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@johanvdw
Created September 13, 2017 10:19
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Determine best classification method
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Goal of this analysis is to check what would be the best way to classify when we have both categorical data and numeric data, a situation which happens frequently in NICHE.\n",
"\n",
"We will be calculating the https://inbo.github.io/niche-vlaanderen/trofie.html#stikstofmineralisatie here.\n",
"\n",
"\n",
"First we load the grids."
]
},
{
"cell_type": "code",
"execution_count": 114,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"grntbeheer.asc\n",
"grntmest.asc\n",
"dd2_glg.asc\n",
"dd2_gvg.asc\n",
"kwel.asc\n",
"grntatmdep.asc\n",
"grntbodem.asc\n",
"dd2_t101_20mz.asc\n",
"dd2_overvz2.asc\n",
"grntnulgrid.asc\n",
"dd2_ghg.asc\n",
"grntcond.asc\n"
]
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import os\n",
"import matplotlib.pyplot as plt\n",
"\n",
"%matplotlib inline\n",
"##\n",
"\n",
"\n",
"# we now load the grids from the testcase and try the same\n",
"from osgeo import gdal\n",
"from osgeo import osr\n",
"import glob\n",
"\n",
"path_input_raster = \"../testcase/InputSnapBodem/*asc\"\n",
"input_rasters = {}\n",
"for path in glob.glob(path_input_raster+'*.asc'):\n",
" input_rasters[path.split(\"/\")[-1]] = gdal.Open(path)\n",
" if input_rasters[path.split(\"/\")[-1]].GetProjection() == \"\":\n",
" print(path.split(\"/\")[-1], \"data set has no projection info!\")\n",
" \n",
"##\n",
"\n",
"def raster_to_numpy(filename):\n",
" '''Read a GDAL grid as numpy array\n",
" \n",
" Notes\n",
" ------\n",
" No-data values are 0 for integer types and np.nan for real types.\n",
" '''\n",
" # Read the raster file with GDAL\n",
" ds = gdal.Open(filename)\n",
"\n",
" # Extract the data, transformation and projection information\n",
" data = ds.ReadAsArray()\n",
" gt = ds.GetGeoTransform()\n",
" raster_wkt = ds.GetProjection()\n",
" spatial_ref = osr.SpatialReference()\n",
" spatial_ref.ImportFromWkt(raster_wkt)\n",
" proj = spatial_ref.ExportToProj4()\n",
" \n",
" nodata = ds.GetRasterBand(1).GetNoDataValue()\n",
" # create a mask for no-data values, taking into account the data-types\n",
" if data.dtype == 'float32':\n",
" data[data == nodata] = np.nan\n",
" else:\n",
" data[data == nodata] = 0 #is het niet vreemd om 0 als no data te gebruiken? \n",
" \n",
" # destroy the gdal object\n",
" del ds\n",
" return data, gt, proj\n",
"##\n",
" \n",
"input_arrays = {}\n",
"for path in glob.glob(path_input_raster):\n",
" data, _, _ = raster_to_numpy(path)\n",
" input_arrays[path.split(\"/\")[-1]] = data\n",
" print(path.split(\"/\")[-1])\n",
"##\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The class below contains 4 methods to derive the nitrogen mineralisation. The first method (get) calculates the nitrogen mineralisation for single values.\n",
"\n",
"The three other methods are ways to calculate the nitrogen mineralisation for array inputs:\n",
"\n",
" * get_array is a naive implementation that loops over the get function. From tests it turns out this method is too slow.\n",
" * get_array_digitize uses the same method as the original software: converting both numerical and categorial data to one number and using digitize to classify this. This method is very fast, but has the disadvantage that some values can not be classified (eg what if msw > 5000). \n",
" Compared to the original version I think it is a better idea to generate the classification codes from the classification table on the fly.\n",
" * get_array_split is a combination: it will loop over the categorical data and use digitize for every category. I think this is the best method, combining speed without sacrifying readability and options in the code table. \n",
" \n",
" \n",
"Note that all methods require a valid classification table (eg no overlapping zones, minima of one category are the same as the maxima of the previous one, ...\n",
"Checks should be in place to enforce this."
]
},
{
"cell_type": "code",
"execution_count": 134,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"75.0"
]
},
"execution_count": 134,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"class NitrogenMineralisation(object):\n",
" ''' class to calculate mineralisation\n",
" '''\n",
" def __init__(self):\n",
" self.table = pd.read_csv(\"../SystemTables/nitrogen_mineralisation.csv\")\n",
" \n",
" # convert the mineralisation columns to float so we can use np.nan for nodata\n",
" self.table.nitrogen_mineralisation = self.table.nitrogen_mineralisation.astype(\"float64\")\n",
" \n",
" \n",
" def get(self,soil_code, msw):\n",
" result= self.table.nitrogen_mineralisation[((self.table.soil_code == soil_code) \n",
" & (self.table.msw_min <= msw )&( self.table.msw_max >msw))].values\n",
" return result[0] if result.size >0 else np.nan\n",
" \n",
" def get_array(self, soil_code_array, msw_array):\n",
" h = lambda x, y: self.get(x,y)\n",
" \n",
" return [h(x, y) for x,y in zip(soil_code_array.flatten(),msw_array.flatten())]\n",
" \n",
" def get_array_digitize(self, soil_code_array, msw_array):\n",
" # reclassify the code table\n",
" self.table.code = self.table.soil_code + self.table.msw_max\n",
" \n",
" #reclassify the input grid\n",
" code = soil_code_array + msw_array\n",
" \n",
" index = np.digitize(code.flatten(), self.table.code)\n",
" result = self.table.nitrogen_mineralisation[index]\n",
" \n",
" result = result.values.reshape(soil_code_array.shape) \n",
" result[((soil_code_array == 0) | (msw_array < -5000) | (msw_array >5000))] = np.nan \n",
" # value of 5000 above should be part of the documentation. It makes sense though to use no-data here (unrealistic value)\n",
" \n",
" return result\n",
" \n",
" def get_array_split(self, soil_code_array, msw_array):\n",
" # logic: use digitize per unique code\n",
" orig_shape = soil_code_array.shape\n",
" soil_code_array = soil_code_array.flatten()\n",
" msw_array = msw_array.flatten()\n",
" result = np.empty(soil_code_array.shape)\n",
" result[:]= np.nan\n",
" \n",
" for code in self.table.soil_code.unique():\n",
" # we must reset the index because digitize will give indexes compared to the new table.\n",
" table_sel = self.table[self.table.soil_code == code].copy(deep=True).reset_index(drop=True)\n",
" soil_code_sel = (soil_code_array == code)\n",
" index = np.digitize(msw_array[soil_code_sel], table_sel.msw_max)\n",
" \n",
" result[soil_code_sel] = table_sel.nitrogen_mineralisation[index]\n",
" \n",
" result = result.reshape(orig_shape\n",
" )\n",
" return result\n",
" \n",
"\n",
"nm = NitrogenMineralisation()\n",
"##\n",
"\n",
"nm.get(140000, 33)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"wat simpele tests om te kijken of we zelfde resultaat krijgen"
]
},
{
"cell_type": "code",
"execution_count": 135,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[75.0, 87.0]"
]
},
"execution_count": 135,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nm.get_array(np.array([140000, 140000]), np.array([33, 50]))"
]
},
{
"cell_type": "code",
"execution_count": 136,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 75., 87.])"
]
},
"execution_count": 136,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nm.get_array_digitize(np.array([140000, 140000]), np.array([33, 50]))"
]
},
{
"cell_type": "code",
"execution_count": 137,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 75., 87.])"
]
},
"execution_count": 137,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nm.get_array_split(np.array([140000, 140000]), np.array([33, 50]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Hoe zit het met de looptijd?"
]
},
{
"cell_type": "code",
"execution_count": 139,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 loop, best of 3: 8.38 ms per loop\n"
]
}
],
"source": [
"%timeit -n1 nm.get_array_digitize(input_arrays[\"grntbodem.asc\"], input_arrays[\"dd2_gvg.asc\"])"
]
},
{
"cell_type": "code",
"execution_count": 140,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 loop, best of 3: 23 ms per loop\n"
]
}
],
"source": [
"%timeit -n1 nm.get_array_split(input_arrays[\"grntbodem.asc\"], input_arrays[\"dd2_gvg.asc\"])"
]
},
{
"cell_type": "code",
"execution_count": 143,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 8min 33s, sys: 408 ms, total: 8min 34s\n",
"Wall time: 8min 34s\n"
]
}
],
"source": [
"%time slow = nm.get_array(input_arrays[\"grntbodem.asc\"], input_arrays[\"dd2_gvg.asc\"])"
]
},
{
"cell_type": "code",
"execution_count": 154,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.colorbar.Colorbar at 0x7f0586f63a90>"
]
},
"execution_count": 154,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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X+sMWN/zDCZmilSkWY78mAAAAAKA5S7IiodHKDnFWYmjmdXqBCxM6MUgwajhj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\nVGvHoK9bh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"text/plain": [
"<matplotlib.figure.Figure at 0x7f058726d710>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize=(20, 10))\n",
"slow = np.array(slow)\n",
"slow = slow.reshape(input_arrays[\"grntbodem.asc\"].shape)\n",
"plt.imshow(slow)\n",
"plt.colorbar()"
]
},
{
"cell_type": "code",
"execution_count": 155,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"fast = nm.get_array_digitize(input_arrays[\"grntbodem.asc\"], input_arrays[\"dd2_gvg.asc\"])"
]
},
{
"cell_type": "code",
"execution_count": 156,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.colorbar.Colorbar at 0x7f0586f2b9b0>"
]
},
"execution_count": 156,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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X+sMWN/zDCZmilSkWY78mAAAAAKA5S7IiodHKDnFWYmjmdXqBCxM6MUgwajhj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\nVGvHoK9bh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"text/plain": [
"<matplotlib.figure.Figure at 0x7f05878bfe80>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize=(20, 10))\n",
"plt.imshow(fast)\n",
"plt.colorbar()"
]
},
{
"cell_type": "code",
"execution_count": 157,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"split = nm.get_array_split(input_arrays[\"grntbodem.asc\"], input_arrays[\"dd2_gvg.asc\"])"
]
},
{
"cell_type": "code",
"execution_count": 146,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.colorbar.Colorbar at 0x7f05878e3c88>"
]
},
"execution_count": 146,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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X+sMWN/zDCZmilSkWY78mAAAAAKA5S7IiodHKDnFWYmjmdXqBCxM6MUgwajhj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\nVGvHoK9bh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"text/plain": [
"<matplotlib.figure.Figure at 0x7f05877671d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize=(20, 10))\n",
"plt.imshow(split)\n",
"plt.colorbar()"
]
},
{
"cell_type": "code",
"execution_count": 158,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 0, 0, 0, 0, 0, 79262, 0, 0, 0, 0]),\n",
" array([-0.5, -0.4, -0.3, -0.2, -0.1, 0. , 0.1, 0.2, 0.3, 0.4, 0.5]))"
]
},
"execution_count": 158,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.histogram((fast - slow)[np.isfinite(slow)])"
]
},
{
"cell_type": "code",
"execution_count": 159,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 0, 0, 0, 0, 0, 79262, 0, 0, 0, 0]),\n",
" array([-0.5, -0.4, -0.3, -0.2, -0.1, 0. , 0.1, 0.2, 0.3, 0.4, 0.5]))"
]
},
"execution_count": 159,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.histogram((split - slow)[np.isfinite(slow)])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Alle methodes leveren hier zelfde resultaat. Nog te controleren met het origineel!"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
@stijnvanhoey
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I agree to use the get_array_split method, as this provides a proper balance. Nice comparison

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