Generate and return the approximate polynomial interpolation value of the input specified point x for the specified method.
For polynomial interpolation, the computation relies on the Neville algorithm.
- Parameters
-
| [in] | method | : The input scalar constant that can be,
-
The scalar constant neimean or a scalar object of type neimean_type implying the use of the average of the
func values of the two nearest neighbors of the input queryx smaller and larger than it as the output interp.
-
The scalar constant neinear or a scalar object of type neinear_type implying the use of the average of the
func value of the nearest neighbor of the input queryx as the output interp.
Note that the nearest neighbor in this case is measured by actual Euclidean distances of neighbors to the input queryx.
-
The scalar constant neiprev or a scalar object of type neiprev_type implying the use of the
func value of the largest abscissa in the input crdx smaller than the input queryx as the output interp.
-
The scalar constant neinext or a scalar object of type neinext_type implying the use of the
func value of the smallest abscissa in the input crdx larger than the input queryx as the output interp.
-
The scalar constant piwilin or a scalar object of type piwilin_type implying the use of the linear interpolation of the
func values of the two crdx points that bracket queryx as the output interp.
The linear interpolation implemented in this constructor is based on the Lagrange classical formula for linear interpolation.
Suppose an input query point \(x\) falls between two nodes \(x_i\) and \(x_{i+1}\) with the corresponding function values \(y_i\) and \(y_{i+1}\) and we wish to estimate the corresponding interpolated value \(y(x)\), which can be computed as,
\begin{equation*}
y(x) = \frac {x - x_{i+1}} {x_i - x_{i+1}} y_i + \frac {x - x_{i}} {x_{i+1} - x_{i}} y_{i+1} ~.
\end{equation*}
-
The scalar constant monopol or a scalar object of type monopol_type implying the use of a single polynomial interpolation of highest degree
size(crdx) - 1 possible to all pairs of (crdx, func) for computing the output interp.
The Neville algorithm is used to approximate the polynomial interpolation.
|
| [in] | crdx | : The input contiguous vector of
-
type
real of kind any supported by the processor (e.g., RK, RK32, RK64, or RK128),
containing the set of abscissa in strictly ascending order through which the constructed polynomial must pass.
If needed, the input values for crdx and sortedY can be sorted in ascending order by calling either setSorted() or setSorted(). |
| [in] | func | : The input contiguous vector of the same type, kind, and size as crdx, containing the set of function values corresponding to the input abscissa crdx through which the constructed polynomial must pass. |
| [in] | queryx | : The input scalar or vector of the same type and kind as crdx, containing the abscissa (x-value) of the queryx point. |
- Returns
interp : The output object of the same type, kind, rank, and shape as queryx, containing the (approximate) interpolated y-value(s) corresponding to the queryx point(s).
Possible calling interfaces ⛓
interp
= getInterp(method, crdx(
1:nsam), func(
1:nsam), queryx)
interp(
1:nque)
= getInterp(method, crdx(
1:nsam), func(
1:nsam), queryx(
1:nque))
Generate and return the approximate polynomial interpolation value of the input specified point x for...
This module contains procedures and data types for interpolation of finite samples of data.
- Warning
- The condition
size(crdx) == size(func) must hold for the corresponding input arguments.
The condition all([minval(crdx, 1) <= queryx .and. queryx <= maxval(crdx, 1)) must hold for the corresponding input arguments.
The condition isAscendingAll(crdx) .or. same_type_as(method, monopol_type()) must hold for the corresponding input arguments.
These conditions are verified only if the library is built with the preprocessor macro CHECK_ENABLED=1.
-
The
pure procedure(s) documented herein become impure when the ParaMonte library is compiled with preprocessor macro CHECK_ENABLED=1.
By default, these procedures are pure in release build and impure in debug and testing builds.
- See also
- getExtrap
setExtrap
getInterp
setInterp
pm_sampleQuan
pm_arraySort
pm_quadRomb
Example usage ⛓
11 type(display_type) :: disp
12 integer(IK) :: itry, ntry
= 5
13 integer(IK) :: dim, isam, ndim, nsam
25 real(RKG),
parameter :: PI
= PI_RKH
26 real(RKG),
allocatable :: crdx(:), func(:), queryx(:), interp(:)
27 integer(IK) :: ncrd, nquery
29 call disp%show(
"ncrd = 9; nquery = 33")
31 call disp%show(
"crdx = getLinSpace(0._RKG, 2 * PI, ncrd)")
39 call disp%show(
"queryx = getLinSpace(0._RKG, 2 * PI, nquery)")
44 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
45 call disp%show(
"!1D mean neighbors interpolation.")
46 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
48 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.neimean.crd.txt', reshape([crdx, func], [ncrd, 2_IK]), header = SK_'crdx,func')) error stop 'interpolation node outputting failed.'")
49 if (
0 /= getErrTableWrite(SK_
'getInterp.neimean.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
50 call disp%show(
"interp = getInterp(neimean, crdx, func, queryx)")
54 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.neimean.interp.txt', reshape([queryx, interp], [nquery, 2_IK]), header = SK_'queryx,interp')) error stop 'interpolation outputting failed.'")
55 if (
0 /= getErrTableWrite(SK_
'getInterp.neimean.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
57 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
58 call disp%show(
"!1D nearest neighbor interpolation.")
59 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
61 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.neinear.crd.txt', reshape([crdx, func], [ncrd, 2_IK]), header = SK_'crdx,func')) error stop 'interpolation node outputting failed.'")
62 if (
0 /= getErrTableWrite(SK_
'getInterp.neinear.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
63 call disp%show(
"interp = getInterp(neinear, crdx, func, queryx)")
67 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.neinear.interp.txt', reshape([queryx, interp], [nquery, 2_IK]), header = SK_'queryx,interp')) error stop 'interpolation outputting failed.'")
68 if (
0 /= getErrTableWrite(SK_
'getInterp.neinear.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
70 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
71 call disp%show(
"!1D next neighbor interpolation.")
72 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
74 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.neinext.crd.txt', reshape([crdx, func], [ncrd, 2_IK]), header = SK_'crdx,func')) error stop 'interpolation node outputting failed.'")
75 if (
0 /= getErrTableWrite(SK_
'getInterp.neinext.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
76 call disp%show(
"interp = getInterp(neinext, crdx, func, queryx)")
80 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.neinext.interp.txt', reshape([queryx, interp], [nquery, 2_IK]), header = SK_'queryx,interp')) error stop 'interpolation outputting failed.'")
81 if (
0 /= getErrTableWrite(SK_
'getInterp.neinext.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
83 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
84 call disp%show(
"!1D previous neighbor interpolation.")
85 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
87 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.neiprev.crd.txt', reshape([crdx, func], [ncrd, 2_IK]), header = SK_'crdx,func')) error stop 'interpolation node outputting failed.'")
88 if (
0 /= getErrTableWrite(SK_
'getInterp.neiprev.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
89 call disp%show(
"interp = getInterp(neiprev, crdx, func, queryx)")
93 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.neiprev.interp.txt', reshape([queryx, interp], [nquery, 2_IK]), header = SK_'queryx,interp')) error stop 'interpolation outputting failed.'")
94 if (
0 /= getErrTableWrite(SK_
'getInterp.neiprev.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
96 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
97 call disp%show(
"!1D piecewise linear interpolation.")
98 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
100 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.piwilin.crd.txt', reshape([crdx, func], [ncrd, 2_IK]), header = SK_'crdx,func')) error stop 'interpolation node outputting failed.'")
101 if (
0 /= getErrTableWrite(SK_
'getInterp.piwilin.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
102 call disp%show(
"interp = getInterp(piwilin, crdx, func, queryx)")
106 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.piwilin.interp.txt', reshape([queryx, interp], [nquery, 2_IK]), header = SK_'queryx,interp')) error stop 'interpolation outputting failed.'")
107 if (
0 /= getErrTableWrite(SK_
'getInterp.piwilin.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
109 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
110 call disp%show(
"!1D single polynomial interpolation.")
111 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
113 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.monopol.crd.txt', reshape([crdx, func], [ncrd, 2_IK]), header = SK_'crdx,func')) error stop 'interpolation node outputting failed.'")
114 if (
0 /= getErrTableWrite(SK_
'getInterp.monopol.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
115 call disp%show(
"interp = getInterp(monopol, crdx, func, queryx)")
119 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.monopol.interp.txt', reshape([queryx, interp], [nquery, 2_IK]), header = SK_'queryx,interp')) error stop 'interpolation outputting failed.'")
120 if (
0 /= getErrTableWrite(SK_
'getInterp.monopol.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
122 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
123 call disp%show(
"!1D single polynomial interpolation showing Runge effect.")
124 call disp%show(
"!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
128 call disp%show(
"ncrd = 9; nquery = 50 * ncrd")
129 ncrd
= 9; nquery
= 50 * ncrd
130 call disp%show(
"crdx = getLinSpace(-5., +5., ncrd)")
134 call disp%show(
"func = exp(getNormLogPDF(crdx))")
138 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.rungeEffect.crd.txt', reshape([crdx, func], [ncrd, 2_IK]), header = SK_'crdx,func')) error stop 'interpolation node outputting failed.'")
139 if (
0 /= getErrTableWrite(SK_
'getInterp.rungeEffect.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
140 call disp%show(
"queryx = getLinSpace(minval(crdx, 1), maxval(crdx, 1), nquery)")
141 queryx
= getLinSpace(
minval(crdx,
1),
maxval(crdx,
1), nquery)
144 call disp%show(
"interp = getInterp(monopol, crdx, func, queryx)")
148 call disp%show(
"if (0 /= getErrTableWrite(SK_'getInterp.rungeEffect.interp.txt', reshape([queryx, interp], [nquery, 2_IK]), header = SK_'queryx,interp')) error stop 'interpolation outputting failed.'")
149 if (
0 /= getErrTableWrite(SK_
'getInterp.rungeEffect.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
Generate count evenly spaced points over the interval [x1, x2] if x1 < x2, or [x2,...
Generate the natural logarithm of probability density function (PDF) of the univariate Normal distrib...
Generate and return the iostat code resulting from writing the input table of rank 1 or 2 to the spec...
This is a generic method of the derived type display_type with pass attribute.
This is a generic method of the derived type display_type with pass attribute.
This module contains procedures and generic interfaces for generating arrays with linear or logarithm...
This module contains classes and procedures for computing various statistical quantities related to t...
This module contains classes and procedures for input/output (IO) or generic display operations on st...
type(display_type) disp
This is a scalar module variable an object of type display_type for general display.
This module defines the relevant Fortran kind type-parameters frequently used in the ParaMonte librar...
integer, parameter LK
The default logical kind in the ParaMonte library: kind(.true.) in Fortran, kind(....
integer, parameter IK
The default integer kind in the ParaMonte library: int32 in Fortran, c_int32_t in C-Fortran Interoper...
integer, parameter SK
The default character kind in the ParaMonte library: kind("a") in Fortran, c_char in C-Fortran Intero...
integer, parameter RKS
The single-precision real kind in Fortran mode. On most platforms, this is an 32-bit real kind.
This module contains relevant mathematical constants.
real(RKB), parameter PI
The scalar real constant of kind with highest available precision RKB representing the irrational num...
type(piwilin_type), parameter piwilin
type(neiprev_type), parameter neiprev
type(neinext_type), parameter neinext
type(monopol_type), parameter monopol
type(neinear_type), parameter neinear
type(neimean_type), parameter neimean
Generate and return an object of type display_type.
Example Unix compile command via Intel ifort compiler ⛓
3ifort -fpp -standard-semantics -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
Example Windows Batch compile command via Intel ifort compiler ⛓
2set PATH=..\..\..\lib;%PATH%
3ifort /fpp /standard-semantics /O3 /I:..\..\..\include main.F90 ..\..\..\lib\libparamonte*.lib /exe:main.exe
Example Unix / MinGW compile command via GNU gfortran compiler ⛓
3gfortran -cpp -ffree-line-length-none -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
Example output ⛓
10+0.00000000,
+0.785398185,
+1.57079637,
+2.35619450,
+3.14159274,
+3.92699099,
+4.71238899,
+5.49778748,
+6.28318548
13+0.00000000,
+0.707106769,
+1.00000000,
+0.707106769,
-0.874227766E-7,
-0.707106888,
-1.00000000,
-0.707106531,
+0.174845553E-6
16+0.00000000,
+0.196349546,
+0.392699093,
+0.589048624,
+0.785398185,
+0.981747746,
+1.17809725,
+1.37444687,
+1.57079637,
+1.76714587,
+1.96349549,
+2.15984511,
+2.35619450,
+2.55254412,
+2.74889374,
+2.94524312,
+3.14159274,
+3.33794236,
+3.53429174,
+3.73064137,
+3.92699099,
+4.12334061,
+4.31969023,
+4.51603937,
+4.71238899,
+4.90873861,
+5.10508823,
+5.30143785,
+5.49778748,
+5.69413662,
+5.89048624,
+6.08683586,
+6.28318548
22if (
0 /= getErrTableWrite(SK_
'getInterp.neimean.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
25+0.00000000,
+0.353553385,
+0.353553385,
+0.353553385,
+0.707106769,
+0.853553414,
+0.853553414,
+0.853553414,
+1.00000000,
+0.853553414,
+0.853553414,
+0.853553414,
+0.707106769,
+0.353553355,
+0.353553355,
+0.353553355,
-0.874227766E-7,
-0.353553474,
-0.353553474,
-0.353553474,
-0.707106888,
-0.853553414,
-0.853553414,
-0.853553414,
-1.00000000,
-0.853553295,
-0.853553295,
-0.853553295,
-0.707106531,
-0.353553176,
-0.353553176,
-0.353553176,
+0.174845553E-6
26if (
0 /= getErrTableWrite(SK_
'getInterp.neimean.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
32if (
0 /= getErrTableWrite(SK_
'getInterp.neinear.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
35+0.00000000,
+0.00000000,
+0.707106769,
+0.707106769,
+0.707106769,
+0.707106769,
+0.707106769,
+1.00000000,
+1.00000000,
+1.00000000,
+0.707106769,
+0.707106769,
+0.707106769,
+0.707106769,
-0.874227766E-7,
-0.874227766E-7,
-0.874227766E-7,
-0.874227766E-7,
-0.874227766E-7,
-0.707106888,
-0.707106888,
-0.707106888,
-1.00000000,
-1.00000000,
-1.00000000,
-1.00000000,
-0.707106531,
-0.707106531,
-0.707106531,
-0.707106531,
-0.707106531,
+0.174845553E-6,
+0.174845553E-6
36if (
0 /= getErrTableWrite(SK_
'getInterp.neinear.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
42if (
0 /= getErrTableWrite(SK_
'getInterp.neinext.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
45+0.00000000,
+0.707106769,
+0.707106769,
+0.707106769,
+0.707106769,
+1.00000000,
+1.00000000,
+1.00000000,
+1.00000000,
+0.707106769,
+0.707106769,
+0.707106769,
+0.707106769,
-0.874227766E-7,
-0.874227766E-7,
-0.874227766E-7,
-0.874227766E-7,
-0.707106888,
-0.707106888,
-0.707106888,
-0.707106888,
-1.00000000,
-1.00000000,
-1.00000000,
-1.00000000,
-0.707106531,
-0.707106531,
-0.707106531,
-0.707106531,
+0.174845553E-6,
+0.174845553E-6,
+0.174845553E-6,
+0.174845553E-6
46if (
0 /= getErrTableWrite(SK_
'getInterp.neinext.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
52if (
0 /= getErrTableWrite(SK_
'getInterp.neiprev.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
55+0.00000000,
+0.00000000,
+0.00000000,
+0.00000000,
+0.707106769,
+0.707106769,
+0.707106769,
+0.707106769,
+1.00000000,
+1.00000000,
+1.00000000,
+1.00000000,
+0.707106769,
+0.707106769,
+0.707106769,
+0.707106769,
-0.874227766E-7,
-0.874227766E-7,
-0.874227766E-7,
-0.874227766E-7,
-0.707106888,
-0.707106888,
-0.707106888,
-0.707106888,
-1.00000000,
-1.00000000,
-1.00000000,
-1.00000000,
-0.707106531,
-0.707106531,
-0.707106531,
-0.707106531,
+0.174845553E-6
56if (
0 /= getErrTableWrite(SK_
'getInterp.neiprev.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
62if (
0 /= getErrTableWrite(SK_
'getInterp.piwilin.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
65+0.00000000,
+0.176776692,
+0.353553385,
+0.530330062,
+0.707106769,
+0.780330062,
+0.853553355,
+0.926776707,
+1.00000000,
+0.926776707,
+0.853553414,
+0.780330062,
+0.707106769,
+0.530330002,
+0.353553236,
+0.176776677,
-0.874227766E-7,
-0.176776841,
-0.353553355,
-0.530330122,
-0.707106888,
-0.780330181,
-0.853553534,
-0.926776707,
-1.00000000,
-0.926776648,
-0.853553295,
-0.780329883,
-0.707106531,
-0.530330181,
-0.353553414,
-0.176776618,
+0.174845553E-6
66if (
0 /= getErrTableWrite(SK_
'getInterp.piwilin.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
72if (
0 /= getErrTableWrite(SK_
'getInterp.monopol.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
75+0.00000000,
+0.196270034,
+0.383659512,
+0.556001663,
+0.707106769,
+0.831272066,
+0.923677325,
+0.980677783,
+1.00000000,
+0.980852842,
+0.923959076,
+0.831517816,
+0.707106769,
+0.555531383,
+0.382632047,
+0.195055515,
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76if (
0 /= getErrTableWrite(SK_
'getInterp.monopol.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
82ncrd
= 9; nquery
= 50 * ncrd
85-5.00000000,
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89if (
0 /= getErrTableWrite(SK_
'getInterp.rungeEffect.crd.txt',
reshape([crdx, func], [ncrd,
2_IK]), header
= SK_
'crdx,func'))
error stop 'interpolation node outputting failed.'
90queryx
= getLinSpace(
minval(crdx,
1),
maxval(crdx,
1), nquery)
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96if (
0 /= getErrTableWrite(SK_
'getInterp.rungeEffect.interp.txt',
reshape([queryx, interp], [nquery,
2_IK]), header
= SK_
'queryx,interp'))
error stop 'interpolation outputting failed.'
Postprocessing of the example output ⛓
3import matplotlib.pyplot
as plt
12for kind
in [
"neimean",
"neinear",
"neinext",
"neiprev",
"piwilin",
"monopol",
"rungeEffect"]:
14 crd = pd.read_csv(glob.glob(
"*."+kind+
".crd.txt")[0], delimiter =
",")
15 pattern =
"*."+kind+
".interp.txt"
16 fileList = glob.glob(pattern)
20 df = pd.read_csv(file, delimiter =
",")
23 fig = plt.figure(figsize = (8, 6))
24 ax = plt.subplot(1,1,1)
26 ax.scatter ( df.values[:, 0]
32 ax.scatter ( crd.values[:, 0]
40 ax.set_xlabel(
"X", fontsize = 17)
41 ax.set_ylabel(
"Y", fontsize = 17)
42 plt.grid(visible =
True, which =
"both", axis =
"both", color =
"0.85", linestyle =
"-")
43 ax.tick_params(axis =
"x", which =
"minor")
44 ax.tick_params(axis =
"y", which =
"minor")
45 ax.legend([file.split(
".")[-3],
"nodes"], fontsize = fontsize)
48 plt.savefig(file.replace(
".txt",
".png"))
Visualization of the example output ⛓
- Test:
- test_pm_polation
Final Remarks ⛓
If you believe this algorithm or its documentation can be improved, we appreciate your contribution and help to edit this page's documentation and source file on GitHub.
For details on the naming abbreviations, see this page.
For details on the naming conventions, see this page.
This software is distributed under the MIT license with additional terms outlined below.
-
If you use any parts or concepts from this library to any extent, please acknowledge the usage by citing the relevant publications of the ParaMonte library.
-
If you regenerate any parts/ideas from this library in a programming environment other than those currently supported by this ParaMonte library (i.e., other than C, C++, Fortran, MATLAB, Python, R), please also ask the end users to cite this original ParaMonte library.
This software is available to the public under a highly permissive license.
Help us justify its continued development and maintenance by acknowledging its benefit to society, distributing it, and contributing to it.
- Copyright
- Computational Data Science Lab
- Author:
- Amir Shahmoradi, September 1, 2017, 12:00 AM, Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin
Definition at line 492 of file pm_polation.F90.
1.9.3