declare   @param1 INT=100
declare   @param2 INT=50
declare   @param3 INT=3

EXECUTE sp_execute_external_script @language = N'Python'
    , @script = N'
import numpy
import pandas
OutputDataSet = pandas.DataFrame(numpy.random.normal(size=mynumbers, loc=mymean, scale=mysd));
'
    , @input_data_1 = N'   ;'
    , @params = N' @mynumbers int, @mymean int, @mysd int'
    , @mynumbers = @param1
    , @mymean = @param2
    , @mysd = @param3
WITH RESULT SETS(([Density] FLOAT NOT NULL));
GO

DECLARE @pscript NVARCHAR(MAX);
DECLARE @path NVARCHAR(MAX)=N'e:\\charts\\Anomalies2.pdf';
SET @pscript = N'
# import Python modules
import matplotlib
matplotlib.use("PDF")
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from microsoftml import rx_oneclass_svm, rx_predict
# create data frame
iris = load_iris()
df = pd.DataFrame(iris.data)
df.reset_index(inplace=True)
df.columns = ["Plant", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth"]
# split data frame into training and test data
train, test = train_test_split(df, test_size=.06)
# generate model
svm = rx_oneclass_svm(
  formula="~ SepalLength + SepalWidth + PetalLength + PetalWidth", data=train)
# add anomalies to test data
test2 = pd.DataFrame(data=dict(
Plant = [175, 200],
SepalLength = [2.9, 3.1], 
SepalWidth = [.85, 1.1],
PetalLength = [2.6, 2.5], 
PetalWidth = [2.7, 3.2]))
test = test.append(test2)
# score test data
scores = rx_predict(svm, data=test, extra_vars_to_write="Plant")
# create scatter plot
pt = scores.plot.scatter(x="Plant", y="Score", c="navy", s=35, alpha=.8)
# configure scatter plot title and grid
pt.set_title(label=" Identifying Iris Anomalies", y=1.04, 
  fontsize=14, weight=500, color="navy")
pt.grid(color="slategray", alpha=.5, linestyle="dotted", linewidth=.5)
# configure scatter plot Y-axis and X-axis labels
pt.set_ylabel("Species Scoring", labelpad=20, fontsize=12, color="navy")
pt.set_xlabel("Iris Species (by ID)", labelpad=20, fontsize=12, color="navy")
# save scatter plot to .pdf file
plt.savefig(chartpath,
  bbox_inches="tight", pad_inches=.8)';
--plt.savefig("e:\\charts\\Anomalies.pdf",

EXEC sp_execute_external_script
  @language = N'Python',
  @params = N' @chartpath NVARCHAR(MAX)',
  @chartpath = @path,
  @script = @pscript;     
GO