017-08-03T00:00:00.000000000'\n",
      " '2018-09-12T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-08-24T00:00:00.000000000 to 2015-09-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-01T00:00:00.000000000 to 2016-09-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-15T00:00:00.000000000 to 2017-08-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-03T00:00:00.000000000 to 2018-09-12T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-12T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  44\n",
      "ind num 89 {'Scleronema micranthum (Ducke) Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-05-07T00:00:00.000000000' '2015-06-16T00:00:00.000000000'\n",
      " '2016-07-16T00:00:00.000000000' '2017-06-08T00:00:00.000000000'\n",
      " '2018-06-23T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-05-07T00:00:00.000000000 to 2015-06-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-16T00:00:00.000000000 to 2016-07-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-16T00:00:00.000000000 to 2017-06-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-08T00:00:00.000000000 to 2018-06-23T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-23T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  45\n",
      "ind num 90 {'Pouteria cuspidata (A.DC.) Baehni'} \n",
      "\n",
      "===== original dates in record ['2014-03-23T00:00:00.000000000' '2015-06-10T00:00:00.000000000'\n",
      " '2017-01-13T00:00:00.000000000' '2018-04-02T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-03-23T00:00:00.000000000 to 2015-06-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-10T00:00:00.000000000 to 2017-01-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-01-13T00:00:00.000000000 to 2018-04-02T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-04-02T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  46\n",
      "ind num 91 {'Pouteria cuspidata? (A. DC.) Baehni'} \n",
      "\n",
      "===== original dates in record ['2014-06-24T00:00:00.000000000' '2015-08-10T00:00:00.000000000'\n",
      " '2016-08-14T00:00:00.000000000' '2017-06-16T00:00:00.000000000'\n",
      " '2018-06-24T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-24T00:00:00.000000000 to 2015-08-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-10T00:00:00.000000000 to 2016-08-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-14T00:00:00.000000000 to 2017-06-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-16T00:00:00.000000000 to 2018-06-24T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-24T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  47\n",
      "ind num 92 {'Eschweilera cyathiformis? S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-08-15T00:00:00.000000000' '2016-08-15T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-08-15T00:00:00.000000000 to 2016-08-15T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2016-08-15T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  48\n",
      "ind num 93 {'Mouriri collocarpa? Ducke'} \n",
      "\n",
      "===== original dates in record ['2015-07-22T00:00:00.000000000' '2016-08-09T00:00:00.000000000'\n",
      " '2018-07-07T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2015-07-22T00:00:00.000000000 to 2016-08-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-09T00:00:00.000000000 to 2018-07-07T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-07T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  49\n",
      "ind num 94 {'Pouteria ambelaniifolia (Sandwith) T.D.Penn.'} \n",
      "\n",
      "===== original dates in record ['2013-08-08T00:00:00.000000000' '2014-08-31T00:00:00.000000000'\n",
      " '2018-07-23T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-08T00:00:00.000000000 to 2014-08-31T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-31T00:00:00.000000000 to 2018-07-23T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-23T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  50\n",
      "ind num 95 {'Monopteryx inpae? W.A.Rodrigues'} \n",
      "\n",
      "===== original dates in record ['2013-12-06T00:00:00.000000000' '2014-05-03T00:00:00.000000000'\n",
      " '2015-04-20T00:00:00.000000000' '2016-07-26T00:00:00.000000000'\n",
      " '2017-03-11T00:00:00.000000000' '2018-02-22T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-12-06T00:00:00.000000000 to 2014-05-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-05-03T00:00:00.000000000 to 2015-04-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-04-20T00:00:00.000000000 to 2016-07-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-26T00:00:00.000000000 to 2017-03-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-03-11T00:00:00.000000000 to 2018-02-22T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-02-22T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  51\n",
      "ind num 96 {'Peltogyne catingae Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-08-27T00:00:00.000000000' '2014-09-12T00:00:00.000000000'\n",
      " '2015-09-11T00:00:00.000000000' '2016-08-15T00:00:00.000000000'\n",
      " '2017-08-28T00:00:00.000000000' '2018-08-09T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-27T00:00:00.000000000 to 2014-09-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-12T00:00:00.000000000 to 2015-09-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-11T00:00:00.000000000 to 2016-08-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-15T00:00:00.000000000 to 2017-08-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-28T00:00:00.000000000 to 2018-08-09T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-09T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  52\n",
      "ind num 98 {'Taralea oppositifolia? Aubl.'} \n",
      "\n",
      "===== original dates in record ['2013-08-18T00:00:00.000000000' '2014-09-09T00:00:00.000000000'\n",
      " '2015-08-22T00:00:00.000000000' '2017-05-25T00:00:00.000000000'\n",
      " '2018-08-20T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-18T00:00:00.000000000 to 2014-09-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-09T00:00:00.000000000 to 2015-08-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-22T00:00:00.000000000 to 2017-05-25T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-25T00:00:00.000000000 to 2018-08-20T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-20T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  53\n",
      "ind num 99 {'Neea madeirana Standl.'} \n",
      "\n",
      "===== original dates in record ['2013-08-28T00:00:00.000000000' '2014-09-20T00:00:00.000000000'\n",
      " '2015-09-05T00:00:00.000000000' '2016-10-03T00:00:00.000000000'\n",
      " '2017-02-10T00:00:00.000000000' '2018-07-11T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-28T00:00:00.000000000 to 2014-09-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-20T00:00:00.000000000 to 2015-09-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-05T00:00:00.000000000 to 2016-10-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-03T00:00:00.000000000 to 2017-02-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-02-10T00:00:00.000000000 to 2018-07-11T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-11T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  54\n",
      "ind num 100 {'Stryphnodendron racemiferum? (Ducke) W.A.Rodrigues'} \n",
      "\n",
      "===== original dates in record ['2014-09-29T00:00:00.000000000' '2015-10-06T00:00:00.000000000'\n",
      " '2016-09-26T00:00:00.000000000' '2018-06-07T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-09-29T00:00:00.000000000 to 2015-10-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-10-06T00:00:00.000000000 to 2016-09-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-26T00:00:00.000000000 to 2018-06-07T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-07T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  55\n",
      "ind num 101 {'Licaria chrysophylla? (Meisn.) Kosterm.'} \n",
      "\n",
      "===== original dates in record ['2013-07-07T00:00:00.000000000' '2014-07-07T00:00:00.000000000'\n",
      " '2015-07-11T00:00:00.000000000' '2016-08-19T00:00:00.000000000'\n",
      " '2017-06-22T00:00:00.000000000' '2018-06-24T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-07T00:00:00.000000000 to 2014-07-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-07-07T00:00:00.000000000 to 2015-07-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-11T00:00:00.000000000 to 2016-08-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-19T00:00:00.000000000 to 2017-06-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-22T00:00:00.000000000 to 2018-06-24T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-24T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  56\n",
      "ind num 102 {'Matayba spruceana? (Benth.) Radlk.'} \n",
      "\n",
      "===== original dates in record ['2013-07-04T00:00:00.000000000' '2014-09-20T00:00:00.000000000'\n",
      " '2015-09-11T00:00:00.000000000' '2017-08-08T00:00:00.000000000'\n",
      " '2018-09-20T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-04T00:00:00.000000000 to 2014-09-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-20T00:00:00.000000000 to 2015-09-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-11T00:00:00.000000000 to 2017-08-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-08T00:00:00.000000000 to 2018-09-20T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-20T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  57\n",
      "ind num 103 {'Pouteria reticulata? (Engl.) Eyma'} \n",
      "\n",
      "===== original dates in record ['2013-11-26T00:00:00.000000000' '2014-12-06T00:00:00.000000000'\n",
      " '2016-12-24T00:00:00.000000000' '2017-10-30T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-11-26T00:00:00.000000000 to 2014-12-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-12-06T00:00:00.000000000 to 2016-12-24T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-12-24T00:00:00.000000000 to 2017-10-30T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-10-30T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  58\n",
      "ind num 105 {'Vataireopsis surinamensis? Lima'} \n",
      "\n",
      "===== original dates in record ['2013-08-24T00:00:00.000000000' '2014-08-07T00:00:00.000000000'\n",
      " '2015-08-30T00:00:00.000000000' '2016-01-29T00:00:00.000000000'\n",
      " '2016-09-17T00:00:00.000000000' '2017-08-12T00:00:00.000000000'\n",
      " '2018-08-28T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-24T00:00:00.000000000 to 2014-08-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-07T00:00:00.000000000 to 2015-08-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-30T00:00:00.000000000 to 2016-01-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-01-29T00:00:00.000000000 to 2016-09-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-17T00:00:00.000000000 to 2017-08-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-12T00:00:00.000000000 to 2018-08-28T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-28T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  59\n",
      "ind num 106 {'Eschweilera micrantha? (O.Berg) Miers'} \n",
      "\n",
      "===== original dates in record ['2015-02-13T00:00:00.000000000' '2016-06-06T00:00:00.000000000'\n",
      " '2017-07-10T00:00:00.000000000' '2018-06-01T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2015-02-13T00:00:00.000000000 to 2016-06-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-06-06T00:00:00.000000000 to 2017-07-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-10T00:00:00.000000000 to 2018-06-01T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-01T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  60\n",
      "ind num 107 {'Scleronema micranthum (Ducke) Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-04-19T00:00:00.000000000' '2015-04-26T00:00:00.000000000'\n",
      " '2016-12-05T00:00:00.000000000' '2017-06-09T00:00:00.000000000'\n",
      " '2018-02-27T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-04-19T00:00:00.000000000 to 2015-04-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-04-26T00:00:00.000000000 to 2016-12-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-12-05T00:00:00.000000000 to 2017-06-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-09T00:00:00.000000000 to 2018-02-27T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-02-27T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  61\n",
      "ind num 109 {'Erisma calcaratum (Link) Warm'} \n",
      "\n",
      "===== original dates in record ['2014-02-16T00:00:00.000000000' '2016-09-01T00:00:00.000000000'\n",
      " '2018-08-18T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-02-16T00:00:00.000000000 to 2016-09-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-01T00:00:00.000000000 to 2018-08-18T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-18T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  62\n",
      "ind num 110 {nan} \n",
      "\n",
      "===== original dates in record ['2013-07-20T00:00:00.000000000' '2014-08-30T00:00:00.000000000'\n",
      " '2016-03-06T00:00:00.000000000' '2017-06-16T00:00:00.000000000'\n",
      " '2018-09-03T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-20T00:00:00.000000000 to 2014-08-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-30T00:00:00.000000000 to 2016-03-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-06T00:00:00.000000000 to 2017-06-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-16T00:00:00.000000000 to 2018-09-03T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-03T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  63\n",
      "ind num 111 {'Astronium spp.'} \n",
      "\n",
      "===== original dates in record ['2013-08-23T00:00:00.000000000' '2014-08-30T00:00:00.000000000'\n",
      " '2015-08-05T00:00:00.000000000' '2016-09-12T00:00:00.000000000'\n",
      " '2017-08-14T00:00:00.000000000' '2018-08-26T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-23T00:00:00.000000000 to 2014-08-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-30T00:00:00.000000000 to 2015-08-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-05T00:00:00.000000000 to 2016-09-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-12T00:00:00.000000000 to 2017-08-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-14T00:00:00.000000000 to 2018-08-26T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-26T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  64\n",
      "ind num 114 {'Brosimum parinarioides Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-10-28T00:00:00.000000000' '2015-09-11T00:00:00.000000000'\n",
      " '2016-03-25T00:00:00.000000000' '2017-11-14T00:00:00.000000000'\n",
      " '2018-09-06T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-28T00:00:00.000000000 to 2015-09-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-11T00:00:00.000000000 to 2016-03-25T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-25T00:00:00.000000000 to 2017-11-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-11-14T00:00:00.000000000 to 2018-09-06T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-06T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  65\n",
      "ind num 116 {'Dicypellium manausense? W.A.Rodrigues'} \n",
      "\n",
      "===== original dates in record ['2013-08-31T00:00:00.000000000' '2014-09-18T00:00:00.000000000'\n",
      " '2015-09-14T00:00:00.000000000' '2016-09-27T00:00:00.000000000'\n",
      " '2017-02-12T00:00:00.000000000' '2018-07-07T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-31T00:00:00.000000000 to 2014-09-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-18T00:00:00.000000000 to 2015-09-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-14T00:00:00.000000000 to 2016-09-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-27T00:00:00.000000000 to 2017-02-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-02-12T00:00:00.000000000 to 2018-07-07T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-07T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  66\n",
      "ind num 117 {'Abarema cochleata (Willd.) Barneby & J.W.Grimes'} \n",
      "\n",
      "===== original dates in record ['2013-08-13T00:00:00.000000000' '2017-09-06T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-13T00:00:00.000000000 to 2017-09-06T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-09-06T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  67\n",
      "ind num 119 {'Pouteria reticulata? (Engl.) Eyma'} \n",
      "\n",
      "===== original dates in record ['2014-10-24T00:00:00.000000000' '2015-05-12T00:00:00.000000000'\n",
      " '2016-09-01T00:00:00.000000000' '2016-12-08T00:00:00.000000000'\n",
      " '2018-06-25T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-10-24T00:00:00.000000000 to 2015-05-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-05-12T00:00:00.000000000 to 2016-09-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-01T00:00:00.000000000 to 2016-12-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-12-08T00:00:00.000000000 to 2018-06-25T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-25T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  68\n",
      "ind num 120 {'Cariniana decandra? Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-10-04T00:00:00.000000000' '2015-07-22T00:00:00.000000000'\n",
      " '2016-08-21T00:00:00.000000000' '2017-08-11T00:00:00.000000000'\n",
      " '2018-10-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-04T00:00:00.000000000 to 2015-07-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-22T00:00:00.000000000 to 2016-08-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-21T00:00:00.000000000 to 2017-08-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-11T00:00:00.000000000 to 2018-10-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  69\n",
      "ind num 122 {'Mezilaurus duckei? van der Werff'} \n",
      "\n",
      "===== original dates in record ['2014-09-09T00:00:00.000000000' '2016-09-03T00:00:00.000000000'\n",
      " '2018-06-12T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-09-09T00:00:00.000000000 to 2016-09-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-03T00:00:00.000000000 to 2018-06-12T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-12T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  70\n",
      "ind num 123 {'Eschweilera cyathiformis? S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-07-04T00:00:00.000000000' '2016-02-18T00:00:00.000000000'\n",
      " '2017-06-23T00:00:00.000000000' '2018-10-31T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-07-04T00:00:00.000000000 to 2016-02-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-02-18T00:00:00.000000000 to 2017-06-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-23T00:00:00.000000000 to 2018-10-31T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-31T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  71\n",
      "ind num 125 {'Scleronema micranthum (Ducke) Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-04-26T00:00:00.000000000' '2015-06-12T00:00:00.000000000'\n",
      " '2016-07-10T00:00:00.000000000' '2017-05-22T00:00:00.000000000'\n",
      " '2018-06-25T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-04-26T00:00:00.000000000 to 2015-06-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-12T00:00:00.000000000 to 2016-07-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-10T00:00:00.000000000 to 2017-05-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-22T00:00:00.000000000 to 2018-06-25T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-25T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  72\n",
      "ind num 126 {'Virola guggenheimii W.A. Rodrigues'} \n",
      "\n",
      "===== original dates in record ['2013-12-17T00:00:00.000000000' '2014-09-08T00:00:00.000000000'\n",
      " '2015-07-15T00:00:00.000000000' '2016-06-28T00:00:00.000000000'\n",
      " '2017-07-21T00:00:00.000000000' '2018-08-08T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-12-17T00:00:00.000000000 to 2014-09-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-08T00:00:00.000000000 to 2015-07-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-15T00:00:00.000000000 to 2016-06-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-06-28T00:00:00.000000000 to 2017-07-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-21T00:00:00.000000000 to 2018-08-08T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-08T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  73\n",
      "ind num 129 {'Balizia elegans? (Ducke) Barneby & J.W.Grimes'} \n",
      "\n",
      "===== original dates in record ['2013-11-18T00:00:00.000000000' '2014-11-01T00:00:00.000000000'\n",
      " '2015-11-13T00:00:00.000000000' '2016-03-06T00:00:00.000000000'\n",
      " '2017-06-23T00:00:00.000000000' '2018-09-20T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-11-18T00:00:00.000000000 to 2014-11-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-11-01T00:00:00.000000000 to 2015-11-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-11-13T00:00:00.000000000 to 2016-03-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-06T00:00:00.000000000 to 2017-06-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-23T00:00:00.000000000 to 2018-09-20T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-20T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  74\n",
      "ind num 130 {'Sterculia excelsa Mart.'} \n",
      "\n",
      "===== original dates in record ['2013-08-15T00:00:00.000000000' '2014-09-28T00:00:00.000000000'\n",
      " '2015-08-11T00:00:00.000000000' '2016-09-30T00:00:00.000000000'\n",
      " '2017-10-22T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-15T00:00:00.000000000 to 2014-09-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-28T00:00:00.000000000 to 2015-08-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-11T00:00:00.000000000 to 2016-09-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-30T00:00:00.000000000 to 2017-10-22T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-10-22T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  75\n",
      "ind num 131 {'Swartzia recurva? Poepp.'} \n",
      "\n",
      "===== original dates in record ['2014-01-03T00:00:00.000000000' '2014-06-09T00:00:00.000000000'\n",
      " '2016-07-24T00:00:00.000000000' '2017-06-04T00:00:00.000000000'\n",
      " '2018-10-18T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-01-03T00:00:00.000000000 to 2014-06-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-06-09T00:00:00.000000000 to 2016-07-24T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-24T00:00:00.000000000 to 2017-06-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-04T00:00:00.000000000 to 2018-10-18T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-18T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  76\n",
      "ind num 133 {'Aspidosperma spruceanum? Benth. ex Mull.Arg.'} \n",
      "\n",
      "===== original dates in record ['2013-08-18T00:00:00.000000000' '2014-09-13T00:00:00.000000000'\n",
      " '2015-09-30T00:00:00.000000000' '2016-09-08T00:00:00.000000000'\n",
      " '2017-08-22T00:00:00.000000000' '2018-10-04T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-18T00:00:00.000000000 to 2014-09-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-13T00:00:00.000000000 to 2015-09-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-30T00:00:00.000000000 to 2016-09-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-08T00:00:00.000000000 to 2017-08-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-22T00:00:00.000000000 to 2018-10-04T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-04T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  77\n",
      "ind num 134 {'Rhodostemonodaphne grandis (Mez) Rohwer'} \n",
      "\n",
      "===== original dates in record ['2014-09-04T00:00:00.000000000' '2015-08-22T00:00:00.000000000'\n",
      " '2016-09-29T00:00:00.000000000' '2017-07-18T00:00:00.000000000'\n",
      " '2018-08-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-09-04T00:00:00.000000000 to 2015-08-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-22T00:00:00.000000000 to 2016-09-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-29T00:00:00.000000000 to 2017-07-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-18T00:00:00.000000000 to 2018-08-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  78\n",
      "ind num 135 {'Eschweilera cyathiformis? S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-06-30T00:00:00.000000000' '2015-07-09T00:00:00.000000000'\n",
      " '2016-03-07T00:00:00.000000000' '2017-06-11T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-30T00:00:00.000000000 to 2015-07-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-09T00:00:00.000000000 to 2016-03-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-07T00:00:00.000000000 to 2017-06-11T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-06-11T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  79\n",
      "ind num 138 {'Handroanthus impetiginosus (Mart. ex DC.) Mattos'} \n",
      "\n",
      "===== original dates in record ['2013-09-24T00:00:00.000000000' '2014-09-23T00:00:00.000000000'\n",
      " '2015-09-25T00:00:00.000000000' '2017-05-25T00:00:00.000000000'\n",
      " '2018-06-09T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-09-24T00:00:00.000000000 to 2014-09-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-23T00:00:00.000000000 to 2015-09-25T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-25T00:00:00.000000000 to 2017-05-25T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-25T00:00:00.000000000 to 2018-06-09T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-09T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  80\n",
      "ind num 140 {'Pouteria guianensis Aubl.'} \n",
      "\n",
      "===== original dates in record ['2013-09-25T00:00:00.000000000' '2014-10-28T00:00:00.000000000'\n",
      " '2016-02-11T00:00:00.000000000' '2016-12-08T00:00:00.000000000'\n",
      " '2017-10-25T00:00:00.000000000' '2018-10-10T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-09-25T00:00:00.000000000 to 2014-10-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-28T00:00:00.000000000 to 2016-02-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-02-11T00:00:00.000000000 to 2016-12-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-12-08T00:00:00.000000000 to 2017-10-25T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-10-25T00:00:00.000000000 to 2018-10-10T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-10T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  81\n",
      "ind num 142 {'Ormosia paraensis Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-10-08T00:00:00.000000000' '2014-09-26T00:00:00.000000000'\n",
      " '2015-09-11T00:00:00.000000000' '2016-09-17T00:00:00.000000000'\n",
      " '2017-09-24T00:00:00.000000000' '2018-09-10T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-08T00:00:00.000000000 to 2014-09-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-26T00:00:00.000000000 to 2015-09-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-11T00:00:00.000000000 to 2016-09-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-17T00:00:00.000000000 to 2017-09-24T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-24T00:00:00.000000000 to 2018-09-10T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-10T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  82\n",
      "ind num 143 {'Pouteria manaosensis? (Aubrév. & Pellegr.) T.D.Penn.'} \n",
      "\n",
      "===== original dates in record ['2014-07-30T00:00:00.000000000' '2015-07-22T00:00:00.000000000'\n",
      " '2016-08-07T00:00:00.000000000' '2017-08-21T00:00:00.000000000'\n",
      " '2018-08-26T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-07-30T00:00:00.000000000 to 2015-07-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-22T00:00:00.000000000 to 2016-08-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-07T00:00:00.000000000 to 2017-08-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-21T00:00:00.000000000 to 2018-08-26T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-26T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  83\n",
      "ind num 144 {'Eschweilera pedicellata (Rich.) S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-05-29T00:00:00.000000000' '2015-08-04T00:00:00.000000000'\n",
      " '2017-06-15T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-05-29T00:00:00.000000000 to 2015-08-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-04T00:00:00.000000000 to 2017-06-15T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-06-15T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  84\n",
      "ind num 149 {'Ocotea cujumary? Mart.'} \n",
      "\n",
      "===== original dates in record ['2014-08-03T00:00:00.000000000' '2015-07-22T00:00:00.000000000'\n",
      " '2016-07-02T00:00:00.000000000' '2017-06-29T00:00:00.000000000'\n",
      " '2018-06-17T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-08-03T00:00:00.000000000 to 2015-07-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-22T00:00:00.000000000 to 2016-07-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-02T00:00:00.000000000 to 2017-06-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-29T00:00:00.000000000 to 2018-06-17T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-17T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  85\n",
      "ind num 150 {'Eschweilera truncata A.C.Sm.'} \n",
      "\n",
      "===== original dates in record ['2014-06-25T00:00:00.000000000' '2015-06-14T00:00:00.000000000'\n",
      " '2017-06-11T00:00:00.000000000' '2018-08-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-25T00:00:00.000000000 to 2015-06-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-14T00:00:00.000000000 to 2017-06-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-11T00:00:00.000000000 to 2018-08-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  86\n",
      "ind num 151 {'Pouteria cuspidata? (A.DC.) Baehni'} \n",
      "\n",
      "===== original dates in record ['2014-03-14T00:00:00.000000000' '2015-06-11T00:00:00.000000000'\n",
      " '2017-01-13T00:00:00.000000000' '2018-04-30T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-03-14T00:00:00.000000000 to 2015-06-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-11T00:00:00.000000000 to 2017-01-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-01-13T00:00:00.000000000 to 2018-04-30T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-04-30T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  87\n",
      "ind num 152 {'Mouriri guianensis Aubl.'} \n",
      "\n",
      "===== original dates in record ['2014-08-11T00:00:00.000000000' '2016-08-30T00:00:00.000000000'\n",
      " '2017-07-24T00:00:00.000000000' '2018-08-08T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-08-11T00:00:00.000000000 to 2016-08-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-30T00:00:00.000000000 to 2017-07-24T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-24T00:00:00.000000000 to 2018-08-08T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-08T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  88\n",
      "ind num 154 {'Duroia macrophylla? Huber'} \n",
      "\n",
      "===== original dates in record ['2013-07-05T00:00:00.000000000' '2014-07-09T00:00:00.000000000'\n",
      " '2015-07-05T00:00:00.000000000' '2016-03-14T00:00:00.000000000'\n",
      " '2017-06-24T00:00:00.000000000' '2018-06-17T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-05T00:00:00.000000000 to 2014-07-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-07-09T00:00:00.000000000 to 2015-07-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-05T00:00:00.000000000 to 2016-03-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-14T00:00:00.000000000 to 2017-06-24T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-24T00:00:00.000000000 to 2018-06-17T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-17T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  89\n",
      "ind num 155 {'Eperua glabriflora (Ducke) Cowan'} \n",
      "\n",
      "===== original dates in record ['2014-03-14T00:00:00.000000000' '2016-04-01T00:00:00.000000000'\n",
      " '2018-07-29T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-03-14T00:00:00.000000000 to 2016-04-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-04-01T00:00:00.000000000 to 2018-07-29T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-29T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  90\n",
      "ind num 158 {'Pouteria ambelaniifolia (Sandwith) T.D.Penn.'} \n",
      "\n",
      "===== original dates in record ['2016-09-02T00:00:00.000000000' '2017-12-27T00:00:00.000000000'\n",
      " '2018-07-10T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2016-09-02T00:00:00.000000000 to 2017-12-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-12-27T00:00:00.000000000 to 2018-07-10T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-10T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  91\n",
      "ind num 159 {'Couratari tauari O.Berg'} \n",
      "\n",
      "===== original dates in record ['2013-10-21T00:00:00.000000000' '2015-08-23T00:00:00.000000000'\n",
      " '2017-09-10T00:00:00.000000000' '2018-10-18T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-21T00:00:00.000000000 to 2015-08-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-23T00:00:00.000000000 to 2017-09-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-10T00:00:00.000000000 to 2018-10-18T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-18T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  92\n",
      "ind num 163 {'Erisma spp.'} \n",
      "\n",
      "===== original dates in record ['2013-08-09T00:00:00.000000000' '2014-07-07T00:00:00.000000000'\n",
      " '2015-09-11T00:00:00.000000000' '2016-09-01T00:00:00.000000000'\n",
      " '2017-09-15T00:00:00.000000000' '2018-08-11T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-09T00:00:00.000000000 to 2014-07-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-07-07T00:00:00.000000000 to 2015-09-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-11T00:00:00.000000000 to 2016-09-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-01T00:00:00.000000000 to 2017-09-15T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-15T00:00:00.000000000 to 2018-08-11T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-11T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  93\n",
      "ind num 164 {'Buchenavia parvifolia Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-09-03T00:00:00.000000000' '2014-10-01T00:00:00.000000000'\n",
      " '2015-09-26T00:00:00.000000000' '2016-08-10T00:00:00.000000000'\n",
      " '2016-11-29T00:00:00.000000000' '2017-10-16T00:00:00.000000000'\n",
      " '2018-08-30T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-09-03T00:00:00.000000000 to 2014-10-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-01T00:00:00.000000000 to 2015-09-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-26T00:00:00.000000000 to 2016-08-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-10T00:00:00.000000000 to 2016-11-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-11-29T00:00:00.000000000 to 2017-10-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-10-16T00:00:00.000000000 to 2018-08-30T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-30T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  94\n",
      "ind num 165 {'Eperua glabriflora (Ducke) Cowan'} \n",
      "\n",
      "===== original dates in record ['2013-09-03T00:00:00.000000000' '2014-10-01T00:00:00.000000000'\n",
      " '2015-09-27T00:00:00.000000000' '2016-08-11T00:00:00.000000000'\n",
      " '2016-11-29T00:00:00.000000000' '2017-10-16T00:00:00.000000000'\n",
      " '2018-09-09T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-09-03T00:00:00.000000000 to 2014-10-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-01T00:00:00.000000000 to 2015-09-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-27T00:00:00.000000000 to 2016-08-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-11T00:00:00.000000000 to 2016-11-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-11-29T00:00:00.000000000 to 2017-10-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-10-16T00:00:00.000000000 to 2018-09-09T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-09T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  95\n",
      "ind num 166 {'Tachigali micropetala (Ducke) Zarucchi & Pipoly'} \n",
      "\n",
      "===== original dates in record ['2013-10-16T00:00:00.000000000' '2014-09-03T00:00:00.000000000'\n",
      " '2015-09-01T00:00:00.000000000' '2016-10-01T00:00:00.000000000'\n",
      " '2017-08-16T00:00:00.000000000' '2018-08-22T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-16T00:00:00.000000000 to 2014-09-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-03T00:00:00.000000000 to 2015-09-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-01T00:00:00.000000000 to 2016-10-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-01T00:00:00.000000000 to 2017-08-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-16T00:00:00.000000000 to 2018-08-22T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-22T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  96\n",
      "ind num 169 {'Micropholis cylindrocarpa? (Poepp.) Pierre'} \n",
      "\n",
      "===== original dates in record ['2014-07-11T00:00:00.000000000' '2015-07-05T00:00:00.000000000'\n",
      " '2017-06-11T00:00:00.000000000' '2018-07-12T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-07-11T00:00:00.000000000 to 2015-07-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-05T00:00:00.000000000 to 2017-06-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-11T00:00:00.000000000 to 2018-07-12T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-12T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  97\n",
      "ind num 173 {'Rinorea guianensis Aubl.'} \n",
      "\n",
      "===== original dates in record ['2013-10-02T00:00:00.000000000' '2017-11-13T00:00:00.000000000'\n",
      " '2018-10-29T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-02T00:00:00.000000000 to 2017-11-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-11-13T00:00:00.000000000 to 2018-10-29T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-29T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  98\n",
      "ind num 175 {'Micrandropsis scleroxylon (W.A.Rodrigues) W.A.Rodrigues'} \n",
      "\n",
      "===== original dates in record ['2014-07-05T00:00:00.000000000' '2015-08-21T00:00:00.000000000'\n",
      " '2016-09-04T00:00:00.000000000' '2017-07-21T00:00:00.000000000'\n",
      " '2018-08-03T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-07-05T00:00:00.000000000 to 2015-08-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-21T00:00:00.000000000 to 2016-09-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-04T00:00:00.000000000 to 2017-07-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-21T00:00:00.000000000 to 2018-08-03T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-03T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  99\n",
      "ind num 177 {'Ormosia paraensis Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-07-17T00:00:00.000000000' '2014-09-22T00:00:00.000000000'\n",
      " '2015-09-17T00:00:00.000000000' '2016-09-19T00:00:00.000000000'\n",
      " '2017-09-03T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-17T00:00:00.000000000 to 2014-09-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-09-22T00:00:00.000000000 to 2015-09-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-17T00:00:00.000000000 to 2016-09-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-19T00:00:00.000000000 to 2017-09-03T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-09-03T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  100\n",
      "ind num 179 {'Eschweilera bracteosa (Poepp. ex O.Berg) Miers'} \n",
      "\n",
      "===== original dates in record ['2013-07-27T00:00:00.000000000' '2014-08-09T00:00:00.000000000'\n",
      " '2015-06-27T00:00:00.000000000' '2017-08-23T00:00:00.000000000'\n",
      " '2018-09-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-27T00:00:00.000000000 to 2014-08-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-09T00:00:00.000000000 to 2015-06-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-27T00:00:00.000000000 to 2017-08-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-23T00:00:00.000000000 to 2018-09-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  101\n",
      "ind num 180 {'Cariniana micrantha? Ducke'} \n",
      "\n",
      "===== original dates in record ['2013-10-24T00:00:00.000000000' '2014-11-11T00:00:00.000000000'\n",
      " '2015-10-26T00:00:00.000000000' '2016-12-11T00:00:00.000000000'\n",
      " '2017-10-26T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-24T00:00:00.000000000 to 2014-11-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-11-11T00:00:00.000000000 to 2015-10-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-10-26T00:00:00.000000000 to 2016-12-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-12-11T00:00:00.000000000 to 2017-10-26T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-10-26T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  102\n",
      "ind num 181 {'Buchenavia tomentosa? Eichler'} \n",
      "\n",
      "===== original dates in record ['2014-09-16T00:00:00.000000000' '2015-12-04T00:00:00.000000000'\n",
      " '2016-08-18T00:00:00.000000000' '2017-08-04T00:00:00.000000000'\n",
      " '2018-09-19T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-09-16T00:00:00.000000000 to 2015-12-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-12-04T00:00:00.000000000 to 2016-08-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-18T00:00:00.000000000 to 2017-08-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-08-04T00:00:00.000000000 to 2018-09-19T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-19T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  103\n",
      "ind num 182 {'Micrandropsis scleroxylon (W.A.Rodrigues) W.A.Rodrigues'} \n",
      "\n",
      "===== original dates in record ['2013-08-04T00:00:00.000000000' '2016-03-09T00:00:00.000000000'\n",
      " '2016-08-29T00:00:00.000000000' '2017-06-05T00:00:00.000000000'\n",
      " '2018-07-04T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-04T00:00:00.000000000 to 2016-03-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-09T00:00:00.000000000 to 2016-08-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-29T00:00:00.000000000 to 2017-06-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-05T00:00:00.000000000 to 2018-07-04T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-04T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  104\n",
      "ind num 183 {'Pouteria pallens T.D.Penn.'} \n",
      "\n",
      "===== original dates in record ['2013-11-13T00:00:00.000000000' '2015-02-09T00:00:00.000000000'\n",
      " '2016-08-19T00:00:00.000000000' '2018-05-21T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-11-13T00:00:00.000000000 to 2015-02-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-02-09T00:00:00.000000000 to 2016-08-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-19T00:00:00.000000000 to 2018-05-21T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-05-21T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  105\n",
      "ind num 184 {'Ecclinusa guianensis? Eyma forma A'} \n",
      "\n",
      "===== original dates in record ['2013-07-05T00:00:00.000000000' '2014-06-29T00:00:00.000000000'\n",
      " '2015-08-05T00:00:00.000000000' '2016-08-08T00:00:00.000000000'\n",
      " '2017-06-01T00:00:00.000000000' '2018-06-16T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-05T00:00:00.000000000 to 2014-06-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-06-29T00:00:00.000000000 to 2015-08-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-05T00:00:00.000000000 to 2016-08-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-08T00:00:00.000000000 to 2017-06-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-01T00:00:00.000000000 to 2018-06-16T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-16T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  106\n",
      "ind num 185 {'Goupia glabra Aubl.'} \n",
      "\n",
      "===== original dates in record ['2014-06-06T00:00:00.000000000' '2015-05-30T00:00:00.000000000'\n",
      " '2016-07-20T00:00:00.000000000' '2017-06-01T00:00:00.000000000'\n",
      " '2018-06-07T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-06T00:00:00.000000000 to 2015-05-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-05-30T00:00:00.000000000 to 2016-07-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-20T00:00:00.000000000 to 2017-06-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-01T00:00:00.000000000 to 2018-06-07T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-07T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  107\n",
      "ind num 186 {'Eschweilera pseudodecolorans S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2014-09-05T00:00:00.000000000' '2015-08-23T00:00:00.000000000'\n",
      " '2016-03-07T00:00:00.000000000' '2017-05-28T00:00:00.000000000'\n",
      " '2018-08-18T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-09-05T00:00:00.000000000 to 2015-08-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-23T00:00:00.000000000 to 2016-03-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-07T00:00:00.000000000 to 2017-05-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-28T00:00:00.000000000 to 2018-08-18T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-18T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  108\n",
      "ind num 187 {'Parkia multijuga Benth.'} \n",
      "\n",
      "===== original dates in record ['2013-10-13T00:00:00.000000000' '2014-11-01T00:00:00.000000000'\n",
      " '2015-08-07T00:00:00.000000000' '2016-06-19T00:00:00.000000000'\n",
      " '2017-06-14T00:00:00.000000000' '2018-09-17T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-13T00:00:00.000000000 to 2014-11-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-11-01T00:00:00.000000000 to 2015-08-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-07T00:00:00.000000000 to 2016-06-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-06-19T00:00:00.000000000 to 2017-06-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-14T00:00:00.000000000 to 2018-09-17T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-17T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  109\n",
      "ind num 188 {'Rhodostemonodaphne grandis (Mez) Rohwer'} \n",
      "\n",
      "===== original dates in record ['2013-07-18T00:00:00.000000000' '2014-08-10T00:00:00.000000000'\n",
      " '2015-08-05T00:00:00.000000000' '2016-08-21T00:00:00.000000000'\n",
      " '2017-06-20T00:00:00.000000000' '2018-07-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-18T00:00:00.000000000 to 2014-08-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-10T00:00:00.000000000 to 2015-08-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-05T00:00:00.000000000 to 2016-08-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-21T00:00:00.000000000 to 2017-06-20T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-20T00:00:00.000000000 to 2018-07-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  110\n",
      "ind num 189 {'Brosimum parinarioides Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-01-06T00:00:00.000000000' '2015-08-23T00:00:00.000000000'\n",
      " '2017-05-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-01-06T00:00:00.000000000 to 2015-08-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-23T00:00:00.000000000 to 2017-05-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-05-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  111\n",
      "ind num 190 {'Roucheria columbiana? Hallier f.'} \n",
      "\n",
      "===== original dates in record ['2014-05-23T00:00:00.000000000' '2015-05-14T00:00:00.000000000'\n",
      " '2017-01-03T00:00:00.000000000' '2018-05-10T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-05-23T00:00:00.000000000 to 2015-05-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-05-14T00:00:00.000000000 to 2017-01-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-01-03T00:00:00.000000000 to 2018-05-10T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-05-10T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  112\n",
      "ind num 193 {'Calyptranthes forsteri O.Berg'} \n",
      "\n",
      "===== original dates in record ['2014-06-15T00:00:00.000000000' '2015-06-06T00:00:00.000000000'\n",
      " '2016-05-05T00:00:00.000000000' '2016-07-28T00:00:00.000000000'\n",
      " '2016-12-04T00:00:00.000000000' '2017-09-06T00:00:00.000000000'\n",
      " '2018-07-31T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-15T00:00:00.000000000 to 2015-06-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-06T00:00:00.000000000 to 2016-05-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-05-05T00:00:00.000000000 to 2016-07-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-28T00:00:00.000000000 to 2016-12-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-12-04T00:00:00.000000000 to 2017-09-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-09-06T00:00:00.000000000 to 2018-07-31T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-31T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  113\n",
      "ind num 194 {'Micropholis spp'} \n",
      "\n",
      "===== original dates in record ['2013-07-14T00:00:00.000000000' '2015-06-26T00:00:00.000000000'\n",
      " '2017-06-23T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-14T00:00:00.000000000 to 2015-06-26T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-26T00:00:00.000000000 to 2017-06-23T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-06-23T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  114\n",
      "ind num 199 {'Pouteria cuspidata? (A.DC.) Baehni'} \n",
      "\n",
      "===== original dates in record ['2013-07-05T00:00:00.000000000' '2015-05-04T00:00:00.000000000'\n",
      " '2016-09-16T00:00:00.000000000' '2017-11-01T00:00:00.000000000'\n",
      " '2018-10-14T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-05T00:00:00.000000000 to 2015-05-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-05-04T00:00:00.000000000 to 2016-09-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-16T00:00:00.000000000 to 2017-11-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-11-01T00:00:00.000000000 to 2018-10-14T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-14T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  115\n",
      "ind num 200 {'Lecythis parvifructa S.A.Mori'} \n",
      "\n",
      "===== original dates in record ['2013-08-06T00:00:00.000000000' '2015-07-28T00:00:00.000000000'\n",
      " '2017-08-01T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-06T00:00:00.000000000 to 2015-07-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-28T00:00:00.000000000 to 2017-08-01T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-08-01T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  116\n",
      "ind num 202 {'Poecilanthe amazonica? (Ducke) Ducke'} \n",
      "\n",
      "===== original dates in record ['2016-02-02T00:00:00.000000000' '2017-01-12T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2016-02-02T00:00:00.000000000 to 2017-01-12T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-01-12T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  117\n",
      "ind num 204 {'Inga paraensis? Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-06-17T00:00:00.000000000' '2015-06-08T00:00:00.000000000'\n",
      " '2016-07-28T00:00:00.000000000' '2017-06-04T00:00:00.000000000'\n",
      " '2018-07-06T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-17T00:00:00.000000000 to 2015-06-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-08T00:00:00.000000000 to 2016-07-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-28T00:00:00.000000000 to 2017-06-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-04T00:00:00.000000000 to 2018-07-06T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-06T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  118\n",
      "ind num 207 {'Chimarrhis duckeana? Delprete'} \n",
      "\n",
      "===== original dates in record ['2014-06-25T00:00:00.000000000' '2015-06-23T00:00:00.000000000'\n",
      " '2016-07-21T00:00:00.000000000' '2017-05-31T00:00:00.000000000'\n",
      " '2018-06-08T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-25T00:00:00.000000000 to 2015-06-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-23T00:00:00.000000000 to 2016-07-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-21T00:00:00.000000000 to 2017-05-31T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-31T00:00:00.000000000 to 2018-06-08T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-08T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  119\n",
      "ind num 208 {'Pouteria macrophylla? (Lam.) Eyma'} \n",
      "\n",
      "===== original dates in record ['2013-07-11T00:00:00.000000000' '2014-08-17T00:00:00.000000000'\n",
      " '2015-07-11T00:00:00.000000000' '2016-07-29T00:00:00.000000000'\n",
      " '2017-05-01T00:00:00.000000000' '2018-07-20T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-07-11T00:00:00.000000000 to 2014-08-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-17T00:00:00.000000000 to 2015-07-11T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-11T00:00:00.000000000 to 2016-07-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-29T00:00:00.000000000 to 2017-05-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-01T00:00:00.000000000 to 2018-07-20T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-20T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  120\n",
      "ind num 210 {'Zygia racemosa (Ducke) Barneby & J.W. Grimes'} \n",
      "\n",
      "===== original dates in record ['2013-10-17T00:00:00.000000000' '2015-09-28T00:00:00.000000000'\n",
      " '2017-06-21T00:00:00.000000000' '2018-11-08T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-17T00:00:00.000000000 to 2015-09-28T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-28T00:00:00.000000000 to 2017-06-21T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-21T00:00:00.000000000 to 2018-11-08T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-11-08T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  121\n",
      "ind num 211 {'Inga laurina (Sw.) Willd.'} \n",
      "\n",
      "===== original dates in record ['2014-06-12T00:00:00.000000000' '2015-04-22T00:00:00.000000000'\n",
      " '2016-08-08T00:00:00.000000000' '2017-05-21T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-12T00:00:00.000000000 to 2015-04-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-04-22T00:00:00.000000000 to 2016-08-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-08T00:00:00.000000000 to 2017-05-21T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-05-21T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  122\n",
      "ind num 212 {'Minquartia guianensis Aubl.'} \n",
      "\n",
      "===== original dates in record ['2014-01-03T00:00:00.000000000' '2014-06-07T00:00:00.000000000'\n",
      " '2015-08-13T00:00:00.000000000' '2016-07-27T00:00:00.000000000'\n",
      " '2017-06-10T00:00:00.000000000' '2018-04-03T00:00:00.000000000'\n",
      " '2018-07-02T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-01-03T00:00:00.000000000 to 2014-06-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-06-07T00:00:00.000000000 to 2015-08-13T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-13T00:00:00.000000000 to 2016-07-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-27T00:00:00.000000000 to 2017-06-10T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-10T00:00:00.000000000 to 2018-04-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2018-04-03T00:00:00.000000000 to 2018-07-02T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-02T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  123\n",
      "ind num 215 {'Clarisia racemosa? Ruiz & Pav.'} \n",
      "\n",
      "===== original dates in record ['2014-05-15T00:00:00.000000000' '2014-12-04T00:00:00.000000000'\n",
      " '2015-07-03T00:00:00.000000000' '2016-06-22T00:00:00.000000000'\n",
      " '2017-05-23T00:00:00.000000000' '2018-06-25T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-05-15T00:00:00.000000000 to 2014-12-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-12-04T00:00:00.000000000 to 2015-07-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-03T00:00:00.000000000 to 2016-06-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-06-22T00:00:00.000000000 to 2017-05-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-05-23T00:00:00.000000000 to 2018-06-25T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-25T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  124\n",
      "ind num 217 {'Tachigali micropetala (Ducke) Zarucchi & Pipoly'} \n",
      "\n",
      "===== original dates in record ['2013-08-02T00:00:00.000000000' '2014-06-17T00:00:00.000000000'\n",
      " '2015-07-16T00:00:00.000000000' '2017-06-12T00:00:00.000000000'\n",
      " '2018-08-16T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-02T00:00:00.000000000 to 2014-06-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-06-17T00:00:00.000000000 to 2015-07-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-16T00:00:00.000000000 to 2017-06-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-12T00:00:00.000000000 to 2018-08-16T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-16T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  125\n",
      "ind num 220 {'Ormosia schunkei? Rudd'} \n",
      "\n",
      "===== original dates in record ['2013-08-27T00:00:00.000000000' '2015-09-03T00:00:00.000000000'\n",
      " '2016-09-17T00:00:00.000000000' '2018-08-10T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-27T00:00:00.000000000 to 2015-09-03T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-09-03T00:00:00.000000000 to 2016-09-17T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-09-17T00:00:00.000000000 to 2018-08-10T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-10T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  126\n",
      "ind num 221 {'Licania heteromorpha? Benth.'} \n",
      "\n",
      "===== original dates in record ['2014-04-26T00:00:00.000000000' '2015-06-06T00:00:00.000000000'\n",
      " '2015-07-14T00:00:00.000000000' '2016-11-04T00:00:00.000000000'\n",
      " '2017-06-04T00:00:00.000000000' '2018-05-22T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-04-26T00:00:00.000000000 to 2015-06-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-06T00:00:00.000000000 to 2015-07-14T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-14T00:00:00.000000000 to 2016-11-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-11-04T00:00:00.000000000 to 2017-06-04T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-04T00:00:00.000000000 to 2018-05-22T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-05-22T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  127\n",
      "ind num 222 {'Maquira guianensis Aubl.'} \n",
      "\n",
      "===== original dates in record ['2013-08-08T00:00:00.000000000' '2015-07-07T00:00:00.000000000'\n",
      " '2016-03-09T00:00:00.000000000' '2016-10-01T00:00:00.000000000'\n",
      " '2017-11-30T00:00:00.000000000' '2018-01-19T00:00:00.000000000'\n",
      " '2018-02-22T00:00:00.000000000' '2018-09-11T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-08T00:00:00.000000000 to 2015-07-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-07T00:00:00.000000000 to 2016-03-09T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-09T00:00:00.000000000 to 2016-10-01T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-10-01T00:00:00.000000000 to 2017-11-30T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-11-30T00:00:00.000000000 to 2018-01-19T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2018-01-19T00:00:00.000000000 to 2018-02-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2018-02-22T00:00:00.000000000 to 2018-09-11T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-09-11T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  128\n",
      "ind num 223 {'Micrandropsis scleroxylon (W.A.Rodrigues) W.A.Rodrigues'} \n",
      "\n",
      "===== original dates in record ['2014-07-08T00:00:00.000000000' '2015-08-05T00:00:00.000000000'\n",
      " '2016-03-08T00:00:00.000000000' '2017-06-16T00:00:00.000000000'\n",
      " '2018-10-19T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-07-08T00:00:00.000000000 to 2015-08-05T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-05T00:00:00.000000000 to 2016-03-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-03-08T00:00:00.000000000 to 2017-06-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-16T00:00:00.000000000 to 2018-10-19T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-10-19T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  129\n",
      "ind num 225 {nan} \n",
      "\n",
      "===== original dates in record ['2013-10-31T00:00:00.000000000' '2014-10-08T00:00:00.000000000'\n",
      " '2015-10-06T00:00:00.000000000' '2016-11-07T00:00:00.000000000'\n",
      " '2017-10-23T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-10-31T00:00:00.000000000 to 2014-10-08T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-10-08T00:00:00.000000000 to 2015-10-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-10-06T00:00:00.000000000 to 2016-11-07T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-11-07T00:00:00.000000000 to 2017-10-23T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2017-10-23T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  130\n",
      "ind num 226 {'Scleronema micranthum (Ducke) Ducke'} \n",
      "\n",
      "===== original dates in record ['2014-09-08T00:00:00.000000000' '2015-06-29T00:00:00.000000000'\n",
      " '2016-08-23T00:00:00.000000000' '2017-06-18T00:00:00.000000000'\n",
      " '2018-08-15T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-09-08T00:00:00.000000000 to 2015-06-29T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-06-29T00:00:00.000000000 to 2016-08-23T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-08-23T00:00:00.000000000 to 2017-06-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-18T00:00:00.000000000 to 2018-08-15T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-08-15T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  131\n",
      "ind num 228 {'Ecclinusa guianensis? Eyma forma A'} \n",
      "\n",
      "===== original dates in record ['2014-06-25T00:00:00.000000000' '2015-04-27T00:00:00.000000000'\n",
      " '2015-08-12T00:00:00.000000000' '2016-02-25T00:00:00.000000000'\n",
      " '2016-07-22T00:00:00.000000000' '2017-06-06T00:00:00.000000000'\n",
      " '2018-06-23T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2014-06-25T00:00:00.000000000 to 2015-04-27T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-04-27T00:00:00.000000000 to 2015-08-12T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-08-12T00:00:00.000000000 to 2016-02-25T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-02-25T00:00:00.000000000 to 2016-07-22T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-07-22T00:00:00.000000000 to 2017-06-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-06-06T00:00:00.000000000 to 2018-06-23T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-06-23T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  132\n",
      "ind num 229 {'Virola michelii? Heckel'} \n",
      "\n",
      "===== original dates in record ['2013-08-19T00:00:00.000000000' '2014-09-13T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-19T00:00:00.000000000 to 2014-09-13T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2014-09-13T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n",
      "================= counter =================  133\n",
      "ind num 232 {'Parinari excelsa? Sabine'} \n",
      "\n",
      "===== original dates in record ['2013-08-25T00:00:00.000000000' '2014-08-16T00:00:00.000000000'\n",
      " '2015-07-02T00:00:00.000000000' '2016-06-18T00:00:00.000000000'\n",
      " '2017-07-06T00:00:00.000000000' '2018-07-27T00:00:00.000000000'] \n",
      "\n",
      "[observed flushing events] flushing events from 2013-08-25T00:00:00.000000000 to 2014-08-16T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2014-08-16T00:00:00.000000000 to 2015-07-02T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2015-07-02T00:00:00.000000000 to 2016-06-18T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2016-06-18T00:00:00.000000000 to 2017-07-06T00:00:00.000000000\n",
      "[observed flushing events] flushing events from 2017-07-06T00:00:00.000000000 to 2018-07-27T00:00:00.000000000\n",
      "[this is projected taking last month as reference] flushing events from 2018-07-27T00:00:00.000000000 to 2018-12-01 00:00:00\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dfall   = pd.DataFrame()\n",
    "\n",
    "# looping over each individual that flushes\n",
    "for i,idx in enumerate(ids):\n",
    "    \n",
    "    print('================= counter ================= ',i)\n",
    "    \n",
    "    # getting the dates in the record, the last date of each individual\n",
    "    # and setting 2018-11 as the last date of reference.\n",
    "    fdate                      = flushing.loc[flushing['ID']==idx,['Date','Specie','Pheno type']].sort_values(by='Date') # getting the flushing dates\n",
    "    mean_days_between_flushing = fdate['Date'].diff().mean() # the mean time between flushing events\n",
    "    last_date                  = pd.to_datetime(fdate['Date'].values[-1]) \n",
    "    # Assumed to be one month later than the actual last month. \n",
    "    # This to enables an age attribution to indivuals that flush in 2018-11\n",
    "    last_obs_month             = pd.to_datetime('2018-12') \n",
    "    \n",
    "    print('ind num',idx,set(fdate['Specie']),'\\n')\n",
    "    print('===== original dates in record',fdate['Date'].values,'\\n')\n",
    "    \n",
    "    df_sp = pd.DataFrame()\n",
    "    \n",
    "    # looping over the dates for each individual to calculate the leaf age\n",
    "    for j,dran in enumerate(fdate['Date'].values,start=1):\n",
    "        \n",
    "        # if the date in the loop is the last date then I take 2018-11 as a reference to \n",
    "        # finish counting\n",
    "        if dran==last_date: \n",
    "            months_between_events = pd.date_range(dran,last_obs_month,freq='M')\n",
    "            months                = [i.month for i in months_between_events]\n",
    "            \n",
    "            # creating a temporal dataframe to count the months between events\n",
    "            fr                    = pd.DataFrame()\n",
    "            fr['dates']           = months_between_events\n",
    "            fr['age_in_month']    = months\n",
    "            fr.set_index('dates',inplace=True)\n",
    "\n",
    "            # counting the cumulative months between events and gathering more data\n",
    "            age_in_month                     = fr.groupby([fr.index.year,fr.index.month]).count()\n",
    "            age_in_month.index.names         = ['year','month']\n",
    "            age_in_month['age_in_month_cum'] = age_in_month.cumsum()\n",
    "            age_in_month['ID']               = idx\n",
    "            age_in_month['Specie']           = list(set(fdate['Specie']))[0]\n",
    "            age_in_month['Pheno type']       = list(set(fdate['Pheno type']))[0]\n",
    "            age_in_month.reset_index(inplace=True)\n",
    "            \n",
    "            print('[this is projected taking last month as reference] flushing events from',dran,'to',last_obs_month)\n",
    "\n",
    "        else: # This else is for all the other dates before the last one.\n",
    "            months_between_events = pd.date_range(dran,fdate['Date'].values[j],freq='M')\n",
    "            months                = [i.month for i in months_between_events]\n",
    "\n",
    "            # creating a temporal dataframe to count the months between events\n",
    "            fr                    = pd.DataFrame()\n",
    "            fr['dates']           = months_between_events\n",
    "            fr['age_in_month']    = months\n",
    "            fr.set_index('dates',inplace=True)\n",
    "\n",
    "            # counting the cumulative months between events and gathering more data\n",
    "            age_in_month = fr.groupby([fr.index.year,fr.index.month]).count()\n",
    "            age_in_month.index.names = ['year','month']\n",
    "            age_in_month['age_in_month_cum'] = age_in_month.cumsum()\n",
    "            age_in_month['ID']    = idx\n",
    "            age_in_month['Specie']    = list(set(fdate['Specie']))[0]\n",
    "            age_in_month['Pheno type'] = list(set(fdate['Pheno type']))[0]\n",
    "            age_in_month.reset_index(inplace=True)\n",
    "            \n",
    "            print('[observed flushing events] flushing events from',dran,'to',fdate['Date'].values[j])\n",
    "\n",
    "        if j == 1:\n",
    "            df_sp = age_in_month\n",
    "        else:\n",
    "            df_sp = pd.concat([df_sp,age_in_month],axis=0)\n",
    "    \n",
    "    # concatening the information for each ind into one dataframe\n",
    "    if i == 0:\n",
    "        dfall = df_sp\n",
    "    else:\n",
    "        dfall = pd.concat([dfall,df_sp],axis=0)\n",
    "        \n",
    "    print('\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The resulting dataframe looks like "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7806, 7)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dfall.head(),\n",
    "dfall.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating bins for age classes depending on the binning type selected above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bins used are = [ 0.  1.  2.  3.  4.  5.  6.  7.  8.  9. 10. 11. 12. 52.]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>age_in_month</th>\n",
       "      <th>age_in_month_cum</th>\n",
       "      <th>ID</th>\n",
       "      <th>Specie</th>\n",
       "      <th>Pheno type</th>\n",
       "      <th>AgeClasses_months</th>\n",
       "      <th>AgeMid</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dates</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>Manilkara huberi (Ducke) Standl.</td>\n",
       "      <td>EV</td>\n",
       "      <td>(0.0, 1.0]</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>199</td>\n",
       "      <td>Pouteria cuspidata? (A.DC.) Baehni</td>\n",
       "      <td>EV</td>\n",
       "      <td>(0.0, 1.0]</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>179</td>\n",
       "      <td>Eschweilera bracteosa (Poepp. ex O.Berg) Miers</td>\n",
       "      <td>semiBD</td>\n",
       "      <td>(0.0, 1.0]</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            year  month  age_in_month  age_in_month_cum   ID  \\\n",
       "dates                                                          \n",
       "2013-07-01  2013      7             1                 1   23   \n",
       "2013-07-01  2013      7             1                 1  199   \n",
       "2013-07-01  2013      7             1                 1  179   \n",
       "\n",
       "                                                    Specie Pheno type  \\\n",
       "dates                                                                   \n",
       "2013-07-01                Manilkara huberi (Ducke) Standl.         EV   \n",
       "2013-07-01              Pouteria cuspidata? (A.DC.) Baehni         EV   \n",
       "2013-07-01  Eschweilera bracteosa (Poepp. ex O.Berg) Miers     semiBD   \n",
       "\n",
       "           AgeClasses_months AgeMid  \n",
       "dates                                \n",
       "2013-07-01        (0.0, 1.0]    0.5  \n",
       "2013-07-01        (0.0, 1.0]    0.5  \n",
       "2013-07-01        (0.0, 1.0]    0.5  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def mid(interval):\n",
    "    return interval.mid\n",
    "\n",
    "if binning == '13classes':\n",
    "    \n",
    "    bins    = [np.arange(0,12,1),np.linspace(12,52,2)]\n",
    "    bins    = np.concatenate(bins).ravel()\n",
    "    print('bins used are =' ,bins)\n",
    "    dfall   = dfall.assign(AgeClasses_months = pd.cut(dfall['age_in_month_cum'],bins,right=True))\n",
    "    dfall   = dfall.assign(AgeMid = dfall.AgeClasses_months.apply(mid))\n",
    "    \n",
    "    columns = [ '1 mo','2 mo', '3 mo', '4 mo', '5 mo', '6 mo', '7 mo', '8 mo', '9 mo','10 mo','11 mo', '12 mo', '>12 mo']\n",
    "\n",
    "elif binning == '4classes':\n",
    "    bins    = [np.linspace(0,2,1),np.linspace(2,6,1),\n",
    "           np.linspace(6,11,1),\n",
    "           np.linspace(12,dfall['age_in_month_cum'].max(),2)]\n",
    "    bins    = np.concatenate(bins).ravel()\n",
    "    print('bins used are =' ,bins)\n",
    "    dfall   = dfall.assign(AgeClasses_months = pd.cut(dfall['age_in_month_cum'],bins,right=True))\n",
    "    dfall   = dfall.assign(AgeMid = dfall.AgeClasses_months.apply(mid))\n",
    "    \n",
    "    columns =  ['Young [0-2 mo]','Mature [2-6 mo]', 'Old [6-12 mo]', 'Old+ [>12 mo]']\n",
    "    \n",
    "# creating a datetime index\n",
    "dfall['dates'] = pd.to_datetime(['%s-%s'%(yr,dfall.month.values[i]) for i,yr in enumerate(dfall.year.values)])\n",
    "dfall.set_index('dates',inplace=True)\n",
    "dfall.sort_index(inplace=True)\n",
    "dfall.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Family</th>\n",
       "      <th>Specie</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Event</th>\n",
       "      <th>Date</th>\n",
       "      <th>Pheno type</th>\n",
       "      <th>FlushFlag</th>\n",
       "      <th>QFlag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>117</td>\n",
       "      <td>Fabaceae</td>\n",
       "      <td>Abarema cochleata (Willd.) Barneby &amp; J.W.Grimes</td>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2013-08-13</td>\n",
       "      <td>semiEV</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>117</td>\n",
       "      <td>Fabaceae</td>\n",
       "      <td>Abarema cochleata (Willd.) Barneby &amp; J.W.Grimes</td>\n",
       "      <td>2017</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>init_flush</td>\n",
       "      <td>2017-09-06</td>\n",
       "      <td>semiEV</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID    Family                                           Specie  Year  \\\n",
       "445  117  Fabaceae  Abarema cochleata (Willd.) Barneby & J.W.Grimes  2013   \n",
       "446  117  Fabaceae  Abarema cochleata (Willd.) Barneby & J.W.Grimes  2017   \n",
       "\n",
       "     Month  Day       Event       Date Pheno type  FlushFlag  QFlag  \n",
       "445      8   13  init_flush 2013-08-13     semiEV       True  False  \n",
       "446      9    6  init_flush 2017-09-06     semiEV       True  False  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1408x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# displaying the ages for a random individual including the projected time period\n",
    "\n",
    "################## You can select between semiBD, BD, EV or semiEV and run multiple times to check\n",
    "################## different individuals\n",
    "wanted_phenotype = 'semiEV' \n",
    "##################\n",
    "\n",
    "tree   = get_random_ind(dfall,pheno=wanted_phenotype) \n",
    "dfplot = dfall[dfall['ID']==tree] \n",
    "\n",
    "display(data[data['ID']==tree]) # displaying the data for the individual\n",
    "\n",
    "# Plotting\n",
    "# setting the dates properly so it can be plotted and other details\n",
    "datesi  = dfplot.reset_index().sort_values(by=['year','month'])['dates'].astype(str).values\n",
    "datesf  = [datetime.datetime.strptime(str(d), \"%Y-%m-%d\") for d in datesi]                                               \n",
    "names   = ['Lancamento'] * len(datesf)\n",
    "sp      = list(set(dfplot['Specie']))[0]\n",
    "ind_num = list(set(dfplot['ID']))[0]\n",
    "#lastObs = dfplot[dfplot['ProjectionFlag']==True].index[0]\n",
    "lastObs = dfplot.index[-1]\n",
    "\n",
    "# selecting levels for the height of the lines in plot\n",
    "levels  = dfplot['age_in_month_cum'].values\n",
    "\n",
    "# Create figure and plot a stem plot with the date\n",
    "fig, ax = plt.subplots(figsize=(8.8, 4), dpi=160,constrained_layout=True)\n",
    "\n",
    "ax.set(title=\"Leaf age development for %s \\n Individual number %i\"%(sp,ind_num))\n",
    "ax.vlines(datesf, 0, levels, color=\"tab:red\")  # The vertical stems.\n",
    "#ax.axvspan(str(lastObs),'2019-06',color='grey',alpha=.2)\n",
    "    \n",
    "# remove y axis and spines\n",
    "ax.spines[\"top\"].set_visible(False)\n",
    "ax.spines[\"right\"].set_visible(False)\n",
    "ax.yaxis.set_minor_locator(tck.AutoMinorLocator())\n",
    "ax.set_xlabel('Month')\n",
    "ax.set_ylabel('Leaf Age [months]')\n",
    "\n",
    "years     = mdates.YearLocator()   # every year\n",
    "months    = mdates.MonthLocator()  # every month\n",
    "years_fmt = mdates.DateFormatter('%Y')\n",
    "\n",
    "ax.xaxis.set_major_locator(years)\n",
    "ax.xaxis.set_major_formatter(years_fmt)\n",
    "ax.xaxis.set_minor_locator(months)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting rid of duplicates\n",
    "- In the original dataset there are individuals that are reported twice within a same month. \n",
    "- So to calculate the age classes we need to avoid counting twice each tree, because this will affect the fraction of crowns flushing for that month.  So, we have to get rid of these extra counts in those months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates_loop  = sorted(list(set(dfall.index)))\n",
    "dfall_nodup = pd.DataFrame()\n",
    "printme     = False\n",
    "\n",
    "for i in dates_loop[:67]:\n",
    "    shape_origi = dfall.loc[i].shape[0]\n",
    "    shape_drop  = dfall.loc[i,'ID'].drop_duplicates().shape[0]\n",
    "    \n",
    "    if printme: print(dfall.loc[i].shape,i,dfall.loc[i,'ID'].drop_duplicates().shape)\n",
    "    \n",
    "    if shape_origi==shape_drop:\n",
    "        dfall_nodup = pd.concat([dfall.loc[i,:],dfall_nodup],axis=0)\n",
    "    else:\n",
    "        dfall_nodup = pd.concat([dfall_nodup,dfall.loc[i,:].drop_duplicates(subset='ID')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7789, 9)"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfall_nodup.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>1 mo</th>\n",
       "      <th>2 mo</th>\n",
       "      <th>3 mo</th>\n",
       "      <th>4 mo</th>\n",
       "      <th>5 mo</th>\n",
       "      <th>6 mo</th>\n",
       "      <th>7 mo</th>\n",
       "      <th>8 mo</th>\n",
       "      <th>9 mo</th>\n",
       "      <th>10 mo</th>\n",
       "      <th>11 mo</th>\n",
       "      <th>12 mo</th>\n",
       "      <th>&gt;12 mo</th>\n",
       "      <th>Unknown</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dates</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-03-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-04-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-05-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>7</td>\n",
       "      <td>0.134328</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.865672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-08-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>0.156716</td>\n",
       "      <td>0.134328</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.708955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>9</td>\n",
       "      <td>0.044776</td>\n",
       "      <td>0.156716</td>\n",
       "      <td>0.134328</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.664179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "      <td>0.119403</td>\n",
       "      <td>0.044776</td>\n",
       "      <td>0.156716</td>\n",
       "      <td>0.134328</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.544776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-11-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>11</td>\n",
       "      <td>0.059701</td>\n",
       "      <td>0.119403</td>\n",
       "      <td>0.044776</td>\n",
       "      <td>0.156716</td>\n",
       "      <td>0.134328</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.485075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-01</th>\n",
       "      <td>2013</td>\n",
       "      <td>12</td>\n",
       "      <td>0.022388</td>\n",
       "      <td>0.059701</td>\n",
       "      <td>0.119403</td>\n",
       "      <td>0.044776</td>\n",
       "      <td>0.156716</td>\n",
       "      <td>0.134328</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.462687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>0.029851</td>\n",
       "      <td>0.022388</td>\n",
       "      <td>0.059701</td>\n",
       "      <td>0.119403</td>\n",
       "      <td>0.044776</td>\n",
       "      <td>0.156716</td>\n",
       "      <td>0.126866</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.440299</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            year  month      1 mo      2 mo      3 mo      4 mo      5 mo  \\\n",
       "dates                                                                       \n",
       "2013-01-01  2013      1  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "2013-02-01  2013      2  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "2013-03-01  2013      3  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "2013-04-01  2013      4  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "2013-05-01  2013      5  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "2013-06-01  2013      6  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "2013-07-01  2013      7  0.134328  0.000000  0.000000  0.000000  0.000000   \n",
       "2013-08-01  2013      8  0.156716  0.134328  0.000000  0.000000  0.000000   \n",
       "2013-09-01  2013      9  0.044776  0.156716  0.134328  0.000000  0.000000   \n",
       "2013-10-01  2013     10  0.119403  0.044776  0.156716  0.134328  0.000000   \n",
       "2013-11-01  2013     11  0.059701  0.119403  0.044776  0.156716  0.134328   \n",
       "2013-12-01  2013     12  0.022388  0.059701  0.119403  0.044776  0.156716   \n",
       "2014-01-01  2014      1  0.029851  0.022388  0.059701  0.119403  0.044776   \n",
       "\n",
       "                6 mo      7 mo  8 mo  9 mo  10 mo  11 mo  12 mo  >12 mo  \\\n",
       "dates                                                                     \n",
       "2013-01-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-02-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-03-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-04-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-05-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-06-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-07-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-08-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-09-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-10-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-11-01  0.000000  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2013-12-01  0.134328  0.000000   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "2014-01-01  0.156716  0.126866   0.0   0.0    0.0    0.0    0.0     0.0   \n",
       "\n",
       "             Unknown  \n",
       "dates                 \n",
       "2013-01-01  1.000000  \n",
       "2013-02-01  1.000000  \n",
       "2013-03-01  1.000000  \n",
       "2013-04-01  1.000000  \n",
       "2013-05-01  1.000000  \n",
       "2013-06-01  1.000000  \n",
       "2013-07-01  0.865672  \n",
       "2013-08-01  0.708955  \n",
       "2013-09-01  0.664179  \n",
       "2013-10-01  0.544776  \n",
       "2013-11-01  0.485075  \n",
       "2013-12-01  0.462687  \n",
       "2014-01-01  0.440299  "
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Organzing the resulting dataframe to have months classes in the columns and the dates of the time series in the rows.\n",
    "df_ages_ts = dfall_nodup.pivot_table(values='AgeMid',columns='AgeClasses_months',index=['year','month'],aggfunc='count')\n",
    "df_ages_ts.columns = columns\n",
    "\n",
    "if doPercent:\n",
    "    # Note that the Unknown class is only created if doPercent is True\n",
    "    df_ages_ts = df_ages_ts / 134 # 134 is the total of flushing tress, I divide to get the percentage for each month\n",
    "    # Adding the \"Unknown class\" \n",
    "    df_ages_ts['Unknown'] = 1-df_ages_ts.sum(axis=1)\n",
    "else:\n",
    "    df_ages_ts = df_ages_ts\n",
    "\n",
    "df_ages_ts.reset_index(inplace=True)\n",
    "df_ages_ts['dates'] = pd.to_datetime(['%s-%s'%(yr,df_ages_ts.month.values[i]) for i,yr in enumerate(df_ages_ts.year.values)])\n",
    "df_ages_ts.set_index('dates',inplace=True)\n",
    "df_ages_ts.sort_index(inplace=True)\n",
    "df_ages_ts.head(13)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Note on previous dataframe:\n",
    "- See that the diagonal sometimes decreases. For example from rows 2013-12-01 to 2014-01-01 there is a decrease in the percentage of the upper diagonal.\n",
    "- This is because one of the trees in this group, flushed again. Therefore, the timing is renewed and this individual enters the 1-month age class.\n",
    "- It is normal that the diagonal decreases because fo the mentioned effect, but it should never increase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if doPercent:\n",
    "    fig,ax2  = plt.subplots(1,1,figsize=(9,4),dpi=160)\n",
    "    \n",
    "    cols=df_ages_ts.columns[2:]\n",
    "    df_ages_ts[cols].plot(kind='bar',stacked=True,ax=ax2,cmap='gist_earth') # nipy_spectral,gist_earth,gist_ncar\n",
    "\n",
    "    ticklabels = ['']*len(df_ages_ts.index)\n",
    "    # Every 4th ticklable shows the month and day\n",
    "    ticklabels[::2] = [item.strftime('%b %Y') for item in df_ages_ts.index[::2]]\n",
    "    ax2.xaxis.set_major_formatter(tck.FixedFormatter(ticklabels))\n",
    "    ax2.legend(bbox_to_anchor=(0.1,0.4),ncol=1,fontsize=6,title='Age Classes')\n",
    "    ax2.set_ylabel('Fraction of crowns (n=134)')\n",
    "    ax2.set_xlabel('Date')\n",
    "    ax2.set_xlim(-0.5,64.5)\n",
    "    plt.tight_layout()\n",
    "    plt.rcParams.update({'font.size': 8,})\n",
    "    plt.show()\n",
    "    #fig.savefig('fraction_crowns_%s_201811ref.png'%(binning),dpi=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. LAI Normalization\n",
    "- This is done only if binning == '4classes' and doPercent == False\n",
    "- The reason is that for the LAI normalization we worked with the 194 individuals and thus we used the number of individuals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "if binning == '4classes' and doPercent==False:\n",
    "    \n",
    "    pd.options.mode.chained_assignment = None\n",
    "    \n",
    "    # getting the number of individuals in each Pheno type\n",
    "    deciduous = flushing.set_index('Date')\n",
    "    deciduous = pd.DataFrame(deciduous.groupby([deciduous.index.year,deciduous.index.month,'Pheno type'])['ID'].count())\n",
    "    deciduous['dates'] =  pd.to_datetime(['%i-%i'%(m,deciduous.index.get_level_values(level=1)[i]) for i,m in enumerate(deciduous.index.get_level_values(level=0))] )\n",
    "    deciduous.index.names = ['year','month','pheno']\n",
    "    deciduous = deciduous.reset_index()\n",
    "    \n",
    "    # dataframe for only the BD class\n",
    "    deciduous_bd_only = deciduous[(deciduous['pheno']=='BD' )]\n",
    "    deciduous_bd_only.set_index('dates',inplace=True)\n",
    "\n",
    "    # dataframe for only the BD and semiBD classes\n",
    "    deciduous_bd_nbd  = deciduous[(deciduous['pheno']=='BD' ) | (deciduous['pheno']=='semiBD')]\n",
    "    deciduous_bd_nbd  = deciduous_bd_nbd.groupby(by=['year','month']).sum()\n",
    "    deciduous_bd_nbd['dates'] =  pd.to_datetime(['%i-%i'%(m,deciduous_bd_nbd.index.get_level_values(level=1)[i]) \n",
    "                                                 for i,m in enumerate(deciduous_bd_nbd.index.get_level_values(level=0))] )\n",
    "    deciduous_bd_nbd.reset_index(inplace=True)\n",
    "    deciduous_bd_nbd.set_index('dates',inplace=True)\n",
    "\n",
    "    date_i = '%i-%i'%(flushing['Date'].sort_values().iloc[0].year,flushing['Date'].sort_values().iloc[0].month)\n",
    "    date_e = '%i-%i'%(flushing['Date'].sort_values().iloc[-1].year,flushing['Date'].sort_values().iloc[-1].month)\n",
    "    dtr    = pd.date_range(date_i, date_e, freq='MS')\n",
    "    print(date_i,date_e,dtr.shape)\n",
    "    s      = pd.Series(index=dtr)\n",
    "\n",
    "    # filling with zeros missing dates in deciduos datafrmes\n",
    "    deciduous_bd_only = pd.concat([deciduous_bd_only,s[~s.index.isin(deciduous_bd_only.index)]]) #.sort_index()\n",
    "    deciduous_bd_only = deciduous_bd_only.drop([0],axis=1).fillna(0).sort_index()\n",
    "\n",
    "    deciduous_bd_nbd  = pd.concat([deciduous_bd_nbd,s[~s.index.isin(deciduous_bd_nbd.index)]])\n",
    "    deciduous_bd_nbd  = deciduous_bd_nbd.drop([0],axis=1).fillna(0).sort_index()\n",
    "\n",
    "    # LAI normalization \n",
    "    df_ages_ts_subset = df_ages_ts.loc['2013-07':'2018-11']\n",
    "    df_ages_ts_subset['# deciduous BD']        = deciduous_bd_only['ID'].values\n",
    "    df_ages_ts_subset['# deciduous semiBD + BD']  = deciduous_bd_nbd['ID'].values\n",
    "\n",
    "    df_ages_ts_subset['TotalGreenCrownBD']        = 194 - df_ages_ts_subset['# deciduous BD']\n",
    "    df_ages_ts_subset['TotalGreenCrownBD+semiBD'] = 194 - df_ages_ts_subset['# deciduous semiBD + BD']\n",
    "    df_ages_ts_subset['Old_joinedBD']             = df_ages_ts_subset['TotalGreenCrownBD'] - df_ages_ts_subset['Young [0-2 mo]'] - df_ages_ts_subset['Mature [2-6 mo]']\n",
    "    df_ages_ts_subset['Old_joinedBD+semiBD']      = df_ages_ts_subset['TotalGreenCrownBD+semiBD'] - df_ages_ts_subset['Young [0-2 mo]'] - df_ages_ts_subset['Mature [2-6 mo]']\n",
    "    df_ages_ts_subset['Total Canopy LAI']         = 5.32 # Giordane's and Pedro's value\n",
    "\n",
    "    df_ages_ts_subset['Young LAI BD']             = df_ages_ts_subset['Young [0-2 mo]'] / df_ages_ts_subset['TotalGreenCrownBD'] * df_ages_ts_subset['Total Canopy LAI']\n",
    "    df_ages_ts_subset['Young LAI BD+semiBD']      = df_ages_ts_subset['Young [0-2 mo]'] / df_ages_ts_subset['TotalGreenCrownBD+semiBD'] * df_ages_ts_subset['Total Canopy LAI']\n",
    "\n",
    "    df_ages_ts_subset['Mature LAI BD']            = df_ages_ts_subset['Mature [2-6 mo]'] / df_ages_ts_subset['TotalGreenCrownBD'] * df_ages_ts_subset['Total Canopy LAI']\n",
    "    df_ages_ts_subset['Mature LAI BD+semiBD']     = df_ages_ts_subset['Mature [2-6 mo]'] / df_ages_ts_subset['TotalGreenCrownBD+semiBD'] * df_ages_ts_subset['Total Canopy LAI']\n",
    "\n",
    "    df_ages_ts_subset['OLD LAI BD']               = df_ages_ts_subset['Old_joinedBD'] / df_ages_ts_subset['TotalGreenCrownBD'] * df_ages_ts_subset['Total Canopy LAI']\n",
    "    df_ages_ts_subset['OLD LAI BD+semiBD']        = df_ages_ts_subset['Old_joinedBD+semiBD'] / df_ages_ts_subset['TotalGreenCrownBD+semiBD'] * df_ages_ts_subset['Total Canopy LAI']\n",
    "    \n",
    "    display(df_ages_ts_subset.loc['2013-07':'2018-11'].head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "print('done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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