diff --git a/generate_dataset.py b/generate_dataset.py
new file mode 100644
index 00000000..b1044a25
--- /dev/null
+++ b/generate_dataset.py
@@ -0,0 +1,124 @@
+import csv
+from pathlib import Path
+
+import yaml
+
+from CPDShell.generator.generator import ScipyDatasetGenerator
+from CPDShell.generator.saver import DatasetSaver
+
+SAMPLE_SIZE = 500
+CP_LOCATION = 250
+
+NUM_OF_SAMPLES = 1000
+
+DIR_PATH = "/experiment/stage_1/"
+CONFIG_NAME = "config.yml"
+
+WORKING_DIR = Path()
+
+
+class VerboseSafeDumper(yaml.SafeDumper):
+    def ignore_aliases(self, data):
+        return True
+
+
+def distribution_template(distribution_type, length, parameters):
+    return {"type": distribution_type, "length": length, "parameters": parameters}
+
+
+def add_distribution(distributions, distribution_type, parameters, length=CP_LOCATION):
+    distributions[distribution_type] = distribution_template(distribution_type, length, parameters)
+
+
+distributions_left = {}
+add_distribution(distributions_left, "normal", {"mean": 0.0, "variance": 1.0})
+add_distribution(distributions_left, "exponential", {"rate": 1.0})
+add_distribution(distributions_left, "uniform", {"min": 0.0, "max": 1.0})
+add_distribution(distributions_left, "weibull", {"shape": 1.0, "scale": 0.5})
+add_distribution(distributions_left, "beta", {"alpha": 0.5, "beta": 0.5})
+
+distributions_right = {}
+add_distribution(distributions_right, "normal", {"mean": 10.0, "variance": 5.0})
+add_distribution(distributions_right, "exponential", {"rate": 5.0})
+add_distribution(distributions_right, "uniform", {"min": 1.0, "max": 4.0})
+add_distribution(distributions_right, "weibull", {"shape": 1.0, "scale": 5.0})
+add_distribution(distributions_right, "beta", {"alpha": 5.0, "beta": 5.0})
+
+distributions_no_cp = {}
+add_distribution(distributions_no_cp, "normal", {"mean": 0.0, "variance": 1.0}, SAMPLE_SIZE)
+add_distribution(distributions_no_cp, "exponential", {"rate": 1.0}, SAMPLE_SIZE)
+add_distribution(distributions_no_cp, "uniform", {"min": 0.0, "max": 1.0}, SAMPLE_SIZE)
+add_distribution(distributions_no_cp, "weibull", {"shape": 1.0, "scale": 0.5}, SAMPLE_SIZE)
+add_distribution(distributions_no_cp, "beta", {"alpha": 0.5, "beta": 0.5}, SAMPLE_SIZE)
+
+
+def generate_configs(distributions):
+    distribution_types = []
+    distributions_l, distributions_r, distributions_without_cp = distributions
+    for distribution in distributions_l:
+        distribution_types.append(distribution)
+
+    names = []
+    for distribution_type_l in distribution_types:
+        for distribution_type_r in distribution_types:
+            name = distribution_type_l + "-" + distribution_type_r
+            names.append(name)
+
+            config = [
+                {
+                    "name": name,
+                    "distributions": [distributions_l[distribution_type_l], distributions_r[distribution_type_r]],
+                }
+            ]
+
+            Path(WORKING_DIR / f"experiment/stage_1/{name}/").mkdir(parents=True, exist_ok=True)
+
+            with open(WORKING_DIR / f"experiment/stage_1/{name}/config.yaml", "w") as outfile:
+                yaml.dump(config, outfile, default_flow_style=False, sort_keys=False, Dumper=VerboseSafeDumper)
+
+    for name in distribution_types:
+        names.append(name)
+
+        config = [
+            {
+                "name": name,
+                "distributions": [
+                    distributions_without_cp[name],
+                ],
+            }
+        ]
+
+        Path(WORKING_DIR / f"experiment/stage_1/{name}/").mkdir(parents=True, exist_ok=True)
+
+        with open(WORKING_DIR / f"experiment/stage_1/{name}/config.yaml", "w") as outfile:
+            yaml.dump(config, outfile, default_flow_style=False, sort_keys=False, Dumper=VerboseSafeDumper)
+
+    return names
+
+
+Path(WORKING_DIR / "experiment/stage_1/").mkdir(parents=True, exist_ok=True)
+generated_names = generate_configs((distributions_left, distributions_right, distributions_no_cp))
+
+with open(WORKING_DIR / "experiment/stage_1/experiment_description", "w", newline="") as f:
+    write = csv.writer(f)
+
+    write.writerow(["name", "samples_num"])
+    samples_description = [[s, str(NUM_OF_SAMPLES)] for s in generated_names]
+    write.writerows(samples_description)
+
+for generated_name in generated_names:
+    Path(WORKING_DIR / f"experiment/stage_1/{generated_name}/").mkdir(parents=True, exist_ok=True)
+
+    for sample_num in range(NUM_OF_SAMPLES):
+        print(f"Name: {generated_name}. Sample num: {sample_num}")
+        Path(WORKING_DIR / f"experiment/stage_1/{generated_name}/sample_{sample_num}/").mkdir(
+            parents=True, exist_ok=True
+        )
+        saver = DatasetSaver(WORKING_DIR / f"experiment/stage_1/{generated_name}/sample_{sample_num}/", True)
+        generated = ScipyDatasetGenerator().generate_datasets(
+            Path(WORKING_DIR / f"experiment/stage_1/{generated_name}/config.yaml"), saver
+        )
+
+        Path(
+            WORKING_DIR / f"experiment/stage_1/{generated_name}/sample_{sample_num}/{generated_name}/sample.png"
+        ).unlink(missing_ok=True)