diff --git a/README.md b/README.md
index 9104c6a34aa84afcf215eb941b4e81668f3d9841..6257eef647feb5d26f018bc6caf1926c7a766cc2 100644
--- a/README.md
+++ b/README.md
@@ -33,6 +33,10 @@ If output file `OUTFILE` is undefined, the output is directed to `STDOUT`.
Set the filename of the input spreadsheet.
+- **-w**, **-\-width** *WIDTHS*
+
+ Set comma-separated list of column widths of the input spreadsheet if auto-detection fails.
+
- **-m**, **-\-method** *METHOD*
Set the interpolation method. Select one of the following: `linear` (default), `nearest`, `cubic`. The following options are available for 2D data only: `nearest-up`, `zero`, `slinear`, `quadratic`, `previous`, `next`.
@@ -65,44 +69,44 @@ If output file `OUTFILE` is undefined, the output is directed to `STDOUT`.
Assume the following input file `testdata2.csv` containing scattered data points in 2D:
```text
- x y
- 0.005 0.615
- 0.014 2.935
- 0.019 4.712
- 0.038 13.814
- 0.064 24.658
- 0.076 29.594
- 0.095 39.155
- 0.125 59.091
- 0.145 77.677
+ X Y
+ 0.005 0.615
+ 0.014 2.935
+ 0.019 4.712
+ 0.038 13.814
+ 0.064 24.658
+ 0.076 29.594
+ 0.095 39.155
+ 0.125 59.091
+ 0.145 77.677
```
The following command will parse the file above and produce regular gridded data points using cubic spline interpolation along the first column in the interval `[0.0,0.15]` using `15` steps, i.e. every increment of `0.01` a data point is interpolated in the second column.
```bash
-$ mkgrid --infile testdata2.csv --range 0:0.15 --steps 15 --method cubic
+$ mkgrid -i testdata2.csv -r 0:0.15 -s 15 -m cubic
```
The output will look like the following:
```text
- x y
- 0.000 -0.297
- 0.010 1.780
- 0.020 5.116
- 0.030 9.812
- 0.040 14.762
- 0.050 19.119
- 0.060 23.094
- 0.070 27.051
- 0.080 31.418
- 0.090 36.432
- 0.100 42.011
- 0.110 48.205
- 0.120 55.215
- 0.130 63.249
- 0.140 72.516
- 0.150 83.224
+ X Y
+ 0.000 -0.297
+ 0.010 1.780
+ 0.020 5.116
+ 0.030 9.812
+ 0.040 14.762
+ 0.050 19.119
+ 0.060 23.094
+ 0.070 27.051
+ 0.080 31.418
+ 0.090 36.432
+ 0.100 42.011
+ 0.110 48.205
+ 0.120 55.215
+ 0.130 63.249
+ 0.140 72.516
+ 0.150 83.224
```
An example plot for the above result would look like this:
@@ -114,69 +118,74 @@ An example plot for the above result would look like this:
Assume the following input file `testdata3.csv` containing scattered data points in 3D:
```text
- x y z
- 0.000 0.000 0.000
- 0.019 0.000 4.712
- 0.042 0.000 15.976
- 0.092 0.000 37.076
- 0.109 0.000 47.519
- 0.136 0.000 68.049
- 0.009 0.001 2.413
- 0.026 0.005 11.605
- 0.094 0.032 43.647
- 0.106 0.037 51.925
- 0.134 0.052 76.073
- 0.004 0.004 2.127
- 0.025 0.026 17.043
- 0.059 0.061 30.732
- 0.093 0.095 52.012
- 0.102 0.103 59.315
- 0.113 0.113 68.501
- 0.132 0.132 87.946
- 0.003 0.009 2.752
- 0.007 0.021 8.035
- 0.011 0.033 12.049
- 0.022 0.066 18.954
- 0.040 0.109 27.913
- 0.046 0.122 31.549
- 0.052 0.132 34.542
- 0.000 0.023 5.569
- 0.000 0.072 11.650
- 0.000 0.091 13.370
- 0.000 0.115 15.056
- 0.000 0.134 16.302
+ X Y Z
+ 0.000 0.000 0.000
+ 0.019 0.000 4.712
+ 0.042 0.000 15.976
+ 0.092 0.000 37.076
+ 0.109 0.000 47.519
+ 0.136 0.000 68.049
+
+ 0.009 0.001 2.413
+ 0.026 0.005 11.605
+ 0.094 0.032 43.647
+ 0.106 0.037 51.925
+ 0.134 0.052 76.073
+
+ 0.004 0.004 2.127
+ 0.025 0.026 17.043
+ 0.059 0.061 30.732
+ 0.093 0.095 52.012
+ 0.102 0.103 59.315
+ 0.113 0.113 68.501
+ 0.132 0.132 87.946
+
+ 0.003 0.009 2.752
+ 0.007 0.021 8.035
+ 0.011 0.033 12.049
+ 0.022 0.066 18.954
+ 0.040 0.109 27.913
+ 0.046 0.122 31.549
+ 0.052 0.132 34.542
+
+ 0.000 0.023 5.569
+ 0.000 0.072 11.650
+ 0.000 0.091 13.370
+ 0.000 0.115 15.056
+ 0.000 0.134 16.302
```
The following command will parse the above input file and creates regular gridded data points along data columns 1 and 2 within the interval `[0.0,0.13]` in both dimensions. The corresponding data in column 3 will be interpolated using `13` steps, i.e. `(13+1)×(13+1)=196` records will be created in total.
```bash
-$ mkgrid --infile testdata3.csv --range 0:0.13,0:0.13 --steps 13
+$ mkgrid -i testdata3.csv -r 0:0.13,0:0.13 -s 13
```
The output will look like the following:
```text
- x y z
- 0.000 0.000 0.000
- 0.010 0.000 2.480
- 0.020 0.000 5.202
- 0.030 0.000 10.099
- 0.040 0.000 14.997
- 0.050 0.000 19.352
- 0.060 0.000 23.572
- 0.070 0.000 27.792
- 0.080 0.000 32.012
- 0.090 0.000 36.232
- 0.100 0.000 41.990
- 0.110 0.000 48.279
- 0.120 0.000 55.883
- 0.130 0.000 63.487
- 0.000 0.010 2.421
- 0.010 0.010 5.438
- 0.020 0.010 10.451
- 0.030 0.010 14.423
- 0.040 0.010 17.364
- 0.050 0.010 20.807
+ X Y Z
+ 0.000 0.000 0.000
+ 0.010 0.000 2.480
+ 0.020 0.000 5.202
+ 0.030 0.000 10.099
+ 0.040 0.000 14.997
+ 0.050 0.000 19.352
+ 0.060 0.000 23.572
+ 0.070 0.000 27.792
+ 0.080 0.000 32.012
+ 0.090 0.000 36.232
+ 0.100 0.000 41.990
+ 0.110 0.000 48.279
+ 0.120 0.000 55.883
+ 0.130 0.000 63.487
+
+ 0.000 0.010 2.421
+ 0.010 0.010 5.438
+ 0.020 0.010 10.451
+ 0.030 0.010 14.423
+ 0.040 0.010 17.364
+ 0.050 0.010 20.807
[...]
```
An example plot for the above would look like this:
@@ -188,14 +197,14 @@ An example plot for the above would look like this:
Assume an input file `testdata4.csv` containing 4 columns of scattered input data. In this example, columns 1-3 describe spatial coordinates on the surface of a sphere wheras column 4 holds the surface temperature of that point:
```text
- x y z T
- 0.000 0.000 10.000 0.0
- 2.588 0.000 9.659 7.8
- 5.000 0.000 8.660 15.0
- 7.071 0.000 7.071 21.2
- 8.660 0.000 5.000 26.0
- 9.659 0.000 2.588 29.0
- 10.000 0.000 0.000 30.0
+ X Y Z T
+ 0.000 0.000 10.000 0.0
+ 2.588 0.000 9.659 7.8
+ 5.000 0.000 8.660 15.0
+ 7.071 0.000 7.071 21.2
+ 8.660 0.000 5.000 26.0
+ 9.659 0.000 2.588 29.0
+ 10.000 0.000 0.000 30.0
[...]
```
diff --git a/bin/mkgrid b/bin/mkgrid
index 6390124b0133e99ef888ed9807e83f294e1dfa31..745675e9e8758456184c38e908e5d6180c550f83 100755
--- a/bin/mkgrid
+++ b/bin/mkgrid
@@ -1,7 +1,7 @@
#!/usr/bin/env python3
#
# Created: Mon 2024-07-15 18:40:27 CEST (boljen)
-# Modified: So 2024-07-21 12:10:54 CEST (boljen)
+# Modified: Tue 2024-08-06 20:17:12 CEST (boljen)
#
# mkgrid:
# Convert scattered data to regular gridded data in 2D, 3D and 4D
@@ -42,14 +42,15 @@ def execute_main():
description='Convert scattered data to regular gridded data in 2D, 3D and 4D')
# Add options
- parser.add_argument('-i', '--infile', help='Input filename', type=str, required=True)
- parser.add_argument('-m', '--method', help='Interpolation method', type=str, default='linear', choices=method.keys())
- parser.add_argument('-p', '--plot', help='Plot filename', nargs='?', const='***', type=str, default=None)
- parser.add_argument('-u', '--usecols', help='Comma-separated list of data columns to use from input file', type=str, default=None)
- parser.add_argument('-r', '--range', help='Comma-separated list of range specifiers for output', type=str, default=None)
- parser.add_argument('-s', '--steps', help='Comma-separated list of discretization steps', type=str, default=None)
- parser.add_argument('-y', '--yes', help='Overwrite existing output file', default=False, action=argparse.BooleanOptionalAction)
- parser.add_argument('outfile', help='Output filename', nargs='?', type=str, default=sys.stdout.buffer)
+ parser.add_argument('-i', '--infile', help='Input filename', type=str, required=True)
+ parser.add_argument('-m', '--method', help='Interpolation method', type=str, default='linear', choices=method.keys())
+ parser.add_argument('-p', '--plot', help='Plot filename', nargs='?', const='***', type=str, default=None)
+ parser.add_argument('-u', '--usecols', help='Comma-separated list of data columns to use from input file', type=str, default=None)
+ parser.add_argument('-r', '--range', help='Comma-separated list of range specifiers for output', type=str, default=None)
+ parser.add_argument('-s', '--steps', help='Comma-separated list of discretization steps', type=str, default=None)
+ parser.add_argument('-w', '--widths', help='Comma-separated list of column widths', type=str, default=None)
+ parser.add_argument('-y', '--yes', help='Overwrite existing output file', default=False, action=argparse.BooleanOptionalAction)
+ parser.add_argument('outfile', help='Output filename', nargs='?', type=str, default=sys.stdout.buffer)
# Parse options
args = parser.parse_args()
@@ -58,14 +59,33 @@ def execute_main():
if args.outfile != sys.stdout.buffer and os.path.exists(args.outfile) and not args.yes:
raise ValueError("File {:s} exists".format(args.outfile))
- # Read input file
- df = pd.read_fwf(args.infile)
+ if args.widths is None:
+
+ # Initialize list
+ widths = None
+
+ else:
+
+ # Split widths string in list of comma-seperated tokens
+ widths = [ x.strip() for x in args.widths.split(',') ]
+
+ # Loop over tokens
+ for i,x in enumerate(widths):
+
+ # Assert boundary values are floating-point data
+ try:
+ widths[i] = int(x)
+ except:
+ raise ValueError('Invalid token {:s} in widths list'.format(x))
+
+ # Read from input file
+ df = pd.read_fwf(args.infile, widths=widths, comment="#", skip_empty_rows=True)
data = df.to_dict('list')
# Initialize column list
usecols = None
- # Parse --usecols
+ # Parse usecols argument
if args.usecols is None:
# Use all available columns unless otherwise defined
@@ -75,6 +95,7 @@ def execute_main():
# Use columns specified by comma-separated list only
usecols = [ x.strip() for x in args.usecols.split(',') ]
+
# Convert strings to integers
for i,x in enumerate(usecols):
try:
@@ -99,7 +120,7 @@ def execute_main():
# Initialize range lists
myrange = []
- # Parse --range
+ # Parse range argument
if args.range is not None:
# Split comma-separated list of values
@@ -154,8 +175,12 @@ def execute_main():
except:
raise ValueError('Invalid token {:s} in steps list'.format(x))
- # Initialize labels list
+ # Initialize labels and formats list
label = []
+ fmtlist = []
+
+ # Assemble header
+ headstr = ''
# Loop over columns
for i,x in enumerate(usecols):
@@ -163,6 +188,20 @@ def execute_main():
# Assign column label
label.append(df.columns[usecols[i]])
+ # Auto-determine column width
+ width = max(len(label[-1]),12)
+ if widths is not None and widths[usecols[i]] > width:
+ width = widths[usecols[i]]
+
+ # Set format string
+ fmtstr = '%{:d}.{:d}f'.format(width,width-6)
+ fmtlist.append(fmtstr)
+
+ # Set header
+ if headstr != '': headstr += ' '
+ fmtstr = '{:>' + '{:d}s'.format(width) + '}'
+ headstr += fmtstr.format(df.columns[usecols[i]])
+
# Auto-detect array value
if i >= len(steps):
# Apply default or last element value
@@ -254,14 +293,8 @@ def execute_main():
for i,j,k,l in np.nditer([xi,yi,zi,ci]):
xout.append([i,j,k,l])
- # Assemble header
- headstr = ''
- for i in label:
- if headstr != '': headstr += ' '
- headstr += '{:>16s}'.format(i)
-
# Save regular gridded data to output file
- np.savetxt(args.outfile, xout, header=headstr, comments='', fmt='%16.7f')
+ np.savetxt(args.outfile, xout, header=headstr, comments='', fmt=fmtlist)
# =================
# Create plot
diff --git a/test/Makefile b/test/Makefile
index bd2de87c54944c76e8d6d9578c366462f9ed203b..370e1345405f092ef87a2ed1f42f19469ae2caed 100644
--- a/test/Makefile
+++ b/test/Makefile
@@ -5,13 +5,13 @@ OUTFILES = $(addsuffix .out, testdata2 testdata3 testdata4)
default: $(OUTFILES)
testdata2.out: testdata2.csv
- $(MKGRID) -y -i $< -p $(subst .csv,.png,$<) -s 15 -r 0:0.15 -m cubic $@
+ $(MKGRID) -y -i $< -p $(subst .csv,.png,$<) -s 15 -r 0:0.15 -m cubic -w 12,12 $@
testdata3.out: testdata3.csv
- $(MKGRID) -y -i $< -p $(subst .csv,.png,$<) -s 13 -r 0:0.13,0:0.13 $@
+ $(MKGRID) -y -i $< -p $(subst .csv,.png,$<) -s 13 -r 0:0.13,0:0.13 -w 12,12,12 $@
testdata4.out: testdata4.csv
- $(MKGRID) -y -i $< -p $(subst .csv,.png,$<) -s 10 -u 4,5,6,7 $@
+ $(MKGRID) -y -i $< -p $(subst .csv,.png,$<) -s 10 -u 4,5,6,7 -w 10,10,10,10,10,10,10 $@
clean:
$(RM) $(OUTFILES) $(subst .out,.png,$(OUTFILES))
diff --git a/test/testdata2.csv b/test/testdata2.csv
index 774c0d3e96ae85bab31a292923ad289494fc4fd4..c757038236c94d4a45d6bbc3e4628c4aca860e64 100644
--- a/test/testdata2.csv
+++ b/test/testdata2.csv
@@ -1,10 +1,10 @@
- x y
- 0.005 0.615
- 0.014 2.935
- 0.019 4.712
- 0.038 13.814
- 0.064 24.658
- 0.076 29.594
- 0.095 39.155
- 0.125 59.091
- 0.145 77.677
+ x y
+ 0.005 0.615
+ 0.014 2.935
+ 0.019 4.712
+ 0.038 13.814
+ 0.064 24.658
+ 0.076 29.594
+ 0.095 39.155
+ 0.125 59.091
+ 0.145 77.677
diff --git a/test/testdata3.csv b/test/testdata3.csv
index cb7b804a438049f3b256c3023bb109fc97fef081..0765956d9b42773f305b2fa981ae729f889162b0 100644
--- a/test/testdata3.csv
+++ b/test/testdata3.csv
@@ -1,31 +1,31 @@
- x y z
- 0.000 0.000 0.000
- 0.019 0.000 4.712
- 0.042 0.000 15.976
- 0.092 0.000 37.076
- 0.109 0.000 47.519
- 0.136 0.000 68.049
- 0.009 0.001 2.413
- 0.026 0.005 11.605
- 0.094 0.032 43.647
- 0.106 0.037 51.925
- 0.134 0.052 76.073
- 0.004 0.004 2.127
- 0.025 0.026 17.043
- 0.059 0.061 30.732
- 0.093 0.095 52.012
- 0.102 0.103 59.315
- 0.113 0.113 68.501
- 0.132 0.132 87.946
- 0.003 0.009 2.752
- 0.007 0.021 8.035
- 0.011 0.033 12.049
- 0.022 0.066 18.954
- 0.040 0.109 27.913
- 0.046 0.122 31.549
- 0.052 0.132 34.542
- 0.000 0.023 5.569
- 0.000 0.072 11.650
- 0.000 0.091 13.370
- 0.000 0.115 15.056
- 0.000 0.134 16.302
+ x y z
+ 0.000 0.000 0.000
+ 0.019 0.000 4.712
+ 0.042 0.000 15.976
+ 0.092 0.000 37.076
+ 0.109 0.000 47.519
+ 0.136 0.000 68.049
+ 0.009 0.001 2.413
+ 0.026 0.005 11.605
+ 0.094 0.032 43.647
+ 0.106 0.037 51.925
+ 0.134 0.052 76.073
+ 0.004 0.004 2.127
+ 0.025 0.026 17.043
+ 0.059 0.061 30.732
+ 0.093 0.095 52.012
+ 0.102 0.103 59.315
+ 0.113 0.113 68.501
+ 0.132 0.132 87.946
+ 0.003 0.009 2.752
+ 0.007 0.021 8.035
+ 0.011 0.033 12.049
+ 0.022 0.066 18.954
+ 0.040 0.109 27.913
+ 0.046 0.122 31.549
+ 0.052 0.132 34.542
+ 0.000 0.023 5.569
+ 0.000 0.072 11.650
+ 0.000 0.091 13.370
+ 0.000 0.115 15.056
+ 0.000 0.134 16.302
diff --git a/test/testdata4.csv b/test/testdata4.csv
index 17edfff559a3dca1846493136f3c7f380a7eebab..a4a8bf5513ce740ccaaed73ae9895fe074e81879 100644
--- a/test/testdata4.csv
+++ b/test/testdata4.csv
@@ -1,290 +1,290 @@
- r theta phi x y z T
- 10.0 0.0 0.0 0.000 0.000 10.000 0.0
- 10.0 15.0 0.0 2.588 0.000 9.659 7.8
- 10.0 30.0 0.0 5.000 0.000 8.660 15.0
- 10.0 45.0 0.0 7.071 0.000 7.071 21.2
- 10.0 60.0 0.0 8.660 0.000 5.000 26.0
- 10.0 75.0 0.0 9.659 0.000 2.588 29.0
- 10.0 90.0 0.0 10.000 0.000 0.000 30.0
- 10.0 105.0 0.0 9.659 0.000 -2.588 29.0
- 10.0 120.0 0.0 8.660 0.000 -5.000 26.0
- 10.0 135.0 0.0 7.071 0.000 -7.071 21.2
- 10.0 150.0 0.0 5.000 0.000 -8.660 15.0
- 10.0 165.0 0.0 2.588 0.000 -9.659 7.8
- 10.0 180.0 0.0 0.000 0.000 -10.000 0.0
+ r theta phi x y z T
+ 10.0 0.0 0.0 0.000 0.000 10.000 0.0
+ 10.0 15.0 0.0 2.588 0.000 9.659 7.8
+ 10.0 30.0 0.0 5.000 0.000 8.660 15.0
+ 10.0 45.0 0.0 7.071 0.000 7.071 21.2
+ 10.0 60.0 0.0 8.660 0.000 5.000 26.0
+ 10.0 75.0 0.0 9.659 0.000 2.588 29.0
+ 10.0 90.0 0.0 10.000 0.000 0.000 30.0
+ 10.0 105.0 0.0 9.659 0.000 -2.588 29.0
+ 10.0 120.0 0.0 8.660 0.000 -5.000 26.0
+ 10.0 135.0 0.0 7.071 0.000 -7.071 21.2
+ 10.0 150.0 0.0 5.000 0.000 -8.660 15.0
+ 10.0 165.0 0.0 2.588 0.000 -9.659 7.8
+ 10.0 180.0 0.0 0.000 0.000 -10.000 0.0
- 10.0 15.0 15.0 2.500 0.670 9.659 7.8
- 10.0 30.0 15.0 4.830 1.294 8.660 15.0
- 10.0 45.0 15.0 6.830 1.830 7.071 21.2
- 10.0 60.0 15.0 8.365 2.241 5.000 26.0
- 10.0 75.0 15.0 9.330 2.500 2.588 29.0
- 10.0 90.0 15.0 9.659 2.588 0.000 30.0
- 10.0 105.0 15.0 9.330 2.500 -2.588 29.0
- 10.0 120.0 15.0 8.365 2.241 -5.000 26.0
- 10.0 135.0 15.0 6.830 1.830 -7.071 21.2
- 10.0 150.0 15.0 4.830 1.294 -8.660 15.0
- 10.0 165.0 15.0 2.500 0.670 -9.659 7.8
+ 10.0 15.0 15.0 2.500 0.670 9.659 7.8
+ 10.0 30.0 15.0 4.830 1.294 8.660 15.0
+ 10.0 45.0 15.0 6.830 1.830 7.071 21.2
+ 10.0 60.0 15.0 8.365 2.241 5.000 26.0
+ 10.0 75.0 15.0 9.330 2.500 2.588 29.0
+ 10.0 90.0 15.0 9.659 2.588 0.000 30.0
+ 10.0 105.0 15.0 9.330 2.500 -2.588 29.0
+ 10.0 120.0 15.0 8.365 2.241 -5.000 26.0
+ 10.0 135.0 15.0 6.830 1.830 -7.071 21.2
+ 10.0 150.0 15.0 4.830 1.294 -8.660 15.0
+ 10.0 165.0 15.0 2.500 0.670 -9.659 7.8
- 10.0 15.0 30.0 2.241 1.294 9.659 7.8
- 10.0 30.0 30.0 4.330 2.500 8.660 15.0
- 10.0 45.0 30.0 6.124 3.536 7.071 21.2
- 10.0 60.0 30.0 7.500 4.330 5.000 26.0
- 10.0 75.0 30.0 8.365 4.830 2.588 29.0
- 10.0 90.0 30.0 8.660 5.000 0.000 30.0
- 10.0 105.0 30.0 8.365 4.830 -2.588 29.0
- 10.0 120.0 30.0 7.500 4.330 -5.000 26.0
- 10.0 135.0 30.0 6.124 3.536 -7.071 21.2
- 10.0 150.0 30.0 4.330 2.500 -8.660 15.0
- 10.0 165.0 30.0 2.241 1.294 -9.659 7.8
+ 10.0 15.0 30.0 2.241 1.294 9.659 7.8
+ 10.0 30.0 30.0 4.330 2.500 8.660 15.0
+ 10.0 45.0 30.0 6.124 3.536 7.071 21.2
+ 10.0 60.0 30.0 7.500 4.330 5.000 26.0
+ 10.0 75.0 30.0 8.365 4.830 2.588 29.0
+ 10.0 90.0 30.0 8.660 5.000 0.000 30.0
+ 10.0 105.0 30.0 8.365 4.830 -2.588 29.0
+ 10.0 120.0 30.0 7.500 4.330 -5.000 26.0
+ 10.0 135.0 30.0 6.124 3.536 -7.071 21.2
+ 10.0 150.0 30.0 4.330 2.500 -8.660 15.0
+ 10.0 165.0 30.0 2.241 1.294 -9.659 7.8
- 10.0 15.0 45.0 1.830 1.830 9.659 7.8
- 10.0 30.0 45.0 3.536 3.536 8.660 15.0
- 10.0 45.0 45.0 5.000 5.000 7.071 21.2
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