diff options
Diffstat (limited to 'src/lib/ndpi_analyze.c')
| -rw-r--r-- | src/lib/ndpi_analyze.c | 39 |
1 files changed, 39 insertions, 0 deletions
diff --git a/src/lib/ndpi_analyze.c b/src/lib/ndpi_analyze.c index bb0b74fd4..7a2fd495c 100644 --- a/src/lib/ndpi_analyze.c +++ b/src/lib/ndpi_analyze.c @@ -66,6 +66,20 @@ struct ndpi_analyze_struct* ndpi_alloc_data_analysis(u_int16_t _max_series_len) /* ********************************************************************************* */ +struct ndpi_analyze_struct* ndpi_alloc_data_analysis_from_series(const u_int32_t *values, u_int16_t num_values) { + u_int16_t i; + struct ndpi_analyze_struct *ret = ndpi_alloc_data_analysis(num_values); + + if(ret == NULL) return(NULL); + + for(i=0; i<num_values; i++) + ndpi_data_add_value(ret, (const u_int64_t)values[i]); + + return(ret); +} + +/* ********************************************************************************* */ + void ndpi_free_data_analysis(struct ndpi_analyze_struct *d, u_int8_t free_pointer) { if(d && d->values) ndpi_free(d->values); if(free_pointer) ndpi_free(d); @@ -1670,6 +1684,31 @@ int ndpi_predict_linear(u_int32_t *values, u_int32_t num_values, /* ********************************************************************************* */ +double ndpi_pearson_correlation(u_int32_t *values_a, u_int32_t *values_b, u_int16_t num_values) { + double sum_a = 0, sum_b = 0, sum_squared_diff_a = 0, sum_squared_diff_b = 0, sum_product_diff = 0; + u_int16_t i; + double mean_a, mean_b, variance_a, variance_b, covariance; + + if(num_values == 0) return(0.0); + + for(i = 0; i < num_values; i++) + sum_a += values_a[i], sum_b += values_b[i]; + + mean_a = sum_a / num_values, mean_b = sum_b / num_values; + + for(i = 0; i < num_values; i++) + sum_squared_diff_a += pow(values_a[i] - mean_a, 2), + sum_squared_diff_b += pow(values_b[i] - mean_b, 2), + sum_product_diff += (values_a[i] - mean_a) * (values_b[i] - mean_b); + + variance_a = sum_squared_diff_a / (double)num_values, variance_b = sum_squared_diff_b / (double)num_values; + covariance = sum_product_diff / (double)num_values; + + return(covariance / sqrt(variance_a * variance_b)); +} + +/* ********************************************************************************* */ + static const u_int16_t crc16_ccitt_table[256] = { 0x0000, 0x1189, 0x2312, 0x329B, 0x4624, 0x57AD, 0x6536, 0x74BF, 0x8C48, 0x9DC1, 0xAF5A, 0xBED3, 0xCA6C, 0xDBE5, 0xE97E, 0xF8F7, |