From 70d9b0ad8ec47fdd2ad6412e536a2cb9cac031b4 Mon Sep 17 00:00:00 2001
From: acpaquette <acp263@nau.edu>
Date: Thu, 3 May 2018 06:25:20 -0700
Subject: [PATCH] Ipf Writer (#37)
* Added to ipf from dataframe. Also updated both gpf and ipf writer tests
* Added test output file.
* Added asserts to gpf and ipf tests
* Reverted save_gpf testing to numpy array almost equals
---
notebooks/Socet2ISIS.ipynb | 181 +++--
plio/io/io_bae.py | 51 +-
.../tests/temp/P20_008845_1894_XN_09N203W.ipf | 729 ++++++++++++++++++
plio/io/tests/test_io_bae.py | 39 +-
4 files changed, 917 insertions(+), 83 deletions(-)
create mode 100644 plio/io/tests/temp/P20_008845_1894_XN_09N203W.ipf
diff --git a/notebooks/Socet2ISIS.ipynb b/notebooks/Socet2ISIS.ipynb
index 04b6b2c..636ba38 100644
--- a/notebooks/Socet2ISIS.ipynb
+++ b/notebooks/Socet2ISIS.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
@@ -15,12 +15,12 @@
"import numpy as np\n",
"\n",
"from plio.examples import get_path\n",
- "from plio.io.io_bae import read_gpf"
+ "from plio.io.io_bae import read_gpf, read_ipf"
]
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@@ -69,80 +69,7 @@
" # Sets the value of PATH to the path of the ATF file\n",
" files_dict['PATH'] = os.path.dirname(os.path.abspath(atf_file))\n",
" \n",
- " return files_dict\n",
- " \n",
- "@singledispatch\n",
- "def read_ipf(arg):\n",
- " return str(arg)\n",
- "\n",
- "@read_ipf.register(str)\n",
- "def read_ipf_str(input_data):\n",
- " \"\"\"\n",
- " Read a socet ipf file into a pandas data frame\n",
- "\n",
- " Parameters\n",
- " ----------\n",
- " input_data : str\n",
- " path to the an input data file\n",
- "\n",
- " Returns\n",
- " -------\n",
- " df : pd.DataFrame\n",
- " containing the ipf data with appropriate column names and indices\n",
- " \"\"\"\n",
- "\n",
- " # Check that the number of rows is matching the expected number\n",
- " with open(input_data, 'r') as f:\n",
- " for i, l in enumerate(f):\n",
- " if i == 1:\n",
- " cnt = int(l)\n",
- " elif i == 2:\n",
- " col = l\n",
- " break\n",
- " \n",
- " columns = np.genfromtxt(input_data, skip_header=2, dtype='unicode',\n",
- " max_rows = 1, delimiter = ',')\n",
- "\n",
- " # TODO: Add unicode conversion\n",
- " d = [line.split() for line in open(input_data, 'r')]\n",
- " d = np.hstack(np.array(d[3:]))\n",
- " \n",
- " d = d.reshape(-1, 12)\n",
- " \n",
- " df = pd.DataFrame(d, columns=columns)\n",
- " file = os.path.split(os.path.splitext(input_data)[0])[1]\n",
- " df['ipf_file'] = pd.Series(np.full((len(df['pt_id'])), file), index = df.index)\n",
- "\n",
- " assert int(cnt) == len(df), 'Dataframe length {} does not match point length {}.'.format(int(cnt), len(df))\n",
- " \n",
- " # Soft conversion of numeric types to numerics, allows str in first col for point_id\n",
- " df = df.apply(pd.to_numeric, errors='ignore')\n",
- "\n",
- " return df\n",
- "\n",
- "@read_ipf.register(list)\n",
- "def read_ipf_list(input_data_list):\n",
- " \"\"\"\n",
- " Read a socet ipf file into a pandas data frame\n",
- "\n",
- " Parameters\n",
- " ----------\n",
- " input_data_list : list\n",
- " list of paths to the a set of input data files\n",
- "\n",
- " Returns\n",
- " -------\n",
- " df : pd.DataFrame\n",
- " containing the ipf data with appropriate column names and indices\n",
- " \"\"\"\n",
- " frames = []\n",
- "\n",
- " for input_file in input_data_list:\n",
- " frames.append(read_ipf(input_file))\n",
- "\n",
- " df = pd.concat(frames)\n",
- "\n",
- " return df"
+ " return files_dict"
]
},
{
@@ -2019,6 +1946,106 @@
"new_df"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "@singledispatch\n",
+ "def read_ipf(arg):\n",
+ " return str(arg)\n",
+ "\n",
+ "@read_ipf.register(str)\n",
+ "def read_ipf_str(input_data):\n",
+ " \"\"\"\n",
+ " Read a socet ipf file into a pandas data frame\n",
+ "\n",
+ " Parameters\n",
+ " ----------\n",
+ " input_data : str\n",
+ " path to the an input data file\n",
+ "\n",
+ " Returns\n",
+ " -------\n",
+ " df : pd.DataFrame\n",
+ " containing the ipf data with appropriate column names and indices\n",
+ " \"\"\"\n",
+ "\n",
+ " # Check that the number of rows is matching the expected number\n",
+ " with open(input_data, 'r') as f:\n",
+ " for i, l in enumerate(f):\n",
+ " if i == 1:\n",
+ " cnt = int(l)\n",
+ " elif i == 2:\n",
+ " col = l\n",
+ " break\n",
+ " \n",
+ " columns = np.genfromtxt(input_data, skip_header=2, dtype='unicode',\n",
+ " max_rows = 1, delimiter = ',')\n",
+ "\n",
+ " # TODO: Add unicode conversion\n",
+ " d = [line.split() for line in open(input_data, 'r')]\n",
+ " d = np.hstack(np.array(d[3:]))\n",
+ " \n",
+ " d = d.reshape(-1, 12)\n",
+ " \n",
+ " df = pd.DataFrame(d, columns=columns)\n",
+ " file = os.path.split(os.path.splitext(input_data)[0])[1]\n",
+ " df['ipf_file'] = pd.Series(np.full((len(df['pt_id'])), file), index = df.index)\n",
+ "\n",
+ " assert int(cnt) == len(df), 'Dataframe length {} does not match point length {}.'.format(int(cnt), len(df))\n",
+ " \n",
+ " # Soft conversion of numeric types to numerics, allows str in first col for point_id\n",
+ " df = df.apply(pd.to_numeric, errors='ignore')\n",
+ "\n",
+ " return df\n",
+ "\n",
+ "@read_ipf.register(list)\n",
+ "def read_ipf_list(input_data_list):\n",
+ " \"\"\"\n",
+ " Read a socet ipf file into a pandas data frame\n",
+ "\n",
+ " Parameters\n",
+ " ----------\n",
+ " input_data_list : list\n",
+ " list of paths to the a set of input data files\n",
+ "\n",
+ " Returns\n",
+ " -------\n",
+ " df : pd.DataFrame\n",
+ " containing the ipf data with appropriate column names and indices\n",
+ " \"\"\"\n",
+ " frames = []\n",
+ "\n",
+ " for input_file in input_data_list:\n",
+ " frames.append(read_ipf(input_file))\n",
+ "\n",
+ " df = pd.concat(frames)\n",
+ "\n",
+ " return df"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "True\n"
+ ]
+ }
+ ],
+ "source": [
+ "x = np.array(['1', '2', '3'])\n",
+ "y = np.array(['1', '2', '3'])\n",
+ "\n",
+ "print((x == y).all())"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
diff --git a/plio/io/io_bae.py b/plio/io/io_bae.py
index c69ddc8..37e5abc 100644
--- a/plio/io/io_bae.py
+++ b/plio/io/io_bae.py
@@ -85,11 +85,10 @@ def read_ipf_str(input_data):
columns = np.genfromtxt(input_data, skip_header=2, dtype='unicode',
max_rows = 1, delimiter = ',')
- # TODO: Add unicode conversion
d = [line.split() for line in open(input_data, 'r')]
d = np.hstack(np.array(d[3:]))
- d = d.reshape(-1, 12)
+ d = d.reshape(-1, 12).astype('unicode')
df = pd.DataFrame(d, columns=columns)
file = os.path.split(os.path.splitext(input_data)[0])[1]
@@ -126,6 +125,54 @@ def read_ipf_list(input_data_list):
return df
+def save_ipf(df, output_path):
+ """
+ Write a socet gpf file from a gpf-defined pandas dataframe
+
+ Parameters
+ ----------
+ df : pd.DataFrame
+ Pandas DataFrame
+
+ output_file : str
+ path to the output data file
+
+ Returns
+ -------
+ int : success value
+ 0 = success, 1 = errors
+ """
+
+ for ipf_file, ipf_df in df.groupby('ipf_file'):
+
+ output_file = os.path.join(output_path, ipf_file + '.ipf')
+
+ # Check that file can be opened
+ try:
+ outIPF = open(output_file, 'w', newline='\r\n')
+ except:
+ print('Unable to open output ipf file: {0}'.format(output_file))
+ return 1
+
+ #grab number of rows in pandas dataframe ipf group
+ numpts = len(ipf_df)
+
+ #Output ipf header
+ outIPF.write('IMAGE POINT FILE\n')
+ outIPF.write('{0}\n'.format(numpts))
+ outIPF.write('pt_id,val,fid_val,no_obs,l.,s.,sig_l,sig_s,res_l,res_s,fid_x,fid_y\n')
+
+ for index, row in ipf_df.iterrows():
+ #Output coordinates to ipf file
+ outIPF.write('{0} {1} {2} {3}\n'.format(row['pt_id'], row['val'], row['fid_val'], row['no_obs']))
+ outIPF.write('{:0.6f} {:0.6f}\n'.format(row['l.'], row['s.']))
+ outIPF.write('{:0.6f} {:0.6f}\n'.format(row['sig_l'], row['sig_s']))
+ outIPF.write('{:0.6f} {:0.6f}\n'.format(row['res_l'], row['res_s']))
+ outIPF.write('{:0.6f} {:0.6f}\n\n'.format(row['fid_x'], row['fid_y']))
+
+ outIPF.close()
+ return
+
def read_gpf(input_data):
"""
Read a socet gpf file into a pandas data frame
diff --git a/plio/io/tests/temp/P20_008845_1894_XN_09N203W.ipf b/plio/io/tests/temp/P20_008845_1894_XN_09N203W.ipf
new file mode 100644
index 0000000..4a377c8
--- /dev/null
+++ b/plio/io/tests/temp/P20_008845_1894_XN_09N203W.ipf
@@ -0,0 +1,729 @@
+IMAGE POINT FILE
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diff --git a/plio/io/tests/test_io_bae.py b/plio/io/tests/test_io_bae.py
index 105680b..2817c88 100644
--- a/plio/io/tests/test_io_bae.py
+++ b/plio/io/tests/test_io_bae.py
@@ -1,10 +1,11 @@
import json
+import os
import numpy as np
import pandas as pd
from pandas.util.testing import assert_frame_equal
-from plio.io.io_bae import socetset_keywords_to_json, read_gpf, save_gpf, read_ipf
+from plio.io.io_bae import socetset_keywords_to_json, read_gpf, save_gpf, read_ipf, save_ipf
from plio.examples import get_path
import pytest
@@ -25,15 +26,42 @@ def insight_ipf():
def insight_expected_ipf():
return pd.read_csv(get_path('P20_008845_1894_XN_09N203W.csv'))
+@pytest.mark.parametrize('ipf, expected', [([insight_ipf()],insight_expected_ipf())])
+def test_read_ifp(ipf, expected):
+ df = read_ipf(ipf)
+ assert_frame_equal(df, expected)
+
@pytest.mark.parametrize('gpf, expected', [(insight_gpf(),insight_expected_gpf())])
def test_read_gfp(gpf, expected):
df = read_gpf(gpf)
assert_frame_equal(df, expected)
-@pytest.mark.parametrize('ipf, expected', [([insight_ipf()],insight_expected_ipf())])
-def test_read_ifp(ipf, expected):
+@pytest.mark.parametrize('ipf, file', [(insight_ipf(), 'plio/io/tests/temp')])
+def test_write_ipf(ipf, file):
df = read_ipf(ipf)
- assert_frame_equal(df, expected)
+ save_ipf(df, file)
+
+ file = os.path.join(file, 'P20_008845_1894_XN_09N203W.ipf')
+
+ with open(ipf) as f:
+ fl = f.readlines()
+
+ with open(file) as f:
+ fs = f.readlines()
+
+ # Check that the header is the same
+ for i in range(3):
+ assert fl[i] == fs[i]
+
+ truth_arr = [line.split() for line in open(ipf, 'r')][3:]
+ truth_arr = np.hstack(np.array(truth_arr))
+ truth_arr = truth_arr.reshape(-1, 12)
+
+ test_arr = [line.split() for line in open(file, 'r')][3:]
+ test_arr = np.hstack(np.array(test_arr))
+ test_arr = test_arr.reshape(-1, 12)
+
+ assert (truth_arr == test_arr).all()
@pytest.mark.parametrize('gpf, file', [(insight_gpf(), 'out.gpf')])
def test_write_gpf(gpf, file):
@@ -56,8 +84,11 @@ def test_write_gpf(gpf, file):
truth_arr = np.genfromtxt(gpf, skip_header=3)
test_arr = np.genfromtxt(file, skip_header=3)
+
np.testing.assert_array_almost_equal(truth_arr, test_arr)
+ # np.testing.assert_array_almost_equal(truth_arr, test_arr)
+
def test_create_from_socet_lis():
socetlis = get_path('socet_isd.lis')
socetell = get_path('ellipsoid.ell')
--
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