Repository: flimlib/flimlib (language: python)

Issue:
Build issues
Builds are currently in the process of being migrated to GitHub Actions. This issue is to track this process.

Currently, build fails on Ubuntu due to tests failing. It turns out that the old CI (Travis) was not running the tests (at least not in a way that failed the build), and some of the tests (using cram) don't run on Windows, so we have accumulated some failing tests.

In a few cases it appears that the tests are too numerically stringent, but other failures might indicate real bugs. I am reviewing each test.


Discussion / hints:

Fix patch:
diff --git a/.github/build.sh b/.github/build.sh
index 51cb35b..539d59c 100755
--- a/.github/build.sh
+++ b/.github/build.sh
@@ -6,12 +6,12 @@ exit_code=$?
 if [ $exit_code -ne 0 ]; then exit $exit_code; fi
 
 # NB: We skip tests when doing a release, because:
-# A) The target folder structure differs, and cram hardcodes it; and
+# A) The target folder structure differs, and prysk hardcodes it; and
 # B) The release already happened and was deployed by now. ;-)
 if [ ! -f ./target/checkout/release.properties ]
 then
   # Run the unit tests
-  python -m cram ./tests
+  python -m prysk ./tests
 
   exit_code=$((exit_code | $?))
 fi
diff --git a/.github/workflows/build-main.yml b/.github/workflows/build-main.yml
index 95466dd..be996b2 100644
--- a/.github/workflows/build-main.yml
+++ b/.github/workflows/build-main.yml
@@ -32,10 +32,10 @@ jobs:
         uses: actions/setup-python@v1
         with:
           python-version: 3.8
-      - name: Set up cram
+      - name: Set up prysk
         run: |
           python -m pip install --upgrade pip
-          pip install cram==0.6
+          pip install prysk==0.12.2
       - name: Set up Java
         uses: actions/setup-java@v2
         with:
diff --git a/.github/workflows/build-pr.yml b/.github/workflows/build-pr.yml
index a4726d7..2fcfd78 100644
--- a/.github/workflows/build-pr.yml
+++ b/.github/workflows/build-pr.yml
@@ -30,10 +30,10 @@ jobs:
         uses: actions/setup-python@v1
         with:
           python-version: 3.8
-      - name: Set up cram
+      - name: Set up prysk
         run: |
           python -m pip install --upgrade pip
-          pip install cram==0.6
+          pip install prysk==0.12.2
       - name: Set up Java
         uses: actions/setup-java@v2
         with:
diff --git a/.gitignore b/.gitignore
index d8fd115..4e8efab 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,4 @@
+*~
 .classpath
 .project
 .settings
@@ -5,6 +6,7 @@ target
 build
 src/matlab/*.mex*
 src/main/c/doxygen.exe
+tests/*.t.err
 *.log
 /bin/
 /Debug/
diff --git a/src/flimlib-cmd/cpp/main.cpp b/src/flimlib-cmd/cpp/main.cpp
index 70ca05d..5feaafc 100644
--- a/src/flimlib-cmd/cpp/main.cpp
+++ b/src/flimlib-cmd/cpp/main.cpp
@@ -59,29 +59,27 @@ int main(int argc, const char * argv[])
 
 	// Run the RLD fit function: Basic fit, no prompt, on data subset
 	iterations = flimLib.fitRLD();
-	if (iterations <= 0) {
-		// An error occurred
-		cout << "ERROR with FLIMLib.fitRLD\n";
-		exit(0);
-	}
 	cout << "RLD Z:" << flimLib.param[FLIMLIB_RLD_PARAM_Z]
 		<< " A:"    << flimLib.param[FLIMLIB_RLD_PARAM_A] 
 		<< " tau:"  << flimLib.param[FLIMLIB_RLD_PARAM_TAU]
 		<< " chisq:" << flimLib.getReducedChiSq() 
 		<< " iterations:" << iterations << "\n";
-
-	// Run the LMA fit function; all flimLib.param values will carry over into the next fit as a starting point
-	iterations = flimLib.fitLMA(FLIMLIB_MONO);
 	if (iterations <= 0) {
-		// An error occurred
-		cout << "ERROR with FLIMLib.fitLMA\n";
+		cout << "ERROR with FLIMLib.fitRLD\n";
 		exit(0);
 	}
+
+	// Run the LMA fit function; all flimLib.param values will carry over into the next fit as a starting point
+	iterations = flimLib.fitLMA(FLIMLIB_MONO);
 	cout << "LMA Z:" << flimLib.param[FLIMLIB_MONO_PARAM_Z]
 		<< " A:" << flimLib.param[FLIMLIB_MONO_PARAM_A]
 		<< " tau:" << flimLib.param[FLIMLIB_MONO_PARAM_TAU]
 		<< " chisq:" << flimLib.getReducedChiSq() 
 		<< " iterations:" << iterations << "\n";
+	if (iterations <= 0) {
+		cout << "ERROR with FLIMLib.fitLMA\n";
+		exit(0);
+	}
 	
 
 	// Use an instrument function
@@ -89,16 +87,15 @@ int main(int argc, const char * argv[])
 
 	// Run the RLD fit function: simple
 	iterations = flimLib.fitRLD();
-	if (iterations <= 0) {
-		// An error occurred
-		cout << "ERROR with FLIMLib.fitRLD\n";
-		exit(0);
-	}
 	cout << "RLDi Z:" << flimLib.param[FLIMLIB_RLD_PARAM_Z]
 		<< " A:" << flimLib.param[FLIMLIB_RLD_PARAM_A]
 		<< " tau:" << flimLib.param[FLIMLIB_RLD_PARAM_TAU]
 		<< " chisq:" << flimLib.getReducedChiSq()
 		<< " iterations:" << iterations << "\n";
+	if (iterations <= 0) {
+		cout << "ERROR with FLIMLib.fitRLD\n";
+		exit(0);
+	}
 
 	// Assign the optional fitter Outputs to make plots if we want
 	flimLib.fitted = fitted;
@@ -107,16 +104,15 @@ int main(int argc, const char * argv[])
 	// Run the LMA fit function: with instr and maximum likelihood (NOISE_MLE)
 	flimLib.noise_model = NOISE_MLE;
 	iterations = flimLib.fitLMA(FLIMLIB_MONO);
-	if (iterations <= 0) {
-		// An error occurred
-		cout << "ERROR with FLIMLib.fitLMA\n";
-		exit(0);
-	}
 	cout << "LMAi Z:" << flimLib.param[FLIMLIB_MONO_PARAM_Z]
 		<< " A:" << flimLib.param[FLIMLIB_MONO_PARAM_A]
 		<< " tau:" << flimLib.param[FLIMLIB_MONO_PARAM_TAU]
 		<< " chisq:" << flimLib.getReducedChiSq()
 		<< " iterations:" << iterations << "\n";
+	if (iterations <= 0) {
+		cout << "ERROR with FLIMLib.fitLMA\n";
+		exit(0);
+	}
 
 	// Setup a resonable start for tri-exp
 	flimLib.param[FLIMLIB_TRI_PARAM_A1] /= 3.0;      // divide the amplitude A1
@@ -129,11 +125,6 @@ int main(int argc, const char * argv[])
 	// Run the LMA Bi exp
 	// all starting params from last fit
 	iterations = flimLib.fitLMA(FLIMLIB_BI);
-	if (iterations <= 0) {
-		// An error occurred
-		cout << "ERROR with FLIMLib.fitLMA\n";
-		exit(0);
-	}
 	cout << "LMAi Z:" << flimLib.param[FLIMLIB_BI_PARAM_Z]
 		<< " A1:" << flimLib.param[FLIMLIB_BI_PARAM_A1]
 		<< " tau1:" << flimLib.param[FLIMLIB_BI_PARAM_TAU1]
@@ -141,6 +132,10 @@ int main(int argc, const char * argv[])
 		<< " tau2:" << flimLib.param[FLIMLIB_BI_PARAM_TAU2]
 		<< " chisq:" << flimLib.getReducedChiSq()
 		<< " iterations:" << iterations << "\n";
+	if (iterations <= 0) {
+		cout << "ERROR with FLIMLib.fitLMA\n";
+		exit(0);
+	}
 
 	// Let's restrain Z>0
 	flimLib.restrainParameter(FLIMLIB_STRETCHED_PARAM_Z, 0.0, INFINITY);
@@ -150,11 +145,6 @@ int main(int argc, const char * argv[])
 
 	// Run the LMA Tri exp, fix tau3=0.5;
 	iterations = flimLib.fitLMA(FLIMLIB_TRI);
-	if (iterations <= 0) {
-		// An error occurred
-		cout << "ERROR with FLIMLib.fitLMA\n";
-		exit(0);
-	}
 	cout << "LMAi Z:" << flimLib.param[FLIMLIB_TRI_PARAM_Z]
 		<< " A1:" << flimLib.param[FLIMLIB_TRI_PARAM_A1]
 		<< " tau1:" << flimLib.param[FLIMLIB_TRI_PARAM_TAU1]
@@ -164,10 +154,17 @@ int main(int argc, const char * argv[])
 		<< " tau3:" << flimLib.param[FLIMLIB_TRI_PARAM_TAU3]
 		<< " chisq:" << flimLib.getReducedChiSq()
 		<< " iterations:" << iterations << "\n";
+	if (iterations <= 0) {
+		cout << "ERROR with FLIMLib.fitLMA\n";
+		exit(0);
+	}
 
 	// Setup a resonable start for stretched-exp
+	flimLib.setupIRF(NULL, 0);
+	flimLib.param[FLIMLIB_STRETCHED_PARAM_Z] = 1.0;
+	flimLib.param[FLIMLIB_STRETCHED_PARAM_A] = 10000.0;
 	flimLib.param[FLIMLIB_STRETCHED_PARAM_TAU] = 2.0;
-	flimLib.param[FLIMLIB_STRETCHED_PARAM_H] = 1.5;
+	flimLib.param[FLIMLIB_STRETCHED_PARAM_H] = 1.0;
 	// all other params carry over from last fit
 
 	// Clear previous fixing and restraining
@@ -176,31 +173,29 @@ int main(int argc, const char * argv[])
 
 	// Run the LMA stretched exp
 	iterations = flimLib.fitLMA(FLIMLIB_STRETCHED);
-	if (iterations <= 0) {
-		// An error occurred
-		cout << "ERROR with FLIMLib.fitLMA\n";
-		exit(0);
-	}
 	cout << "LMAi Z:" << flimLib.param[FLIMLIB_STRETCHED_PARAM_Z]
 		<< " A:" << flimLib.param[FLIMLIB_STRETCHED_PARAM_A]
 		<< " tau:" << flimLib.param[FLIMLIB_STRETCHED_PARAM_TAU]
 		<< " h:" << flimLib.param[FLIMLIB_STRETCHED_PARAM_H]
 		<< " chisq:" << flimLib.getReducedChiSq()
 		<< " iterations:" << iterations << "\n";
+	if (iterations <= 0) {
+		cout << "ERROR with FLIMLib.fitLMA\n";
+		exit(0);
+	}
 
 	
 	// Run the phasor analysis
 	int error = flimLib.fitPhasor(50.0f);
-	if (FLIMLIB_SUCCESS != error) {
-		// An error occurred
-		cout << "ERROR with FLIMLib.fitPhasor\n";
-		exit(0);
-	}
 	cout << "Phasor Z:" << flimLib.param[FLIMLIB_PHASOR_PARAM_Z]
 		<< " tau:" << flimLib.param[FLIMLIB_PHASOR_PARAM_TAU]
 		<< " u:" << flimLib.param[FLIMLIB_PHASOR_PARAM_U]
 		<< " v:" << flimLib.param[FLIMLIB_PHASOR_PARAM_V]
 		<< " chisq:" << flimLib.getReducedChiSq() << "\n";
+	if (error != FLIMLIB_SUCCESS) {
+		cout << "ERROR with FLIMLib.fitPhasor\n";
+		exit(0);
+	}
 
 	return 0;
 }


Test patch:
diff --git a/src/test/c/README.txt b/src/test/c/README.txt
index 2c7ff83..759152b 100644
--- a/src/test/c/README.txt
+++ b/src/test/c/README.txt
@@ -42,12 +42,12 @@ There is a tests.c source file that is customized to look for the test name stri
 
 II.  Running the Tests
 
-There are two test files provided, original.json and test.json.  (They are actually identical except the original.json file has empty output sections [i.e. '"outputs":{}']).
+There are two test files provided, original.json and ref.json.  (They are actually identical except the original.json file has empty output sections [i.e. '"outputs":{}']).
 
 If you run the test with the file original.json (in Windows, '"FLIMLib Testing" original.json > output') it will run with the old NR-dependent versions of the fitting methods, add the results to the JSON tree, and print out the JSON document to standard output.
 
-You can cut & paste from standard output and build test.json.  Running this version exercises the new code under test and prints out test results.
+You can cut & paste from standard output and build ref.json.  Running this version exercises the new code under test and prints out test results.
 
-Unfortunately the JSON document is printed without any whitespace (this is common with JSON).  Fortunately there are many web-based JSON validators available, such as http://jsonformatter.curiousconcept.com/#jsonformatter (or just Google "JSON validator").  It's best to copy and paste the JSON text from the output using original.json into the validator, then copy and paste the validated/formatted results into test.json.
+Unfortunately the JSON document is printed without any whitespace (this is common with JSON).  Fortunately there are many web-based JSON validators available, such as http://jsonformatter.curiousconcept.com/#jsonformatter (or just Google "JSON validator").  It's best to copy and paste the JSON text from the output using original.json into the validator, then copy and paste the validated/formatted results into ref.json.
 
-So if you want to change one of the input parameters you have to edit original.json and go through this two stage process building a new test.json.  If you are just tweaking the new code and regression testing just running with the existing test.json will suffice.
+So if you want to change one of the input parameters you have to edit original.json and go through this two stage process building a new test.json.  If you are just tweaking the new code and regression testing just running with the existing ref.json will suffice.
diff --git a/src/test/java/flimlib/FLIMLibJavaTest.java b/src/test/java/flimlib/FLIMLibJavaTest.java
index 6b6edee..1791fcb 100644
--- a/src/test/java/flimlib/FLIMLibJavaTest.java
+++ b/src/test/java/flimlib/FLIMLibJavaTest.java
@@ -303,7 +303,10 @@ public void testGCI_marquardt_fitting_engine() {
 				noise, sig, param0, paramfree, restrain, FitFunc.GCI_MULTIEXP_TAU, fitted, 
 				residuals, chisquare, covar, alpha, erraxes, chisq_target, chisq_delta, 
 				chisq_percent);
-		assertEquals("return value incorrect", 14, ret0);
+
+		// Exact return value depends on CPU architecture.
+		assertTrue("iterations greater than 10", ret0 > 10);
+
 		assertArrayEqualsScaled("param matrix incorrect", new float[] {207.12376f, 12719.01f, 2.2813265f}, param0, tolerance);
 		assertEqualsScaled("covariance matrix incorrect", -0.088296, covar.asArray()[1][2], tolerance);
 		assertEqualsScaled("alpha matrix incorrect", 13.714218, alpha.asArray()[1][2], tolerance);
@@ -319,7 +322,10 @@ public void testGCI_marquardt_fitting_engine() {
 				noise, sig, param1, paramfree, restrain, FitFunc.GCI_MULTIEXP_LAMBDA, fitted, 
 				residuals, chisquare, covar, alpha, erraxes, chisq_target, chisq_delta, 
 				chisq_percent);
-		assertEquals("return value incorrect", 15, ret1);
+
+		// Exact return value depends on CPU architecture.
+		assertTrue("iterations greater than 10", ret0 > 10);
+
 		assertArrayEqualsScaled("param matrix incorrect", new float[] {207.12376f, 12719.01f, 1 / 2.2813265f}, param1, tolerance);
 		assertEqualsScaled("covariance matrix incorrect", 0.0169655140, covar.asArray()[1][2], tolerance);
 		assertEqualsScaled("alpha matrix incorrect", -71.375, alpha.asArray()[1][2], tolerance);
diff --git a/test_files/test.json b/test_files/test.json
deleted file mode 100644
index 1f5c011..0000000
--- a/test_files/test.json
+++ /dev/null
@@ -1,2052 +0,0 @@
-{
-   "testrun":{
-      "tests":[
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"59",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"0,3,1,2,2,0,0,0,1,1,0,0,1,1,0,1,0,2,2,1,1,1,1,1,0,1,2,1,0,0,1,0,2,3,2,0,0,0,0,1,0,2,0,2,0,0,0,2,0,0,2,3,2,3,4,3,7,12,3,5,3,7,10,1,7,3,6,8,1,10,6,4,6,7,6,4,7,4,3,4,3,0,2,3,1,4,2,3,5,1,3,6,5,7,4,3,4,6,6,5,3,3,5,5,4,1,3,4,4,5,5,3,4,3,2,2,4,3,3,2,4,1,3,3,4,4,2,6,0,1,0,6,3,3,4,3,3,4,1,3,0,2,1,1,2,1,1,0,3,2,1,1,2,1,3,1,1,3,1,1,0,2,1,1,3,0,3,1,1,2,0,1,3,0,2,0,1,4,1,1,3,0,3,1,3,2,4,1,1,0,3,1,2,0,1,1,0,2,1,4,2,0,2,0,2,0,2,0,2,0,0,1,2,0,0,1,0,1,1,2,2,1,3,3,1,1,1,2,0,0,0,4,2,1,1,2,3,4,1,4,1,2,1,2,2,0,2,0,1,0,1,1,0,1,1,1"
-               }
-            },
-            "outputs":{
-               "a":"11.476249",
-               "t":"3.052528",
-               "z":"0.317843"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"59",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"0,3,1,2,2,0,0,0,1,1,0,0,1,1,0,1,0,2,2,1,1,1,1,1,0,1,2,1,0,0,1,0,2,3,2,0,0,0,0,1,0,2,0,2,0,0,0,2,0,0,2,3,2,3,4,3,7,12,3,5,3,7,10,1,7,3,6,8,1,10,6,4,6,7,6,4,7,4,3,4,3,0,2,3,1,4,2,3,5,1,3,6,5,7,4,3,4,6,6,5,3,3,5,5,4,1,3,4,4,5,5,3,4,3,2,2,4,3,3,2,4,1,3,3,4,4,2,6,0,1,0,6,3,3,4,3,3,4,1,3,0,2,1,1,2,1,1,0,3,2,1,1,2,1,3,1,1,3,1,1,0,2,1,1,3,0,3,1,1,2,0,1,3,0,2,0,1,4,1,1,3,0,3,1,3,2,4,1,1,0,3,1,2,0,1,1,0,2,1,4,2,0,2,0,2,0,2,0,2,0,0,1,2,0,0,1,0,1,1,2,2,1,3,3,1,1,1,2,0,0,0,4,2,1,1,2,3,4,1,4,1,2,1,2,2,0,2,0,1,0,1,1,0,1,1,1"
-               }
-            },
-            "outputs":{
-               "a":"11.476249",
-               "t":"3.052528",
-               "z":"0.317843"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, noise type 2",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"2",
-               "xinc":"0.0390625",
-               "fitstart":"59",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"0,3,1,2,2,0,0,0,1,1,0,0,1,1,0,1,0,2,2,1,1,1,1,1,0,1,2,1,0,0,1,0,2,3,2,0,0,0,0,1,0,2,0,2,0,0,0,2,0,0,2,3,2,3,4,3,7,12,3,5,3,7,10,1,7,3,6,8,1,10,6,4,6,7,6,4,7,4,3,4,3,0,2,3,1,4,2,3,5,1,3,6,5,7,4,3,4,6,6,5,3,3,5,5,4,1,3,4,4,5,5,3,4,3,2,2,4,3,3,2,4,1,3,3,4,4,2,6,0,1,0,6,3,3,4,3,3,4,1,3,0,2,1,1,2,1,1,0,3,2,1,1,2,1,3,1,1,3,1,1,0,2,1,1,3,0,3,1,1,2,0,1,3,0,2,0,1,4,1,1,3,0,3,1,3,2,4,1,1,0,3,1,2,0,1,1,0,2,1,4,2,0,2,0,2,0,2,0,2,0,0,1,2,0,0,1,0,1,1,2,2,1,3,3,1,1,1,2,0,0,0,4,2,1,1,2,3,4,1,4,1,2,1,2,2,0,2,0,1,0,1,1,0,1,1,1"
-               }
-            },
-            "outputs":{
-               "a":"11.477409",
-               "t":"3.051929",
-               "z":"0.318245"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, noise type 3",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"3",
-               "xinc":"0.0390625",
-               "fitstart":"59",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"0,3,1,2,2,0,0,0,1,1,0,0,1,1,0,1,0,2,2,1,1,1,1,1,0,1,2,1,0,0,1,0,2,3,2,0,0,0,0,1,0,2,0,2,0,0,0,2,0,0,2,3,2,3,4,3,7,12,3,5,3,7,10,1,7,3,6,8,1,10,6,4,6,7,6,4,7,4,3,4,3,0,2,3,1,4,2,3,5,1,3,6,5,7,4,3,4,6,6,5,3,3,5,5,4,1,3,4,4,5,5,3,4,3,2,2,4,3,3,2,4,1,3,3,4,4,2,6,0,1,0,6,3,3,4,3,3,4,1,3,0,2,1,1,2,1,1,0,3,2,1,1,2,1,3,1,1,3,1,1,0,2,1,1,3,0,3,1,1,2,0,1,3,0,2,0,1,4,1,1,3,0,3,1,3,2,4,1,1,0,3,1,2,0,1,1,0,2,1,4,2,0,2,0,2,0,2,0,2,0,0,1,2,0,0,1,0,1,1,2,2,1,3,3,1,1,1,2,0,0,0,4,2,1,1,2,3,4,1,4,1,2,1,2,2,0,2,0,1,0,1,1,0,1,1,1"
-               }
-            },
-            "outputs":{
-               "a":"11.476304",
-               "t":"3.052500",
-               "z":"0.317862"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, noise type 4",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"59",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
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-            "comment":"Test mono-exp transient 1, noise type 5",
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-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, instrument response, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
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-               "fitstart":"55",
-               "fitstop":"230",
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-               "instr":{
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-            "outputs":{
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-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, instrument response, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
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-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
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-               "ninstr":"9",
-               "instr":{
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-            "outputs":{
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-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, instrument response, noise type 2",
-            "tolerance":"0.45",
-            "inputs":{
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-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-               "ninstr":"9",
-               "instr":{
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-            "outputs":{
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-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, instrument response, noise type 3",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"3",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-               "ninstr":"9",
-               "instr":{
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-            "outputs":{
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, instrument response, noise type 4",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
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-               "ninstr":"9",
-               "instr":{
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-            "outputs":{
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 1, instrument response, noise type 5",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-               "ninstr":"9",
-               "instr":{
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-            "outputs":{
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"62",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            },
-            "outputs":{
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"62",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            },
-            "outputs":{
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-               "t":"2.444936",
-               "z":"1.079027"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, noise type 2",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"2",
-               "xinc":"0.0390625",
-               "fitstart":"62",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            "outputs":{
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-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, noise type 3",
-            "tolerance":"0.45",
-            "inputs":{
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-               "xinc":"0.0390625",
-               "fitstart":"62",
-               "fitstop":"230",
-               "ndata":"256",
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-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, noise type 4",
-            "tolerance":"0.45",
-            "inputs":{
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-               "xinc":"0.0390625",
-               "fitstart":"62",
-               "fitstop":"230",
-               "ndata":"256",
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-            "outputs":{
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-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, noise type 5",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"62",
-               "fitstop":"230",
-               "ndata":"256",
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-            "outputs":{
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-               "t":"2.667919",
-               "z":"0.965483"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, instrument response, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-               "instr":{
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-            "outputs":{
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-               "z":"0.823123"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, instrument response, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-               "ninstr":"9",
-               "instr":{
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-            "outputs":{
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-               "z":"0.823123"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, instrument response, noise type 2",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"2",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-               "ninstr":"9",
-               "instr":{
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-            "outputs":{
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-               "z":"0.823019"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, instrument response, noise type 3",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"3",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-               "ninstr":"9",
-               "instr":{
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-            },
-            "outputs":{
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-               "t":"2.530944",
-               "z":"1.076326"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, instrument response, noise type 4",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"0,2,1,1,0,1,1,0,1,0,1,3,1,0,2,0,1,2,1,2,2,0,1,4,1,0,1,3,0,0,2,2,2,1,2,1,4,3,0,0,2,2,0,2,0,2,0,1,0,0,2,0,1,7,6,6,6,10,5,8,6,7,6,3,6,7,6,6,6,4,3,2,3,5,4,5,3,3,2,10,8,9,2,4,3,1,5,5,5,4,2,1,5,2,5,1,3,7,3,4,4,3,2,4,3,1,2,2,2,4,6,5,5,3,6,1,1,4,2,3,5,1,2,1,2,3,1,1,1,1,1,2,1,5,3,3,2,0,3,3,1,1,6,2,1,3,4,4,2,4,3,5,1,3,2,2,3,2,3,1,2,3,1,2,2,1,1,0,0,2,0,2,0,4,4,1,2,1,3,1,3,1,0,1,5,0,1,1,4,1,1,3,0,3,1,5,2,3,2,2,3,0,0,3,1,1,1,1,2,2,0,1,1,3,2,3,3,0,0,1,0,0,0,0,3,0,0,3,1,3,1,0,2,2,2,0,1,1,1,2,0,2,4,0,0,1,0,0,0,3,0,0,0,2,1,2"
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-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
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-            },
-            "outputs":{
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-               "t":"1.454719",
-               "z":"1.819299"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 2, instrument response, noise type 5",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"0,2,1,1,0,1,1,0,1,0,1,3,1,0,2,0,1,2,1,2,2,0,1,4,1,0,1,3,0,0,2,2,2,1,2,1,4,3,0,0,2,2,0,2,0,2,0,1,0,0,2,0,1,7,6,6,6,10,5,8,6,7,6,3,6,7,6,6,6,4,3,2,3,5,4,5,3,3,2,10,8,9,2,4,3,1,5,5,5,4,2,1,5,2,5,1,3,7,3,4,4,3,2,4,3,1,2,2,2,4,6,5,5,3,6,1,1,4,2,3,5,1,2,1,2,3,1,1,1,1,1,2,1,5,3,3,2,0,3,3,1,1,6,2,1,3,4,4,2,4,3,5,1,3,2,2,3,2,3,1,2,3,1,2,2,1,1,0,0,2,0,2,0,4,4,1,2,1,3,1,3,1,0,1,5,0,1,1,4,1,1,3,0,3,1,5,2,3,2,2,3,0,0,3,1,1,1,1,2,2,0,1,1,3,2,3,3,0,0,1,0,0,0,0,3,0,0,3,1,3,1,0,2,2,2,0,1,1,1,2,0,2,4,0,0,1,0,0,0,3,0,0,0,2,1,2"
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-               "ninstr":"9",
-               "instr":{
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-            },
-            "outputs":{
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-               "z":"0.872214"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 3, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"69",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            },
-            "outputs":{
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-               "t":"2.278997",
-               "z":"0.941666"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 3, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"69",
-               "fitstop":"230",
-               "ndata":"256",
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-               "fitstart":"58",
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-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 3, instrument response, noise type 5",
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-            "inputs":{
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-               "fitstart":"58",
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-            "outputs":{
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-               "z":"1.104923"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"69",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            "outputs":{
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-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"69",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            "outputs":{
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-               "t":"1.235993",
-               "z":"1.435321"
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-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, noise type 2",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"2",
-               "xinc":"0.0390625",
-               "fitstart":"69",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-            "outputs":{
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-               "t":"1.531626",
-               "z":"1.279627"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, noise type 3",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"3",
-               "xinc":"0.0390625",
-               "fitstart":"69",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-            "outputs":{
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-               "t":"1.236277",
-               "z":"1.435171"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, noise type 4",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"69",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-            },
-            "outputs":{
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-               "t":"0.720932",
-               "z":"2.016968"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, noise type 5",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"69",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-            },
-            "outputs":{
-               "a":"12.032950",
-               "t":"2.465053",
-               "z":"0.823239"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, instrument response, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"52",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-               "ninstr":"9",
-               "instr":{
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-            },
-            "outputs":{
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-               "t":"1.920439",
-               "z":"1.098533"
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-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, instrument response, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"52",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
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-            },
-            "outputs":{
-               "a":"15.143789",
-               "t":"1.920439",
-               "z":"1.098533"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, instrument response, noise type 2",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"2",
-               "xinc":"0.0390625",
-               "fitstart":"52",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
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-            },
-            "outputs":{
-               "a":"15.147234",
-               "t":"1.920120",
-               "z":"1.098789"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, instrument response, noise type 3",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"3",
-               "xinc":"0.0390625",
-               "fitstart":"52",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
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-            },
-            "outputs":{
-               "a":"15.147747",
-               "t":"1.920056",
-               "z":"1.098833"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, instrument response, noise type 4",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"52",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
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-            },
-            "outputs":{
-               "a":"51.163067",
-               "t":"0.916023",
-               "z":"1.952853"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 4, instrument response, noise type 5",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"52",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 2, 4, 1, 1, 2, 0, 0, 1, 1, 0, 2, 1, 0, 3, 0, 2, 4, 0, 2, 1, 2, 2, 2, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 4, 2, 0, 1, 2, 3, 0, 1, 1, 0, 0, 1, 2, 2, 0, 1, 3, 4, 1, 8, 7, 10, 8, 2, 8, 5, 11, 4, 7, 5, 4, 4, 6, 8, 6, 11, 3, 4, 4, 3, 6, 4, 5, 5, 9, 6, 3, 4, 4, 4, 3, 2, 6, 5, 4, 1, 3, 2, 1, 4, 3, 4, 4, 4, 3, 4, 2, 4, 4, 1, 3, 6, 2, 1, 2, 2, 5, 1, 2, 0, 0, 1, 1, 1, 4, 3, 2, 2, 1, 2, 0, 2, 4, 2, 2, 2, 3, 3, 2, 5, 1, 4, 1, 2, 2, 1, 2, 2, 1, 3, 3, 2, 4, 6, 1, 1, 1, 6, 2, 2, 3, 1, 1, 4, 2, 1, 1, 1, 3, 1, 5, 2, 2, 3, 2, 0, 1, 2, 4, 1, 0, 2, 1, 1, 2, 2, 0, 2, 2, 2, 2, 0, 3, 2, 2, 1, 1, 4, 0, 0, 3, 1, 2, 3, 2, 2, 0, 5, 2, 1, 0, 0, 3, 1, 1, 0, 1, 2, 0, 2, 1, 1, 1, 0, 3, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 2, 1, 1, 0, 0, 2, 0, 1, 0, 2, 3, 0, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 3, 0, 0, 3"
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-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
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-            },
-            "outputs":{
-               "a":"13.346864",
-               "t":"2.165953",
-               "z":"0.953730"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"72",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
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-            },
-            "outputs":{
-               "a":"14.501482",
-               "t":"2.016140",
-               "z":"1.224505"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"72",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
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-            },
-            "outputs":{
-               "a":"14.501482",
-               "t":"2.016140",
-               "z":"1.224505"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, noise type 2",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"2",
-               "xinc":"0.0390625",
-               "fitstart":"72",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
-               }
-            },
-            "outputs":{
-               "a":"14.486575",
-               "t":"2.017008",
-               "z":"1.223951"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, noise type 3",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"3",
-               "xinc":"0.0390625",
-               "fitstart":"72",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
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-            },
-            "outputs":{
-               "a":"14.501482",
-               "t":"2.016140",
-               "z":"1.224505"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, noise type 4",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"72",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
-               }
-            },
-            "outputs":{
-               "a":"9.188335",
-               "t":"2.930474",
-               "z":"0.884615"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, noise type 5",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"72",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
-               }
-            },
-            "outputs":{
-               "a":"13.371982",
-               "t":"2.136205",
-               "z":"1.172080"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, instrument response, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
-               },
-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
-               }
-            },
-            "outputs":{
-               "a":"17.014448",
-               "t":"1.783159",
-               "z":"1.296659"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, instrument response, noise type 1",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
-               },
-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
-               }
-            },
-            "outputs":{
-               "a":"17.014448",
-               "t":"1.783159",
-               "z":"1.296659"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, instrument response, noise type 2",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"2",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
-               },
-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
-               }
-            },
-            "outputs":{
-               "a":"17.014450",
-               "t":"1.783159",
-               "z":"1.296659"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, instrument response, noise type 3",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"3",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
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-               "ninstr":"9",
-               "instr":{
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-            "outputs":{
-               "a":"17.013817",
-               "t":"1.783214",
-               "z":"1.296624"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, instrument response, noise type 4",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
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-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
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-            },
-            "outputs":{
-               "a":"45.211170",
-               "t":"1.019955",
-               "z":"1.929968"
-            }
-         },
-         {
-            "test":"mono-exp",
-            "comment":"Test mono-exp transient 5, instrument response, noise type 5",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"55",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"1, 0, 1, 2, 1, 1, 2, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 2, 1, 1, 2, 1, 2, 0, 0, 1, 1, 0, 1, 1, 3, 2, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 1, 2, 3, 2, 0, 1, 3, 1, 3, 10, 6, 1, 10, 6, 8, 6, 7, 6, 5, 13, 4, 4, 4, 5, 6, 9, 6, 2, 4, 4, 1, 8, 6, 6, 5, 4, 5, 5, 3, 7, 4, 3, 5, 2, 7, 2, 3, 4, 5, 4, 7, 3, 3, 2, 3, 5, 3, 7, 0, 0, 2, 2, 4, 2, 4, 2, 1, 5, 1, 3, 2, 3, 1, 3, 3, 3, 0, 2, 3, 4, 4, 3, 2, 2, 3, 2, 0, 7, 5, 1, 3, 1, 3, 2, 0, 1, 1, 3, 0, 1, 2, 2, 2, 1, 0, 2, 3, 2, 5, 1, 2, 0, 4, 3, 0, 4, 1, 3, 1, 2, 0, 0, 3, 4, 1, 4, 3, 3, 1, 0, 5, 1, 5, 4, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 0, 2, 3, 2, 3, 1, 1, 2, 1, 1, 2, 1, 3, 2, 0, 2, 2, 0, 1, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 2, 5, 2, 0, 1, 1, 0, 1, 2, 1, 0, 0, 1, 1, 3, 0, 1, 1, 3, 2, 1, 0, 3, 0, 2, 1, 1, 0, 1, 1, 1, 0, 2, 0, 0"
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-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
-               }
-            },
-            "outputs":{
-               "a":"16.946907",
-               "t":"1.785548",
-               "z":"1.298483"
-            }
-         },
-         {
-            "test":"bi-exp",
-            "comment":"Test bi-exp transient, noise type 0",
-            "tolerance":"0.45",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"60",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"101, 83, 89, 97, 83, 80, 92, 79, 88, 81, 82, 75, 67, 55, 69, 65, 82, 76, 73, 65, 56, 60, 60, 64, 76, 66, 56, 46, 63, 62, 63, 49, 43, 45, 54, 44, 65, 52, 57, 66, 49, 36, 66, 41, 50, 46, 39, 56, 123, 485, 1746, 4865, 10291, 16303, 20929, 23418, 23929, 23380, 22832, 21937, 21722, 20867, 20354, 19595, 19251, 18931, 18252, 17541, 17174, 16984, 16517, 15699, 15419, 14931, 14485, 14276, 13887, 13382, 13060, 12804, 12418, 12116, 11828, 11471, 11100, 10841, 10572, 10201, 10124, 9764, 9662, 9291, 9029, 8798, 8561, 8362, 8042, 8060, 7783, 7600, 7307, 7325, 6990, 6826, 6701, 6485, 6492, 6271, 5980, 5934, 5788, 5725, 5434, 5382, 5357, 5072, 4880, 4879, 4820, 4610, 4515, 4483, 4347, 4124, 4214, 4132, 3939, 3832, 3894, 3701, 3658, 3531, 3412, 3426, 3316, 3318, 3244, 3086, 3002, 2985, 2977, 2720, 2717, 2560, 2601, 2582, 2542, 2538, 2443, 2260, 2299, 2254, 2124, 2068, 2154, 2153, 2032, 1991, 1871, 1891, 1869, 1794, 1736, 1769, 1799, 1704, 1660, 1587, 1604, 1548, 1468, 1503, 1503, 1440, 1328, 1348, 1353, 1272, 1284, 1255, 1234, 1148, 1173, 1156, 1097, 1121, 1036, 1008, 1057, 1023, 979, 1008, 953, 933, 922, 928, 932, 884, 812, 882, 836, 816, 765, 754, 739, 705, 751, 740, 702, 646, 613, 674, 660, 625, 592, 622, 575, 567, 545, 512, 584, 542, 525, 536, 532, 512, 486, 416, 427, 479, 461, 464, 432, 420, 398, 404, 382, 383, 373, 358, 346, 334, 366, 304, 314, 336, 305, 318, 351, 269, 275, 266, 279, 282, 263, 259"
-               }
-            },
-            "outputs":{
-               "a1":"68755.687500",
-               "t1":"1.680661",
-               "a2":"106172.164063",
-               "t2":"0.737423",
-               "z":"153.060089"
-            }
-         },
-         {
-            "test":"bi-exp",
-            "comment":"Test bi-exp transient, noise type 1",
-            "tolerance":"0.06",
-            "inputs":{
-               "noise":"1",
-               "xinc":"0.0390625",
-               "fitstart":"60",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"101, 83, 89, 97, 83, 80, 92, 79, 88, 81, 82, 75, 67, 55, 69, 65, 82, 76, 73, 65, 56, 60, 60, 64, 76, 66, 56, 46, 63, 62, 63, 49, 43, 45, 54, 44, 65, 52, 57, 66, 49, 36, 66, 41, 50, 46, 39, 56, 123, 485, 1746, 4865, 10291, 16303, 20929, 23418, 23929, 23380, 22832, 21937, 21722, 20867, 20354, 19595, 19251, 18931, 18252, 17541, 17174, 16984, 16517, 15699, 15419, 14931, 14485, 14276, 13887, 13382, 13060, 12804, 12418, 12116, 11828, 11471, 11100, 10841, 10572, 10201, 10124, 9764, 9662, 9291, 9029, 8798, 8561, 8362, 8042, 8060, 7783, 7600, 7307, 7325, 6990, 6826, 6701, 6485, 6492, 6271, 5980, 5934, 5788, 5725, 5434, 5382, 5357, 5072, 4880, 4879, 4820, 4610, 4515, 4483, 4347, 4124, 4214, 4132, 3939, 3832, 3894, 3701, 3658, 3531, 3412, 3426, 3316, 3318, 3244, 3086, 3002, 2985, 2977, 2720, 2717, 2560, 2601, 2582, 2542, 2538, 2443, 2260, 2299, 2254, 2124, 2068, 2154, 2153, 2032, 1991, 1871, 1891, 1869, 1794, 1736, 1769, 1799, 1704, 1660, 1587, 1604, 1548, 1468, 1503, 1503, 1440, 1328, 1348, 1353, 1272, 1284, 1255, 1234, 1148, 1173, 1156, 1097, 1121, 1036, 1008, 1057, 1023, 979, 1008, 953, 933, 922, 928, 932, 884, 812, 882, 836, 816, 765, 754, 739, 705, 751, 740, 702, 646, 613, 674, 660, 625, 592, 622, 575, 567, 545, 512, 584, 542, 525, 536, 532, 512, 486, 416, 427, 479, 461, 464, 432, 420, 398, 404, 382, 383, 373, 358, 346, 334, 366, 304, 314, 336, 305, 318, 351, 269, 275, 266, 279, 282, 263, 259"
-               }
-            },
-            "outputs":{
-               "a1":"68755.687500",
-               "t1":"1.680661",
-               "a2":"106172.164063",
-               "t2":"0.737423",
-               "z":"153.060089"
-            }
-         },
-         {
-            "test":"bi-exp",
-            "comment":"Test bi-exp transient, noise type 2",
-            "tolerance":"0.0002",
-            "inputs":{
-               "noise":"2",
-               "xinc":"0.0390625",
-               "fitstart":"60",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"101, 83, 89, 97, 83, 80, 92, 79, 88, 81, 82, 75, 67, 55, 69, 65, 82, 76, 73, 65, 56, 60, 60, 64, 76, 66, 56, 46, 63, 62, 63, 49, 43, 45, 54, 44, 65, 52, 57, 66, 49, 36, 66, 41, 50, 46, 39, 56, 123, 485, 1746, 4865, 10291, 16303, 20929, 23418, 23929, 23380, 22832, 21937, 21722, 20867, 20354, 19595, 19251, 18931, 18252, 17541, 17174, 16984, 16517, 15699, 15419, 14931, 14485, 14276, 13887, 13382, 13060, 12804, 12418, 12116, 11828, 11471, 11100, 10841, 10572, 10201, 10124, 9764, 9662, 9291, 9029, 8798, 8561, 8362, 8042, 8060, 7783, 7600, 7307, 7325, 6990, 6826, 6701, 6485, 6492, 6271, 5980, 5934, 5788, 5725, 5434, 5382, 5357, 5072, 4880, 4879, 4820, 4610, 4515, 4483, 4347, 4124, 4214, 4132, 3939, 3832, 3894, 3701, 3658, 3531, 3412, 3426, 3316, 3318, 3244, 3086, 3002, 2985, 2977, 2720, 2717, 2560, 2601, 2582, 2542, 2538, 2443, 2260, 2299, 2254, 2124, 2068, 2154, 2153, 2032, 1991, 1871, 1891, 1869, 1794, 1736, 1769, 1799, 1704, 1660, 1587, 1604, 1548, 1468, 1503, 1503, 1440, 1328, 1348, 1353, 1272, 1284, 1255, 1234, 1148, 1173, 1156, 1097, 1121, 1036, 1008, 1057, 1023, 979, 1008, 953, 933, 922, 928, 932, 884, 812, 882, 836, 816, 765, 754, 739, 705, 751, 740, 702, 646, 613, 674, 660, 625, 592, 622, 575, 567, 545, 512, 584, 542, 525, 536, 532, 512, 486, 416, 427, 479, 461, 464, 432, 420, 398, 404, 382, 383, 373, 358, 346, 334, 366, 304, 314, 336, 305, 318, 351, 269, 275, 266, 279, 282, 263, 259"
-               }
-            },
-            "outputs":{
-               "a1":"86874.460938",
-               "t1":"1.581499",
-               "a2":"127616.460938",
-               "t2":"0.285007",
-               "z":"182.147400"
-            }
-         },
-         {
-            "test":"bi-exp",
-            "comment":"Test bi-exp transient, noise type 3",
-            "tolerance":"0.0002",
-            "inputs":{
-               "noise":"3",
-               "xinc":"0.0390625",
-               "fitstart":"60",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            },
-            "outputs":{
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-               "t1":"1.581217",
-               "a2":"128072.304688",
-               "t2":"0.281658",
-               "z":"184.600952"
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-         },
-         {
-            "test":"bi-exp",
-            "comment":"Test bi-exp transient, noise type 4",
-            "tolerance":"0.0002",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"60",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            },
-            "outputs":{
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-               "t1":"1.581217",
-               "a2":"128072.304688",
-               "t2":"0.281658",
-               "z":"184.600952"
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-         },
-         {
-            "test":"bi-exp",
-            "comment":"Test bi-exp transient, noise type 5",
-            "tolerance":"0.0002",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"60",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
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-            },
-            "outputs":{
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-               "t1":"1.586344",
-               "a2":"136081.343750",
-               "t2":"0.229470",
-               "z":"178.260345"
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-         },
-         {
-            "test":"bi-exp",
-            "comment":"Test bi-exp transient, instrument response, noise type 0",
-            "tolerance":"0.0002",
-            "inputs":{
-               "noise":"0",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
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-               "counts":{
-                  "size":"256",
-                  "value":"3102, 3121, 3011, 2862, 2921, 2845, 2829, 2722, 2754, 2729, 2531, 2643, 2551, 2441, 2390, 2354, 2302, 2246, 2251, 2101, 2170, 2092, 1961, 1943, 1986, 1946, 1857, 1885, 1874, 1703, 1766, 1722, 1724, 1708, 1685, 1557, 1553, 1597, 1463, 1512, 1384, 1446, 1351, 1410, 1303, 1309, 1390, 2443, 10705, 54702, 211928, 596954, 1241170, 1963470, 2482740, 2685120, 2657250, 2532180, 2388290, 2248020, 2117630, 1993910, 1881530, 1774240, 1673230, 1582200, 1497130, 1415110, 1340320, 1266940, 1200790, 1140030, 1082490, 1028160, 975479, 926857, 885298, 843306, 802319, 764264, 729296, 695312, 665769, 636973, 610006, 584721, 558325, 536757, 513647, 493768, 473211, 456484, 439242, 420860, 406809, 391160, 376442, 363239, 351274, 338990, 327756, 316141, 306749, 295526, 286497, 276509, 269125, 259433, 252171, 244852, 236319, 230373, 224303, 216848, 210679, 203728, 198610, 192158, 187583, 182628, 177700, 172448, 168035, 163521, 159511, 155475, 151213, 147680, 143557, 139704, 135780, 133137, 129620, 126749, 123679, 120498, 117304, 115550, 112023, 109536, 107368, 104221, 101913, 99262, 97041, 94868, 92585, 90539, 88466, 86622, 84712, 82443, 81301, 78833, 77267, 75134, 74081, 72468, 70407, 69072, 67321, 66025, 64303, 63371, 62079, 60343, 58900, 57882, 57166, 55194, 54168, 53182, 52356, 51288, 49615, 48539, 48106, 46835, 45817, 44838, 43525, 43102, 42009, 41078, 40322, 39328, 38651, 38308, 36835, 36814, 35392, 34799, 34152, 33443, 32756, 32452, 31414, 30811, 30370, 29820, 29024, 28295, 27985, 27355, 26490, 26243, 25871, 24821, 24435, 24080, 23563, 22785, 22752, 22167, 21756, 21293, 20745, 20620, 19889, 19514, 19437, 19044, 18480, 17955, 17745, 17282, 17125, 16808, 16321, 15856, 15757, 15499, 14965, 14855, 14369, 14407, 13841, 13746, 13187, 13347, 12918, 12602, 12386, 12200, 11873, 11685, 11372, 11249, 11038, 10726, 10524, 10383, 10220, 9973, 9598, 9693"
-               },
-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
-               }
-            },
-            "outputs":{
-               "a1":"14711292.000000",
-               "t1":"1.018355",
-               "a2":"7355646.000000",
-               "t2":"0.509178",
-               "a3":"3677823.000000",
-               "t3":"0.254589",
-               "z":"21808.125000"
-            }
-         },
-         {
-            "test":"tri-exp",
-            "comment":"Test tri-exp transient, instrument response, noise type 4",
-            "tolerance":"0.0002",
-            "inputs":{
-               "noise":"4",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"3102, 3121, 3011, 2862, 2921, 2845, 2829, 2722, 2754, 2729, 2531, 2643, 2551, 2441, 2390, 2354, 2302, 2246, 2251, 2101, 2170, 2092, 1961, 1943, 1986, 1946, 1857, 1885, 1874, 1703, 1766, 1722, 1724, 1708, 1685, 1557, 1553, 1597, 1463, 1512, 1384, 1446, 1351, 1410, 1303, 1309, 1390, 2443, 10705, 54702, 211928, 596954, 1241170, 1963470, 2482740, 2685120, 2657250, 2532180, 2388290, 2248020, 2117630, 1993910, 1881530, 1774240, 1673230, 1582200, 1497130, 1415110, 1340320, 1266940, 1200790, 1140030, 1082490, 1028160, 975479, 926857, 885298, 843306, 802319, 764264, 729296, 695312, 665769, 636973, 610006, 584721, 558325, 536757, 513647, 493768, 473211, 456484, 439242, 420860, 406809, 391160, 376442, 363239, 351274, 338990, 327756, 316141, 306749, 295526, 286497, 276509, 269125, 259433, 252171, 244852, 236319, 230373, 224303, 216848, 210679, 203728, 198610, 192158, 187583, 182628, 177700, 172448, 168035, 163521, 159511, 155475, 151213, 147680, 143557, 139704, 135780, 133137, 129620, 126749, 123679, 120498, 117304, 115550, 112023, 109536, 107368, 104221, 101913, 99262, 97041, 94868, 92585, 90539, 88466, 86622, 84712, 82443, 81301, 78833, 77267, 75134, 74081, 72468, 70407, 69072, 67321, 66025, 64303, 63371, 62079, 60343, 58900, 57882, 57166, 55194, 54168, 53182, 52356, 51288, 49615, 48539, 48106, 46835, 45817, 44838, 43525, 43102, 42009, 41078, 40322, 39328, 38651, 38308, 36835, 36814, 35392, 34799, 34152, 33443, 32756, 32452, 31414, 30811, 30370, 29820, 29024, 28295, 27985, 27355, 26490, 26243, 25871, 24821, 24435, 24080, 23563, 22785, 22752, 22167, 21756, 21293, 20745, 20620, 19889, 19514, 19437, 19044, 18480, 17955, 17745, 17282, 17125, 16808, 16321, 15856, 15757, 15499, 14965, 14855, 14369, 14407, 13841, 13746, 13187, 13347, 12918, 12602, 12386, 12200, 11873, 11685, 11372, 11249, 11038, 10726, 10524, 10383, 10220, 9973, 9598, 9693"
-               },
-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
-               }
-            },
-            "outputs":{
-               "a1":"14711292.000000",
-               "t1":"1.018355",
-               "a2":"7355646.000000",
-               "t2":"0.509178",
-               "a3":"3677823.000000",
-               "t3":"0.254589",
-               "z":"21808.125000"
-            }
-         },
-         {
-            "test":"tri-exp",
-            "comment":"Test tri-exp transient, instrument response, noise type 5",
-            "tolerance":"0.0002",
-            "inputs":{
-               "noise":"5",
-               "xinc":"0.0390625",
-               "fitstart":"51",
-               "fitstop":"230",
-               "ndata":"256",
-               "counts":{
-                  "size":"256",
-                  "value":"3102, 3121, 3011, 2862, 2921, 2845, 2829, 2722, 2754, 2729, 2531, 2643, 2551, 2441, 2390, 2354, 2302, 2246, 2251, 2101, 2170, 2092, 1961, 1943, 1986, 1946, 1857, 1885, 1874, 1703, 1766, 1722, 1724, 1708, 1685, 1557, 1553, 1597, 1463, 1512, 1384, 1446, 1351, 1410, 1303, 1309, 1390, 2443, 10705, 54702, 211928, 596954, 1241170, 1963470, 2482740, 2685120, 2657250, 2532180, 2388290, 2248020, 2117630, 1993910, 1881530, 1774240, 1673230, 1582200, 1497130, 1415110, 1340320, 1266940, 1200790, 1140030, 1082490, 1028160, 975479, 926857, 885298, 843306, 802319, 764264, 729296, 695312, 665769, 636973, 610006, 584721, 558325, 536757, 513647, 493768, 473211, 456484, 439242, 420860, 406809, 391160, 376442, 363239, 351274, 338990, 327756, 316141, 306749, 295526, 286497, 276509, 269125, 259433, 252171, 244852, 236319, 230373, 224303, 216848, 210679, 203728, 198610, 192158, 187583, 182628, 177700, 172448, 168035, 163521, 159511, 155475, 151213, 147680, 143557, 139704, 135780, 133137, 129620, 126749, 123679, 120498, 117304, 115550, 112023, 109536, 107368, 104221, 101913, 99262, 97041, 94868, 92585, 90539, 88466, 86622, 84712, 82443, 81301, 78833, 77267, 75134, 74081, 72468, 70407, 69072, 67321, 66025, 64303, 63371, 62079, 60343, 58900, 57882, 57166, 55194, 54168, 53182, 52356, 51288, 49615, 48539, 48106, 46835, 45817, 44838, 43525, 43102, 42009, 41078, 40322, 39328, 38651, 38308, 36835, 36814, 35392, 34799, 34152, 33443, 32756, 32452, 31414, 30811, 30370, 29820, 29024, 28295, 27985, 27355, 26490, 26243, 25871, 24821, 24435, 24080, 23563, 22785, 22752, 22167, 21756, 21293, 20745, 20620, 19889, 19514, 19437, 19044, 18480, 17955, 17745, 17282, 17125, 16808, 16321, 15856, 15757, 15499, 14965, 14855, 14369, 14407, 13841, 13746, 13187, 13347, 12918, 12602, 12386, 12200, 11873, 11685, 11372, 11249, 11038, 10726, 10524, 10383, 10220, 9973, 9598, 9693"
-               },
-               "ninstr":"9",
-               "instr":{
-                  "size":"9",
-                  "value":"0.013579,0.0494665,0.123181,0.20999,0.245635,0.197381,0.108875,0.0412221,0.0106693"
-               }
-            },
-            "outputs":{
-               "a1":"14711292.000000",
-               "t1":"1.018355",
-               "a2":"7355646.000000",
-               "t2":"0.509178",
-               "a3":"3677823.000000",
-               "t3":"0.254589",
-               "z":"21808.125000"
-            }
-         }
-      ]
-   }
-}
\ No newline at end of file
diff --git a/tests/flimlib-cmd-cpp.t b/tests/flimlib-cmd-cpp.t
index db038d2..9991b1c 100644
--- a/tests/flimlib-cmd-cpp.t
+++ b/tests/flimlib-cmd-cpp.t
@@ -1,9 +1,9 @@
   $ "$TESTDIR/../target/build/bin/flimlib-cmd-cpp"
   RLD Z:160.399 A:13382.2 tau:2.44568 chisq:15.8987 iterations:2
-  LMA Z:207.124 A:11414.5 tau:2.28133 chisq:12.8064 iterations:16
-  RLDi Z:160.399 A:12220.6 tau:2.44568 chisq:16.1303 iterations:2
-  LMAi Z:207.12 A:12719 tau:2.28134 chisq:12.8205 iterations:13
-  LMAi Z:68.1251 A1:8812.06 tau1:2.94505 A2:6959.48 tau2:0.796451 chisq:1.55814 iterations:36
-  LMAi Z:0 A1:5048.54 tau1:3.75549 A2:6927.9 tau2:1.66671 A3:4460.28 tau3:0.5 chisq:1.38668 iterations:49
-  LMAi Z:0.00* A:17260.* tau:1.5439* h:1.3868* chisq:1.491* iterations:* (glob)
+  LMA Z:207.124 A:11414.5 tau:2.28133 chisq:12.806* iterations:1? (glob)
+  RLDi Z:160.399 A:12220.6 tau:2.44568 chisq:16.130* iterations:2 (glob)
+  LMAi Z:207.12 A:12719 tau:2.28134 chisq:12.8205 iterations:1? (glob)
+  LMAi Z:68.1* A1:8812.* tau1:2.94* A2:6959.* tau2:0.796* chisq:1.55814 iterations:3? (glob)
+  LMAi Z:0 A1:5048.5* tau1:3.75549 A2:6927.* tau2:1.66671 A3:4460.28 tau3:0.5 chisq:1.38668 iterations:49 (glob)
+  LMAi Z:11.3* A:13897.* tau:1.769* h:1.314* chisq:1.587* iterations:?? (glob)
   Phasor Z:50 tau:2.46083 u:0.386278 v:0.439788 chisq:30.2931
diff --git a/tests/flimlib-cmd.t b/tests/flimlib-cmd.t
index f3adf28..c2f95b4 100644
--- a/tests/flimlib-cmd.t
+++ b/tests/flimlib-cmd.t
@@ -5,42 +5,42 @@
   Transient Data: data.dat
   TRI2 TR Settings File
   RLD return_value 2
-  RLD estimate A 11515.900391 T 2.392674 Z 208.731979 X2 8.997931
-  LMA return value 19
-  LMA fitted A 11807.464844 T 2.268578 Z 252.651108 X2 7.323193
+  RLD estimate A 11515.900391 T 2.392674 Z 208.731* X2 8.9979* (glob)
+  LMA return value [12][0-9] (re)
+  LMA fitted A 11807.4* T 2.2685* Z 252.6* X2 7.3231* (glob)
 
   $ ./flimlib-cmd settings2.ini data.dat
   Settings: settings2.ini
   Transient Data: data.dat
   TRI2 TR Settings File
   RLD return_value 2
-  RLD estimate A 11515.900391 T 2.392674 Z 208.731979 X2 8.997931
-  LMA return value 21
-  LMA fitted A1 8786.699219 T1 2.841778 A2 5456.799316 T2 0.779751 Z 100.473969 X2 1.210896
+  RLD estimate A 11515.900391 T 2.392674 Z 208.7319* X2 8.99793* (glob)
+  LMA return value [12][0-9] (re)
+  LMA fitted A1 8786.69* T1 2.841778 A2 5456.799* T2 0.77975* Z 100.473* X2 1.210* (glob)
 
   $ ./flimlib-cmd settings3.ini data.dat
   Settings: settings3.ini
   Transient Data: data.dat
   TRI2 TR Settings File
   RLD return_value 2
-  RLD estimate A 11515.900391 T 2.392674 Z 208.731979 X2 8.997931
-  LMA return value 34
-  LMA fitted A1 7850.844238 T1 3.024728 A2 5444.664551 T2 1.022018 A3 4237.820312 T3 0.162697 Z 71.399940 X2 1.133069
+  RLD estimate A 11515.900391 T 2.392674 Z 208.7319* X2 8.99793* (glob)
+  LMA return value 3? (glob)
+  LMA fitted A1 785?.* T1 3.02* A2 544?.* T2 1.02* A3 42??.* T3 0.162* Z 71.* X2 1.133* (glob)
 
   $ ./flimlib-cmd settings4.ini data.dat
   Settings: settings4.ini
   Transient Data: data.dat
   TRI2 TR Settings File
   RLD return_value 2
-  RLD estimate A 11515.900391 T 2.392674 Z 208.731979 X2 8.997931
-  LMA return value * (glob)
-  LMA fitted A 15745.* T 1.6161* H 1.3704* Z 0.00* X2 1.145* (glob)
+  RLD estimate A 11515.900391 T 2.392674 Z 208.7319* X2 8.99793* (glob)
+  LMA return value [1-5][0-9] (re)
+  LMA fitted A 15745.* T 1.6161* H 1.3704* Z 0.0* X2 1.145* (glob)
 
   $ ./flimlib-cmd settings5.ini data.dat
   Settings: settings5.ini
   Transient Data: data.dat
   TRI2 TR Settings File
   RLD return_value 2
-  RLD estimate A 11515.900391 T 2.392674 Z 208.731979 X2 8.997931
+  RLD estimate A 11515.900391 T 2.392674 Z 208.7319* X2 8.99793* (glob)
   Phasor return value 0
-  Phasor fitted T 2.330856 Z 208.731979 X2 7.946539
+  Phasor fitted T 2.330856 Z 208.7319* X2 7.9465* (glob)
diff --git a/tests/flimlib-native-test.t b/tests/flimlib-native-test.t
deleted file mode 100644
index 9125ab7..0000000
--- a/tests/flimlib-native-test.t
+++ /dev/null
@@ -1,14 +0,0 @@
-  $ cp "$TESTDIR/../target/build/bin/flimlib-test" "$TESTDIR"/../test_files/* .
-
-  $ (./flimlib-test ./test.json) | grep "TESTS RUN"
-  84 TESTS RUN, 32 SUCCESSES, 52 FAILURES
-
-  $ (./flimlib-test ./test.json) | grep "TESTS RUN"
-  84 TESTS RUN, 32 SUCCESSES, 52 FAILURES
-
-# greps changed json string from output as new reference
-#  $ (./flimlib-test ./original.json) | grep '^[\s\S]*{' > ref.json
-
-# finds FAILed tests from output
-  $ (./flimlib-test ./ref.json) | perl -0777 -ne "while(m/\nTEST((.*\S.*)\n)+FAIL((.*\S.*)\n)+/g){print $&}"
-
diff --git a/tests/flimlib-native-test.t.disabled b/tests/flimlib-native-test.t.disabled
new file mode 100644
index 0000000..a01de9c
--- /dev/null
+++ b/tests/flimlib-native-test.t.disabled
@@ -0,0 +1,32 @@
+  $ cp "$TESTDIR/../target/build/bin/flimlib-test" "$TESTDIR"/../test_files/* .
+
+# greps changed json string from output as new reference
+#  $ (./flimlib-test ./original.json) | grep '^[\s\S]*{' > ref.json
+
+# finds FAILed tests from output
+  $ (./flimlib-test ./ref.json) | perl -0777 -ne "while(m/\nTEST((.*\S.*)\n)+FAIL((.*\S.*)\n)+/g){print $&}"
+
+# This test is currently disabled (by renaming this file) because
+# 1. Much of the test data (original.json/ref.json) consists of low random
+#    counts, where the fit is useless. Testing for the same output under those
+#    conditions is completely pointless, unless the goal is to forbid any code
+#    change (even that would only work under the same CPU architecture).
+# 2. It was found that flimlib-test does not execute the tests correctly. It
+#    appears to have the following issues:
+#     - When there is no IRF, the RLD and Marquardt interpret the relationship
+#       between fitstart and A (the amplitude parameter) differently. Therefore
+#       the Marquardt fit parameters are not initialized correclty.
+#     - When an IRF is given, I'm not sure entirely what happens but the RLD
+#       clearly does not work the same way. We really need tests for RLD
+#       alone first.
+#     - Use of a single fractional tolerance for all of the fit parameters is
+#       problematic, because Z will usually have a larger error. This could be
+#       worked around by using data with large Z values with relatively low
+#       noise, but that is not very realistic.
+# Because of point 2, it is not clear what is being tested even with the tests
+# that do have realistic-looking decay data.
+#
+# We need to
+# - Fix flimlib-test to address the above issues
+# - Use test data generated in a known manner (i.e., use an exponential, add
+#   poisson noise, optionally convolve with a known IRF, etc.)
diff --git a/tests/readme.txt b/tests/readme.txt
index 91db61b..c5b8968 100644
--- a/tests/readme.txt
+++ b/tests/readme.txt
@@ -1,5 +1,9 @@
-This directory houses automated tests for use with cram.
+This directory houses automated tests for use with prysk.
 
-  https://bitheap.org/cram/
+  https://www.prysk.net
 
-To run them, type "cram tests" from the toplevel directory.
+  https://github.com/Nicoretti/prysk
+
+  pip install prysk
+
+To run them, type "prysk tests" from the toplevel directory.