diff --git a/R/calculatePower.R b/R/calculatePower.R index 79a7338..471b1fa 100644 --- a/R/calculatePower.R +++ b/R/calculatePower.R @@ -19,11 +19,12 @@ library(readr) # (1) - Get the pilot data and clean it #source('~/Research/tor_wikipedia_edits/handcoded_edits/inter_coder_reliability_ns0.R') #source ('/data/users/mgaughan/kkex_data_110823_3') -data1 <- read_csv('../power_data_111023_mmt_ufm.csv',show_col_types = FALSE) - +data1 <- read_csv('../power_data_110923_mmt.csv',show_col_types = FALSE) +data2 <- read_csv('/data_ext/users/kcz1100/kaylea_dissertation/collabnetXS/raw_data/inst_all_packages_full_results.csv') #d$nd <- to_logical(d$not.damaging, custom_true=c("Y")) #levels(d$source) <- c("IP-based Editors", "New Editors", "Registered Editors", "Tor-based Editors") +data1$up.fac.mean <- as.numeric(data2$up.fac.mean[match(data1$pkg, data2$pkg)]) # (2) - Run the model on the pilot data pilotM <- glm(up.fac.mean ~ ((mmt) / (milestones/age)), # give the anticipated regression a try family=gaussian(link='identity'), data=data1) @@ -45,8 +46,8 @@ n <- 100 #a guess for necessary sample size (per group) #makeData(10) #DEBUGGING CODE -- you can uncomment this if you want to see it work #<==== -print("Levels are:") -print(levels(d$source)) +#print("Levels are:") +#print(levels(d$source)) powerCheck(n, nSims) #Sample values diff --git a/consolidate_data.py b/consolidate_data.py index 65e23cc..931e307 100644 --- a/consolidate_data.py +++ b/consolidate_data.py @@ -13,6 +13,7 @@ csv_2 = pandas.read_csv('/data_ext/users/kcz1100/kaylea_dissertation/collabnetXS print(csv_2['pkg']) up_fac_mean = [] +pkg_name = [] for index, row in csv_1.iterrows(): temporary_proj_name = row['repo'][:-12].split('_')[1] proj_name = "" @@ -20,13 +21,17 @@ for index, row in csv_1.iterrows(): proj_name = temporary_proj_name[:-4] else: proj_name = temporary_proj_name - row = csv_2.loc[csv_2['pkg'] == proj_name] + row = csv_2.loc[proj_name == csv_2['pkg']] + if proj_name == "hacking": + 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