Merge branch 'main' into fix_poly

.github/workflows/lint.yml

@@ -13,31 +13,31 @@ permissions:
   contents: read
 
 jobs:
-  super-linter:
-    name: Lint Code Base
-    runs-on: ubuntu-latest
-    permissions:
-      contents: read
-      pull-requests: write
-      actions: read
-      checks: read
-      statuses: write
-    steps:
-      - name: Checkout Code
-        uses: actions/checkout@v4
-        with:
-          # Full git history is needed to get a proper
-          # list of changed files within `super-linter`
-          fetch-depth: 0
-
-      - name: Lint Code Base
-        uses: super-linter/super-linter/slim@v6
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-          VALIDATE_ALL_CODEBASE: false
-          DEFAULT_BRANCH: master
-          LINTER_RULES_PATH: .
-          MARKDOWN_CONFIG_FILE: .markdownlint.json
+##  super-linter:
+##    name: Lint Code Base
+##    runs-on: ubuntu-latest
+##    permissions:
+##      contents: read
+##      pull-requests: write
+##      actions: read
+##      checks: read
+##      statuses: write
+##    steps:
+##      - name: Checkout Code
+##        uses: actions/checkout@v4
+##        with:
+##          # Full git history is needed to get a proper
+##          # list of changed files within `super-linter`
+##          fetch-depth: 0
+##
+##      - name: Lint Code Base
+##        uses: super-linter/super-linter/slim@v6.7.0
+##        env:
+##          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+##          VALIDATE_ALL_CODEBASE: false
+##          DEFAULT_BRANCH: main
+##          LINTER_RULES_PATH: .
+##          MARKDOWN_CONFIG_FILE: .markdownlint.json
 
   docs:
     runs-on: ubuntu-latest

Dockerfile

@@ -77,3 +77,7 @@ EOF
 
 # install Docker tools (cli, buildx, compose)
 COPY --from=gloursdocker/docker / /
+
+USER ${USERNAME}
+HEALTHCHECK CMD true
+

consts/README.md

@@ -46,6 +46,12 @@ consts.mksa_plancks_constant_hbar
 
 Planck's constant divided by `2\pi`, `\hbar`.
 
+```console
+consts.mksa_planck_temperature
+```
+
+Planck temperature `T_p`.
+
 ```console
 consts.num_avogadro
 ```

consts/cgs.v

@@ -8,6 +8,8 @@ pub const cgs_plancks_constant_h = 6.62606896e-27 // g cm^2 / s
 
 pub const cgs_plancks_constant_hbar = 1.05457162825e-27 // g cm^2 / s
 
+pub const cgs_planck_temperature = 1.416785e+32 // Kelvin
+
 pub const cgs_astronomical_unit = 1.49597870691e+13 // cm
 
 pub const cgs_light_year = 9.46053620707e+17 // cm

consts/cgsm.v

@@ -8,6 +8,8 @@ pub const cgsm_plancks_constant_h = 6.62606896e-27 // g cm^2 / s
 
 pub const cgsm_plancks_constant_hbar = 1.05457162825e-27 // g cm^2 / s
 
+pub const cgsm_planck_temperature = 1.416785e+32 // Kelvin
+
 pub const cgsm_astronomical_unit = 1.49597870691e+13 // cm
 
 pub const cgsm_light_year = 9.46053620707e+17 // cm

consts/mks.v

@@ -8,6 +8,8 @@ pub const mks_plancks_constant_h = 6.62606896e-34 // kg m^2 / s
 
 pub const mks_plancks_constant_hbar = 1.05457162825e-34 // kg m^2 / s
 
+pub const mks_planck_temperature = 1.416785e+32 // Kelvin
+
 pub const mks_astronomical_unit = 1.49597870691e+11 // m
 
 pub const mks_light_year = 9.46053620707e+15 // m

consts/mksa.v

@@ -8,6 +8,8 @@ pub const mksa_plancks_constant_h = 6.62606896e-34 // kg m^2 / s
 
 pub const mksa_plancks_constant_hbar = 1.05457162825e-34 // kg m^2 / s
 
+pub const mksa_planck_temperature = 1.416785e+32 // Kelvin
+
 pub const mksa_astronomical_unit = 1.49597870691e+11 // m
 
 pub const mksa_light_year = 9.46053620707e+15 // m

deriv/README.md

@@ -63,6 +63,18 @@ for values greater than `x`. 📉
 
 This function is equivalent to calling `deriv.forward` with a negative step-size.
 
+### `partial`
+
+```v ignore
+pub fn partial(f fn ([]f64) f64, x []f64, variable int, h f64) (f64, f64)
+```
+
+This function computes the partial derivative of the function `f` with respect to
+a specified variable at point `x` using step-size `h`. It returns the derivative
+in `result` and an error estimate in `abserr`. The function `f` should take an array
+of coordinates and return a single value. This method provides both the derivative
+and its error estimate.
+
 ## References and Further Reading
 
 This work is a spiritual descendent of the Differentiation module in [GSL](https://github.com/ampl/gsl). 📖

deriv/deriv.v

@@ -1,6 +1,7 @@
 module deriv
 
 import vsl.func
+import vsl.errors
 import vsl.internal.prec
 import math
 
@@ -113,3 +114,32 @@ pub fn forward(f func.Fn, x f64, h f64) (f64, f64) {
 pub fn backward(f func.Fn, x f64, h f64) (f64, f64) {
 	return forward(f, x, -h)
 }
+
+/**
+* partial is a function that computes the partial derivative of a multivariable function with respect to a specified variable.
+*
+* @param f       The multivariable function for which the partial derivative is to be computed.
+* @param x       The point at which the partial derivative is to be computed, represented as an array of coordinates.
+* @param variable The index of the variable with respect to which the partial derivative is to be computed.
+* @param h       The step size to be used in the central difference method.
+*
+* @return        A tuple containing the value of the partial derivative and the estimated error.
+*/
+pub fn partial(f fn ([]f64) f64, x []f64, variable int, h f64) (f64, f64) {
+	if variable < 0 || variable >= x.len {
+		errors.vsl_panic('Invalid variable index', .efailed)
+	}
+
+	// Define a helper function that converts the multivariate function
+	// to a univariate function for the specified variable
+	partial_helper := func.Fn{
+		f: fn [f, x, variable] (t f64, _ []f64) f64 {
+			mut x_new := x.clone()
+			x_new[variable] = t
+			return f(x_new)
+		}
+	}
+
+	// Use the central difference method to compute the partial derivative
+	return central(partial_helper, x[variable], h)
+}

deriv/deriv_test.v

@@ -68,6 +68,18 @@ fn df6(x f64, _ []f64) f64 {
 	return -1.0 / (x * x)
 }
 
+fn f_multi(x []f64) f64 {
+	return x[0] * x[0] + x[1] * x[1] // f(x,y) = x^2 + y^2
+}
+
+fn df_multi_dx(x []f64) f64 {
+	return 2 * x[0] // ∂f/∂x = 2x
+}
+
+fn df_multi_dy(x []f64) f64 {
+	return 2 * x[1] // ∂f/∂y = 2y
+}
+
 fn test_deriv() {
 	f1_ := func.Fn.new(f: f1)
 	df1_ := func.Fn.new(f: df1)
@@ -100,6 +112,18 @@ fn test_deriv() {
 	assert deriv_test('central', f6_, df6_, 10.0)
 	assert deriv_test('forward', f6_, df6_, 10.0)
 	assert deriv_test('backward', f6_, df6_, 10.0)
+
+	// Partial derivative test
+	x := [2.0, 3.0]
+	h := 1e-5
+
+	// Partial derivative with respect to x
+	dx, _ := partial(f_multi, x, 0, h)
+	assert float64.tolerance(dx, df_multi_dx(x), 1e-5)
+
+	// Partial derivative with respect to y
+	dy, _ := partial(f_multi, x, 1, h)
+	assert float64.tolerance(dy, df_multi_dy(x), 1e-5)
 }
 
 fn deriv_test(deriv_method string, f func.Fn, df func.Fn, x f64) bool {

errors/errno.v

@@ -2,73 +2,73 @@ module errors
 
 pub enum ErrorCode {
 	// success
-	success      = 0
+	success = 0
 	// generic failure
-	failure      = -1
+	failure = -1
 	// iteration has not converged
 	can_continue = -2
 	// input domain error, e.g sqrt(-1)
-	edom         = 1
+	edom = 1
 	// output range error, e.g. exp(1e+100)
-	erange       = 2
+	erange = 2
 	// invalid pointer
-	efault       = 3
+	efault = 3
 	// invalid argument supplied by user
-	einval       = 4
+	einval = 4
 	// generic failure
-	efailed      = 5
+	efailed = 5
 	// factorization failed
-	efactor      = 6
+	efactor = 6
 	// sanity check failed - shouldn't happen
-	esanity      = 7
+	esanity = 7
 	// malloc failed
-	enomem       = 8
+	enomem = 8
 	// problem with user-supplied function
-	ebadfunc     = 9
+	ebadfunc = 9
 	// iterative process is out of control
-	erunaway     = 10
+	erunaway = 10
 	// exceeded max number of iterations
-	emaxiter     = 11
+	emaxiter = 11
 	// tried to divide by zero
-	ezerodiv     = 12
+	ezerodiv = 12
 	// user specified an invalid tolerance
-	ebadtol      = 13
+	ebadtol = 13
 	// failed to reach the specified tolerance
-	etol         = 14
+	etol = 14
 	// underflow
-	eundrflw     = 15
+	eundrflw = 15
 	// overflow
-	eovrflw      = 16
+	eovrflw = 16
 	// loss of accuracy
-	eloss        = 17
+	eloss = 17
 	// failed because of roundoff error
-	eround       = 18
+	eround = 18
 	// matrix, vector lengths are not conformant
-	ebadlen      = 19
+	ebadlen = 19
 	// matrix not square
-	enotsqr      = 20
+	enotsqr = 20
 	// apparent singularity detected
-	esing        = 21
+	esing = 21
 	// integral or series is divergent
-	ediverge     = 22
+	ediverge = 22
 	// requested feature is not supported by the hardware
-	eunsup       = 23
+	eunsup = 23
 	// requested feature not (yet) implemented
-	eunimpl      = 24
+	eunimpl = 24
 	// cache limit exceeded
-	ecache       = 25
+	ecache = 25
 	// table limit exceeded
-	etable       = 26
+	etable = 26
 	// iteration is not making progress towards solution
-	enoprog      = 27
+	enoprog = 27
 	// jacobian evaluations are not improving the solution
-	enoprogj     = 28
+	enoprogj = 28
 	// cannot reach the specified tolerance in F
-	etolf        = 29
+	etolf = 29
 	// cannot reach the specified tolerance in X
-	etolx        = 30
+	etolx = 30
 	// cannot reach the specified tolerance in gradient
-	etolg        = 31
+	etolg = 31
 	// end of file
-	eof          = 32
+	eof = 32
 }

examples/README.md

@@ -1,6 +1,9 @@
 # V Scientific Library - Examples Directory 📚
 
-This directory contains various examples demonstrating the capabilities and usage of the V Scientific Library. Each example showcases different functionalities, from machine learning algorithms to plotting and mathematical computations. Below is a summary of the examples included in this directory:
+This directory contains various examples demonstrating the capabilities and usage
+of the V Scientific Library. Each example showcases different functionalities,
+from machine learning algorithms to plotting and mathematical computations.
+Below is a summary of the examples included in this directory:
 
 ## Machine Learning Examples 🤖
 
@@ -91,7 +94,11 @@ This directory contains various examples demonstrating the capabilities and usag
 
 ### Important Information ⚠️
 
-- Each example contains a `main.v` file with the V code demonstrating the specific functionality.
-- Some examples include an additional `README.md` file. **You must read the `README.md` before running the example** to understand any prerequisites or specific instructions.
+- Each example contains a `main.v` file with the V code demonstrating
+the specific functionality.
+- Some examples include an additional `README.md` file.
+**You must read the `README.md` before running the example** to understand
+any prerequisites or specific instructions.
 
-To get started, navigate to the respective example directory and run the `main.v` file using the V compiler.
+To get started, navigate to the respective example directory
+and run the `main.v` file using the V compiler.

examples/deriv_example/README.md

@@ -1,6 +1,7 @@
 # Example - deriv_example 📘
 
-This example demonstrates the usage of the V Scientific Library for demonstrating derivative calculation.
+This example demonstrates the usage of the V Scientific Library
+for demonstrating derivative calculation.
 
 ## Instructions
 

examples/dist_histogram/README.md

@@ -1,11 +1,13 @@
 # Example - dist_histogram 📘
 
-This example demonstrates the usage of the V Scientific Library for creating a distribution histogram.
+This example demonstrates the usage of the V Scientific Library
+for creating a distribution histogram.
 
 ## Instructions
 
 1. Ensure you have the V compiler installed. You can download it from [here](https://vlang.io).
-2. Ensure you have the VSL installed. You can do it following the [installation guide](https://github.com/vlang/vsl?tab=readme-ov-file#-installation)!
+2. Ensure you have the VSL installed. You can do it
+following the [installation guide](https://github.com/vlang/vsl?tab=readme-ov-file#-installation)!
 3. Navigate to this directory.
 4. Run the example using the following command:
 

examples/fft_plot_example/README.md

@@ -1,6 +1,7 @@
 # Example - fft_plot_example 📘
 
-This example demonstrates the usage of the V Scientific Library for demonstrating Fast Fourier Transform (FFT) with plotting.
+This example demonstrates the usage of the V Scientific Library
+for demonstrating Fast Fourier Transform (FFT) with plotting.
 
 ## Instructions
 

examples/io_h5_dataset/README.md

@@ -1,11 +1,13 @@
 # Example - io_h5_dataset 📘
 
-This example demonstrates the usage of the V Scientific Library for demonstrating HDF5 I/O for datasets.
+This example demonstrates the usage of the V Scientific Library
+for demonstrating HDF5 I/O for datasets.
 
 ## Instructions
 
 1. Ensure you have the V compiler installed. You can download it from [here](https://vlang.io).
-2. Ensure you have the VSL installed. You can do it following the [installation guide](https://github.com/vlang/vsl?tab=readme-ov-file#-installation)!
+2. Ensure you have the VSL installed. You can do it
+following the [installation guide](https://github.com/vlang/vsl?tab=readme-ov-file#-installation)!
 3. Navigate to this directory.
 4. Run the example using the following command: